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The Role of Probiotic Lactobacillus in
Immune Regulation and Modulation of the
Vaginal Microbiota During Pregnancy
by
Siwen Yang
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Department of Physiology
University of Toronto
© Copyright by Siwen Yang 2015
ii
The Role of Probiotic Lactobacillus in Immune Regulation and
Modulation of the Vaginal Microbiota During Pregnancy
Siwen Yang
Doctor of Philosophy
Department of Physiology
University of Toronto
2015
Abstract
Preterm birth (PTB) occurs in 10% of all pregnancies globally. Premature babies have a
mortality rate 40 times higher than term infants. Approximately 25-30% of PTB can be
attributed to intrauterine infection/inflammation. A disturbance of the vaginal microbiota as
observed in bacterial vaginosis (BV) is associated with an increased risk of PTB. Treatment
of preterm labor with antibiotics is largely ineffective, and probiotic lactobacilli have been
proposed as a potential preventive therapy for BV and PTB. The objectives of this thesis
were to assess 1) the effect of Lactobacillus rhamnosus GR-1 (GR-1) and its supernatant
(GR-1 SN) on the prevention of lipopolysaccharide (LPS)-induced PTB and systemic and
intra-uterine cytokine and chemokine profiles in pregnant CD-1 mice, 2) the effect of GR-1
on the mouse vaginal microbiota, and 3) the effect of GR-1 and L. reuteri RC-14 on the
cervico-vaginal cytokine profile and vaginal microbiota in pregnant women with an
abnormal Nugent score. Pregnant mice were pre-treated with intra-peritoneal injections of
iii
GR-1 SN or oral GR-1 live bacteria prior to intrauterine injection of LPS in two separate
studies. The expression of cytokines and chemokines in the maternal plasma, amniotic fluid
and intrauterine tissues were then measured. The vaginal microbiota was also determined in
animals treated with oral GR-1 live bacteria. Pre-treatment with GR-1 SN, but not with GR-1
live bacteria, reduced LPS-induced PTB and inflammation in pregnant mice. The vaginal
microbiota of pregnant mice was altered with oral GR-1 live bacteria. A randomized, double
blind placebo-controlled trial was conducted, in which pregnant women with an abnormal
Nugent score in their first trimester of pregnancy received orally either placebo or GR-1 and
RC-14 for 12 weeks. Their cervico-vaginal cytokine profile and vaginal microbiota was then
determined. Oral GR-1 and RC-14, at the dose and duration used, did not change the
cytokine profile and vaginal microbiota of pregnant women with an abnormal Nugent score.
We conclude that L. rhamnosus GR-1 supernatant, but not the live bacteria, may have the
potential to serve as a prophylactic therapy for inflammation-associated conditions during
pregnancy, including PTB.
iv
Dedication
To my beloved parents, for their continuous support and unconditional love.
v
Acknowledgements
With sincere respect, I would like to express my gratitude to my supervisor, Dr. Alan
Bocking, for his continuous guidance and unfaltering belief in me for the past years. Your
professional work ethics served as a role model to me. I appreciate your patience,
understanding and support through the tough times. I am forever thankful for your
encouragement and valuable ideas that make my PhD experience meaningful and productive.
My deepest thanks to my co-supervisor, Dr. John Challis, for sharing his wealth of
knowledge in physiology and providing his continuous support throughout the years. I am
grateful for your constructive recommendations while challenging me to think beyond my
intellectual comfort zone.
Many thanks to members of my advisory committee for keeping me on the right track to the
completion of my projects. I would like to thank Dr. Stephen Lye, for offering his advice on
the physiological aspect of my project. I would also like to thank Dr. Sung Kim, for sharing
his knowledgeable insights in immunology. I am thankful to Dr. Gregory Gloor for his
advice on interpreting sequencing data. His excellent teaching skills made learning R less
nerve wrecking.
I would like to extend my gratitude to Dr. Gregor Reid for sharing his knowledge on
probiotics and his willingness to devote time to engage in my work. I would like to
acknowledge members of his laboratory, Shannon, Jordan, Grace, Leslie, Amy, Camilla and
Yige for making me feel at home during my stay in London. Special thanks to Ms Shannon
vi
Seney, Mr Rod McPhee and Ms Amy McMillian for providing Nugent scores for my project.
I would like to acknowledge members of Dr. Gloor’s laboratory, Jean and Julia, for helping
me learn R. Special thanks to David Carter at the London Research Institute for his help with
Illumina Sequencing.
Sincere thanks to examiners of my qualifying exam, Drs Michelle Letarte and Theodore
Brown, and examiners of my CIHR grant proposal course, Drs Lee Adamson, Denise
Belsham and Clifford Librach, for your critical evaluations of my project and for your
valuable suggestions at the examinations.
I would like to thank members of the VOGUE team who have generously contributed their
ideas and time discussing my project. I would also like to thank Dr. Laurent Briollais, for
offering his help with the statistical analysis of my project. I would like to thank the research
nurses, Ms Mary-Jean Martin and Ms Tara Maria Rocco, of Mount Sinai Hospital for the
recruitment of participants and collection of vaginal swabs, as well as the volunteer
participants for their generous contribution of samples for the project.
I am lucky to have the great companion from members of the Bocking lab and the Lye lab.
Thank you all for providing such a supportive and enjoyable working environment. My
special thanks to Dr. Wei Li for mentoring me during times of technical difficulties, and my
deepest gratitude to Dr. Oksana Shynolva, for both your scientific insights and for offering
me emotional support. Many thanks to executive assistants, Ms Elaine Dwek and Ms Beverly
vii
Bessey, for being miracle creators. No matter how busy their bosses’ schedules were, you
can always accommodate my continuous requests to schedule meetings.
I would like to thank the Department of Physiology for being a haven of intellectual freedom,
and the wonderful staffs of the department, especially Ms Colleen Shea and Ms Rosalie Pang
for your continuous support with administrative issues. I would also like to acknowledge the
support of the funding agencies, the Genesis Research Foundation, the University of Toronto
and Mount Sinai Hospital, for supporting my education and recognizing the importance of
my project.
I am grateful for the company and steadfast support of my best friends, Sally Shi and Lydia
Zhou. Thank you girls for the wonderful moments we had together and for always believing
in me. Special thanks to Han Li, for taking care of me like a big sister.
Finally, I would like to dedicate my work to my beloved parents, who are my source of
strength. Thank you for your unconditional love and for your support in realizing my dreams.
Thank you for your guidance in life and for teaching me the most important aspects of life
are to have Peace, Happiness and Health.
viii
Table of Contents
3. Table of Contents
Abstract ............................................................................................................................... ii
Dedication ........................................................................................................................... iv
Acknowledgements ............................................................................................................. v
Table of Contents ............................................................................................................. viii
List of Abbreviations ........................................................................................................ xii
List of Figures .................................................................................................................. xiv
List of Tables ................................................................................................................... xvii
1 General Introduction ........................................................................................................ 2
1.1 Human Pregnancy and Parturition ......................................................................... 2
1.1.1 Anatomy of the Intra-uterine Environment ........................................................... 3
1.2 Mechanisms of Human Parturition ............................................................................ 8
1.2.1 Prostaglandins (PGs) ............................................................................................. 12
1.2.2 Matrix Metalloproteinase (MMPs) ....................................................................... 12
1.2.3 Cytokines and Chemokines ................................................................................... 15
1.3 Preterm Birth .............................................................................................................. 24
1.3.1 Epidemiology ......................................................................................................... 24
1.3.2 Etiology .................................................................................................................. 25
1.3.3 Infection Routes ..................................................................................................... 25
1.3.4 Infection and/or Inflammation- induced PTB ........................................................ 26
1.3.5 Current Treatment Approaches .............................................................................. 28
1.3.6 Animal Models of Preterm Birth ........................................................................... 29
1.4 Vaginal Microbiota and Preterm Birth ................................................................. 30
1.4.1 The human vaginal microbiota ........................................................................... 30
1.4.2 Bacterial Vaginosis ............................................................................................. 32
1.5 Probiotics .................................................................................................................. 33
1.5.1 Safety and Compliance ....................................................................................... 34
1.5.2 Lactobacilli .......................................................................................................... 35
1.6 Summary ..................................................................................................................... 37
ix
2. Rationale and Hypotheses ............................................................................................. 40
2.1 Rationale ...................................................................................................................... 40
2.2 Hypotheses ................................................................................................................... 41
3. Probiotic Lactobacillus rhamnosus GR-1 supernatant (GR-1 SN) prevents
Lipopolysaccharide (LPS)-induced preterm birth and reduces inflammation in
pregnant CD-1 mice. ............................................................................................................. 43
3.1 Introduction ................................................................................................................. 43
3.2 Material and Methods ................................................................................................ 44
3.2.1 Animals .................................................................................................................. 44
3.2.2 L. rhamnosus GR-1 supernatant preparation ......................................................... 45
3.2.3 Intra-uterine injection of LPS by mini-laparotomy ............................................... 45
3.2.4 Dose effect of LPS on PTB rate (Set 1) ................................................................. 45
3.2.5 Effect of GR-1 supernatant on the timing of LPS-induced PTB (Set 2) ............... 46
3.2.6 Effect of GR-1 supernatant on cytokines and chemokines (Set 3) ........................ 46
3.2.7 Fetal Sex ratios (Set 4) ........................................................................................... 47
3.2.8 Cytokine assay ....................................................................................................... 47
3.2.9 Maternal progesterone measurement ..................................................................... 47
3.2.10 Sex determination by PCR ................................................................................... 48
3.2.11 Statistical Analyses .............................................................................................. 48
3.3 Results .......................................................................................................................... 48
3.3.1 GR-1 SN reduced LPS-induced PTB (Set 2) ...................................................... 48
3.3.2 GR-1 SN attenuated LPS induced cytokines and chemokines (Set 3) .................. 49
3.3.3 Plasma progesterone (Set 3) .................................................................................. 50
3.3.4 Fetal sex ratio (Set 4) ............................................................................................. 50
3.4 Comment .................................................................................................................. 50
4. Oral Probiotic Lactobacillus rhamnosus GR-1 stimulates systemic and intrauterine
production of cytokines and chemokines and modulates the vaginal microbiota in
pregnant CD-1 mice. ............................................................................................................. 69
4.1 Introduction ................................................................................................................. 69
4.2 Material and Methods ................................................................................................ 71
4.2.1 Animals .................................................................................................................. 71
x
4.2.2 Lactobacillus rhamnosus GR-1 preparation .......................................................... 71
4.2.3 Intra-uterine injection of LPS by mini-laparotomy ............................................... 72
4.2.4 Oral administration of GR-1 by oral gavage ......................................................... 72
4.2.5 Effect of oral GR-1 on the timing of LPS-induced PTB (Set 1) ........................... 72
4.2.6 Effect of oral GR-1 on the gestational length (Set 2) ............................................ 73
4.2.7 Effect of oral GR-1 on cytokines and chemokines (Set 3) .................................... 73
4.2.8 Effect of oral GR-1 on the vaginal and cecal microbiota (Set 4) .......................... 73
4.2.9 Cytokine Assay ...................................................................................................... 74
4.2.10 Maternal progesterone measurement ................................................................... 74
4.2.11 DNA isolation and V6 ribosomal DNA PCR amplification ................................ 75
4.2.12 Sequencing ........................................................................................................... 75
4.2.13 Statistical Analysis ............................................................................................... 75
4.3 Results .......................................................................................................................... 76
4.3.1 Effect of oral GR-1 on the incidence of LPS-induced PTB and gestational length
(Set 1 and Set 2) .............................................................................................................. 76
4.3.2 Effect of oral GR-1 on the cytokines and chemokines (Set 3) .............................. 77
4.3.3 Maternal plasma progesterone (Set 3) ................................................................... 78
4.3.4 Vaginal and Cecal Microbiota (Set 4) ................................................................... 78
4.3.5 Effect of oral GR-1 on the vaginal microbiota (Set 4) .......................................... 79
4.3.6 Effect of oral GR-1 on the cecal microbiota (Set 4) .............................................. 79
4.4 Comment .................................................................................................................. 79
5. Effect of oral probiotics Lactobacillus rhamnosus GR-1® and Lactobacillus reuteri
RC-14® on the vaginal microbiota and cervico-vaginal cytokines and chemokines in
low risk pregnant women with an intermediate or high Nugent score. ......................... 112
5.1 Introduction ............................................................................................................... 112
5.2 Materials and Methods ............................................................................................. 114
5.2.1 Study Participants ................................................................................................ 114
5.2.2 Study groups and randomization ......................................................................... 114
5.2.4 Probiotic Strains ................................................................................................... 115
5.2.5 DNA Isolation and PCR amplification of V6 region of 16S rDNA .................... 116
5.2.6 Sequencing ........................................................................................................... 116
xi
5.2.7 Protein Extraction and Cytokine/Chemokine Multiplex Assay ........................... 117
5.2.8 Statistical Analyses .............................................................................................. 117
5.3 Results ........................................................................................................................ 118
5.3.1 Pre-randomization characteristics ........................................................................ 118
5.3.2 Pregnancy Outcomes ........................................................................................... 119
5.3.3 Compliance to the treatment protocol .................................................................. 119
5.3.4 Effect of oral probiotic GR-1 and RC-14 on the Nugent score ........................... 120
5.3.5 Effect of oral probiotic GR-1 and RC-14 on the vaginal microbiota .................. 120
5.3.6 Effect of GR-1 and RC-14 on the concentrations of cervico-vaginal
cytokines/chemokine .................................................................................................... 121
5.4 Comment ................................................................................................................... 122
6. General Discussion ....................................................................................................... 141
List of References ................................................................................................................ 152
List of Appendices ............................................................................................................... 178
xii
List of Abbreviations 11β-HSD-1 11β-Hydroxysteroid Dehydrogenase-1
ACTH Adrenocorticotropic Hormone
ANOVA Analysis of Variance
BV Bacterial Vaginosis
CAP Contraction-Associated Protein
COX-2 Cyclooxygenase-2
CRH Corticotropin-Releasing Hormone
CSF Colony Stimulating Factors
DC Dendritic Cells
dNK Decidual Natural Killer
ECM Extracellular Matrix
HPA Hypothalamic-Pituitary-Adrenal
IFN Interferon
IL Interleukin
JAK/STAT Janus Kinases and Signal Transducers and Activators of Transcription
KC KC Keratinocyte Chemo-attractant
Km Factor for converting mg/kg dose to mg/m2 dose
L.rhamnosus Lactobacillus rhamnosus
LPS LPS Lipopolysaccharide
MLCK MLCK Myosin Light-Chain Kinase
MMP MMP Matrix Metalloproteinase
MRS MRS de Man, Rogosa and Sharpe
NF-κB Nuclear Factor-Kappa B
NK Natural Killer
OT Oxytocin
OTR Oxytocin Receptor
PCR Polymerase Chain Reaction
PG Prostaglandin
PGDH Prostaglandin 15-Hydroxy Dehydrogenase
xiii
PGE2 Prostaglandin E2
PGF2α Prostaglandin F2α
PGHS Prostaglandin H Synthase
PPROM Preterm Premature Rupture of the Membranes
PTB Preterm Birth
PTB Preterm Delivery
PTL Preterm Labor
PTGS2 Prostaglandin-Endoperoxide Synthase 2
SD Standard Deviation
SDI Shannon Diversity Index
SEM Standard Error of the Mean
SMC Smooth Muscle Cell
Th T-helper
TL Term Labor
TLR Toll-Like Receptor
TNF-α Tumor Necrosis Factor-Alpha
xiv
List of Figures
Figure 1-1 Anatomy of the intra-uterine environment. ................................................................... 7 Figure 1-2 Proposed mechanisms that underlie relaxation and contraction of the
myometrium during pregnancy or labor. ............................................................................... 10 Figure 1-3 The proposed pathway of human parturition. ............................................................. 14 Figure 3-1 Experimental design to investigate the effect of GR-1 supernatant (GR-1 SN) on
the timing of LPS-induced PTB (Set 2). ................................................................................ 54 Figure 3-2 Experimental design to investigate the effect of GR-1 supernatant (GR-1 SN) on
the concentration of cytokines and chemokines in the maternal plasma, amniotic fluid and intra-uterine tissues (Set 3). ............................................................................................ 55
Figure 3-3 Cumulative frequency plot showing the percentage of pregnant CD-1 mice that
delivered at various gestational days following four different treatments (Set 2). ................ 56 Figure 3-4 Histogram showing concentrations of pro-inflammatory cytokines IL-1β, IL-6,
IL-12p40, IL-12p70, TNFα and IL-17 in the maternal plasma (n=10 animals per treatment group), myometrium (n=7), placenta (n=7) and amniotic fluid (n=10) of pregnant CD-1 mice (Set 3). .................................................................................................. 57
Figure 3-5 Histogram showing concentrations of chemokines CCL3, CCL4, CCL5 and
hematopoietic factor CSF2 in the maternal plasma (n=10 animals per treatment group), myometrium (n=7), placenta (n=7) and amniotic fluid (n=10) of pregnant CD-1 mice (Set 3). .................................................................................................................................... 58
Figure 3-6 Histogram showing concentrations of anti-inflammatory cytokines IL-4 and IL-
10 in the maternal plasma (n=10 animals per treatment group), myometrium (n=7), placenta (n=7) and amniotic fluid (n=10) of pregnant CD-1 mice (Set 3). ........................... 59
Figure 3-7 Histogram showing maternal plasma progesterone concentrations for different
treatment groups (Set 3). ........................................................................................................ 60 Figure 4-1 Probiotic Lactobacillus dose translation from a human dose to a mouse
equivalent dose based on the body surface area (Km) and weight. ....................................... 85
xv
Figure 4-2 Experimental design to investigate the effect of oral GR-1 on the timing of LPS-induced PTB (Set 1). .............................................................................................................. 86
Figure 4-3 Experimental design to investigate the effect of oral GR-1 on the gestational
length (Set 2). ......................................................................................................................... 87 Figure 4-4 Experimental design to investigate the effect of oral GR-1 on cytokines and
chemokines (Set 3). ............................................................................................................... 88 Figure 4-5 Experimental design to investigate the effect of oral GR-1 on the vaginal and
cecal microbiota (Set 4). ........................................................................................................ 89 Figure 4-6 Histogram showing the concentration of pro-inflammatory cytokine IL-1α, IL-1β,
IL-6, IL-17, IL-12p40, IL-12p70, TNFα and IFN-γ in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3). ............ 90
Figure 4-7 Histogram showing the concentration of pro-inflammatory cytokines IL-1α, IL-
1β, IL-6, IL-17, IL-12p40, IL-12p70, TNFα and IFN-γ in the fetal membranes, placenta, decidua and myometrium of pregnant mice that received saline and GR-1 at 109 cfu via oral gavage (Set 3). ................................................................................................................ 91
Figure 4-8 Histogram showing the concentration of anti-inflammatory cytokines IL-2, IL-4,
IL-10 and IL-13 in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3). ......................................................................... 92
Figure 4-9 Histogram showing the concentration of anti-inflammatory cytokines IL-2, IL-4,
IL-10 and IL-13 in the fetal membranes, placenta, decidua and myometrium of pregnant mice that received saline and oral GR-1 at 109 cfu (Set 3). ................................................... 93
Figure 4-10 Histogram showing the concentration of chemokines CCL2, CCL3, CCL4,
CCL5, CCL11, CXCL1 in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3). ................................................. 94
Figure 4-11 Histogram showing the concentration of chemokines CCL2, CCL3, CCL4,
CCL5, CCL11, CXCL1 in the fetal membranes, placenta, decidua and myometrium of pregnant mice that received saline and oral GR-1 at 109 cfu (Set 3). .................................... 95
Figure 4-12 Histogram showing the concentration of hematopoietic factors CSF2, CSF3 and
IL-3 in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3). ................................................................................ 96
xvi
Figure 4-13 Histogram showing the concentrations of hematopoietic factors CSF2, CSF3 and IL-3 in the fetal membranes, placenta, decidua and myometrium of pregnant CD-1 mice that received saline and oral GR-1 at 109 cfu (Set 3). ................................................... 97
Figure 4-14 Stacked barplots showing the vaginal and cecal bacterial compositions of
pregnant CD-1 mice that received either oral saline or GR-1. .............................................. 98 Figure 4-15 Scatterplot showing the Shannon diversity index (SDI) of the vaginal and cecal
microbiota of pregnant CD-1 mice. ....................................................................................... 99 Figure 5-1 Consort flow chart of pregnant women enrolled in the study. .................................. 126 Figure 5-2 Stacked bar plot showing the vaginal microbiota clustered by bacteria similarity
in pregnant women prior to treatment, at 13 weeks gestation (n=66). ................................ 127 Figure 5-3 Stacked bar plots showing the vaginal microbiota clustered by bacteria similarity
in pregnant women with a BV (n=24) or an intermediate (n=42) Nugent score prior to treatment, at 13 weeks gestation. ......................................................................................... 128
Figure 5-4 Stacked bar plots showing the vaginal microbiota across pregnancy clustered by
bacteria similarity in pregnant women who received either placebo (n=34) or probiotic (n=32) treatment. ................................................................................................................. 129
Figure 5-5 Scatterplot showing the Shannon Diversity Index (SDI) across gestations in
pregnant women who received either placebo or probiotic treatment. ................................ 130 Figure 5-6 Scatterplots showing the concentrations of cervico-vaginal cytokines IL-4, IL-10
and CSF3 across gestation in pregnant women who received either placebo or probiotic treatment. ............................................................................................................................. 131
Figure 6-1 Changes in sytemic and intrauterine cytokines after treatment with Lactobacillus
rhamnosus GR-1 supernatant or live bacteria. .................................................................... 149 Figure 6-2 LPS-induced sytemic and intrauterine cytokines that were dampened with GR-1
supernatant pretreatment. ..................................................................................................... 150
xvii
List of Tables
Table 3-1 Delivery outcome of pregnant CD-1 mice that delivered preterm following different doses of LPS intrauterine injection (Set 1). .......................................................................... 61
Table 3-2 Litter size and fetal weight of neonates born to pregnant CD-1 mice that received
different treatments (Set 2). .................................................................................................. 62 Table 3-3 Baseline cytokine and chemokine concentrations in the maternal plasma, myometrium,
amniotic fluid and placenta of pregnant CD-1 mice (Set 3). ................................................ 63 Table 3-4 Cytokine and chemokine concentrations in the maternal plasma of pregnant CD-1
mice following different treatments (Set 3). ......................................................................... 64 Table 3-5 Cytokine and chemokine concentrations in the myometrium of pregnant CD-1 mice
following different treatments (Set 3). .................................................................................. 65 Table 3-6 Cytokine and chemokine concentrations in the amniotic fluid of pregnant CD-1 mice
following different treatments (Set 3). .................................................................................. 66 Table 3-7 Cytokine and chemokine concentrations in the placenta of pregnant CD-1 mice
following different treatments (Set 3). .................................................................................. 67 Table 4-1 Delivery outcome of pregnant CD-1 following different treatments in Set 1. .......... 100 Table 4-2 Litter size and fetal weight of live term neonates born to pregnant CD-1 mice at term
that received different treatments in Set 1. ......................................................................... 101 Table 4-3 Hours to delivery, litter size and fetal weight of neonates born to pregnant CD-1 mice
that received saline or oral GR-1 (Set 2). ........................................................................... 102 Table 4-4 Summary table of cytokines and chemokines in the maternal plasma, amniotic fluid
and intrauterine tissues following varying doses of oral GR-1 treatment. ......................... 103 Table 4-5 Maternal plasma progesterone concentrations in pregnant CD-1 mice with varying
dose of GR-1 (Set 3) ........................................................................................................... 104 Table 4-6 Bacteria genera unique to the cecal and vaginal tissues of saline-treated pregnant CD-
1 mice. ................................................................................................................................. 105
xviii
Table 4-7 Bacteria genera present in both the cecal and vaginal tissues of saline-treated pregnant CD-1 mice. .......................................................................................................................... 106
Table 4-8 Bacteria at different taxonomic levels that have statistically significant higher
abundance in the vaginal tissues than in the cecal tissues of saline-treated pregnant CD-1 mice. .................................................................................................................................... 107
Table 4-9 Bacteria at different taxonomic levels that have statistically significant higher
abundance in the cecal tissues than in the vaginal tissues of saline-treated pregnant CD-1 mice. .................................................................................................................................... 108
Table 4-10 Bacteria at different taxonomic levels that decreased significantly with oral GR-1
treatment in the vaginal tissues of pregnant CD-1 mice. .................................................... 109 Table 4-11 Bacteria at different taxonomic levels that increased significantly with oral GR-1
treatment in the vaginal tissues of pregnant CD-1 mice. .................................................... 110 Table 5-1 Characteristics of pregnant women randomized at 13 weeks gestation. ................... 132 Table 5-2 Pregnancy outcomes. ................................................................................................. 133 Table 5-3 Compliance of women in the probiotic and placebo groups. .................................... 134 Table 5-4 Nugent scores of pregnant women across pregnancy in the probiotic and placebo
groups. ................................................................................................................................. 135 Table 5-5 The relative to mean abundance of vaginal bacterial species in pregnant women with a
BV (7-10) or an intermediate (4-6) Nugent score at 13 weeks gestation. .......................... 136 Table 5-6 The relative to mean abundance of vaginal bacteria species that decreased across
gestation in pregnant women treated with placebo or probiotics. ...................................... 137 Table 5-7 The relative to mean abundance of vaginal bacterial species that increased across
gestation in pregnant women treated with placebo or probiotics. ...................................... 138 Table 5-8 Summary table of cervico-vaginal cytokines and chemokines across gestation in
pregnant women who received either placebo or probiotic treatment. ............................... 139
1
Chapter One
General Introduction
Part of the contents of this chapter (Section 1.3 to 1.5) was published in Front Immunol.
2015 Feb;6:62 and appears here with the permission of the journal (authorization attached).
My role involves manuscript preparation.
2
Chapter 1
1 General Introduction
1.1 Human Pregnancy and Parturition There are four phases in human pregnancy: uterine quiescence (phase 0), contraction-
associated protein (CAP)-activated myometrium (Phase 1), uterotonins stimulated
myometrium (Phase 2) and uterine involution (Phase 3) (Challis et al., 2000).
During pregnancy, uterine quiescence (Phase 0) is maintained by high levels of signaling
molecules, including progesterone, relaxin and prostacyclin (Challis et al., 2000).
Progesterone, a steroid hormone produced by the placenta, dampens inflammation produced
by inflammatory cytokines and prostaglandins (PGs), which would otherwise
induce parturition prior to term (Parizek et al., 2014). In addition, progesterone suppresses
the production of estrogen and PGs, thereby reducing smooth muscle cell contractility
(Parizek et al., 2014). During pregnancy, progesterone receptor type B (PR-B) dominates
(Parizek et al., 2014). The binding of progesterone to PR-B promotes an anti-inflammatory
environment and maintains uterine quiescence (Tan et al., 2012). Prior to parturition,
functional progesterone withdrawal is observed when the expression of PR-A increases with
a concomitant decrease in the expression of PR-B (Tan et al., 2012). The inhibitory effect of
progesterone on estrogen, PGs and myometrial contraction is then removed (Mesiano et al.,
2002). Furthermore, mechanical stretch caused by the growing fetus results in an up-
regulation in the expression of CAPs including oxytocin receptors (OTR), connexin-43 (Cx-
43), PGF2a and its receptors (FP) (Gibb and Challis, 2002). The CAPs activate the
myometrium (Phase 1), making it receptive to stimulation by uterotonins such as OT and
PGs (Phase 2) (Gibb and Challis, 2002). This results in the production of forceful myometrial
contractions, essential for delivery of the fetus and the placenta (Gibb and Challis, 2002).
The fetus also secretes signaling molecules that determine the timing of parturition.
Activation of the fetal hypothalamic-pituitary-adrenal (HPA) axis results in an increased
3
production of fetal adrenal cortisol, which suppresses progesterone production and promotes
estrogen production (Marciniak et al., 2011). These mediators then promote uterine
contractions and initiate the inflammatory cascade leading to parturition (Marciniak et al.,
2011). Uterine involution (Phase 3), which occurs after the delivery of the fetus, is mediated
by the effect of OT (Challis et al., 2000).
1.1.1 Anatomy of the Intra-uterine Environment
A. Myometrium The human myometrium, comprised primarily of uterine myocytes, lies between the
endometrium (innermost) and the perimetrium of the uterine wall (Coad, 2011).
Myometrium produces several uterotonins and inflammatory cytokines, which stimulate the
circular smooth muscle layer of the myometrium to produce intense and synchronous uterine
contractions during labor (Shynlova et al., 2009). Animal studies revealed uterine myocytes
are highly plastic smooth muscle cells (SMCs), which undergo phenotypic changes from a
contractile state to a synthetic state, and proliferate during pregnancy (Shynlova et al., 2009).
Under the influence of high circulating levels of progesterone and increased mechanical
stretch from the fetus, myometrial SMCs proliferate by hypertrophy and remodel to
accommodate the growing fetus (Shynlova et al., 2009). When progesterone responsiveness
wanes near term, the myometrial SMCs switch from a synthetic state to a contractile state
and are sensitive to the stimulation of uterotonins (Shynlova et al., 2009). Postpartum (after
delivery), myometrium returns to a phenotype similar to its non-pregnant state (Shynlova et
al., 2009).
B. Decidua The decidua forms the maternal side of the fetal-maternal interface. The decidua parietalis
and decidua basalis contact the non-invasive chorion trophoblast cells and the invasive
extravillous trophoblast cells respectively (Coad, 2011) (Figure 1-1, page 7). Decidualization
4
is initiated by a rising level of progesterone, even in the absence of a conceptus, and is the
process whereby endometrial stromal cells near the spiral arteries undergo morphological,
biochemical, and functional changes into decidual stromal cells (DSCs) (Oreshkova et al.,
2012). The elongated endometrium stromal fibroblast cells differentiate into enlarged round-
shaped secretory DSCs, which can synthesize extracellular matrix components (laminin and
fibronectin), hormones, cytokines and matrix metalloproteinase (MMPs) (Oreshkova et al.,
2012). In early pregnancy, DSCs participate in the exchange of nutrients, gas and waste with
the developing embryo, until the placenta becomes fully functional (Coad, 2011). The DSCs
also ensure a controlled trophoblast invasion (Oreshkova et al., 2012). When decidualization
is absent, placenta accreta results (Jauniaux et al., 2012). DSCs contain high proportions of
resident leukocytes, and nearly 40% of the first trimester decidua is made up of leukocytes
(Houser et al., 2012). Decidual leukocytes are important in normal placental development
and the regulation of immune responses at the maternal-fetal interface (Houser et al., 2012).
Among these decidual leukocytes, nearly 60% are decidual Natural Killer (dNK) cells, 25%
are macrophages, 10-20% are T cells and the rest are dendritic cells (DCs) (Houser et al.,
2012). The primary role of dNK cells is to initiate vascular remodelling necessary to ensure
adequate placental blood flow (Wallace et al., 2012). Decidual macrophages and T cells
express inflammatory cytokines and chemokines, which activate and amplify the
inflammatory pathways leading to parturition (Houser et al., 2012). Women in term labor
(TL) have an accumulation of decidual macrophages in comparison to women at term not in
labor (Hamilton et al., 2012).
C. Placenta The human placenta is composed of extensive branching and densely packed chorionic villi
containing fetal blood vessels (Blackburn, 2012). The terminal villi, which make up the
majority of the placenta, are the sites for maternal-fetal exchange (Blackburn, 2012). The
stem or anchoring villi stabilize the villous tree and the intermediate villi are located between
the stem villi and the terminal villi (Blackburn, 2012). Specialized cells of the placenta are
called trophoblast cells, which comprise the outer layer of the blastocyst (Blackburn, 2012).
The human placenta contains 15-30 cotyledons, which are separations of the decidua basalis
5
divided by placental septa (Blackburn, 2012). The cotyledons contain many chorionic villi,
which are finger-like structures formed when the trophoblast cells undergo hyperplasia
during implantation (Blackburn, 2012). The placenta is in contact with both maternal and
fetal tissues. The outer layer of placental trophoblast cells is continuous with the decidua
basalis (Blackburn, 2012). On the fetal side, the placenta is covered by a thin membranous
structure called the chorionic plate that is continuous with the fetal membranes (Blackburn,
2012).
The intervillous space is filled with maternal blood, which is separated from the fetal
circulation by several layers of tissues (Blackburn, 2012). They are (1) the microvillous
membrane of the syncytiotrophoblast, (2) the syncytiotrophoblast cells, (3) the basal
membrane of the syncytiotrophoblast, (4) the connective tissue mesenchyme of the villus,
and (5) the epithelium of the fetal blood vessel (Blackburn, 2012). The inner mesenchymal
core of the chorionic villi contains the umbilical cords and is formed from extraembryonic
primitive mesoderm (Blackburn, 2012). Two umbilical arteries that spiral around the
umbilical vein deliver deoxygenated blood from the fetus to the placenta (Blackburn, 2012).
The arteries branch radially onto the chorionic plate and the chorionic vessels branch into
many villous lobular arteries, which branch further into smaller vessels (Blackburn, 2012).
This extensive branching makes the placenta an extensively vascularized organ.
The placenta serves both metabolic and endocrine functions. Gases, nutrients, and waste
products are exchanged across the endothelial cells between the fetus and the mother
(Blackburn, 2012). The placenta also synthesizes estrogen, progesterone, human chorionic
gonadotropin (hCG) and cytokines that contribute to either pregnancy quiescence or the
onset of parturition (Blackburn, 2012).
D. Fetal Membranes The fetal membranes (amnion, chorion, trophoblast and decidua) surround and protect the
developing fetus during pregnancy (Myatt and Sun, 2010) (Figure 1-1). The amnion is made
up of amniotic epithelium and amniotic mesoderm, which later divides into the basal
6
membrane (Coad, 2011). Adjacent to the amnion is the chorion, which is composed of
vascularized chorionic mesoderm and a basement membrane (Coad, 2011). The chorion is
separated from the decidua by extravillous trophoblast cells (Coad, 2011). The fetal
membranes contribute to amniotic fluid turnover, form a barrier between maternal and fetal
compartments, and produce signaling molecules that contribute to labor initiation (Myatt and
Sun, 2010). Locally produced mediators in the fetal membranes include PGs,
glucocorticoids, pro-inflammatory cytokines and surfactant proteins (Myatt and Sun, 2010).
The majority of PGs are produced in the fetal membranes and PG synthesis is segregated
from its metabolism in different compartments of the fetal membranes (Myatt and Sun,
2010). During pregnancy, PGs produced in the amnion and chorion by PG synthases (PGHS)
are metabolized by 15-hydroxy PG dehydrogenase (PGDH) in the chorion trophoblast
(Keelan et al., 2003). A limited amount of PGs reach the myometrium and uterine quiescence
is maintained. The fetal membranes also synthesize and metabolize glucocorticoids that
increase surfactant synthesis to promote fetal lung maturation, and in turn trigger labor
initiation (Myatt and Sun, 2010)..
E. Amniotic Fluid The amniotic fluid cushions the fetus from potential external trauma and maintains a constant
temperature in the uterus. The amniotic fluid also accommodates fetal movements, which are
important to musculoskeletal structure development (Brace and Wolf, 1989). In addition, the
amniotic fluid serves as a medium for the exchange of secreted cytokines, PGs, fetal adrenal
cortisol and surfactant proteins between the umbilical vessels and the fetus (Brace and Wolf,
1989). The amniotic fluid volume increases in pregnant women from an initial 1.5 ml at 7
weeks of gestation to 770 ml at 28 weeks of gestation (Brace and Wolf, 1989). The change in
the volume is minimal between 29 and 37 weeks of gestation, and after 34 weeks of
gestation, the volume decreases (Brace and Wolf, 1989).
7
Figure 1-1 Anatomy of the intra-uterine environment. The image is modified with permission from The New England Journal of Medicine: Goldenberg RL, Hauth JC, Andrews WW. (2000) Intrauterine infection and preterm delivery. 342 (20):1500-7. Copyright Massachusetts Medical Society.
Fetal membranes
Am
niotic epithelium
Am
niotic fluid
Basem
ent mem
brane
Com
pact Strom
al Layer
Fibroblast Layer
Intermediate S
pongy Layer Amnion
Chorionic m
esoderm
Basem
ent mem
brane
Chorion
Trophoblast
Decidua
Core of mesoderm
Multinucleated syntiocytotrophoblast
Mononucleated cytotrophoblast
Intervillous space (maternal blood)
Villous cytotrophoblast
Myometrium
Cervix
Vagina
Decidua basalis
Decidua parietalis
Placenta septum
Anchoring villus
Extravillous trophoblast
Endometrial vessels
Amniochorionic membrane
Fetal circulation
Amniotic cavity
8
1.2 Mechanisms of Human Parturition
Human parturition (labor), term and preterm, is driven by positive feed-forward cascades of
inflammation produced by increasing levels of PGs and inflammatory cytokines (Challis et
al., 2009). Labor is initiated by factors including uterine mechanical stretch, fetal endocrine
signals and intrauterine infection (Challis et al., 2009). The balance of pro and anti-
inflammatory cytokines, produced by CD4+ T helper (Th) cells, is important in predicting
pregnancy outcomes (Challis et al., 2009). In early pregnancy, a modest Th1 pro-
inflammatory environment promotes successful implantation and placentation (Wilczynski,
2005). As pregnancy progresses, there is a predominance of Th2 anti-inflammatory cytokines
including IL-4 and IL-10, which maintain uterine quiescence (Wilczynski, 2005). A
disruption of the Th1/Th2 balance favoring the predominance of Th1 pro-inflammatory
cytokines such as IL-1, IL-6, and TNFα may be responsible for some cases of PTL (Challis
et al., 2009).
A. Uterine Stretch Mechanical stretch imposed by the fetus increases the expression of CAPs and causes uterine
activation (Gibb and Challis, 2002). The CAPs promote increased myocyte contractility,
excitability and intercellular communication (Gibb and Challis, 2002). The myometrial cells
with an increase in the expression of CAPs are sensitized to uterotonin stimulation, which
leads to the production of coordinated and forceful contractions (Gibb and Challis, 2002)
(Figure 1-2, page 10).
During pregnancy, the myocytes are maintained in a relaxed state by the following factors:
(1) a high intracellular electrochemical potential, (2) an elevated level of intracellular cyclic
AMP (cAMP), and (3) actins in the globular form (Smith, 2007). During pregnancy, the
myometrial cell surfaces are abundant with β2 and β3-sympathomimetic receptors, which
promote the opening of potassium (K+) channels (Smith, 2007). The efflux of K+ leads to an
increase in the intracellular electrochemical potential, which decreases the likelihood of a
depolarization and reduces myocyte excitability (Smith, 2007). A high level of cAMP
9
activates protein kinase A (PKA) that enhances phosphodiesterase activity.
Phosphodiesterase dephosphorylates and inactivates the myosin light chain kinase (MLCK)
and causes calcium (Ca2+) re-uptake by the sarcoplasmic reticulum (SR) (Smith, 2007). The
intracellular Ca2+ can no longer bind calmodulin to form a complex that activates the MLCK
and causes myosin binding to actin, and the subsequent generation of uterine contractions
(Smith, 2007).
In response to the mechanical stretch at the time of labor, myocytes establish physical and
endocrine connections that promote coordinated and forceful uterine contractions. Tension
development is achieved when actins convert into filamentous forms and attach to the
underlying matrix via focal points in the cell membranes (Smith, 2007). An increase in gap
junctions such as connexin (Cx)-43 permits the rapid transmission of action potentials and
synchronous contractions over the entire uterus (Smith, 2007). With an increase in the
expression of receptors for PGE and PGF, the myometrium is more responsive to PGs. The
binding of PGs promotes the opening of ligand-gated calcium channels, which allow Ca2+
influx from extracellular space (Smith, 2007). Furthermore, the binding of OT to the OTR
activates phospholipase C and inositol triphosphate (IP3) (Smith, 2007). IP3 subsequently
promotes Ca2+ release from SR. An increase in intracellular Ca2+ concentration and a
decrease in K+ efflux due to reduced expressions of β2 and β3-sympathomimetic receptors at
labor, reduce the intracellular electronegativity and lead to depolarization (Smith, 2007).
The intracellular Ca2+ forms a complex with calmodulin and activates the MLCK (Smith,
2007). Subsequently, the MLCK phosphorylates the myosin light chain and promotes
ATPase activity, which enables myosin binding to actin and the development of uterine
contractions (Smith, 2007).
Increased mechanical stretch also causes an increase in PGs and inflammatory cytokines,
which in turn lead to the enhanced expression of PR-A (Jiang et al., 2012). PR-A, which
lacks an N-terminal-activating domain, represses the activation and activity of some PR-B
dependent genes (Madsen et al., 2004). The functional progesterone withdrawal removes the
inhibition on estrogen and PGs, and increases their bioavailability to induce uterine
contraction (Mesiano et al., 2002).
10
Figure 1-2 Proposed mechanisms that underlie relaxation and contraction of the myometrium during pregnancy or labor.
Reproduced with permission from The New England Journal of Medicine: Smith R (2007) Parturition. 356: 271-283. Copyright Massachusetts Medical Society.
11
B. Hypothalamic-pituitary-adrenal (HPA) axis High levels of circulating CRH produced by the periventricular nucleus in the fetal
hypothalamus and the placenta are associated with the timing of labor (Voltolini and
Petraglia, 2014). Furthermore, the level of circulating binding protein for CRH (CRHBP)
levels falls, increasing the bioavailability of CRH (Voltolini and Petraglia, 2014). Binding of
CRH to transmembrane G protein-coupled CRH type 1 receptor activates the fetal HPA axis
and stimulates the fetal anterior pituitary to produce adrenocorticotrophic hormone (ACTH)
(Voltolini and Petraglia, 2014) (Figure 1-3, page 14). ACTH causes the fetal adrenal gland to
release the glucocorticoid cortisol (Voltolini and Petraglia, 2014). The placenta regulates the
bioavailability of cortisol. During pregnancy, cortisol is converted into inactive cortisone by
placental 11β-Hydroxysteroid dehydrogenase 2 (11β-HSD2), and at labor, inactive cortisone
is converted into cortisol by placental 11β-HSD1 (Challis et al., 2000). In response to CRH,
the fetal adrenal gland also produces dehydroepiandrosterone sulphate (DHEAS), which is an
important substrate for placental estrogen synthesis (Voltolini and Petraglia, 2014). Elevated
fetal cortisol increases the production of surfactant protein A (SP-A) and phospholipids,
which stimulate fetal lung maturation. Furthermore, SP-A released into the amniotic fluid
activates macrophages and stimulates the production of inflammatory mediators in the
adjacent fetal membranes, which eventually lead to parturition (Smith, 2007). Fetal cortisol
and CRH potentiate myometrial contractions by increasing the expression of PG receptors
(Smith, 2007). Furthermore, fetal cortisol and CRH increase the synthesis of PGs by
prostaglandin endoperoxide H synthases (PTGS) or cyclo-oxygenase (COX)-2 expressed in
the amnion and chorion, and decrease the metabolism of PGs by prostaglandin
dehydrogenase (PGDH) expressed in the chorionic trophoblast cells (Smith, 2007). In turn,
PGs increase cortisol by upregulating placental 11β-HSD1 and downregulating 11β-HSD2
(Challis et al., 2000). Furthermore, CRH also stimulates the secretion of placental matrix
metalloproteinase (MMP)-9, which contributes to fetal membrane rupture and cervical
dilatation (Li and Challis, 2005).
12
1.2.1 Prostaglandins (PGs)
The production of prostaglandins (PG), comprised of 20-carbon chain unsaturated fatty acids,
starts with phospholipase A2 (PLA2) cleaving the membrane phospholipids to release
unesterified arachodonic acids (AA) (Keelan et al., 2003). Through the action of PTGS, AAs
are converted into endoperoxide products, which are ultimately converted into primary PGs
(PGE2, PGF2α, PGD2 and prostacyclin/PGI2) through a series of isomerase reactions (Keelan
et al., 2003).
The synthesis of PGs is regulated by the activity of constitutively expressed COX 1,
inducible COX2 and PG synthases, while the metabolism of PGs is regulated by PGDH
(Keelan et al., 2003). During pregnancy, high levels of 15-hydroxyprostaglandin
dehydrogenase metabolize PGs in the chorion, decidua, placenta, myometrium and cervix,
and maintain pregnancy quiescence (Olson and Ammann, 2007; Giannoulias et al., 2002).
The expression of 15-hydroxyprostaglandin dehydrogenase diminishes in the chorionic
trophoblast cells with the onset of parturition (Olson and Ammann, 2007), exposing the
decidua, cervix and myometrium to PGE2. Concomitantly, an increase in the expression of
COX2 in response to inflammatory stimuli in the amnion, choriodecidua and myometrium
(Slater et al., 1999a; Slater et al., 1999b), and an increase in the expression of microsomal
PGE synthases in the myometrium (Astle et al., 2007), lead to increased production of PGs.
Subsequently, elevated PGs either directly promote myometrial contractility or through the
stimulation of MMPs, cause fetal membrane rupture, cervical ripening and placental
detachment (Olson and Ammann, 2007).
1.2.2 Matrix Metalloproteinase (MMPs)
MMPs are zinc-dependent enzymes that catalyze the degradation of collagen constituted-
extracellular matrix of the cervix, fetal membranes, placenta and the uterus (Olgun and
Reznik, 2010). MMPs are involved in normal parturition as well as in infection-triggered
rupture of fetal membranes and preterm birth (PTB) (Maymon et al., 2001; Olgun et al.,
2010). An increase in the amniotic fluid level of MMP-3 is associated with term and preterm
13
parturition, and with microbial invasion of the amniotic cavity (Park et al., 2003). Mid-
trimester elevation of amniotic fluid MMP-8 is a risk factor for early spontaneous preterm
delivery (PTB) less than 32 weeks, and MMP-8 at a level higher than >23 ng/mL predicts
imminent PTB (Yoon et al., 2001). The non-specific MMP inhibitor, GM6001 reduces
endotoxin induced PTB in the mouse, suggesting that one or more MMPs are critical in the
pathogenesis of infection-associated PTB (Koscica et al., 2007).
14
Figure 1-3 The proposed pathway of human parturition.
During pregnancy (not in labor), high levels of prostaglandin dehydrogenase (PDGH) metabolize prostaglandins (PGs) and maintain pregnancy quiescence (Smith, 2007). At the time of labor, the expression of PGDH diminishes while the expression of PGHS-2 increases in response to elevated pro-inflammatory cytokines, exposing the intrauterine tissues to increasing levels of PGs. Placental corticotropin-releasing hormone (CRH) activates the fetal HPA axis and stimulates the fetal anterior pituitary to produce adrenocorticotrophic hormone (ACTH). ACTH causes the fetal adrenal gland to release the glucocorticoid cortisol. Furthermore, in response to CRH, the fetal adrenal gland produces dehydroepiandrosterone sulphate (DHEA-S), an important substrate for estrogen (E2) synthesis. Fetal cortisol and CRH increase the expression of PGs. Elevated PG promotes myometrial contractility, increases the expression of gap junctions (connexin-43), stimulates the expressions of matrix metalloproteinase (MMPs) and pro-inflammatory cytokines. Many positive feed-forward cascades underlie the process of parturition. The image is modified with permission from The New England Journal of Medicine: Goldenberg RL, Hauth JC, Andrews WW. (2000) Intrauterine infection and preterm delivery. 342 (20):1500-7. Copyright Massachusetts Medical Society.
Not in labor Labor
Connexin-43
Immune cells
Amniochorionic))membrane)
PGHS-2
PGDH
PG
PG
PG
PG
CRH
Pituitary
Lung
Adrenal
ACTH
Cortisol E2 DHEA-S
Positive Feedback
PG
Pro-inflammatory Cytokines/Chemokines
Anti-inflammatory Cytokines
MMP
Myometrial contractions
Cervical Dilatation
Fetal Membrane
rupture
15
1.2.3 Cytokines and Chemokines
Cytokines are small soluble proteins that function as signaling molecules in a paracrine or
autocrine fashion, and are produced mainly by activated immune cells in the presence of
antigens, microbial or viral products (Christiaens et al., 2008). The binding affinity between
cytokines and their receptors is usually high (Km = 1010 - 1012 M-1); therefore, very low
concentrations of cytokines (usually in picomolar) are sufficient to elicit a physiological
change (Mak, 2006). Cytokines are hydrophilic and bind to cell surface receptors to initiate
downstream intracellular signaling, which leads to altered cell functions (Mak, 2006).
Cytokines regulate the innate response, the adaptive response, and the growth and
differentiation of hematopoietic cells (Mak, 2006). One cytokine can cross-regulate other
cytokine(s) and/or their receptors in either an agonistic or an antagonistic fashion (Mak,
2006). This agonistic relationship creates a cascade of myometrial receptivity and a
coordinated action responsible for increased myometrial contractility during labor
(Christiaens et al., 2008). Anti-inflammatory cytokines have been observed to repress the
over-expression of pro-inflammatory cytokines (Christiaens et al., 2008).
Cytokines may be classified based on either their structure motifs or their physiological
functions. Structurally, interleukin (IL)-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-12,
IL-13, IL-15 and Interferon (IFN)-γ belong to the 4α helix family. CCL2, CCL3, CCL4,
CCL5 and CCL11 share the CC chemokine motif, while IL-8 and CXCL10 possess the CXC
chemokine motif (Mak, 2006). Alternatively, cytokines can be classified based on their
functions as pro-inflammatory cytokines, anti-inflammatory cytokines, chemokines or
growth factors (Mak, 2006). In this dissertation, cytokines are discussed based on their
general functions and their roles in pregnancy are outlined below.
The implantation of a blastocyst and placentation in early pregnancy are predominantly
pro-inflammatory processes (Dekel et al., 2014). As pregnancy progresses, the expression
of pro-inflammatory cytokines is inhibited by anti-inflammatory cytokines, and the
intrauterine environment switches to predominantly anti-inflammatory at the feto-
16
maternal interface (Challis et al., 2009). At the time of labor, a pro-inflammatory milieu
is predominant which promotes uterine contractions through the interaction with the PG-
signaling pathway (Challis et al., 2009). At each stage of pregnancy, inflammation is
tightly controlled. Excessive inflammatory responses can lead to adverse pregnancy
outcomes, including PTB, spontaneous abortion, fetal growth restriction, and hypertensive
disorders (Challis et al., 2009).
A. Pro-Inflammatory Cytokines
Interleukin-1 (IL-1) and IL-1 receptor antagonist IL-1 is produced by macrophages, neutrophils, epithelial cells and endothelial cells (Mak,
2006). Of the two isoforms of IL-1 (IL-1α and IL-1β), IL-1β is present in greater abundance
(Mak, 2006). IL-1β has been associated with the process of implantation, decidualization and
labor (Geisert et al., 2012) and is detected in the culture-conditioned media of
preimplantation human embryo (Baranao et al., 1997). Women who experience habitual
abortion have decreased expressions of IL-1β and IL-6 in the endometrium (von Wolff et al.,
2000). In the presence of steroid hormone, IL-1β induces the expression of Insulin like
growth factor binding protein 1, a marker of decidualization, in the baboon stromal
fibroblasts (Strakova et al., 2000). The output of cervico-vaginal IL-1β has been reported
to increase with approaching term labor (Imai et al., 2001), although a recent study did
not observe such an increase (Heng et al., 2014a).
IL-1 receptor antagonist (IL-1ra) binds to both IL-1 receptor type I and II, but does not lead
to a signal transduction; therefore, IL-1ra serves as a competitive inhibitor that limits IL-1-
induced inflammation (Arend et al., 1998). The bioavailability of IL-1ra is several thousand
times higher than IL-1, and the cervico-vaginal output of IL-1ra decreases significantly with
impending term labor (Heng et al., 2014a).
Interleukin-2 (IL-2) IL-2, produced primarily by T-helper lymphocytes type 1 (Th1), promotes the growth and
differentiation of lymphocytes, macrophages and oligodendrocytes (Mak, 2006). The role of
17
IL-2 in pregnancy and parturition is still unclear. IL-2 has been reported to inhibit IL-1β-
induced PGE2 production in human amnion cells, and in cultured chorion and decidua cells
(Coulan et al., 1993a, 1993b). The role of IL-2 in labor in unknown.
Interleukin-6 (IL-6) IL-6, which belongs to the family of gp130 cytokines, is produced by macrophages, T-cells,
mononuclear phagocytes, vascular endothelial cells and intra-uterine tissues (Mak, 2006). IL-
6 plays a role in acute phase reactions, hematopoiesis, differentiation and maturation of
immune cells (B cells, T cells and macrophages) (Mak, 2006). In pregnancy, IL-6 has been
suggested to be important in implantation, placentation and labor (Markert et al., 2011). Mice
deficient in IL-6 have reduced fertility and a reduced number of viable implantation sites
(Robertson et al., 2000). High levels of IL-6 have been detected in the invasive cytotropblast
cells (Das et al., 2002), and IL-6 has been shown to activate MMPs in the trophoblast
(Meisser et al., 1999), suggesting it might play a role in the process of trophoblast invasion.
High concentrations of IL-6 have been observed in the maternal plasma and amniotic fluid of
women in labor (Unal et al., 2011). Elevated maternal plasma IL-6, secreted in a pulsatile
fashion, is also associated with increased uterine contractility during the active phase of labor
(Papatheodorou et al., 2013).
Interleukin-12 (IL-12) IL-12 (or IL-12p70), a 70 kD heterodimer composed of p35 and p40 peptides, is produced
primarily by monocytes and macrophages (Mak, 2006). IL-12 is crucial for the
differentiation of Th0 cells into Th1 cells, which are capable of generating IFN-γ (Mak,
2006). IL-12 has been shown to limit trophoblast invasion by down regulating the expression
of MMPs and up-regulating their inhibitors, tissue inhibitor of metalloproteinase-1 in JEG-3
cells, possibly through the production of IFN-γ (Karmakar et al., 2004). In addition, IL-12
enhances the cytotoxicity of CD8+ T cells and NK cells, which play important roles in cell-
mediated immune response against potential pathogens (Freeman et al., 2012). Pregnant
women with an elevated plasma concentration of IL-12 and low plasma IL-18 have an
increased risk of PTL (Ekelund et al., 2008).
18
Interleukin-17 (IL-17) IL-17, a glycosylated homodimeric polypeptide, is produced by memory CD4+ T cells in the
peripheral blood, decidua and placenta (Nakashima et al., 2010; Pongcharoen et al., 2007).
IL-17 stimulates the production of IL-6, IL-8 and colony stimulating factor (CSF) 2 in
fibroblasts and endothelial cells (Mak, 2006). IL-17 also promotes the processes of
trophoblast invasion and angiogenesis, both of which are important in the establishment of
placental vasculature (Pongcharoen et al., 2006). The plasma levels of IL-17 increase in third
trimester healthy pregnant women (Martinez-Garcia et al., 2011).
Interferon-gamma (IFN-γ) IFN-γ, a type II interferon, is produced by mitogen-activated lymphocytes (Micallef et al.,
2014). It possesses anti-pathogenic and anti-proliferative properties (Mak, 2006). It promotes
pathogen elimination, possibly through the activation of macrophages and the subsequent
production of TNFα and IL-12 (Mak, 2006). IFN-γ, derived from dNK cells, inhibits
trophoblast cell growth and invasion in the mouse (Ain et al., 2003). In addition, IFN-γ is
important in the process of extravillous trophoblast invasion into human first trimester
decidua (Lockwood et al., 2014). However, high levels of IFN-γ have been associated with
miscarriage and inhibition of angiogenesis (Micallef et al., 2014). IFN-γ has been shown to
reduce the expression of COX-2 and the production of PGE2 in term and preterm placenta, in
keeping with functional withdrawal of IFN-γ being involved in labor (Hanna et al., 2004).
Tumor Necrosis Factor alpha (TNFα) TNFα, initially produced as a transmembrane prohormone, is activated after the N-terminal
76 amino acids are proteolytically cleaved by TNF convertase (Mak, 2006). TNFα is
produced by macrophages, lymphocytes, fibroblasts, neutrophils, endothelial cells and
intrauterine issues (Mak, 2006). TNFα binds to TNF receptor-1 and 2, and is involved in the
activation of cell death, cell proliferation and inflammation (Mak, 2006). TNFα is a major
pro-inflammatory cytokine that underlies the inflammatory process leading to the initiation
of labor (Christiaens et al., 2008). The concentration of TNFα in the amniotic fluid remains
low throughout human pregnancy and sharply increases at term labor (Hayashi et al., 2008).
In addition, TNFα induces the production of PGE2 in cultured human chorion, amnion and
19
decidual cells, as well as the expression of MMPs in cultured human chorion, myometrium
and cervical smooth muscle cells (Christiaens et al., 2008).
Mice lacking the genes for pro-inflammatory cytokine IL-6 have delayed parturition,
whereas mice with receptors for IL-1 and TNFα knockout are less susceptible to bacterially
induced PTL (Robertson et al., 2010; Hirsch et al, 2006). These findings suggest IL-1, IL-6
and TNFα are important in the pathogenesis of inflammation-associated labor.
B. Anti-inflammatory Cytokines
Interleukin-4 (IL-4) IL-4, also known as B-cell activating factor-1, is produced by T helper lymphocytes Type 2
(Th2), mast cells, basophils, eosinophils and intrauterine tissues (Mak, 2006). IL-4 is
important in the differentiation and activation of B cells, and the differentiation of naive Th0
cells into Th2 cells (Chatterjee et al., 2014). The production of IL-4 increases in the
peripheral blood mononuclear cells throughout pregnancy and low levels of IL-4 have been
suggested to contribute to higher incidences of infertility, spontaneous abortion, PTB, and
preeclampsia (Chatterjee et al., 2014). IL-4 antagonizes the production of IL-1β, TNFα and
PGE2 by human peritoneal macrophages (Hart et al., 1991).
Interleukin-5 (IL-5) IL-5, also known as eosinophil differentiation factor, is a homodimeric cytokine produced by
eosinophils, Th2 cells, NK cells and mast cells (Mak, 2006). IL-5 promotes the survival,
differentiation and activation of eosinophils (Mak, 2006). The role of IL-5 in pregnancy and
parturition is unknown.
Interleukin-9 (IL-9) IL-9, produced by Th2 cells, plays a role in T lymphocyte proliferation and hematopoiesis
(Mak, 2006). The role of IL-9 in pregnancy and parturition is unknown.
20
Interleukin-10 (IL-10)
IL-10, produced by lymphocytes, macrophages, dendritic cells, placental and decidual
mononuclear cells, is an important anti-inflammatory cytokine that contributes to uterine
quiescence during pregnancy (Cheng and Sharma, 2014). IL-10 inhibits the production of
many pro-inflammatory cytokines by inhibiting the Nuclear Factor-Kappa B (NF-κB)
signalling pathway and activating the Janus Kinases and Signal Transducers and Activators
of Transcription (JAK-STAT) and Phosphatidylinositol-3kinase (PI3K-Akt) signalling
pathways (Cheng and Sharma, 2014). IL-10 also blocks the expression of major
histocompatibility complex (MHC) class II and confers immune tolerance (Cheng and
Sharma, 2014). The placental expression of IL-10 is significantly reduced around the time of
labor (Cheng and Sharma, 2014).
Interleukin-13 (IL-13) IL-13, produced by Th2 cells, shares 30% sequence homology with IL-4 and therefore shares
similar anti-inflammatory properties (Mak, 2006). The concentration of IL-13 has been
detected in first trimester human trophoblast cells (Naruse et al., 2010). In human amnion-
derived WISH (Wistar Institute, Susan Hayflick) cells, IL-13 inhibits the production of IL-8
and PGE2 (Keelan and Mitchell, 1998).
Interleukin-15 (IL-15) IL-15 is produced by activated monocytes of human intrauterine tissues (Mak, 2006). IL-15
stimulates the growth of NK cells and activates peripheral blood T lymphocytes (Mak,
2006), and IL-15 also stimulates the production of angiogenic factors such as IFN-γ in
decidual NK cells (Murphy et al., 2009). Increased expression of IL-15 in human decidua has
been associated with recurrent miscarriage in women (Toth et al., 2010). The amniotic fluid
concentration of IL-15 is higher in pregnant women in the third trimester compared to the
second trimester (Klimkiewicz et al., 2012), and elevated IL-15 produced by human fetal
membranes has been found in in women who delivered preterm (Fortunato et al., 1998).
Among the anti-inflammatory cytokines, IL-10 is thought to be a key anti-inflammatory
modulator of labor. Exogenous administration of IL-10 to mice deficient in the IL-10 gene
reduces the incidence of PTB (Robertson et al., 2006).
21
C. Chemokines Chemokines are a subclass of cytokines that stimulate the migration and activation of
immune cells. Chemokines are classified into different groups based on the conserved
cysteine residues near the N terminus: (1) CC chemokines (CCL2, CCL3, CCL4, CCL5 and
CCL11), and (2) CXC chemokines (CXCL8 and CXCL10) (Mak, 2006).
CXCL8 CXCL8, also known as IL-8, is produced by monocytes, lymphocytes, fibroblasts, epithelial
cells and endothelial cells in response to stimulation by pro-inflammatory cytokines. CXCL8
recruits and activates primarily neutrophils, basophils and T cells (Mak, 2006). CXCL8
activates neutrophils to generate reactive oxygen radicals, which can lead to tissue damage.
In mice, CXCL8 is not present; instead, keratinocyte chemo-attractant (KC) recruits
neutrophils (Mak, 2006). The expression of CXCL8 increases in human myometrium,
choriodecidua and amnion, in association with labor (Elliott et al., 2000; Elliott et al., 2001)
CXCL10 CXCL10, also known as IFN-γ inducible protein 10 (IP-10), is produced upon stimulation
with IFN-γ (Mak, 2006). CXCL10 is a chemo-attractant for activated T cells (Mak, 2006).
The release of CXCL10 by dNK cells has been associated with the process of tissue building
and remodelling of the blood vessels during early pregnancy (Vacca et al., 2013). Elevated
expressions of CXCL10 mRNA and protein have been observed in choriodecidua from
women in term labor (Hamilton et al., 2013).
CCL2 CCL2, also known as monocyte chemotactic protein-1 (MCP-1), is produced by monocytes,
endothelial cells and intrauterine tissues (Mak, 2006). CCL2 is responsible for the
recruitment of monocytes and their differentiation into macrophages (Mak, 2006). CCL2
stimulates the production of several pro-inflammatory cytokines, and the expression of CCL2
increases in the myometrium in pregnant women at term labor (Esplin et al., 2005).
22
CCL3 and CCL4 CCL3 and CCL4, also known as macrophage inflammatory protein (MIP)-1α and -1β
respectively, are produced by macrophages, dendritic cells and lymphocytes (Mak, 2006).
CCL3 and CCL4 recruit granulocytes and activate neutrophils, eosinophils and basophils
(Mak, 2006). Both CCL3 and CCL4 can induce the synthesis and release of pro-
inflammatory cytokines IL-1, IL-6 and TNFα from activated macrophages (Mak, 2006)
CCL4 also promotes the migration of trophoblast cells (Hannan et al., 2006). The
concentration of CCL3 in the amniotic fluid (Dudley et al., 1996) and the concentrations of
CCL3 and CCL4 in the decidual leukocytes increase in pregnant women at term labor
(Hamilton et al., 2013).
CCL5 CCL5, also known as Regulated upon activation, normal T-cell expressed and secreted
(RANTES), is a chemotactic factor for T cells, eosinophils, basophils and lymphocytes
(Mak, 2006) The myometrial concentration of CCL5 is down-regulated in women with
prolonged pregnancy compared to women who delivered at term (Pabona et al., 2014). CCL5
is a pro-implantation factor as it increases regulatory T lymphocytes, favors the survival of
trophoblast cells, confers maternal tolerance of fetal allograft and induces apoptosis of
maternally activated T cells (Perez and Ramhorst, 2013). The role of CCL11 in labor is
unknown.
CCL11 CCL11, also known as Eotaxin, recruits eosinophils and stimulates the migration of the
extra-villous trophoblast (EVT) cells (Mak, 2006). The invasion by EVT cells into the
maternal uterine decidual vessels is important to establish adequate placental blood flow to
the fetus (Chau et al., 2013). The role of CCL11 in labor is unknown.
Chemokines are known to stimulate recruited immune cells to produce pro-inflammatory
cytokines, which further amplify inflammatory responses in labor (Christiaens et al., 2008).
IL-8, CXCL10, CCL2, CCL3 and CCL4 are elevated in the intrauterine tissues and/or
amniotic fluid of women in labor, whereas the role of CCL5 and CCL11 in labor is unclear.
23
D. Growth Factors
Interleukin-3 (IL-3) IL-3, produced by T lymphocytes, mast cells, eosinophils, neurons and astrocytes, promotes
growth and maturation of the hematopoietic progenitor cells into all cell types (Mak, 2006).
IL-3 also recruits mature basophils in allergic reaction and promotes the differentiation and
invasiveness of human trophoblast cells (Di Simone et al., 2000). The role of IL-3 in the
labor process is unknown.
Colony Stimulated Factor 2 (CSF2) and CSF3 CSF is secreted by activated T cells, macrophages, mast cells, NK cells, stromal cells,
endothelial cells and placental cells (Mak, 2006). CSF induces the proliferation and
differentiation of hematopoietic stem cells into monocytes and granulocytes, including
neutrophils, basophils and eosinophils (Mak, 2006). CSF2 acts on the bone marrow to
increase the generation of hematopoietic precursor cells, and stimulates them to differentiate
into granulocytes and monocytes (Mak, 2006). Both CSF2 and CSF3 play an important role
in early pregnancy by promoting normal embryonic development, successful implantation
and normal placentation (Robertson, 2007b; Furmento et al., 2014). CSF2 does not appear to
contribute to the labor process since the level of CSF2 in the amniotic fluid is not different
between women in term labor and those not in labor (Hayashi et al., 2006). In contrast, an
increase in the concentration of CSF3 has been detected in the cervix of women during labor,
suggesting a role of CSF3 in cervical remodeling (Sennstrom et al., 2000).
FGF basic FGF, expressed in the human placenta, is a potent inducer of angiogenesis (Mak, 2006).
Angiogenesis is important for normal implantation and placentation. FGF also plays a role in
the proliferation, differentiation, migration and invasion of human placental trophoblast cells
(Anteby et al., 2005). The role of FGF-b in labor remains unknown.
Platelet Derived Growth Factor-bb (PDGF-bb) PDGF-bb, a pro-angiogenic factor produced primarily by platelets, regulates cell growth and
division (Mak, 2006). PDGF-bb is important in the growth of uterine smooth muscle cells, as
24
well as vascular remodeling during pregnancy (Keyes et al., 1996). PDGF-bb has been
suggested to be important in the migration of endometrial stromal cells, which is important to
the implantation process (Schwenke et al., 2013). The role of PDGF-bb in labor remains
unknown.
Vascular Endothelial Growth Factor (VEGF) VEGF, a pro-angiogenic factor, is ubiquitously expressed in vascularized organs like the
placenta (Mak, 2006). VEGF stimulates the differentiation, proliferation and migration of
endothelial cells (Mak, 2006). In addition, VEGF is important to decidual growth and the
extravasation of white blood cells into the decidua, which subsequently contributes to the
inflammatory process leading to term labor (Elfayomy and Almasry, 2014).
The role of growth factors in the labor process remains to be elucidated.
1.3 Preterm Birth
1.3.1 Epidemiology
Human preterm birth (PTB), defined as delivery prior to 37 weeks of gestation, is observed
in approximately one in every ten pregnancies globally (Blencowe et al., 2012). Infants born
preterm have a mortality rate 40 times higher than term infants; moreover, premature babies
are at a greater risk of suffering from long-term health problems including cerebral palsy and
respiratory disorders (Oskoui et al., 2013; Brostrom et al., 2013). Raising a functionally
impaired premature infant places both emotional stress on parents and financial burden on
society. The cost of neonatal intensive care has been estimated to be at least $26.2 billion in
2005 in the United States (Behrman, 2007). Hospital inpatient admissions cost for children
born very premature (<28 weeks of gestation) during the first 10 years of their life is 20
times greater than for those born at term (Petrou, 2005). Obstetric interventions and the use
of assisted reproduction techniques account for the rise in PTB. Despite advances in the
healthcare system, PTB incidence has not decreased.
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1.3.2 Etiology
Risk factors that contribute to PTB include physiological aspects such as a previous history
of PTB, short cervical length, carrying a male fetus, the overall poor health status of the
mother, advanced maternal age, lower body weight, being a smoker and socioeconomic
factors such as educational background, social class, and race (Goldenberg et al., 2008a). The
etiology of PTB is multifactorial and largely unknown: 50% of the cases are idiopathic while
20-40% are iatrogenic, where the presence of conditions such as pre-clampsia or intrauterine
growth restriction (IUGR) requires delivery. The remaining 25-30% can be attributed to
intrauterine infection and/or inflammation (Goldenberg et al., 2008a).
1.3.3 Infection Routes
The uterine environment during pregnancy is not sterile, and microorganisms can invade the
uterus through the fallopian tube in a retrograde fashion from the abdominal cavity,
haematogeneously via the placenta and most commonly, ascending through the cervix and
vagina (Goldenberg et al., 2000). It has been proposed that once microorganisms reach the
maternal intrauterine tissues, they can secrete phospholipase A2 to act on membrane
phospholipids and through a series of catalytic reactions, primary PGs are formed (discussed
in Section 1.2.1). Bacterial endotoxin such as lipopolysaccharides (LPS) found on the outer
membrane of Gram-negative bacteria can stimulate PG production (Timmons et al., 2014).
Binding of LPS to Toll-like receptor 4 (TLR4), a specific pattern recognition receptor,
activates the NFкB pathway to induce an increase in pro-inflammatory cytokine and
chemokine gene expression in intrauterine tissues (amnion, chorion and decidua),
macrophages and endothelial cells. These inflammatory mediators in turn increase uterine
contractility by either directly upregulating PG production, or indirectly via altering levels of
enzymes involved in PG biosynthetic pathways such as increasing PTGS-2 in amnion and
decidual stroma cells, and decreasing PGDH in chorion trophoblast cells (Smith, 2007). Pro-
inflammatory cytokines stimulate each other as well as PG in a feed-forward cascade, such
that they stimulate and accelerate the production of each other, hence amplifying the
26
inflammatory response. Furthermore, pro-inflammatory cytokines enhance the expression of
MMPs, leading to fetal membrane rupture and cervical dilatation (Smith, 2007).
Fetal responses to infection and/or inflammation also play a role in PTL initiation.
Microorganisms can cross an intact chorioamniotic membrane and create intra-amniotic
inflammation, a condition termed the Fetal Inflammatory Response Syndrome (FIRS)
(Gotsch et al., 2007). Elevated IL-6 has been observed in the umbilical cord blood in preterm
neonates who had FIRS (Buhimschi et al., 2009). A recent study in asymptomatic women
with PPROM has found the umbilical cord blood level of lipopolysaccharide (LPS)-binding
protein (LBP), which can bind to plasma LPS, was significantly higher in preterm neonates
who had FIRS (Pavcnik-Arnol et al., 2014). Pathogenic microorganisms such as Ureaplasma
urealyticum and Mycoplasma hominis have been isolated from the umbilical cord blood of
very preterm newborns (Goldenberg et al., 2008b). Intrauterine infection has also been
associated with activation of the fetal hypothalamic-pituitary-adrenal (HPA) axis, increased
cortisol biosynthesis and decreased cortisol metabolism to inactive cortisone by 11β-HSD2
in the placenta (Gravett et al., 2000). Together, sustained stimulation of fetal cortisol on
placental CRH increases PG production, which in turn promotes uterine contractility and
PTL (Voltolini and Petraglia, 2014).
1.3.4 Infection and/or Inflammation- induced PTB
The etiology of PTB is multifactorial, with inflammation during pregnancy being one of its
causes. The predominance of pro-inflammatory cytokines has been proposed to be
responsible for the early onset of labor or PTL (Challis et al., 2009). The inflammatory
cascade is further amplified by an increase in the expression of chemokines, which attract
decidua leukocytes to produce additional pro-inflammatory cytokines (Hamilton et al., 2013).
The production of various cytokines has been studied in the amniotic fluid, cervico-vaginal
secretions and maternal plasma. Levels of IL-1β, IL-6, IL-8 and TNFα are elevated in
amniotic fluid and cervical fluid of women at risk of PTL, especially those with intra-
amniotic infection (El-Bastawissi et al., 2000; Hitti et al., 2001; Jun et al., 2000; von
27
Mincwitz et al., 2000; Holst et al., 2011). CCL3, CCL4, CCL5 in the amniotic fluid and
CCL2 in the cervical fluid are also significantly higher in PTL women with microbial
invasion of the amniotic cavity (Holst et al., 2011). Elevated levels of IL-6 are found in the
amniotic fluid and umbilical vein of infants born to mothers with chorioamnionitis (Holst et
al., 2011; Chaiworapongsa et al., 2002).
High levels of circulating plasma IL-1β, IL-6 and IL-8 have been observed in women with
PPROM in the presence of chorioamnionitis at 22-36 weeks gestation (von Minckwitz et al.,
2000). Increased levels of plasma TNF-α, IL-12 and IL-18 are also detected in women at risk
of recurrent spontaneous PTB (Vogel et al., 2007). However, recent studies have found IL-6
in the amniotic fluid and cervico-vaginal fluid, but not in plasma, are associated with
spontaneous PTB (Wei et al., 2010). It appears the presence of cytokines and chemokines at
the maternal–fetal interface, including intrauterine tissues, amniotic fluid or cervico-vaginal
fluid, are more representative of the pathology of PTB than are levels in maternal plasma.
Anti-inflammatory cytokines maintain pregnancy quiescence by inhibiting the production of
pro-inflammatory cytokines and PGs (Challis et al., 2009). IL-10 expression in the placenta
is lower in women who give birth preterm with chorioamnionitis compared to samples
obtained from women who underwent elective terminations in their second trimester of
pregnancy (Hanna et al., 2006). The same finding has been observed in women in term labor
with chorioamnionitis compared to women at term not in labor (Hanna et al., 2006). Mid-
trimester amniotic fluid concentrations of IL-10 are not different between preterm and term
delivery (Puchner et al., 2011), while cervico-vaginal levels of IL-4 and IL-10 are often
below the level of detection using current assays (Vogel et al., 2007). There is an association
between elevated plasma IL-10 with an increased risk of preeclampsia or intrauterine growth
restriction (Ferguson et al., 2014). Overall, the positive and negative predictive values of any
single specific cytokine or chemokine for PTB is limited (Menon et al., 2014) although the
examination of interactions with a multifactor dimensionality reduction analysis between
multiple cytokines within maternal–fetal compartments, rather than a single cytokine, may
better predict the risk of PTB (Bhat et al., 2014). Other factors that need to be taken into
account when analyzing cytokine profiles include ethnicity of the study population, maternal
28
body mass index (BMI), a previous history of PTB, whether anti-inflammatory medications
were taken and psychological status (Velez et al., 2008; Cator et al., 2014). For instance,
compared to women who deliver at term, amniotic fluid levels of IL-1β and TNF-α were
higher in African American women, but not in Caucasian women, who delivered preterm
(Velez et al., 2008).
1.3.5 Current Treatment Approaches
A non-invasive diagnostic test with a high positive predictive value and a high negative
predicative value is needed to differentiate between true and false PTL. Recently, Heng et al
discovered that a set of nine genes, together with maternal clinical data, could accurately
predict whether 70% of participants would or would not have a spontaneous PTB within 48
hours of hospital admission. This method for the diagnosis of PTL outperformed the
traditional fetal fibronectin test (Heng et al., 2014b).
The efficacy and safety of interventions to prevent PTB are largely unsatisfactory. The
efficacy of drugs that act as antagonists or inhibitors of oxytocin receptors, PGHS-2,
prostaglandin PTGFR receptors, or phosphodiesterase (PDE4) are yet to be determined
(Papatsonis et al., 2013; Lopez et al., 2007). Though effective, the safety of treatment with
progesterone and progestational agents remains unclear (Jayasooriya and Lamont, 2009;
O’Brien and Lewis., 2009). Antibiotics have been proposed to prevent infection-mediated
PTB; however, antibiotic treatment has limited success at preventing PTB, yielding mixed
results (Subramaniam et al., 2012; Oliver and Lamont, 2013). In practice, the use of
antibiotics to reduce PTB is limited to women with abnormal genital tract biota and
administration has to be early in pregnancy (< 22 completed weeks of gestation) before
substantial inflammatory damage occurs (Oliver and Lamont, 2013). The use of
metronidazole might even increase the incidence of PTB (Shennan et al., 2006). Current
interventions of infection-mediated PTB are aimed at treatment rather than prevention for the
management of PTB. Since intrauterine infection may remain asymptomatic until PTL or
premature rupture of membranes (Goldenberg et al., 2000), safe and effective prophylactic
intervention may be more appropriate.
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1.3.6 Animal Models of Preterm Birth
Animal models are essential research tools for investigating pathways that promote preterm
parturition and for testing potential therapeutic interventions. Mammalian animal models of
PTB include mouse, rat and rabbit. In these species, involution of the corpus luteum and a
subsequent decline in maternal plasma progesterone precedes the onset of labor, which is not
observed in humans (Elovitz and Mrinalini, 2004). Similarly, in the sheep model of PTB, a
decrease in progesterone production and an increase in estradiol production as a result of
fetal cortisol-induced synthesis of placental enzymes eventually lead to parturition (Elovitz
and Mrinalini, 2004). However, in non-human primates and in the human, a functional
progesterone withdrawal precedes the process of parturition (Elovitz and Mrinalini, 2004).
The mouse has been extensively used to study human PTB because the mechanisms of
murine parturition share many similarities with human parturition, including the pro-labor
roles played by pro-inflammatory cytokines, chemokines, PGs and MMPs. In addition to
being inexpensive, small in size, having a short gestational period (19-20 days) and the
ability to tolerate surgery, the mouse confers advantages such as the possibility of genetic
manipulation to help discern the pathways involved in parturition (Elovitz and Mrinalini,
2004). Genetically manipulated mice that are deficient in key genes promote parturition
defects. By studying these mice, some of the pathways involved in parturition have been
found to be redundant for term labor (Elovitz and Mrinalini, 2004). Elovitz et al (2003)
developed an intrauterine approach for the investigation of LPS-induced PTL in CD-1 mice.
A localized model of intrauterine inflammation or infection is clinically useful since most
women with PTL do not display symptoms of systemic illness such as significant increases
in white blood cell counts, C-reactive protein or temperature (Goldenberg et al., 2008a). A
localized intrauterine infection/inflammation using intrauterine injection of LPS mimics
more accurately what is most commonly observed in the human. In mice, this method results
in high rates of preterm delivery with little or no maternal mortality (Elovitz et al., 2003).
30
1.4 Vaginal Microbiota and Preterm Birth
1.4.1 The human vaginal microbiota
The vaginal microbiota composition is dynamic throughout a woman’s life. Before puberty,
it is dominated by anaerobic bacteria (Farage and Maibach, 2006). Rising estrogen levels at
puberty lead to an increase in mucosal glycogen production whose metabolized substrates
support vaginal colonization with lactobacilli (Spear et al., 2014). This is one reason the
vagina is highly colonized by lactobacilli during the reproductive years and pregnancy
(Romero et al., 2014a; Ravel et al., 2011). At menopause, lactobacilli abundance decreases
coinciding with a reduction in circulating estrogen concentration (Gupta et al., 2006;
Hummelen et al., 2011).
Lactobacilli are Gram-positive, facultative anaerobic bacteria, whose adherence to the
vaginal mucosal epithelia appears to form an important line of defense against potential
pathogens (Othman et al., 2007). In the vast majority of pregnant healthy women, lactobacilli
dominate (Romero et al., 2014a; Aagaard et al., 2012). Several important aspects of the
vaginal microbiota have been uncovered recently, particularly by sequencing PCR-amplified
universal 16S ribosomal DNA (rDNA): (1) The healthy vaginal microbiota is dominated by a
few Lactobacillus species (Lamont et al., 2011); (2) The detection of L. iners, Atopobium
vaginae and BV-associated bacteria 1, 2 and 3 (BVAB), is apparent in women with BV
(Lamont et al., 2011; Verstraelen et al., 2004; Fredricks et al., 2005).
The 16S ribosomal RNA gene is highly conserved in prokaryotic bacteria and is most widely
targeted in vaginal microbiome studies (Romero et al., 2014a, Romero et al., 2014b, Gloor et
al., 2010), although the cpn60 gene (Chaban et al., 2014) and the rpoB gene have also been
studied (Vos et al., 2012). Various methods are available to identify bacteria using the 16S
rRNA gene. These include denaturing gradient gel electrophoresis (DGGE), fluorescence in
situ hybridization (FISH), terminal-restriction fragment length polymorphism (T-RFLP),
quantitative polymerase chain reaction (qPCR) and microarray. However, these detection
methods often target specific bacteria and do not provide sufficient resolution to characterize
31
microbial communities (Ling et al,. 2010). High-throughput sequencing technologies such as
454 pyrosequencing and Illumina sequencing provide greater sequencing depth for the
identification of bacterial taxa and their relative abundance (Ling et al., 2010). There are nine
hyper-variable regions (V1 to V9), separated by the conserved regions, in the 16S rRNA
gene. Sequencing these short variable region(s) provides sufficient taxonomic information
and allows identification to the species level. It has been shown that full-length sequencing
missed 58% of the genera identified by V6 (Huse et al, 2008).
Several variable regions have been used in human vaginal microbiome studies, including V1-
V2 (Romero et al., 2014a), V3-V5 (Walther-Antonio et al., 2014), and V6 (Gloor et al.,
2010). There are both pros and cons to using each of the variable regions for the study of
human vaginal microbiome. For microbiome studies in this thesis, I chose the V6 region as it
provides high distinguishing power for Lactobacillus spp. in the vagina (Gloor et al., 2010),
since one of my goals is to determine the relative abundance of vaginal Lactobacillus spp.
after exogenous lactobacilli administration. However, it is important to recognize a limitation
to using the V6 region such as the inability to detect Mycoplasma hominis, Ureaplasma
parvum, and Ureaplasma urealyticum (Gloor et al., 2010).
Although relatively few 16S ribosomal DNA (rDNA) studies have been used with samples
from pregnant women, indications are that the microbiota does fluctuate during this time.
Some researchers have suggested that there are up to five different community state types
(CSTs) of bacteria, clusters generated based on similarity in vaginal bacterial composition, in
asymptomatic pregnant and non-pregnant women (Romero et al., 2014a; Ravel et al., 2011).
Three of the CSTs (I, II, III) are dominated by Lactobacillus spp., namely L. iners, L.
crispatus, or L. jensenii and/or L. gasseri. Two others, CST IV-A and CST IV-B have a low
relative abundance of Lactobacillus spp. and are composed of species within the genera
Peptoniphilus, Anaerococcus, Corynebacterium, Finegoldia and Prevotella (CST IV-A), and
Atopobium, Sneathia, Gardnerella, Ruminococcaceae, Parvimonas and Mobiluncus (CST
IV-B) (Romero et al., 2014a). Such studies have suggested that the vaginal microbiota
composition of pregnant women has a higher abundance of L. vaginalis, L. crispatus, L.
32
gasseri and L. jensenii, but lower CST IV-B bacteria, and is more stable than non-pregnant
women (Romero et al., 2014a; Walther-Antonio et al., 2014; Aagaard et al., 2012), with L.
crispatus in particular, promoting stability (Verstraelen et al., 2009). This remains to be
verified, but it may be due to hormonal changes. With advancing gestational age, the relative
abundance of Lactobacillus spp. increases while that of anaerobic or strict-anaerobic
microbial species decreases (Romero et al., 2014b).
1.4.2 Bacterial Vaginosis
BV is a polymicrobial dysbiosis, characterized by an alteration in the endogenous vaginal
microbiota with an absent or decreased proportion of lactobacilli and dominance of G.
vaginalis, Prevotella bivia, Mobiluncus spp., Mycoplasma hominis and A. vaginae
(Schwebke et al., 2014; Ugwumadu, 2002). In many clinical units, the diagnosis of BV
involves using a Gram stain Nugent scoring system with or without the Amsel criteria (a
vaginal pH > 4.5, an amine fishy odour when vaginal fluid is mixed with potassium chloride,
the presence of clue cells) (Nugent et al., 1991). A Nugent score of 7-10 is seen
microscopically as a near absence of rod shaped lactobacilli and a high abundance of
pathogenic morphotypes is considered BV (Nugent et al., 1991). Sequencing of the vaginal
microbiota of women with BV reveals a diverse array of bacteria, including the presence of L.
iners (Fredricks et al., 2005; Jackobsson and Forsum, 2007). Improvement in diagnostic
accuracy for BV can be accomplished by using a DNA level of ≥109 copies/mL for G.
vaginalis and ≥108 copies/mL for A. vaginae (Menard et al., 2008).
The prevalence of BV can vary between populations, but it remains common during
pregnancy, where it is associated with a 40% increase in the risk of PTB (Ugwumuda, 2002).
Women with an abnormal vaginal biota in their first trimester of pregnancy have a higher
risk of delivering preterm (Donders et al., 2009). Although an earlier Cochrane Review
(McDonald et al., 2007) suggested that antibiotic treatment of abnormal vaginal biota
(intermediate biota or BV) before 20 weeks of gestation may reduce the risk of PTB, a recent
Cochrane Review concluded that antibiotic treatment of BV does not reduce the risk of PTB,
33
regardless of when (before 20 weeks or after 20 weeks of gestation) the treatment is given
(Brocklehurst et al., 2013). Some of these organisms possess sialidase activity, which has
been associated with an increased risk of PTB (Smayevsky et al., 2001). Sialidases are
hydrolytic enzymes that play a role in down-regulating the innate response by degrading
immunoglobin-A (IgA), and it has been used in some diagnostic kits for this reason. Higher
LPS concentrations, mostly from P. bivia (Aroutcheva et al., 2008), and the concentrations of
pro-inflammatory cytokines IL-1β, IL-6 and IL-8 are elevated in the cervico-vaginal fluid of
pregnant women with BV (Mitchell and Marrazzo, 2014).
In African American and Hispanic women, a higher abundance of Mycoplasma spp. and a
lower abundance of BVAB3 is associated with an increased risk of PTB in the second
trimester (Wen et al., 2014). This is unlikely due to race per se, but rather cultural and social
influences. Other pathogens, such as Leptotrichia, Sneathia, BVAB1 and Mobiluncus spp
appear in higher abundance prior to 16 weeks gestation in women with a previous history of
PTB and who deliver preterm (Nelson et al., 2014). Yet, such findings are not universal, and
other studies, albeit small, report no difference in the vaginal microbial composition between
women who have a spontaneous PTB and those who deliver at term (Romero et al., 2014b;
Hyman et al., 2014).
1.5 Probiotics
Probiotics are defined as "live microorganisms which when administered in adequate
amounts, confer a health benefit on the host" (FAO/WHO, 2001). A number of meta-
analyses of clinical trials with probiotics have confirmed that probiotics are both safe and
effective for the treatment and/or prevention of numerous infectious and/or inflammatory
diseases (Goldenberg et al., 2013; Yang et al., 2014a; Grin et al., 2013). Lactobacillus and
Bifidobacterium are the most commonly studied probiotics. Bifodobacteria are present in
intestinal biota, but they can also be detected in the vagina. Lactobacilli play a potential
beneficial role in human reproduction and maintenance of healthy urinary and reproductive
tracts (Reid et al., 2015).
34
Probiotics are used to treat many gastrointestinal diseases including necrotizing enterocolitis
and ulcerative colitis. A systematic review of randomized, controlled trials reported a
decrease in the incidence of necrotizing enterocolitis with probiotic lactobacilli and/or
bifidobacteria supplementation in preterm and very low birth weight neonates (Deshpande et
al., 2010). Probiotic Bifidobacterium breve and galacto-oligosaccharide improves the clinical
condition in patients with ulcerative colitis (Ishikawa et al., 2011). Probiotic yogurt
containing a combination of Lactobacillus rhamnosus GG, Bifidobacterium lactis
and L. acidophilus reduces the incidence of antibiotic-associated diarrhea in children (Fox et
al., 2015). Prenatal supplementation of probiotic bifodobacteria to the mothers and
postnatally to the infants decreases the risk of developing atopic dermatitis in infants
(Enomoto et al., 2014).
The use of antibiotics to treat BV in non-pregnant and pregnant women remains the method
of choice, unchanged for many decades, and still too often ineffective. Metronidazole and
clindamycin, by far the most commonly used agents, do not restore vaginal lactobacilli
abundance, which may account for relapses in some women; and prolonged use promotes the
development of drug resistance. The need for new treatments for BV that restore microbiota
homeostasis and acidity without undesirable side effects has led investigators to study
probiotics. Human studies have provided evidence that probiotic lactobacilli can reduce BV
recurrence and increase lactobacilli abundance in the vagina of non-pregnant women (Reid et
al., 2003a; Homayouni et al., 2014). The use of lactobacilli as an adjuvant therapy to
antibiotics also shows promise in lowering BV recurrence rates (Bodean et al.,
2013). Indeed, the adjunctive use of L. rhamnosus GR-1 and L. reuteri RC-14 with
metronidazole improves the cure of BV (Maritinez et al., 2009; Anukam et al., 2006).
1.5.1 Safety and Compliance
Probiotic intervention in pregnancy is generally acceptable with good compliance among
pregnant women (Lindsay et al., 2014). A recent meta-analysis of randomized clinical trials
found that the use of probiotics Lactobacillus and Bifidobacterium during pregnancy had no
35
effect on the incidence of Caesarean section, birth weight, or gestational age and there were
no adverse effects (Dugoua et al., 2009).
1.5.2 Lactobacilli
Lactobacilli are gram-positive facultative anaerobic bacteria that dominate the vaginal
microbiota of women of reproductive age (Ravel et al., 2011). Probiotic lactobacilli are used
most commonly to maintain healthy vaginal and urogenital tracts.
1.5.2.1 Route of Administration
Oral administration of 109 - 1011 colony-forming units (cfu) of lactobacilli is the standard
dose believed to be required for passage through the intestine and subsequent improvement
of gut and vaginal health (Othman et al., 2007; Homayouni et al., 2014; Morelli et al., 2004;
Reid, 2001a). There are many variables that influence vaginal colonization by lactobacilli
including glycogen levels, substances used in vaginal washing, the use of antibiotics and the
ability of lactobacilli to produce substances such as hydrogen peroxide (Vallor et al., 2001;
Mirmonsef et al., 2014). The oral administration of L. acidophilus and L. bifidus has been
reported to be more effective than the vaginal route in reducing BV occurrence in antibiotic-
treated non-pregnant women (Bodean et al., 2013). However, the probiotic composition of
the oral capsule was different from the vaginal capsule (L. rhamnosus, L. acidophilus, S
thermophilus and L. bulgaricus) in that study, and the potential mechanism seems unclear.
Furthermore, the treatment duration was longer for patients who received the oral capsule
than those who received vaginal capsules (Bodean et al., 2013). An advantage of the oral
route is that it may reduce pathogen ascendance from the rectum to perineum and vagina,
while some women may perceive the intra-vaginal approach to be the more invasive
instillation of microbes.
36
1.5.2.2 Potential Mechanisms of Action
L. rhamnosus GR-1 and L. reuteri RC-14 (GR-1 and RC-14) persist up to 19 days in the
human vagina following intra-vaginal administration (Gardiner et al., 2002). Exogenous
lactobacilli colonization appears to be transient and lactobacilli exert their anti-pathogenic
properties indirectly via a number of mechanisms. These include the production of
antimicrobial substances, competitive exclusion with pathogenic bacteria and fungi,
acidification of the vagina, and modulation of the immune system (Reid and Bocking,
2003b). Endogenous lactobacilli maintain the vaginal pH <4.5 by metabolizing glycogen
secreted by vaginal mucosal epithelia and produce lactic acid, which is a potent microbicide
against potential reproductive tract infections (O’Hanlon et al., 2013). The acidic
environment of a healthy vagina creates a hostile environment for BV-associated pathogens
while favoring lactobacilli growth (O’Hanlon et al., 2013; Borges and Teixeira, 2014). It
may also help to prevent viruses, such as HIV, from infecting the host (Petrova et al., 2013).
The anti-inflammatory property of lactobacilli is important in control of mucosal and
systemic inflammation (Kemgang et al., 2014). L. rhamnosus GR-1 supernatant (GR-1 SN)
enhances IL-10 and colony stimulating factor 3 (CSF3) production in mouse macrophages
(Kim et al., 2006). In primary human placental trophoblast cells, GR-1 SN increases IL-10
and CSF3 production via JAK/STAT and MAPK pathways; down-regulates LPS-induced
TNFα output through c-Jun-N-terminal kinases (JNKs) inhibition and increases the
expression of the PG metabolizing enzyme PGDH in a sex-dependent fashion (Yeganegi et
al., 2009; Yeganegi et al., 2010; Yeganegi et al., 2011).
The effect of lactobacilli on the immune system and their vaginal colonization ability are
species and strain specific. In the mouse gastrointestinal (GI) tract, L. plantarum and L.
rhamnosus GG exacerbate inflammation and the development of DSS-induced colitis while
L. paracasei is protective (Mileti et al., 2009). In the human vagina, L. rhamnosus GR-1 and
L. reuteri RC-14 (GR-1 and RC-14) but not the intestinal probiotic L. rhamnosus GG persists
up to 19 days following intra-vaginal administration of either GR-1 and RC-14 or GG
(Gardiner et al., 2002). Intra-vaginal instillation of L. rhamnosus GR-1 up-regulates some
37
antimicrobial activity in premenopausal women (Krijavainen et al., 2008). A combination of
B. bifidum, B. infantis, L. acidophilus, L. casei, L. salivarius and Lactococcus lactis has been
reported to provide a wider antimicrobial spectrum and greater stimulation of IL-10
production along with suppression of pro-inflammatory cytokines in cultured human
peripheral blood mononuclear cells compared to the individual strains (Timmerman et al.,
2007). A combination of Bacteriocin like inhibitory substances (BLIS) from the L.
rhamnosus L60 and L. fermentum L23 can reduce the growth of group B streptococcal
isolates obtained from pregnant women more effectively than each Lactobacillus strain alone
(Ruiz et al., 2012).
Lipoteichoic Acid (LTA) on the cell surface of lactobacilli can also stimulate macrophages to
secrete immune-mediators. Improved anti-inflammatory activity in a murine model of colitis
in vivo has been observed when LTA is either removed or modified (D-alanylation)
(Grangette et al., 2005; Claes et al., 2010; Mohamadzadeh et al., 2011). The supernatant of
lactobacilli also has anti-inflammatory properties in cultured human placental trophoblast
cells, decidual cells, monocytes and macrophages (Yeganegi et al., 2009; Yeganegi et al.,
2010; Yeganegi et al., 2011; Li et al., 2014; Lin et al., 2008). These studies imply that the
administration of supernatant from lactobacilli may promote desirable effects and represent
an alternative for the prevention and treatment of inflammatory disorders, such as some cases
of PTB. The identification of these bioactive metabolite(s) remains to be achieved.
1.6 Summary
Bacterial vaginosis, which is characterized by a depletion of lactobacilli in the vaginal
microbiota of pregnant women, contributes to an increased risk of PTB (Donders et al.,
2009). Bacterial endotoxin induced over-expression of pro-inflammatory cytokines and
chemokines stimulate the onset of PTL (Challis et al., 2009). Probiotic Lactobacillus
rhamnosus GR-1 has been shown to possess anti-inflammatory properties in cultured human
intra-uterine tissues (Yeganegi et al., 2009; Yeganegi et al., 2010; Yeganegi et al., 2011; Li
et al., 2014) and lactobacilli also have the ability to reverse BV in non-pregnant women
(Reid et al., 2003a). The role of lactobacilli in immune regulation and modulation of the
38
vaginal microbiota in pregnant women with BV remains unknown. Furthermore, the
potential of lactobacilli as a prophylactic therapy for PTB has not been directly examined.
This thesis evaluated the potential of both Lactobacillus rhamnosus GR-1 and L. reuteri RC-
14 live bacteria and its supernatant in the prevention of PTB in a mouse model. In addition,
the effects of live Lactobacillus rhamnosus GR-1 bacteria on the reversal of BV, the
concentration of cytokines and chemokines and the vaginal microbiota in pregnant women
diagnosed with an intermediate or high Nugent score were also investigated.
39
Chapter Two
Rationale and Hypotheses
40
Chapter 2
2. Rationale and Hypotheses
2.1 Rationale Preterm birth (PTB) occurs in 11% of all pregnancies worldwide with premature infants at a
higher risk of developing adverse long-term health outcomes (Blencowe et al., 2012; Oskoui
et al., 2013; Brostrom et al., 2013). Inflammation is one of the major contributing factors to
both infection-mediated PTB and spontaneous PTB (Challis et al., 2009). Antibiotic
administration to prevent PTB has been unsuccessful.
Probiotics, defined as “live microorganisms which, when administered in adequate amounts,
confer a health benefit on the host”, have been used to treat inflammatory conditions in the
gastro-intestinal and genito-urinary tracts (FAO/WHO, 2001; Reid et al., 2015).
Lactobacillus spp. are commensal to the human vagina and intestinal tracts. Lactobacilli can
modulate immune responses, reduce pathogenic adherence and/or produce bacteriocins to
discourage pathogen growth (Reid and Bocking., 2003b). Pro-inflammatory cytokines and
chemokines contribute to the onset of PTB in both humans and animals. Previous studies
demonstrate that L. rhamnosus GR-1 supernatant has anti-inflammatory properties in
cultured human intra-uterine tissues (Yeganegi et al., 2009; Yeganegi et al., 2010; Yeganegi
et al., 2011; Li et al., 2014).
Since the most common route of intrauterine infection is thought to be ascending through the
vagina, I induced localized inflammation and PTB with intra-uterine LPS injection. I
investigated the effect of L. rhamnosus GR-1 supernatant on lipopolysaccharide (LPS)-
induced PTB and concentrations of cytokines and chemokines. Since intra-uterine tissues and
circulating leukocytes are potential sources of cytokines, outputs of cytokines and
chemokines were measured in the maternal plasma, amniotic fluid as well as various intra-
uterine tissues.
41
Bacterial Vaginosis, characterized by the absence of lactobacilli, has been associated with an
increase in the risk of PTB (Donders et al., 2009). Oral Lactobacillus rhamnosus GR-1 and
L. reuteri RC-14 reduce the recurrence of bacterial vaginosis (BV) by restoring the
indigenous lactobacilli in the vagina of non-pregnant women (Reid et al., 2003a). It remains
to be determined whether Lactobacillus rhamnosus GR-1 and L. reuteri RC-14 have a
potential beneficial effect on pregnant women with BV.
I evaluated the potential of using live Lactobacillus rhamnosus GR-1 bacteria and its
supernatant as prophylactic treatments for the prevention of PTB in a mouse model. I also
investigated the effect of live Lactobacillus rhamnosus GR-1 bacteria on the reversal of BV,
the concentrations of cervico-vaginal cytokines and chemokines and the vaginal microbiota
in pregnant women diagnosed with an intermediate or high Nugent score.
2.2 Hypotheses
I hypothesize that
(a) An intra-peritoneal administration of L. rhamnosus GR-1 supernatant (GR-1 SN)
reduces the incidence of LPS-induced PTB, as well as systemic and intrauterine
cytokine and chemokine concentrations in pregnant CD-1 mice (CHAPTER 3).
(b) Oral administration of live L. rhamnosus GR-1 bacteria reduces LPS-induced PTB,
lowers systemic and intrauterine cytokine and chemokine concentrations and alters
the vaginal and cecal microbiota of pregnant CD-1 mice (CHAPTER 4).
(c) In pregnant women with an intermediate or BV Nugent score on vaginal gram stain
smears, oral administration of L. rhamnosus GR-1 and L. reuteri RC-14 will
I. return an abnormal Nugent score to a normal Nugent score,
II. reduce the cervico-vaginal concentrations of pro-inflammatory cytokines and
chemokines and,
III. alter the vaginal microbial profiles (CHAPTER 5)
42
Chapter Three
Probiotic Lactobacillus rhamnosus GR-1 supernatant (GR-1 SN) prevents
Lipopolysaccharide (LPS) -induced preterm birth and reduces inflammation in
pregnant CD-1 mice.
The contents were published in Am J Obstet Gynecol. 2014 Jul;211(1): 44.e1-12 and appear
here with the permission of the journal (authorization attached). My role involved
experiment design, conduct and result analyses as well as manuscript preparation.
43
Chapter 3
3. Probiotic Lactobacillus rhamnosus GR-1 supernatant (GR-1 SN)
prevents Lipopolysaccharide (LPS)-induced preterm birth and
reduces inflammation in pregnant CD-1 mice.
3.1 Introduction Preterm birth (PTB) occurs in 11% of all pregnancies worldwide with premature infants at a
higher risk of developing adverse long-term health outcomes (Blencowe et al., 2012;
Brostrom et al., 2013; Oskoui et al., 2013). Inflammation is a contributing factor to both
infection-mediated PTB as well as spontaneous PTB, and the most common route of
infection is thought to be ascending through the vagina (Goldenberg et al., 2000; Goldenberg
et al., 2008a). In this study, I administered lipopolysaccharide (LPS) to pregnant CD-1 mice
as a model for both infection and inflammation-associated PTB since LPS activates Toll-like
receptor 4 mediated inflammatory pathways (Elovitz et al., 2003.; Koga and Mor, 2010).
Antibiotic administration to prevent PTB has been unsuccessful (Subramaniam et al., 2012),
possibly since they do not replenish vaginal lactobacilli. In addition, prolonged antibiotic use
promotes resistant bacterial strains (Beigi et al., 2004).
Probiotic, defined as “live microorganisms which, when administered in adequate amounts,
confer a health benefit on the host”, have been used to treat inflammatory conditions in the
gastro-intestinal and genito-urinary tracts (FAO/WHO, 2001; Reid et al., 2015; Othman et
al., 2007). Probiotic lactobacilli, a genus commensal to human vagina and intestinal tracts,
reduce the recurrence of bacterial vaginosis (BV) in non-pregnant women (Reid et al.,
2003a), and are associated with a 40% increase in the risk of PTB (Donders et al., 2009).
Lactobacilli can modulate immune responses, reduce pathogenic adherence and/or produce
bacteriocins to discourage pathogen growth (Reid and Bocking, 2003b). Our previous studies
have also demonstrated that L. rhamnosus GR-1 supernatant have anti-inflammatory
44
properties (Yeganegi et al., 2009; Yeganegi et al., 2010; Yeganegi et al., 2011; Li et al.,
2014; Kim et al., 2006).
Cytokines play a pivotal role in PTB in both humans and animals and the predominance of
anti- over pro-inflammatory cytokines is important to pregnancy maintenance (Challis et al.,
2009). Cytokines can act as regulators of the innate and adaptive immune systems as well as
hematopoiesis (Elgert, 2009). Intra-uterine tissues and circulating leukocytes are potential
sources of cytokines (Young et al., 2002). Chemokines can attract decidual leukocytes,
which in turn recruit additional pro-inflammatory cytokines to amplify the inflammatory
cascade (Esplin et al., 2005; Hamilton et al., 2013).
The effect of lactobacilli on PTB and inflammatory responses in pregnant CD-1 mice in vivo
is unknown. In this study, I test the hypothesis that GR-1 supernatant will attenuate LPS
induced PTB and also profile systemic and intra-uterine immune markers in LPS-treated
mice with and without GR-1 SN treatment. Lastly, I examine whether the effect of GR-1 SN
on LPS-induced PTB is dependent on changes in maternal plasma progesterone or sex of the
fetus.
3.2 Material and Methods 3.2.1 Animals Female HSD:ICR (CD-1) outbred mice (8-12 weeks old; Harlan Laboratories) were bred; the
morning of vaginal plug detection was designated Gestational Day (GD) 1. The normal
gestational length of pregnant CD-1 mice is 19-20 days. Animals were handled in accordance
with guidelines of the Canadian Council for Animal Care and all procedures were approved
by the Animal Care Committee of Toronto Center for Phenogenomics (Animal Use Protocol
#0164). Animals were housed in a pathogen-free, humidity controlled 12 h light:12 h dark
cycle animal facility with free access to food and water. I performed 4 sets of independent
experiments and used a total of 155 animals.
45
3.2.2 L. rhamnosus GR-1 supernatant preparation
GR-1 was grown for 8-10 hours anaerobically at 37oC in de Man, Rogosa, and Sharpe
(MRS) broth (BD, Ontario) to an optical density of ~0.9 at 600nm (representing ~108 -109
cfu/mL of bacteria), and centrifuged at 3000 rpm for 10 min at 25oC. The supernatant (GR-1
SN) was filtered twice with 0.22 µm filters to remove residual bacteria. I used 200µL of GR-
1 SN, representing ~2x107 -108 cfu/mL of bacteria for intraperitoneal (i.p) injection, since in
previous studies, i.p injection of ~107 cfu of GR-1 increased anti-inflammatory cytokine G-
CSF production in mice (Martins et al., 2011).
3.2.3 Intra-uterine injection of LPS by mini-laparotomy
Intrauterine injection of LPS was given via mini-laparotomy on GD 15 as previously
described (Elovitz et al., 2003). Mice were anesthetized with isoflurane inhalation and given
analgesic buprenorphine (0.1mg/kg). An incision (~1cm) was made to expose the lower
segments of the uterine horns. Saline (100µL) or LPS (Escherichia coli 055:B5, Sigma-
Aldrich, St. Louis) dissolved in 100µL saline was injected between the two lowest
gestational sacs of either the left or right uterine horn. Fascia and skin were closed with 4.0
vicryl sutures and staples respectively. Mice were housed in individual cages.
3.2.4 Dose effect of LPS on PTB rate (Set 1) A dose response for LPS was established using saline, 25µg, 65µg, 125µg or 250µg of LPS
(n=10 per group) to determine the lowest dose that produced 100% PTB. PTB was defined as
the delivery of at least one pup within 48 hours of LPS injection. LPS 125µg was the lowest
dose that resulted in almost 100% PTB and was therefore chosen for subsequent experiments.
46
3.2.5 Effect of GR-1 supernatant on the timing of LPS-induced PTB (Set 2)
Mice were randomly assigned to receive Saline, GR-1 SN, LPS 125µg or LPS 125µg+GR-1
SN (n=9-17 per group, Figure 3-1). Animals were given two doses of 200 µL GR-1 SN or
saline intra-peritoneally, at 24 hours (GD14) and 15-30 minutes (GD15) prior to intrauterine
LPS or saline injection (GD15). In our preliminary experiments, I did not observe any effect
of orally administered GR-1 SN on PTB, and I chose not to administer GR-1 vaginally
because of concerns of possible vaginal leakage. Given our previous experiments whereby
i.p injection of GR-1 SN caused immune responses in non-pregnant mice as well as in vitro
(Martins et al., 2011; Yeganegi et al., 2009), I chose to give GR-1 SN i.p in these studies.
Saline was given to mice in the control group since I did not observe an effect with MRS
pretreatment on LPS-induced PTB in preliminary experiments. Animals were monitored
hourly until term for the delivery of pups, and the time of delivery was recorded.
3.2.6 Effect of GR-1 supernatant on cytokines and chemokines (Set 3)
Mice were randomly assigned to receive Saline, GR-1 SN, LPS 125µg or LPS 125µg+GR-1
SN (n=10 per group, Figure 3-2). The majority of animals in Group 2 delivered between 10-
15 hours after LPS administration and therefore animals in Group 3 were euthanized with
carbon dioxide 8 hours post LPS or saline injection for the collection of amniotic fluid,
placental and myometrial tissue. Prior to euthanization, maternal blood was collected from
anesthetized mice by cardiac puncture and plasma was obtained by centrifugation at 5,000 xg
for 15 min at 4oC. Amniotic fluid was pooled from all gestational sacs and centrifuged to
remove any cellular debris. Placental tissue was separated from decidua and fetal membranes
in ice-cold PBS and pooled from all fetuses. Myometrium was separated from decidua and
endometrium by scraping (Shynolva et al., 2013). All samples were flash-frozen in liquid
nitrogen and stored at -80 oC. In a subgroup of animals (n=5), I measured progesterone
concentrations in maternal plasma.
47
3.2.7 Fetal Sex ratios (Set 4)
Mice received LPS 125µg +GR-1 SN (n= 16) and were monitored for PTB. After delivery of
at least one pup, animals were euthanized and individual fetal tails were collected and
genotyped to determine fetal sex. For animals that delivered at term, tails from the neonates
were collected. Fetuses and neonates were euthanized by cold anesthesia on ice followed by
decapitation.
3.2.8 Cytokine assay
Cytokine and chemokine concentrations were determined using a mouse 23-multiplex
cytokine assay (Appendix I, Biorad, Ontario) on a Luminex 200 cytometer and Bioplex HTF
(Bio-Rad). The assay measured concentrations of interleukin (IL)-1α, IL-1β, IL-2, IL-3, IL-4,
IL-5, IL-6, IL-9, IL-10, IL-12p40, IL-12p70, IL-13, IL-17, IFN-γ, CXCL 1, CCL2, CCL3,
CCL4, CCL5, CCL11, TNFα, CSF2, and CSF3. Data analysis was performed using Bio-Plex
Manager (version 5.0, Bio-Rad) and results are presented as concentrations (pg/mL). I
randomly chose 7 animals to measure the concentration of cytokines and chemokines in the
intra-uterine tissues. Tissues were crushed and homogenized in EDTA-free protease inhibitor
containing RIPA lysis buffer (1mL per 0.5g of tissue). Homogenized samples were left on
ice for 45 minutes before being centrifuged at 12,000 xg for 15 minutes at 4°C to collect the
supernatant. Protein concentration was measured by Bradford assay kit (Bio-Rad, Ontario)
with bovine serum albumin as standard. 250µg of total protein were used for the
measurement of cytokines/chemokines in myometrium and placenta tissues.
3.2.9 Maternal progesterone measurement
Plasma progesterone concentration was measured with an Enzyme Immunoassay kit
(Appendix II, Cayman Chemical Co, Michigan). Samples were diluted (400 v/v) with EIA
buffer and assayed in duplicate. The intra and inter-assay coefficients of variation were 6.9 %
and 12.1 % respectively.
48
3.2.10 Sex determination by PCR
DNA extracted from individual fetal tails was amplified using Sigma REDExtract-N-Amp
Tissue PCR kit (XNAT, Sigma, St Louis). DNA isolated was amplified using primers
Jarid1d FWD: GCACAGGACCTCAGGGACCCAG, Jarid1d REV:
CAGAGGCATTCATCGATGAGG, Jarid 1c REV2:
TGAGTTGGTACGACGAAGCTGCAG (Clapcote and Roder, 2005). PCR amplified
products were resolved using a 2% agarose gel. Double bands (331 and 302bp) were seen for
males and a single band (331bp) for females. Sex ratio was calculated by expressing the
number of male fetuses over total number of fetuses.
3.2.11 Statistical Analyses
Statistical analysis was carried out using SigmaStat (version 3.5). Comparison of PTB rate
was made with Fisher exact analyses (two tailed). Unpaired Student’s t test, two tailed, was
used to compare sex ratios. Comparison of cytokine, chemokine and progesterone
concentrations in multiple groups were carried out with One-way ANOVA or ANOVA on
Ranks followed by Student Newman Keuls test as post hoc test. Data were tested for
normality and equal variance and data are expressed as mean values ± SEM. Data were
adjusted for false discovery rate using Benjamini Hochberg procedure and an adjusted p-
value of p<0.05 was considered statistically significant.
3.3 Results 3.3.1 GR-1 SN reduced LPS-induced PTB (Set 2) Intrauterine injection of LPS on GD15 resulted in dose-dependent PTB within 48 hours
(Table 3-1). GR-1 SN significantly reduced the rate of PTB from 94% (16/17) in the LPS
125µg group to 57% (8/14) in the LPS 125µg+GR-1 SN group (p=0.028, Figure 3-3). One
mouse in the LPS 125µg-treated group had all fetuses resorbed at term. Four out of six mice
in the LPS125µg+GR-1 SN group delivered live pups at term, and in the remaining two mice,
49
all fetuses had resorbed at term. All animals in the saline and GR-1 SN control groups
delivered live pups at term. The mean litter size was 13.0 ± 0.89 and the mean weight per
pup was 1.72 ± 0.02 grams in the saline group, and these were not different in mice in other
treatment groups (p>0.05, Table 3-2).
3.3.2 GR-1 SN attenuated LPS induced cytokines and chemokines (Set 3) Baseline pro-inflammatory cytokine concentrations (IL-1α, IL-1β and IL-12p70) and LPS-
induced increases (IL-1α, IL-1β, IL-6, IL-17) were highest in the myometrium (Table 3-3).
Compared to other compartments, baseline chemokine concentrations (CXCL1, CCL2,
CCL3, CCL4, CCL5, CCL11) were low in the maternal plasma but their production
increased markedly (CCL2, CCL4, CCL5) with LPS stimulation (57-186 fold) (Table 3-3).
LPS-increased both IL-4 and IL-10 concentrations in all compartments except amniotic fluid
(Table 3-3). Among all cytokines measured, IL-6 and CSF3 had the greatest increases
following LPS treatment (Table 3-3).
LPS significantly increased IL-1α, IL-6, IL-12p70, TNFα; CCL2, CCL3, CCL4, CCL5,
CSF2 and CSF3 in the maternal plasma (Table 3-4), myometrium (Table 3-5), amniotic fluid
(Table 3-6) and placenta (Table 3-7). LPS also significantly increased IL-1β, IL-10, IL-
12p40, IL-17, CCL11, IL-13, IFN-γ and IL-3 in the maternal plasma and myometrium (Table
3-4 and 3-5) but not in the amniotic fluid (Table 3-6). These cytokines/chemokines were also
significantly elevated in the placenta following LPS except for IFN-γ and CCL11 that were
below detection limits (Table 3-7). LPS increased IL-2, IL-4, IL-5, IL-9 and CXCL1 to
various degrees in tissues and fluids (Table 3-4, Table 3-5, Table 3-6 and Table 3-7). IL-5 in
the amniotic fluid and IL-9 in the plasma and amniotic fluid were below the limits of assay
detection (Table 3-4 and Table 3-6).
Pretreatment with GR-1 SN significantly attenuated the LPS-induced elevation in pro-
inflammatory cytokines IL-1β, IL-6, IL-12p40, TNFα as well as chemokines CCL4 and
CCL5 in the plasma and IL-6, IL-12p70, IL-13, IL-17, TNFα in the myometrium (p<0.05,
Figure 3-4 and 3-5). LPS-induced increases in all other cytokines, including IL-10, remained
50
elevated with GR-1 SN treatment (Figure 3-6). GR-1 SN treatment significantly decreased
the LPS-induced elevation in IL-6, TNFα, CCL3 and CCL4 in the amniotic fluid; and IL-6
and IL-12p70 in the placenta (p<0.05, Figure 3-4 and 3-5). GR-1 SN alone increased
placental IL-4 and IL-10 (p<0.05; Figure 3-6). There was no difference in the production of
cytokines and chemokines between saline and GR-1 SN treated mice in the plasma,
myometrium, placenta or amniotic fluid (Figure 3-4, Figure 3-5 and Figure 3-6).
3.3.3 Plasma progesterone (Set 3)
Maternal plasma progesterone concentration (saline: 68 ± 4.6 ng/ml) was significantly
reduced by LPS 125µg (42 ± 7.4 ng/ml) as well as LPS 125µg + GR-1 SN (38 ± 4.5 ng/ml)
treatment (p< 0.05; Figure 3-7). Mice that received GR-1 SN alone maintained high
concentrations of plasma progesterone (59.1 ± 1.7 ng/ml) comparable to that of the saline
group (p>0.05) (Figure 3-7). In order to confirm that these concentrations are identical,
however, a sample size of 6 mice in each group would be required (power analysis test).
With 5 animals, as shown here, I did not demonstrate a statistically significant difference.
3.3.4 Fetal sex ratio (Set 4)
Among mice that received both LPS 125µg and GR-1 SN, there was no difference in the
percentage of male fetuses in mice that delivered preterm (55 ± 4.9%) with a litter size 11.0
±0.84 (n=5) compared to those that delivered at term (49 ± 4.3%) with a litter size of 10.7
±0.54 (n=11).
3.4 Comment
In this study, I have shown that Lactobacillus rhamnosus GR-1 supernatant (GR-1 SN)
reduces LPS-induced PTB and dampens both systemic and intrauterine inflammation in
pregnant CD-1 mice. I profiled multiple cytokines and chemokines in the maternal plasma,
myometrium, placenta and amniotic fluid following LPS alone, and in combination with GR-
1 SN. The reduction of LPS-induced PTB by GR-1 SN was independent of changes in
51
circulating progesterone and fetal sex ratios.
I have focused our studies on the beneficial effects of the L. rhamnosus GR-1 strain, which
decreases the recurrence risk of BV in non-pregnant women and modulates immune
responses (Reid et al., 2003a; Yeganegi et al., 2009; Martins et al., 2011). L. rhamnosus also
has anti-microbial activity against pathogens including E. coli (Reid and Bocking, 2003b).
Analysis of the genomes and phenotypes of 100 L. rhamnosus strains has demonstrated the
presence of two major geno-phenotypes, A and B with different carbohydrate metabolism
and adherence properties and differing beneficial effects (Douillard et al., 2013). Geno-
phenotype B L. rhamnosus strains, but not strains in geno-phenotype A, display traits that
allow them to survive in the GI tract, including expression of mucus-binding pili and bile
resistance. Although it is unclear which geno-phenotype GR-1 belongs to, Reid et al have
demonstrated that GR-1 can adhere to urogenital and vaginal cells in vitro (Reid and Bruce,
2001b). I have administered GR-1 SN prior to LPS injection since it is likely that its
protective benefit in humans would be in prevention of PTB as opposed to treatment once
labor has started. A previous study has demonstrated p40, a 40kDa soluble protein purified
from the supernatant of L. rhamnosus GG, reduces intestinal inflammation in dextran sulfate
sodium (DSS)-induced colitis in mice (Yan and Polk, 2012). Preliminary experiments in our
laboratory have identified a heat-sensitive protein-like molecule (>30kDa), which suppresses
LPS-induced TNFα production to a comparable degree as unfractionated GR-1 SN in
immortalized mouse macrophages (unpublished observations). GR-1 SN may also contain
small molecules such as lactic acid that could account for its anti-pathogenic property. I
propose that the active moiety(ies) in GR-1 SN, when given intra-peritoneally, activate
signaling molecules which lead to the immune-modulatory effects observed.
In this study, LPS stimulated multiple cytokines and chemokines, resulting in systemic and
intrauterine inflammation, consistent with previous studies using the same PTB mouse model
(Yang et al., 2009; Shynlova et al., 2013). Although I found that LPS increased plasma IL-
12p70 and IL-17 in contrast to a previous study (Yang et al., 2009), this may be due to the
higher LPS dose I used. In general, LPS induced the greatest changes in pro-inflammatory
cytokine concentrations in the myometrium, suggesting myometrial immune alterations play
52
a key role in the onset of LPS-induced preterm labor. Despite low baseline maternal plasma
CCL2 and CCL4 concentrations, they increased markedly with LPS stimulation, in keeping
with their role in recruitment of peripheral immune cells. Although I cannot extrapolate our
findings directly to the clinical setting, many of the cytokines and chemokines I report on
have been implicated in the pathogenesis of human PTB (Sweet et al., 2007; Ekelund et al..
2008; Ito et al., 2010; Weissenbacher et al.; 2013).
My findings provide evidence that GR-1 SN promotes an anti-inflammatory environment,
consistent with our previous studies (Yeganegi et al., 2009; Yeganegi et al., 2011). GR-1 SN
decreased LPS-induced TNFα concentrations in myometrium, maternal plasma and amniotic
fluid but not the placenta. IL-6 concentrations were also markedly decreased by pretreatment
with GR-1 SN in all tissues and fluids studied. IL-6 -/- mice have delayed PTB compared to
wild-type mice, and mice with double knockouts for TNFα and IL-1 receptors are refractory
to bacterially induced PTB (Hirsch et al., 2006; Robertson et al., 2010). Together with our
findings, this suggests that both IL-6 and TNFα play an essential role in LPS-induced PTB in
mice. Pretreatment with GR-1 SN did not alter LPS-induced IL-1α whereas the increase in
IL-1β concentration was partially reduced by GR-1 SN in maternal plasma. Although IL-1 is
involved in human PTB, IL-1 signaling may not play a critical role in murine PTB
(Yoshimura and Hirsch 2005). GR-1 SN alone increased placental IL-10 and IL-4
concentrations, which have been shown to counteract inflammatory responses in mice
(Robertson et al., 2007a). IL-10 prolongs gestation in LPS treated IL-10-/- C57BL/6 mice
(Keelan et al., 1999). GR-1 SN also attenuated LPS-induced amniotic fluid CCL3 and CCL4,
as well as plasma CCL4 and CCL5, suggesting GR-1 SN may play a role in reducing
leukocyte recruitment to sites of inflammation. GR-1 SN did not decrease LPS-induced
CCL2 and CXCL1 in plasma or myometrium, which would promote and maintain effective
pathogen clearance. Our previous studies have indicated that Mitogen-Activated Protein
Kinase and Janus Kinase/Signal Transducer and Activator Transcription pathways may be
involved in the mechanism of action of GR-1 SN on LPS-induced cytokine productions
(Yeganegi et al., 2010) and I propose that similar mechanisms may be important in vivo.
53
The role of hematopoietic cytokines CSF2 and CSF3 in human PTB is unclear although
elevated cervico-vaginal fluid CSF2 concentrations have been shown to be associated with
cervical shortening (Chandiramani et al., 2012). In our study, GR-1 SN attenuated LPS-
induced myometrial CSF2 production but not in the placenta, amniotic fluid or maternal
plasma. LPS increased CSF3 concentrations markedly in all tissues and fluids and this was
maintained with prior GR-1 SN treatment. Since CSF3 possesses important anti-
inflammatory properties (Martins et al., 2011; Yeganegi et al., 2011), this is an additional
mechanism whereby GR-1 SN favors an anti-inflammatory environment.
Plasma progesterone decreased in animals treated with both LPS and LPS+GR-1 SN that is
in keeping with a previous study (Fidel et al., 1998), and GR-1 SN alone had no effect on
plasma progesterone concentrations. Unlike in humans, term parturition in mice occurs after
luteolysis and is associated with a decline in plasma progesterone concentrations (Challis et
al., 2000; Mesiano et al., 2002). However, it is not known whether a decline in progesterone
is essential for mice to undergo PTB (Hirsch and Muhle, 2002; Elovitz and Wang, 2004;
Romero and Stanczyk, 2013); I propose inflammation may be a more important factor than
progesterone withdrawal in this PTB model.
Pregnant women carrying male fetuses are more susceptible to PTB than those with female
fetuses (Challis et al., 2013). I have previously shown that LPS increases TNFα output and
prostaglandin-endoperoxide synthase 2 expressions to a greater extent in trophoblast cells
from pregnancies with a male fetus (Yeganegi et al., 2009; Yeganegi et al., 2011). In the
current study, I did not observe any differences in fetal sex ratios between mice that
delivered preterm and those that delivered at term when treated with LPS+GR-1 SN.
In summary, probiotic Lactobacillus rhamnosus GR-1 supernatant attenuates LPS-induced
inflammation as well as the rate of PTB in pregnant mice. This study provides further
evidence regarding the potential mechanisms whereby probiotic lactobacilli may reduce the
risk of PTB, and hence supports the need for clinical trials to assess their efficacy.
54
Figure 3-1 Experimental design to investigate the effect of GR-1 supernatant (GR-1 SN)
on the timing of LPS-induced PTB (Set 2).
Mice received an intra-peritoneal injection of either saline or GR-1 SN on GD 14. A second dose of saline or GR-1 SN was given on GD 15, approximately 15-30 minutes prior to an intrauterine injection of saline or LPS 125µg. Animals were monitored for the time of delivery in individual cages till term (GD19/20). Preterm delivery was defined as delivery of at least one pup 48 hours after intrauterine injection of LPS (GD 17).
Pregnant CD-1 mice
Intra-peritoneal (200µL)
1 14 15 16 17 18
19/20
……….#
Gestational Day (GD)
Saline
GR-1
Supernatant
Saline
LPS 125µg
Laparotomy Intra-uterine
infusion (100µL)
Monitor for time of delivery Preterm
Term
15-30 min#
LPS 125µg
Saline
n=9 n=17 n=9 n=14
55
Figure 3-2 Experimental design to investigate the effect of GR-1 supernatant (GR-1 SN) on the concentration of cytokines and chemokines in the maternal plasma, amniotic fluid and intra-uterine tissues (Set 3).
Mice received an intra-peritoneal injection of either saline or GR-1 SN on GD 14. A second dose of saline or GR-1 SN was given on GD 15, approximately 15-30 minutes prior to an intrauterine injection of saline or LPS 125µg. The maternal blood, amniotic fluid and intrauterine tissues (placenta and myometrium) were collected 8 hours after intrauterine injection of saline or LPS for the measurement of cytokines and chemokines.
Pregnant CD-1 mice
Intra-peritoneal (200µL)
1 14 15 16 17 18
19/20
……….#
Gestational Day (GD)
Saline
GR-1 Supernatant
Saline
LPS 125µg
Laparotomy Intra-uterine
infusion (100µL)
Preterm
Term
15-30 min# LPS 125µg
Saline
n=10 n=10 n=10 n=10 8 hours#
Sample Collection
• Maternal blood • Amniotic Fluid • Intra-uterine tissues
56
Figure 3-3 Cumulative frequency plot showing the percentage of pregnant CD-1 mice that delivered at various gestational days following four different treatments (Set 2).
Preterm birth is defined as delivery of at least one pup within 48 hours of LPS injection. Four treatment groups are shown: LPS 125µg (solid triangle, n=17), LPS 125µg+GR-1 SN (open triangle, n=14), saline (open circle, n=9) and GR-1 SN (solid circle, n=9). The LPS group was compared with each of the three remaining groups using Fisher’s exact test. Statistical significance was denoted with different letters. a: p<0.0001 versus saline; b: p<0.0001 versus GR-1 SN; c: p=0.0281 versus LPS 125µg +GR-1 SN.
gestational day
15 16 17 18 19
% d
eliv
ered
0
20
40
60
80
100
Gestational Day
% d
eliv
ered a,b,c
LPS
LPS + GR-1 SN
Saline GR-1 SN
57
Figure 3-4 Histogram showing concentrations of pro-inflammatory cytokines IL-1β, IL-6, IL-12p40, IL-12p70, TNFα and IL-17 in the maternal plasma (n=10 animals per treatment group), myometrium (n=7), placenta (n=7) and amniotic fluid (n=10) of pregnant CD-1 mice (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are 4 treatment groups: saline (white); GR-1 SN (light grey); LPS 125µg (dark grey) and LPS 125µg+GR-1 SN (black bars). Comparison within groups was assessed with 2 tailed, One Way ANOVA for IL-12p70 and TNFα in the myometrium and ANOVA on ranks followed by Newman Keuls test for all other cytokines. Statistical significance was denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001).
IL-17
0
20
40
60
80
MaternalPlasma
Myometrium Placenta AmnoticFluid
Conc
entr
atio
n (p
g/m
L)
IL-1β
0
100
200
2000400060008000
MaternalPlasma
Myometrium Placenta AmnioticFluid
Conc
entr
atio
n (p
g/m
L)
IL-6
0
500
1000
1500
2000
2500
MaternalPlasma
Myometrium Placenta AmnioticFluid
Conc
entra
tion
(pg/
mL)
IL-12p70
0
100
200
300
400
500
MaternalPlasma
Myometrium Placenta AmnioticFluid
Conc
entra
tion
(pg/
mL)
TNFα
0
50
100
150
200
MaternalPlasma
Myometrium Placenta AmnioticFluid
Conc
entra
tion
(pg/
mL)
IL-12p40
0
100
200
300500
1000
1500
2000
MaternalPlasma
Myometrium Placenta AmnioticFluid
Conc
entr
atio
n (p
g/m
L)
b
c a a
NS
NS
NS
b
c a a
b
c a a
b
c a a
b c a a
b
c
a a
b
c
a a b a a a
b b a a
b
c
a a
b
c
a a
b
a
a a
b
c a a
a a
b b a
b b a
a a b b
a,c a,b b a,b,c
a a ab
b ab
b b
a
a
a a
a
b b
b b **
**
**
***
**
** *
**
*
*
** *
Saline GR-1 SN LPS 125ug LPS 125ug + GR-1 SN
58
Figure 3-5 Histogram showing concentrations of chemokines CCL3, CCL4, CCL5 and hematopoietic factor CSF2 in the maternal plasma (n=10 animals per treatment group), myometrium (n=7), placenta (n=7) and amniotic fluid (n=10) of pregnant CD-1 mice (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are 4 treatment groups: saline (white); GR-1 SN (light grey); LPS 125µg (dark grey) and LPS 125µg+GR-1 SN (black bars). Comparison within groups was assessed with 2 tailed, One Way ANOVA on ranks followed by Newman Keuls post-hoc test. Statistical significance was denoted with different letters and as asterisks (*p<0.05; **p<0.01; ***p<0.001).
CCL3
0
100
200
300
1000
2000
3000
MaternalPlasma
Myometrium Placenta AmnioticFluid
Con
cent
ratio
n (p
g/m
L)CCL4
0
200
400
600
MaternalPlasma
Myometrium Placenta AmnioticFluid
Con
cent
ratio
n (p
g/m
L)
CSF2
0
100
200
300
400
MaternalPlasma
Myometrium Placenta AmnioticFluid
Con
cent
ratio
n (p
g/m
L)
CCL5
0255075
100
500
1000
1500
2000
MaternalPlasma
Myometrium Placenta AmnioticFluid
Con
cent
ratio
n (p
g/m
L)
b
c
a a
b
c
a a
b
c a a
b
c
a a
b
c a a
b b
b b
b b a a
a
a a
a a a a a
b b
b b
b b
b b
b b a a a a a
a a a a
a a a
b b b
b
b b
* **
*** ***
*
Saline GR-1 SN LPS 125ug LPS 125ug + GR-1 SN
59
Figure 3-6 Histogram showing concentrations of anti-inflammatory cytokines IL-4 and IL-10 in the maternal plasma (n=10 animals per treatment group), myometrium (n=7), placenta (n=7) and amniotic fluid (n=10) of pregnant CD-1 mice (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are 4 treatment groups: saline (white); GR-1 SN (light grey); LPS 125µg (dark grey) and LPS 125µg+GR-1 SN (black bars). Comparison within groups was assessed with 2 tailed, One Way ANOVA on ranks followed by Newman Keuls post-hoc test. Statistical significance was denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001).
IL-4
0
2
4
6
8
MaternalPlasma
Myometrium Placenta AmnoticFluid
Con
cent
ratio
n (p
g/m
L)IL-10
01020304050
150
200
250
300
MaternalPlasma
Myometrium Placenta AmnoticFluid
Con
cent
ratio
n (p
g/m
L)
b b
a a a a
b b
b b
a a a a
b b
a
b
c c
a,b
a,c a,b,c
b a,b
a,b,c
b
a,c
a b b b
60
Figure 3-7 Histogram showing maternal plasma progesterone concentrations for different treatment groups (Set 3).
Results are mean values ± SEM and expressed in ng/mL (5 animals per group). Comparison within groups was assessed with 2 tailed, One Way ANOVA followed by Newman Keuls post-hoc test. Statistical significance was denoted as different letters (p<0.05).
0
20
40
60
80
Saline GR-1 SN LPS125µg LPS125µg+GR-1 SN
Mat
erna
l Pro
gest
eron
e co
ncen
trat
ion
(ng/
mL)
a
a
b b
61
Table 3-1 Delivery outcome of pregnant CD-1 mice that delivered preterm following different doses of LPS intrauterine injection (Set 1).
Mice received 0 (saline), 25µg, 50µg, 125µg, and 250µg LPS (10 animals in each group). One mouse from each of the LPS 65µg group and LPS125µg group had all fetuses absorbed at term. Preterm delivery is defined as delivery of at least one pup within 48 hours of LPS injection. The saline group was compared with each of the four remaining groups using Fisher’s exact test. Statistical significance was denoted with different letters.
LPS dose (µg)
No. of animals delivered preterm
No. of animals delivered term
Saline 0 a 10 a
LPS 25 µg 4 a 6 a
LPS 65 µg 8 b 1 b
LPS 125 µg 9 b 0 b
LPS 250 µg 10 b 0 b
62
Table 3-2 Litter size and fetal weight of neonates born to pregnant CD-1 mice that received different treatments (Set 2).
Results are mean values ± SEM. One-Way ANOVA followed by Newman Keuls post-hoc test was used to compare the groups with one another. Mice in the LPS 125µg group delivered preterm. Number of animals is indicated in brackets.
Group Litter size Weight per pup (gram)
P-value
Saline 13.0 ± 0.89 (n=9) 1.72 ± 0.02 (n=9) > 0.05
GR-1 SN 12.4 ± 0.51 (n=9) 1.73 ± 0.02 (n=9) > 0.05
LPS 125 µg - - -
LPS 125 µg + GR-1 SN
10.0 ± 1.04 (n=4)
1.69 ± 0.04 (n=4)
> 0.05
63
Table 3-3 Baseline cytokine and chemokine concentrations in the maternal plasma, myometrium, amniotic fluid and placenta of pregnant CD-1 mice (Set 3).
Results are mean values ± SEM and expressed in pg/mL (maternal plasma (n=10), myometrium (n=7), placenta (n=7) and amniotic fluid (n=10)). Increases in concentrations following LPS 125µg treatment are indicated in brackets (fold increase).
Cytokine/
Chemokine
Maternal
Plasma
Myometrium
Amniotic
Fluid
Placenta
IL-1α 9.8±2.4 (7) 679.6±170.6 (174) 1.8±0.6 (26) 357.2±222.8 (3)
IL-1β 43.6±4.2 (4) 174.9±19.7 (37) 71.9±8.7 (1) 39.5±9.3 (22)
IL-2 4.9±1.3 (4) 0.2±0.1 (33) 5.3±0.9 (0.5) < OOR (OOR)
IL-3 0.1±0.01 (16) 7.4±2.9 (2) 7.9±1.5 (1) 1.1±0.2 (6)
IL-4 0.7±0.1 (4) 1.1±0.2 (4) 3.5±0.6 (1) 0.9±0.1 (3)
IL-5 5.9±2.5 (3) 2.4±0.4 (6) < OOR 2.6±0.7 (2)
IL-6 11.8±1.8 (110) 6.2±1.2 (275) 9.3±1.1 (190) 5.7±0.7 (28)
IL-9 < OOR 331.5±93.8 (1) < OOR 164.6±11.2 (3)
IL-10 7.6±3.6 (26) 9.5±1.3 (4) 25.8±3.7 (1) 8.2±1.4 (3)
IL-12p40 37.0±6.0 (37) 34.1±15.1 (11) 58.5±6.3 (1) 92.0±29.6 (2)
IL-12p70 24.0±7.1 (3) 86.1±21.1 (5) 69.9±11.3 (1) 18.8±4.0 (5)
IL-13 21.6±4.1 (4) 18.1±3.3 (11) 75.1±15.3 (1) 16.6±3.0 (6)
IL-17 4.4±1.3 (3) 4.2±1.6 (15) 3.5±0.9 (2) 0.9±0.3 (7)
CSF2 19.2±1.0 (4) 57.6±9.3 (5) 52.2±3.9 (2) 11.4±3.1 (16)
CSF3 2409.5±289.8 (63) 437.2±142.5 (449) 214.8±72.4 (288) 478.7±96.0 (390)
IFN-γ 0.6±0.1 (19) 5.1±0.6 (3) 3.0±0.3 (1) < OOR
CXCL1 48.1±8.7 (77) 116.3±51.7 56.1±4.7 (220) 1855.3±142.2
CCL2 50.7±14.1 (149) 132.2±40.0 (138) 1508.2±157.1 (2) 77.8±20.0 (8)
CCL3 1.4±0.3 (48) 47.2±14.8 (49) 21.6±4.9 (10) 67.2±13.6 (15)
CCL4 2.7±0.7 (57) 31.8±5.5 (9) 10.4±1.7 (37) 15.3±1.4 (4)
CCL5 8.7±2.4 (186) 6.6±1.3 (49) 10.1±0.8 (7) 1.9±0.6 (8)
CCL11 183.8±33.5 (5) 227.8±30.0 (4) 618.8±26.5 (1) < OOR
TNFα 19.3±2.3 (4) 38.4±11.3 (3) 51.0±6.0 (3) 7.5±1.4 (5)
< OOR: out of range (below lowest detectable concentration) > OOR: out of range (above highest detectable concentration)
64
Table 3-4 Cytokine and chemokine concentrations in the maternal plasma of pregnant CD-1 mice following different treatments (Set 3).
Results are mean values ± SEM and expressed in pg/mL for each treatment group (10 animals per group). Comparison within groups was assessed with One Way ANOVA for IL-13 and ANOVA on ranks followed by Newman Keuls post-hoc test for all other cytokines. Statistical significance is denoted by different letters (p<0.05).
Maternal Plasma
Cytokine
Saline GR-1 SN LPS125µg LPS 125µg
+GR-1 SN
IL-1α 9.8±2.4a 16.7±4.0a 69.5±6.0b 72.5±9.4b
IL-1β 43.6±4.2a 56.0±7.9a 181.2±21.9b 98.8±8.2c
IL-2 4.9±1.3a 4.9±1.4a 17.6±4.1b 16.7±0.9b
IL-3 0.1±0.01a 0.1±0.01a 1.6±0.3b 0.9±0.1b
IL-4 0.7±0.1a 0.7±0.1a 2.9±0.7b 2.2±0.3b
IL-5 5.9±2.5a 3.4±0.3a 16.5±4.3b 8.9±1.2b
IL-6 11.8±1.8a 12.6±1.8a 1300.0±324.4b 362.8±74.9c
IL-9 < OOR < OOR < OOR < OOR
IL-10 7.6±3.6a 10.8±1.8a 196.5±27.2b 224.5±33.6b
IL-12p40 37.0±6.0a 43.2±4.7a 1384.8±280.8b 278.1±74.9c
IL-12p70 24.0±7.1a 19.2±8.3a 64.4±13.9b 37.5±7.6b
IL-13 21.6±4.1a 30.9±3.5a 76.9±6.1b 65.8±4.1b
IL-17 4.4±1.3a 2.3±0.4a 13.9±1.1b 14.4±2.7b
CSF2 19.2±1.0a 27.3±3.9a 85.8±3.7b 93.2±3.6b
CSF3 2409.5±289.8a 3338.3±515.1a 150981.9±32647.3b 233038.8±63249.0b
IFN-γ 0.6±0.1a 0.8±0.2a 11.5±2.9b 18.3±6.9b
CXCL1 48.1±8.7a 37.5±8.9a 3702.7±748.8b 3366.0±1096.5b
CCL2 50.7±14.1a 132.9±34.7a 7570.9±1186.8b 5916.8±833.6b
CCL3 1.4±0.3a 3.6±1.2a 66.9±4.3b 57.8±7.4b
CCL4 2.7±0.7a 3.6±0.5a 136.3±18.9b 45.7±8.0c
CCL5 8.7±2.4a 15.4±3.8a 1622.4±182.3b 922.1±45.0c
CCL11 183.8±33.5a 121.7±32.3a 831.8±91.5b 754.2±175.3b
TNFα 19.3±2.3a 25.3±3.4a 80.3±11.1b 50.6±2.4c
< OOR: out of range (below lowest detectable concentration)
65
Table 3-5 Cytokine and chemokine concentrations in the myometrium of pregnant CD-1 mice following different treatments (Set 3).
Results are mean values ± SEM and expressed in pg/mL for each treatment group (7 animals per group). Comparison within groups was assessed with One Way ANOVA for IL-4, IL-12p70, IFN-γ and TNFα, and ANOVA on ranks followed by Newman Keuls post-hoc test for all other cytokines. Statistical significance is denoted by different letters (p<0.05).
Myometrium
Cytokine
Saline GR-1 SN LPS125µg LPS 125µg
+GR-1 SN
IL-1α 679.6±170.6a 974.8±70.2a 118194.4±112940.0b 34851.9±20441.5b
IL-1β 174.9±19.7a 373.8±117.8a 6422.0±837.8b 4991.7±1111.0b
IL-2 0.2±0.1a 0.19±0.1a 6.6±3.9b 4.1±1.4b
IL-3 7.4±2.9a,b 6.2±2.5a 15.6±2.3b 10.2±1.3a,b
IL-4 1.1±0.2a 1.6±0.1a 4.4±0.4b 3.8±0.2b
IL-5 2.4±0.4a 4.3±1.6a 13.5±7.2b 9.8±3.5b
IL-6 6.2±1.2a 12.1±2.3a 1704.4±494.6b 291.1±67.5c
IL-9 331.5±93.8a 248.5±113.1a 329.6±72.5a 196.5±85.5a
IL-10 9.5±1.3a 8.9±0.5a 36.9±4.3b 37.8±4.8b
IL-12p40 34.1±15.1a 35.5±6.3a 362.9±81.0b 400.3±121.9b
IL-12p70 86.1±21.1a 99.0±19.2a 400.4±39.3b 295.4±36.7c
IL-13 18.1±3.3a 24.7±5.9a 206.8±21.5b 133.1±19.3c
IL-17 4.2±1.6a 3.8±1.4a 63.0±16.7b 16.2±3.3c
CSF2 57.6±9.3a 58.2±7.9a 313.4±50.2b 168.8±15.0c
CSF3 437.2±142.5a 1434.5±834.1a 196003.8±66522.5b 184154.1±118930.5b
IFN-γ 5.1±0.6a 4.6±0.9a 17.8±1.3b 13.9±1.3c
CXCL1 116.3±51.7 232.8±118.9 > OOR 39265.4±6534.7
CCL2 132.2±40.0a 195.2±82.5a 18245.8±5702.7b 45343.6±23004.8b
CCL3 47.2±14.8a 148.4±49.7a 2299.8±471.2b 1981.6±349.7b
CCL4 31.8±5.5a 48.1±12.1a 300.3±53.9b 319.1±86.4b
CCL5 6.6±1.3a 27.5±10.7a 325.7±46.8b 313.8±72.9b
CCL11 227.8±30.0a 233.5±23.5a 861.7±203.5b 670.7±154.4b
TNFα 38.4±11.3a 32.6±10.5a 128.7±19.2b 78.8±10.6a
> OOR: out of range (above highest detectable concentration)
66
Table 3-6 Cytokine and chemokine concentrations in the amniotic fluid of pregnant CD-1 mice following different treatments (Set 3).
Results are mean values ± SEM and expressed in pg/mL for each treatment group (10 animals per group). Comparison within groups was assessed with One Way ANOVA for IL-1β, IL-2, IL-12p70, CSF2 and IFN-γ, and ANOVA on ranks followed by Newman Keuls post-hoc test for all other cytokines. Statistical significance is denoted by different letters (p<0.05).
Amniotic Fluid
Cytokine
Saline GR-1 SN LPS125µg LPS 125µg
+GR-1 SN
IL-1α 1.8±0.6a 2.6±1.1a 46.4±9.1b 35.8±8.7b
IL-1β 71.9±8.7a 75.5±11.2a 75.9±13.3a 65.4±9.0a
IL-2 5.3±0.9a 5.5±0.4a 2.9±0.5b 3.7±0.7a,b
IL-3 7.9±1.5a 7.6±1.3a 10.2±1.6a 7.9±1.6a
IL-4 3.5±0.6a,b 1.9±0.3b 5.1±0.9a,c 4.0±0.9a,b,c
IL-5 < OOR < OOR < OOR < OOR
IL-6 9.3±1.1a 9.2±0.9a 1767.4±584.6b 365.6±35.9c
IL-9 < OOR < OOR < OOR < OOR
IL-10 25.8±3.7a,b 22.7±3.0b 40.6±5.6a,c 33.0±4.4a,b,c
IL-12p40 58.5±6.3a 51.3±5.0a 73.0±6.7a 65.2±5.8a
IL-12p70 69.9±11.3a,b 46.7±7.8b 93.1±7.4a,c 76.3±8.5a,b,c
IL-13 75.1±15.3a 90.8±13.1a 112.4±15.9a 77.3±8.5a
IL-17 3.5±0.9a 2.0±0.7a 6.2±1.6a 4.1±1.0a
CSF2 52.2±3.9a 49.7±4.9a 97.6±15.0b 88.3±8.6b
CSF3 214.8±72.4a 297.9±118.6a 61939.9±28767.9b 33742.1±11824.3b
IFN-γ 3.0±0.3a 4.2±0.5a 4.7±0.8a 4.0±0.4a
CXCL1 56.1±4.7a 65.9±12.8a 12298.9±3378.9b 9714.0±3461.3b
CCL2 1508.2±157.1a 1251.1±113.3a 3538.2±819.7b 2678.4±538.3b
CCL3 21.6±4.9a 23.2±3.5a 222.8±33.8b 75.5±16.4c
CCL4 10.4±1.7a 13.2±2.0a 389.5±138.1b 138.1±47.9c
CCL5 10.1±0.8a 8.4±0.8a 66.6±11.5b 47.3±8.9b
CCL11 618.8±26.5a 572.8±82.4a 578.6±116.2a 481.7±94.9a
TNFα 51.0±6.0a 40.3±3.3a 162.8±17.5b 89.5±16.4c
< OOR: out of range (below lowest detectable concentration)
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Table 3-7 Cytokine and chemokine concentrations in the placenta of pregnant CD-1 mice following different treatments (Set 3).
Results are mean values ± SEM and expressed in pg/mL for each treatments group (7 animals per group). Comparison within groups was assessed with 2 tailed, One Way ANOVA for IL-12p40, CCL5 and TNFα, and ANOVA on ranks followed by Newman Keuls post-hoc test for all other cytokines. Statistical significance is denoted by different letters (p<0.05).
Placenta
Cytokine
Saline GR-1 SN LPS125µg LPS 125µg
+GR-1 SN
IL-1α 357.2±222.8a 398.5±196.0a 905.8±130.6b 661.2±89.6b
IL-1β 39.5±9.3a 139.8±83.8a 875.2±275.9b 662.1±23.7b
IL-2 < OOR < OOR < OOR < OOR
IL-3 1.1±0.2a 2.8±1.6a 7.1±2.9b 5.3±1.8b
IL-4 0.9±0.1a 3.6±1.2b 2.3±0.1c 2.2±0.1c
IL-5 2.6±0.7a 3.1±0.6a 6.2±1.5b 5.8±1.0b
IL-6 5.7±0.7a 9.25±4.3a 169.2±22.0b 42.7±4.2c
IL-9 164.6±11.2a 147.7±29.8a 551.2±217.7b 511.0±138.9b
IL-10 8.2±1.4a 14.2±1.6b 25.9±1.4b 22.8±2.0b
IL-12p40 92.0±29.6a 120.8±33.7a,b 227.1±33.8b 162.5±25.9a,b
IL-12p70 18.8±4.0a 37.9±13.6a 93.7±12.3b 34.7±9.8a
IL-13 16.6±3.0a 41.5±21.5a 96.9±10.2b 94.6±7.7b
IL-17 0.9±0.3a 1.74±0.4a 6.3±1.3b 4.8±1.5b
CSF2 11.4±3.1a 57.9±39.8a 187.3±35.2b 110.2±9.4b
CSF3 478.7±96.0a 2400.1±1706.7a 186810.4±54388.5b 192855.0±126303.9b
IFN-γ < OOR < OOR < OOR < OOR
CXCL1 1855.3±142.2 3846.7±2108.0 > OOR > OOR
CCL2 77.8±20.0a 89.7±6.9a 649.2±214.6b 877.2±229.6b
CCL3 67.2±13.6a 121.3±31.6a 992.8±200.7b 910.2±150.6b
CCL4 15.3±1.4a 17.1±2.3a 58.6±11.9b 51.1±4.9b
CCL5 1.9±0.6a 2.6±0.8a 15.3±2.1b 12.4±1.7b
CCL11 < OOR < OOR < OOR < OOR
TNFα 7.5±1.4a 10.5±2.6a 39.2±6.0b 30.9±3.9b
< OOR: out of range (below lowest detectable concentration) > OOR: out of range (above highest detectable concentration)
68
Chapter Four
Oral Probiotic Lactobacillus rhamnosus GR-1 stimulates systemic and
intrauterine production of cytokines and chemokines and modulates the vaginal
microbiota in pregnant CD-1 mice.
I would like to thank Dr. Gregory Gloor for his advice on the analyses of sequencing data
and for his help on filtering and organizing the data into operational taxonomic unit tables. I
would like to express my gratitude to Dr. David Carter at the Robarts Research Institute
(London, Ontario, Canada) for performing the Ion torrent sequencing.
69
Chapter 4
4. Oral Probiotic Lactobacillus rhamnosus GR-1 stimulates systemic and
intrauterine production of cytokines and chemokines and modulates the
vaginal microbiota in pregnant CD-1 mice.
4.1 Introduction Cytokines and chemokines play a pivotal role in infection/inflammation-induced preterm
labor (PTL) (Challis et al., 2009). The intra-uterine tissues (amnion, chorion, placenta,
decidual and myometrium), as well as the leukocytes infiltrating these tissues, are potential
sources of cytokines and chemokines (Young et al., 2002). Pro- and anti-inflammatory
cytokines balance the production of one another throughout pregnancy and during labor
(Keelan et al., 2003). A shift to a pro-inflammatory bias ends uterine quiescence and leads to
the onset of parturition (Challis et al., 2009). Chemokines recruit immune cells, phagocytize
pathogens and induce pathogenic cell lysis (Hamilton et al., 2013). Recruited immune cells
can also produce more pro-inflammatory cytokines, which amplify the inflammatory cascade
leading to PTL (Hamilton et al., 2013). Chemokines such as IL-8 in the cord blood, cervical
and amniotic fluid are increased in association with preterm birth (PTB) and cervical
ripening (Sennstrom et al., 2000; Jacobsson et al., 2005; Matoba et al., 2009).
An abnormal vaginal microbiota, such as that found in bacterial vaginosis (BV) that is
characterized by a depletion of endogenous vaginal lactobacilli, has been associated with an
increased risk of PTB (Donders et al., 2009). Probiotics are defined as “live microorganisms
which, when administered in adequate amounts, confer a health benefit to the host”
(FAO/WHO, 2001). Lactobacillus spp. are normal commensals of the human vaginal
microbiota, and have been used to treat urogenital infections and reduce bacterial vaginosis
(BV) occurrence (Reid, 2012, Reid, 2001a). Previous studies have demonstrated that
probiotic L. rhamnosus GR-1 supernatant (GR-1 SN) increases anti-inflammatory cytokine
IL-10 production while reducing lipopolysaccharides (LPS)-induced pro-inflammatory
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cytokine TNF-α production in cultured human placental trophoblast cells (Yeganegi et al.,
2009; Yeganegi et al., 2011) and decidual cells (Li et al., 2014).
L. rhamnosus GR-1 and L. reuteri RC-14 live bacteria taken orally at a daily dose of 109 to
1010 colony-forming units (cfu) decrease BV relapse and re-establish the vaginal ecosystem
in non-pregnant women (Reid et al., 2003a; Reid, 2012). I wished to investigate whether a
higher dose of lactobacilli leads to an improved efficacy, using varying doses of lactobacilli
in pregnant CD-1 mice in this study. The mouse gut microbiota resembles that of the adult
human from the family to the phylum taxonomic level, with Bacteroidetes and Firmicutes
being the most abundant phyla in both human and mouse gut microbiota (Kostic et al., 2013).
The vaginal microbiota of non-pregnant BALB/cJ mice (Meysick and Garber, 1992) and the
vaginal microbiota of women diagnosed with BV share the common characteristic of low
lactobacilli abundance, and this gives the opportunity to detect potential lactobacilli
colonization after an exogenous administration of oral lactobacilli in mice.
In Chapter 3 of this thesis, I demonstrated that GR-1 SN, harvested from approximately 108 –
109 cfu of GR-1 live bacteria per mL, reduces LPS-induced PTB in mice. Therefore, in this
study, I treated mice with 109 cfu of GR-1 orally. Furthermore, oral administration of 109 -
1011 cfu of lactobacilli is the dose range used in previous studies to improve human vaginal
health (Mastromarino et al., 2013; Homayouni et al.. 2014). To calculate the mouse
equivalent dose, I used the following factors (Km of mouse = 3; Km of human = 37) to
account for the difference in the body surface area, and I also took into consideration the
difference in body weight (mouse ≈ 20g; human ≈ 60kg) (Reagan-Shaw et al., 2008). The
detailed calculations are shown in Figure 4-1. The normal gestational length of pregnant CD-
1 mice is 19-20 days, and gestational day (GD) 9 to GD 15 is equivalent to the second
trimester in human pregnancy. I chose to treat the pregnant mice for 7 consecutive days (GD
9-15) since this corresponds to the 12 weeks treatment protocol used in pregnant women in
the next chapter (Chapter 5).
Mice are widely used to study the mechanisms underlying human PTB and an established
model of intrauterine infection using 250µg of LPS to induce 100% preterm delivery in
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pregnant CD-1 mice with no maternal mortality has been developed (Elovitz et al., 2003).
Building on our previous studies that demonstrated GR-1 SN reduces LPS-induced PTB as
well as systemic and intrauterine inflammation (Chapter 3), in this study, I evaluated whether
oral GR-1 live bacteria has similar anti-inflammatory properties in the mouse. I hypothesized
that oral GR-1 can reduce LPS-induced PTB, and GR-1 alone can increase anti-inflammatory
cytokines in the plasma, amniotic fluid and intrauterine tissues in pregnant CD-1 mice.
Furthermore, I hypothesized that oral GR-1 would modulate both the mouse vaginal and
cecal (gut) microbiota.
4.2 Material and Methods 4.2.1 Animals Female HSD:ICR (CD-1) outbred mice (8-12 weeks old; Harlan Laboratories) were bred and
the morning of vaginal plug detection was designated as GD 1. Animals were handled in
accordance with guidelines of the Canadian Council for Animal Care and all procedures
were approved by the Animal Care Committee of Toronto Center for Phenogenomics
(Animal Use Protocol #0164). Animals were housed in a pathogen-free, humidity controlled
12 h light:12 h dark cycle animal facility with free access to food and water. I performed 4
sets of independent experiments with a total of 180 animals.
4.2.2 Lactobacillus rhamnosus GR-1 preparation Lactobacillus rhamnosus GR-1 (GR-1) was grown for 8-10 hours anaerobically at 37 oC in
de Man, Rogosa, and Sharpe (MRS) broth (Becton Dickinson, Ontario) to an optical density
of ~0.9 at 600 nm (representing ~108 -109 cfu per mL of bacteria), and then centrifuged at
3000 rpm for 10 min at 25 oC. The GR-1 pellet was then washed twice with sterile saline,
centrifuged, and re-suspended in saline to obtain a final concentration of 108, 109 or 1010 cfu.
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4.2.3 Intra-uterine injection of LPS by mini-laparotomy
Intrauterine injection of LPS was given via mini-laparotomy on GD 15 as previously
described (Elovtiz et al., 2003). Mice were anesthetized with isoflurane inhalation and given
analgesic buprenorphine (0.1mg/kg). An incision (~1cm) was made to expose the lower
segments of the uterine horns. Sterile saline (100µL) or LPS (Escherichia coli 055:B5,
Sigma-Aldrich, St. Louis) dissolved in 100µL sterile saline was injected between the two
lowest gestational sacs of either the left or right uterine horn. Fascia and skin were closed
with 4.0 vicryl sutures and staples, respectively. Mice were housed in individual cages.
4.2.4 Oral administration of GR-1 by oral gavage
Mice received 100-300µL of either 109 cfu of GR-1 or saline by oral gavage using an
autoclaved animal feeding needle (Richtree, NY, USE) once daily from GD 9 to GD 15. In
this study, I chose the oral route over the vaginal route so I could more accurately measure
the dose administered since GR-1 inoculum may leak after vaginal instillation. GR-1 was
given via oral gavage instead of in drinking water because GR-1 live bacteria sediment to the
bottom of the water bottle with time.
4.2.5 Effect of oral GR-1 on the timing of LPS-induced PTB (Set 1)
Mice were randomly assigned to receive either saline or GR-1 via oral gavage once daily
from GD 9 to GD15. On GD15, approximately 30 minutes after the last dose of GR-1 or
saline, the animals were divided to receive saline, LPS 25µg or LPS 50µg via mini-
laparotomy (Elovitz et al., 2003). A separate group of animals (sham group) received neither
oral gavage nor mini-laparotomy. There were seven groups in Set 1, with 11 animals in each
group (Figure 4-2). Animals were then housed in individual cages and monitored hourly until
term (GD 19-20) for the delivery of pups. Time (hours) to delivery, fetal weight and litter
size were recorded. PTB was defined as delivery of at least one pup within 48 hours (GD 17)
of LPS injection.
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4.2.6 Effect of oral GR-1 on the gestational length (Set 2) Mice received either 100-300µL of GR-1 (108, 109 or 1010 cfu) or saline by oral gavage once
daily from GD 9 to 15, and were housed in individual cages, monitored hourly until term
(GD 19-20) for the delivery of pups. A separate group of animals (sham group) did not
receive oral gavage. There were five groups in Set 2, with 11 animals in each group (Figure
4-3). Time (hours) to delivery, fetal weight and litter size were recorded.
4.2.7 Effect of oral GR-1 on cytokines and chemokines (Set 3) Mice were randomly assigned into four groups (Figure 4-4). The animals received 100-
300µL of 1) saline (n=13), 2) GR-1 108 (n=7), 3) GR-1 109 (n=8) or 4) GR-1 1010 cfu (n=6)
by oral gavage once daily from GD 9 to 15. After the last dose of GR-1 or saline on GD 15,
mice were anesthetized by isoflurane inhalation and maternal blood was collected by cardiac
puncture. Blood was centrifuged at 5,000 xg for 15 min at 4oC and plasma was transferred
into a clean tube and stored at -80 oC. Mice were then euthanized in a carbon dioxide
chamber, and both uterine horns were dissected and kept in ice-cold phosphate buffer
solution (PBS). The amniotic fluid was collected using a 1mL syringe with 27-gauge needle,
pooled from all gestational sacs and centrifuged to remove any cellular debris before stored
at -80 oC. Placental tissue was separated from decidua and fetal membranes in ice-cold PBS.
Myometrium was obtained by scraping off the endometrium on a petri dish cover, which was
kept on top of ice. Each intra-uterine tissue (fetal membrane, placental, myometrial and
decidual tissues) was dissected with sterile instruments and pooled from all fetuses in a given
mouse. All tissue samples were flash-frozen in liquid nitrogen and stored at -80 oC.
4.2.8 Effect of oral GR-1 on the vaginal and cecal microbiota (Set 4) Mice were randomly assigned to two groups (Figure 4-5). They received 100-300µL of either
saline or 109 cfu of GR-1 by oral gavage (n=7 per group) once daily from GD 9 to GD 15.
After the last dose of GR-1 or saline on GD 15, mice were euthanized with carbon dioxide.
The vagina was everted using sterile tweezers and ~1/3 cm of the vaginal tissue was removed.
74
The cecum pouch (~3/4 cm) long was identified at the beginning of the large intestine and
was dissected free. Both vaginal and cecal tissues were stored at -20 oC. In one vaginal
sample and one cecal sample (saline group) and one cecal sample (GR-1 group), insufficient
sample was available for analysis.
4.2.9 Cytokine Assay Cytokine and chemokine concentrations were determined in duplicate using a mouse 23-
multiplex cytokine assay (Appendix I, Biorad, Ontario) on a Luminex 200 cytometer and
Bioplex HTF (Bio-Rad). The assay measured concentrations of interleukin (IL)-1α, IL-1β,
IL-2, IL-3, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p40, IL-12p70, IL-13, IL-17, IFN-γ, CXCL 1,
CCL2, CCL3, CCL4, CCL5, CCL11, TNFα, CSF2, and CSF3. Data analysis was performed
using Bio-Plex Manager (version 5.0, Bio-Rad) and results are presented as concentrations
(pg/mL). There were two plasma samples and two amniotic fluid samples that had
insufficient protein for assay. Samples from 7 animals in the saline group and 7 samples in
the GR-1 109 cfu group were used for intrauterine tissue analyses. Tissues were crushed and
homogenized in EDTA-free protease inhibitor containing RIPA lysis buffer (1mL per 0.5g of
tissue). Homogenized samples were left on ice for 45 minutes before being centrifuged at
12,000 xg for 15 minutes at 4°C to collect the supernatant. Protein concentration was
measured by Bradford assay kit (Bio-Rad, Ontario) with bovine serum albumin as standard.
250µg of total protein was used for the measurement of cytokines and chemokines in the
tissues.
4.2.10 Maternal progesterone measurement Plasma progesterone concentration was measured with an Enzyme Immunoassay kit
(Appendix II, Cayman Chemical Co, Michigan). Samples were diluted 400X with EIA buffer
and assayed in duplicate. The intra and inter-assay coefficients of variation were 5.4 % and
11.2 % respectively.
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4.2.11 DNA isolation and V6 ribosomal DNA PCR amplification DNA was isolated from the vaginal and cecal tissues using PowerSoil DNA Isolation Kit
(Appendix III, VWR, Ontario, Canada). The bacterial DNA was PCR amplified using bar-
coded primers targeting the V6 region of 16S ribosomal DNA (rDNA) with colorless GO-
Taq hot start master mix (Promega, Ontario, Canada) for 25 repeating cycles of 95°C, 55°C
and 72°C for 1 minute each step. The amplified products were then quantified using the
QuBit broad-range double-stranded DNA fluorometric quantitation reagent kit (Life
technologies, Ontario, Canada). Samples were pooled at equal molar concentrations and
purified using a Wizard PCR Clean-Up Kit (Promega, Ontario, Canada) prior to sequencing.
4.2.12 Sequencing Barcoded DNA was sequenced in pairs on the Ion Torrent platform (316 DNA chips, 12
samples per chip) at the Robarts Research Institute (Western University, Canada). The
sequence results were provided in a fastq format. All sequences were filtered and a table of
counts was generated for each sample containing sequences grouped at 97% operational
taxonomic unit (OTU) and 100% identical sequence unit identity. Sequences were then
classified to distinct taxonomic species using the online Ribosomal Database Project
(http://rdp.cme.msu.edu/seqmatch/seqmatch_intro.jsp). Sequences not identical across all
best matches were marked as unclassified.
4.2.13 Statistical Analysis
Statistical analyses of the cytokine, chemokine and progesterone data were carried out using
SigmaStat (version 3.5). Comparison of PTB rate was made with Fisher exact analyses (two
tailed). One-Way ANOVA was used to detect a difference in gestational length, litter size
and fetal weight following different treatments. Comparison between multiple groups in the
maternal plasma and amniotic fluid were carried out with One Way ANOVA followed by
Tukey test. Kruskal-Wallis ANOVA on Ranks followed by Dunn’s method was used for data
that were not normally distributed. Comparison between two groups in the intrauterine
76
tissues was performed with unpaired Student’s t-test or Mann-Whitney Rank Sum Test. The
sequencing data was centered ratio logarithm transformed (Aitchison, 1986) before
performing statistical analyses with R (version 3.0.1). Briefly, the geometric mean of the
proportions of all species detected in a sample was computed. A ratio x was determined from
the proportion of species i over the geometric mean. Then, the relative abundance of species i
was calculated by taking natural logarithm of x. Both protein and sequencing data were
tested for normality and equal variance and were expressed as mean values ± SEM or mean
values ± SD. Data were adjusted for false discovery rate using Benjamini Hochberg
procedure and an adjusted p-value of p<0.05 was considered statistically significant. The
Shannon diversity index was calculated by first taking the proportion of a bacterial
species relative to the total number of species detected in a given sample, and multiplied the
value by the natural logarithm of this proportion. The product was then summed across all
bacterial species, and multiplied by -1 (Magurran, 2003).
4.3 Results 4.3.1 Effect of oral GR-1 on the incidence of LPS-induced PTB and
gestational length (Set 1 and Set 2) Intrauterine injection of LPS 25µg on GD 15 resulted in 36% PTB (4 out of 11 animals) and
pretreatment with oral GR-1 led to 64% PTB (7 out of 11 animals) (p>0.05, Table 4-1). Mice
that received LPS 50µg had 100% PTB (11 out of 11 animals), and the incidence of PTB did
not change with oral GR-1 pretreatment (p>0.05, Table 4-1). Animals in the sham, saline and
GR-1 treated groups delivered live pups at term (Table 4-1). The mean litter size was 12.5 ±
0.37 and the mean weight per pup was 1.70 ± 0.09 grams in the sham group. These were not
different between different treatment groups (p>0.05, Table 4-2).
The mean hours to delivery were 106 ± 3.3 hours, the mean litter size was 12.4 ± 0.36, and
the mean weight per pup was 1.68 ± 0.08 grams in the sham group. These were not different
in mice that received saline or different doses of GR-1 (p>0.05, Table 4-3).
77
4.3.2 Effect of oral GR-1 on the cytokines and chemokines (Set 3) The concentrations of the pro-inflammatory cytokine TNFα in the maternal plasma increased
with 108 and 109 cfu of oral GR-1 (p<0.05, Figure 4-6). The concentrations of plasma IL-
12p40, as well as IL-6 and IFN-γ in the amniotic fluid increased with GR-1 (1010 cfu)
treatment (p<0.05, Figure 4-6). Concentrations of TNFα and IL-17 increased in the placenta,
as did IL-12p70 in the fetal membranes and IL-1α in the myometrium with GR-1 (109 cfu)
treatment (p<0.05, Figure 4-7). There was no significant change in any of the pro-
inflammatory cytokines measured in the decidua with GR-1 treatment (p>0.05, Figure 4-7).
There was no change in the concentration of IL-1β in the maternal plasma, amniotic fluid or
any of the intrauterine tissues between the different treatment groups (p>0.05, Figure 4-6 and
Figure 4-7).
The concentrations of the anti-inflammatory cytokines IL-2, IL-4 and IL-10 did not change
in the maternal plasma, amniotic fluid, or in the placenta and decidua between the different
treatment groups (p>0.05, Figure 4-8 and Figure 4-9). Concentrations of IL-10 increased in
the fetal membranes and IL-4 in the myometrium with GR-1 (109 cfu) treatment (p<0.05,
Figure 4-9). GR-1 decreased the concentration of IL-4 in the fetal membranes, IL-10 in the
myometrium and IL-2 in the placenta (p<0.05, Figure 4-9). The concentration of IL-13 did
not change in any compartment between the different treatment groups (p>0.05, Figure 4-8
and Figure 4-9).
GR-1, at a dose of 1010 cfu, significantly increased the concentrations of chemokine CCL2,
CCL3, CCL4, CCL5 and CCL11 in the amniotic fluid (p<0.05, Figure 4-10). There was no
change in chemokine concentrations in the maternal plasma, placenta or decidua, following
GR-1 treatment (p>0.05, Figure 4-10 and Figure 4-11). The concentration of CCL5 increased
with GR-1 (109 cfu) treatment in the fetal membranes, and decreased in the myometrium
(p<0.05, Figure 4-11). GR-1 did not alter the concentration of CXCL1 in the maternal
plasma, amniotic fluid or in any of the tissues (p>0.05, Figure 4-10 and Figure 4-11).
78
The concentration of hematopoietic factors CSF2 and CSF3 did not change in the maternal
plasma, amniotic fluid, or tissues with GR-1 treatment alone at any dose (p>0.05, Figure 4-
12 and Figure 4-13). The concentration of IL-3 also did not change in the maternal plasma
and amniotic fluid (p>0.05, Figure 4-12). The concentration of IL-3 increased with GR-1
(109 cfu) treatment in the fetal membranes and placenta, and decreased in the myometrium
(p<0.05, Figure 4-13).
The concentrations of IL-5 and IL-9 were below the detection limits of the assay in the
maternal plasma, amniotic fluid and tissues. With GR-1 treatment (1010 cfu), the
concentrations of CCL4 and CCL11 in the maternal plasma (Figure 4-10) and CSF3 in the
amniotic fluid (Figure 4-12) were below the limits of assay detection. The changes in
cytokines and chemokines with GR-1 treatment are summarized in Table 4-4.
4.3.3 Maternal plasma progesterone (Set 3)
There was no difference in plasma progesterone concentrations between mice that received
saline (39.5 ± 4.4 ng/ml) and varying doses of GR-1 (108 cfu: 50.9 ± 4.4 ng/ml; 109 cfu: 48.6
± 4.9 ng/ml and 1010 cfu: 47.1 ± 7.0 ng/ml) (p>0.05, Table 4-5).
4.3.4 Vaginal and Cecal Microbiota (Set 4)
Sixty-two bacterial genera were detected in the vaginal tissues and 44 genera were identified
in the cecal tissues (Table 4-6 and 4-7). There were 24 bacterial genera unique to the vaginal
microbiota and 6 genera unique to the cecal microbiota (Table 4-6). The major bacterial
orders in the cecum of saline-treated mice were Bacteroidales and Clostridiales, while
Bacillales, Deinococcales and Pasteurellales dominated the vaginal microbiota in these mice
(Figure 4-14). There was no difference in the Shannon diversity index (SDI) between the
vaginal tissues and cecal tissues of saline-treated mice (p>0.05, Figure 4-15).
The relative mean abundance of 8 bacterial orders: Lactobacillales, Pseudomonadales,
Actinomycetales, Enterobacteriales, Hydrogenophilales, Neisseriales, Xanthomonadales, and
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Chromatiales were higher in the vaginal tissues than in the cecal tissues (Table 4-8). The
relative mean abundance of 5 bacteria order Bacteroidales, Clostridiales, Deinococcales,
Achleplasmatales and Opitutales were higher in the cecal tissues than in the vaginal tissues
(Table 4-9). The significance differences between the vaginal and cecal tissues of saline
treated pregnant CD-1 mice at lower taxonomic levels are summarized in Table 4-8 and
Table 4-9.
4.3.5 Effect of oral GR-1 on the vaginal microbiota (Set 4)
The relative abundance of bacteria order Bacillales, Pseudomonadales, Burkholderiales,
Hydrogenophilales decreased with oral GR-1 treatment (p<0.05, Table 4-10). Oral GR-1
significantly increased the relative abundance of bacteria order Bacteroidales and
Clostridiales (p<0.05, Table 4-11). The significance differences at lower taxonomic levels in
the vaginal microbiota between saline and GR-1 treated pregnant CD-1 mice are summarized
in Table 4-10 and Table 4-11. There was no difference in the SDI ratio in the vaginal tissues
between the saline and GR-1-treated mice (p>0.05, Figure 4-15).
4.3.6 Effect of oral GR-1 on the cecal microbiota (Set 4)
The SDI ratio was higher in the cecal tissues of GR-1 treated mice compared to saline treated
mice (p<0.05, Figure 4-15). The oral administration of GR-1 to pregnant CD-1 mice had no
effect on their cecal microbial profiles. There was no change in the abundance of
Lactobacillus in the mouse vaginal and cecal tissues. Although the vaginal microbiota
appears to resemble the cecal microbiota in pregnant mice treated with GR-1, there was no
statistical significant difference between the two groups (p>0.05, Figure 4-14).
4.4 Comment In this study, I have shown that the oral administration of Lactobacillus rhamnosus GR-1
live bacteria at a dose of 109 cfu does not reduce LPS-induced PTB nor does it have an effect
80
on the gestational length, fetal weight, litter size and the maternal circulating progesterone
concentration in pregnant CD-1 mice. Oral GR-1 live bacteria given alone can modulate the
systemic and intrauterine cytokines and chemokines.
Pretreatment with oral GR-1 live bacteria does not alter the incidence of LPS-induced PTB,
which is in contrast to our previous findings that GR-1 SN reduces LPS-induced PTB (Yang
et al., 2014b). Oral GR-1 alone stimulates the production of both systemic and intra-uterine
pro-inflammatory cytokines and chemokines. These findings are consistent with a previous
report that demonstrated in human decidual cells, L. rhamnosus CNCM I-4036 stimulate the
production of various pro-inflammatory cytokine and chemokines (Bermudez-Brito et al.,
2014). One plausible explanation is that the lipoteichoic acid (LTA) on the cell surface of
lactobacilli live bacteria may stimulate immune cells such as macrophages to secrete
inflammatory cytokines. When LTA is removed or modified (D-alanylation), improved anti-
inflammatory activity has been observed in a murine model of colitis (Grangette et al., 2005;
Claes et al., 2010; Mohamadzadeh et al., 2011).
The concentration of various pro-inflammatory cytokines increased following GR-1
treatment in the maternal plasma, amniotic fluid as well as in the intra-uterine tissues. In the
maternal plasma, pro-inflammatory cytokine was observed to increase significantly starting
at the lowest dose of GR-1 (108 cfu) (Figure 4-6), whereas a higher dose (1010 cfu) was
needed to elicit an increase in the concentration of various pro-inflammatory cytokines and
chemokines in the amniotic fluid (Figure 4-6 and Figure 4-10). Inflammatory cytokines
including TNFα, IL-1, and IL-6 have been implicated in the pathogenesis of human PTB
(Challis et al., 2009). Mice with the TNFα and IL-1 receptors knocked out (Hirsch et al.,
2006) or mice deficient in the IL-6 gene have delayed PTB compared to wild-type mice
(Robertson et al., 2010). In this study, a number of chemokines increased in the amniotic
fluid with GR-1 treatment, including CCL2 and CCL4. Elevated levels of CCL2 have been
observed in the mid-trimester amniotic fluid of women who delivered preterm (La Sala et al.,
2012). The concentration of amniotic fluid CCL4 has also been noted to be higher in women
with clinical signs of intrauterine infection and/or inflammation compared to women who
were asymptomatic (Weissenbacher et al., 2013). In this study, GR-1 increased the
81
production of IFN-γ, which has been shown to have antimicrobial properties and promotes
pathogen elimination (Mak, 2006). GR-1 also increased the concentration of CCL2, which is
important in pathogen phagocytosis (Mak, 2006). The concentration of IL-12 increased with
GR-1 treatment. IL-12 is important for the differentiation of Th0 cells into Th1 cells, which
play an important role in cell-mediated immune responses (Mak, 2006). Taken together, GR-
1 given orally promotes some degree of systemic and intra-uterine inflammation in pregnant
CD-1 mice.
Despite an increase in the concentration of TNFα and IL-6 with GR-1 treatment, labor was
not initiated, even at the highest doses of GR-1 (1010 cfu) used in this study. Furthermore, the
elevation in plasma TNFα was not sustained at a higher dose of GR-1 (1010 cfu), suggesting
there may be a degree of tolerance to excess GR-1 stimulation. Although the anti-
inflammatory cytokines IL-4 and IL-10 decreased with GR-1 treatment in fetal membranes
and myometrium respectively, the concentrations of IL-10 and IL-4 in the fetal membranes
and myometrium increased respectively, suggesting the anti-inflammatory cytokines may
interact with each other. This would be consistent with a previous study that has shown that
IL-4 dampens the production of IL-10 in dendritic cells (Yao et al., 2005). Oral GR-1 also
increased IL-2 in the placenta. IL-2 has been demonstrated to inhibit IL-1β-induced PGE2
production in human amnion cells, and PGE2 production in culture chorion and decidua cells
(Coulam et al., 1993a; Coulam et al., 1993b).
Oral GR-1 increased placental IL-17 and IL-3 concentrations. IL-17 promotes the process of
trophoblast invasion and angiogenesis, which are important in the establishment of placental
vasculature (Pongcharoen et al., 2006; Pongcharoen et al., 2007) and IL-3 is involved in the
differentiation and invasiveness of human trophoblast cells (Di Simone et al., 2000). Taken
together, these findings suggest that GR-1 may also affect the processes of angiogenesis and
placenta development in pregnant mice.
In this study, 44% (30 out of 68) of the identified bacterial genera were unique to either the
vaginal microbiota or the cecal microbiota of pregnant CD-1 mice although the common
bacteria genera shared by both the cecal and vaginal microbiota were present in different
82
relative abundances. Bacteroides and Barnesiella were found in both the vaginal and cecal
microbiota (Table 4-7) but the relative abundance of the two genera were significantly higher
in the cecal tissues than in the vaginal tissues (Table 4-9). These observations are in
agreement with a previous study, which reported the cecal and vaginal microbiota in non-
pregnant BALB/cJ mice each have its own distinct bacterial genera although there is some
overlap with each other (Barfod et al., 2013). These investigators have reported that the
vaginal and cecal microbiota only have bacterial genera Ruminococcus in common and that
three bacterial genera, Robinsoniella, Parasutterella and Ramlibacter, are unique to the cecal
microbiota (Barfod et al., 2013). In contrast, I have identified 38 bacterial genera shared by
both the vaginal and cecal microbiota (Table 4-7). It is known that different strains of mice,
C3H, Balb/c, Nude FoxN1nu and C57BL/6J mice display their own unique gut microbiomes
(Gutierrez-Orozco et al., 2015). In the human, the vaginal microbiome between pregnant and
non-pregnant women has also been found to be different, with a higher abundance of various
Lactobacillus spp. observed in pregnant women (Romero et al., 2014a). There is little
information known about the vaginal microbiome of pregnant mice versus non-pregnant
mice in different strains. The microbiome analysis is also influenced by the choice of PCR
primer that targets the 16S rDNA (Kuczynski et al., 2012). Primers that target the V6 region
have been reported to overestimate species richness (Youssef et a., 2009). Therefore, the
differences between the previous study (Barfod et al., 2013) and this study might be the
result of the use of a different strain of mice (CD-1 versus BALB/cj), the pregnancy status
(pregnant versus non-pregnant mice), a difference in sequencing protocol (primers target the
V6 region versus the V3-4 region of 16S rDNA) or a difference in housing conditions.
In this study, Clostridiales and Bacteroidales, which belong to the phyla Firmicutes and
Bacteroidetes respectively, were found to dominate the cecal microbiota of pregnant CD-1
mice. This is in agreement with a previous study, which found that Firmicutes and
Bacteroidetes were the most abundant phyla in the cecal microbiota of non-pregnant
BALB/cJ mice (Barfod et al., 2013). I have found Pasteurellales, Bacillales and
Deinococcales, which belong to the phyla Proteobacteria, Firmicutes, and Deinococcus
respectively, to be present in greater abundances in the vaginal tissues of pregnant CD-1
mice, which is consistent with the previous study that found Proteobacteria, Firmicutes,
83
Bacteroidetes, Actinobacteria and Cyanobacteria to be the major phyla in the vaginal
microbiota of non-pregnant BALB/cJ mice (Barfod et al., 2013). I found the species diversity
was higher in the cecal tissue with GR-1 treatment, suggesting GR-1 may promote the
growth of other bacteria in the mouse gut. In addition, there was high variability in the
species diversity in the vaginal microbiota of saline-treated mice (Figure 5-15). Some of the
animals received a higher volume of saline than others (range: 100-300µL), and it is possible
that excessive urination may have affected the vaginal species richness through dilution.
Since GR-1 bacteria, which were resuspended in saline, have high viscosity, this dilutional
effect would not have been observed in the GR-1-treated mice (Figure 5-15).
Oral GR-1 altered the mouse vaginal microbiota in this study. The relative abundance of
bacterial order Bacillales decreased with oral GR-1 treatment, with representative genera in
Bacillales including Staphylococcus. Certain strains of Staphylococcus such as S.
aureus rectovaginal colonization have been associated with an increased risk of infections in
pregnant women (Top et al., 2012). Oral GR-1 also decreased the relative abundances of
bacteria orders Pseudomonadales, Burkholderiales, Hydrogenophilales, which collectively
belong to the phylum Proteobacteria. Many disease-causing bacteria can be found within
this phylum, including Escherichia (urinary tract infection), Salmonella (enteritis and
typhoid fever), Vibrio (cholera), and Helicobacter (gastritis). Inflammatory conditions such
as inflammatory bowel diseases have been associated with an increased abundance of
Proteobacteria in the human gut (Mukhopadhya et al., 2012). Furthermore, an increase in the
proportion of Proteobacteria in the stool of third trimester pregnant women has been
associated with an increase in various pro-inflammatory cytokines (Koren et al., 2012).
In contrast, oral GR-1 increased the relative abundance of bacteria order Bacteroidales,
which belongs to the phylum Bacteroidetes. It has been observed that Bacteroidetes is
present in higher abundance in lean people than in obese people, and the abundance of
Bacteroidetes increases in adults on low-calorie weight loss diets (Ley et al., 2006). Oral
GR-1 also significantly increased the relative abundance of bacterial order Clostridiales and
the genus Clostridium. The genus Clostridium contains species such as C. botulinum toxin A,
which interestingly has been shown to inhibit oxytocin-induced uterine contractions in
84
cultured human myometrial cells (Burd et al., 2009). Many species belonging to the same
genus of bacteria may have diverging effects on the host. There may also be potential
interactions between the bacteria, as well as between multiple microbiomes at different body
sites. Future metabolomic studies will help provide functional interpretations to the changes
in the vaginal microbiota observed in this study.
It has been previously shown that oral GR-1 and RC-14 colonize the vagina of non-pregnant
women (Anukam et al., 2006). It is not known however whether the lactobacilli given orally
persist in the gut and are later transmitted to the vagina due to the proximity of rectum, or the
Lactobacillus strains transiently colonize the gut and induce the gut epithelium to produce
signaling molecules, which in turn alter the vaginal environment to favor the growth of the
Lactobacillus spp. In this study, oral GR-1 altered the mouse vaginal microbiota, but not the
cecal microbiota, and there was no difference in the relative abundance of Lactobacillus
rhamnosus after GR-1 treatment. These findings suggest that GR-1 taken orally did not
persist in the gut and instead, GR-1 may induce signaling mediators to modulate the vaginal
environment, inducing changes in cytokines and altering the growth of bacteria other than
lactobacilli.
In summary, this study has demonstrated that oral GR-1 live bacteria have immune-
stimulatory properties in pregnant CD-1 mice, which is different from the anti-inflammatory
effect observed with GR-1 SN. A high dose of GR-1 live bacteria may have adverse effects
due to its inflammatory stimulation evident particularly in the amniotic fluid. Furthermore,
oral GR-1 modulates the vaginal but not the cecal microbiota, suggesting the potential
mechanism of GR-1 whereby probiotic lactobacilli exert its effect is primarily through the
secretion of signalling molecules. Findings in this study suggest that the supernatant of
lactobacilli, rather than its live bacterial counterpart, may be more appropriate for the
prevention of PTB.
85
Figure 4-1 Probiotic Lactobacillus dose translation from a human dose to a mouse equivalent dose based on the body surface area (Km) and weight.
Km: factor for converting mg/kg dose to mg/m2 dose. The equation is modified from Reagan-Shaw S, Nihal M, Ahmad N (2008) Dose translation from animal to human studies revisited. FASEB J 22: 659-661.
Mouse (cfu/kg) = Human (cfu/kg) X Human Km Animal Km Human: ~60kg Animal Km: 3 Human Km: 37 Mouse (cfu/kg) = 109 to 1011 cfu per 60kg X 37/3 = ~ 2x109 to 1011 cfu Each mouse weighs approximately 20g, Per Mouse = 2 X 109 to 1011 cfu 1000/20 = 2 X 108 to 109 cfu
86
Figure 4-2 Experimental design to investigate the effect of oral GR-1 on the timing of LPS-induced PTB (Set 1).
Pregnant mice were given saline or GR-1 (109 cfu) via oral gavage once daily from GD 9 to GD 15. Animals were then divided to receive intra-uterine injection of saline, LPS (25µg) or LPS (50µg). Mice in the sham group did not receive any experimental procedures (oral gavage or mini-laparotomy). Mice were monitored for the time of delivery in individual cages until term (GD 19/20). Preterm delivery was defined as delivery of at least one pup 48 hours after intrauterine injection of LPS (GD 17).
Pregnant CD-1 mice
0ral Gavage (100-300µL) 1 9 10 11 12 13 14 15 16 17 18
19/20
……….#
Gestational Day (GD)
Saline GR-1 (109 cfu)
7 consecutive days (GD 9 -15) Once daily
Saline LPS 50µg LPS 25µg Saline LPS 50µg LPS 25µg
Laparotomy/ Intra-uterine infusion (100µL) GD 15
Monitor for time of delivery Preterm
Term Sham No oral gavage or
laparotomy
n=11 n=11 n=11 n=11 n=11 n=11
n=11
87
Figure 4-3 Experimental design to investigate the effect of oral GR-1 on the gestational length (Set 2).
Pregnant mice were given saline or three increasing doses of GR-1 (108 cfu, 109 cfu, 1010cfu) via oral gavage once daily from GD 9 to GD 15. Mice in the sham group did not receive any experimental procedures. Mice were monitored for the time of delivery in individual cages until term (GD 19/20).
Pregnant CD-1 mice
0ral Gavage (100-300µL) 1 9 10 11 12 13 14 15 16 17 18
19/20
……….#
Gestational Day (GD)
Saline GR-1 (1010 cfu)
7 consecutive days (GD 9-15) Once daily
Preterm
Term
GR-1 (108 cfu) GR-1 (109 cfu)
Sham No oral gavage
Monitor for time of delivery
n=11 n=11 n=11 n=11
n=11
88
Figure 4-4 Experimental design to investigate the effect of oral GR-1 on cytokines and chemokines (Set 3).
Pregnant mice were given saline or three increasing doses of GR-1 (108 cfu, 109 cfu, 1010cfu) via oral gavage once daily from GD 9 to GD 15. Maternal plasma and amniotic fluid were collected from mice in all four groups on GD 15. Intra-uterine tissues (fetal membranes, placenta, decidua and myometrium) were harvested from mice in the saline and GR-1 109 cfu groups.
Pregnant CD-1 mice
0ral Gavage (100-300µL) 1 9 10 11 12 13 14 15 16 17 18
19/20
……….#
Gestational Day (GD)
Saline GR-1 (1010 cfu)
7 consecutive days (GD 9-15) Once daily
GR-1 (108 cfu) GR-1 (109 cfu)
……….#
Maternal Plasma ✔ ✔ ✔ ✔
Amniotic Fluid ✔ ✔ ✔ ✔
Tissues ✔ - ✔ -
n=13 n=7 n=8 n=6
Cytokine and chemokine protein measurement
89
Figure 4-5 Experimental design to investigate the effect of oral GR-1 on the vaginal and cecal microbiota (Set 4).
Pregnant mice were given either saline of GR-1 (109 cfu) via oral gavage once daily from GD 9 to GD 15. Vaginal and cecal tissues were collected on GD 15 for sequencing analysis.
Pregnant CD-1 mice
0ral Gavage (100-300µL) 1 9 10 11 12 13 14 15 16 17 18
19/20
……….#
Gestational Day (GD)
Saline GR-1 (109 cfu)
7 consecutive days (GD 9-15) Once daily
Sample
Collection
• Vaginal Tissue • Cecal Tissue
n=7 n=7
90
Figure 4-6 Histogram showing the concentration of pro-inflammatory cytokine IL-1α, IL-1β, IL-6, IL-17, IL-12p40, IL-12p70, TNFα and IFN-γ in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are four treatment groups: saline (white, MP n=13, AF n=12); GR-1 108 cfu (light grey, MP n=7, AF n=6); GR-1 109 cfu (dark grey, MP n=6, AF n=8) and GR-1 1010 cfu (black bars, MP n=6, AF n=6). Comparison within groups was assessed with Kruskal-Wallis test followed by Dunns post-hoc test. Statistical significance was denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001).
010203040
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IL-6
Maternal Plasma
AmnioticFluid
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Maternal Plasma
AmnioticFluid
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Maternal Plasma
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Maternal Plasma
AmnioticFluid
** a a a b
a a,b
a,b
b **
** a b b a
** a a a b
Saline GR-1 108 cfu GR-1 109 cfu GR-1 1010 cfu
91
Figure 4-7 Histogram showing the concentration of pro-inflammatory cytokines IL-1α, IL-1β, IL-6, IL-17, IL-12p40, IL-12p70, TNFα and IFN-γ in the fetal membranes, placenta, decidua and myometrium of pregnant mice that received saline and GR-1 at 109 cfu via oral gavage (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are two treatment groups, saline (white, n=7) and GR-1 at 109 cfu (dark grey, n=5) in the fetal membranes. There are 6 samples in the saline group and 6 samples in the GR-1 group for the placenta, decidua and myometrium. Comparison between the two groups was assessed with Mann-Whitney test. Statistical significance is denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001).
05
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FetalMembranes
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FetalMembranes
Placenta MyometriumDecidua
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FetalMembranes
Placenta MyometriumDecidua
** a b
** a b
** a b
** a b
Saline GR-1 109 cfu
92
Figure 4-8 Histogram showing the concentration of anti-inflammatory cytokines IL-2, IL-4, IL-10 and IL-13 in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3). Results are mean values ± SEM and expressed in pg/mL. There are four treatment groups: saline (white, MP n=13, AF n=12); GR-1 108 cfu (light grey, MP n=7, AF n=6); GR-1 109 cfu (dark grey, MP n=6, AF n=8) and GR-1 1010 cfu (black bars, MP n=6, AF n=6). Comparison within groups was assessed with Kruskal-Wallis test followed by Dunns post-hoc test.
0123455
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Maternal Plasma
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Maternal Plasma
AmnioticFluid
Saline GR-1 10
8 cfu
GR-1 109 cfu
GR-1 1010
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93
Figure 4-9 Histogram showing the concentration of anti-inflammatory cytokines IL-2, IL-4, IL-10 and IL-13 in the fetal membranes, placenta, decidua and myometrium of pregnant mice that received saline and oral GR-1 at 109 cfu (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are two treatment groups, saline (white, n=7) and GR-1 at 109 cfu (dark grey, n=5) in the fetal membranes. There are 6 samples in the saline group and 6 samples in the GR-1 group for the placenta, decidua and myometrium. Comparison between the two groups was assessed with Mann-Whitney test. Statistical significance was denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001).
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Placenta MyometriumDecidua0123455
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** a b
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Saline GR-1 10
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94
Figure 4-10 Histogram showing the concentration of chemokines CCL2, CCL3, CCL4, CCL5, CCL11, CXCL1 in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are four treatment groups: saline (white, MP n=13, AF n=12); GR-1 108 cfu (light grey, MP n=7, AF n=6); GR-1 109 cfu (dark grey, MP n=6, AF n=8) and GR-1 1010 cfu (black bars, MP n=6, AF n=6). Comparison within groups was assessed with Kruskal-Wallis test followed by Dunns post-hoc test. Statistical significance is denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001). <OOR denotes out of the detection range.
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Maternal Plasma
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<OOR
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Saline GR-1 108 cfu GR-1 109 cfu GR-1 1010 cfu
95
Figure 4-11 Histogram showing the concentration of chemokines CCL2, CCL3, CCL4, CCL5, CCL11, CXCL1 in the fetal membranes, placenta, decidua and myometrium of pregnant mice that received saline and oral GR-1 at 109 cfu (Set 3). Results are mean values ± SEM and expressed in pg/mL. There are two treatment groups, saline (white, n=7) and GR-1 at 109 cfu (dark grey, n=5) in the fetal membranes. There are 6 samples in the saline group and 6 samples in the GR-1 group for the placenta, decidua and myometrium. Comparison between the two groups was assessed with Mann-Whitney test. Statistical significance is denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001).
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** a b
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Saline GR-1 109 cfu
96
Figure 4-12 Histogram showing the concentration of hematopoietic factors CSF2, CSF3 and IL-3 in the maternal plasma (MP) and amniotic fluid (AF) of pregnant mice that received varying doses of GR-1 (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are four treatment groups: saline (white, MP n=13, AF n=12); GR-1 108 cfu (light grey, MP n=7, AF n=6); GR-1 109 cfu (dark grey, MP n=6, AF n=8) and GR-1 1010 cfu (black bars, MP n=6, AF n=6). Comparison within groups was assessed with Kruskal-Wallis test followed by Dunns post-hoc test. Statistical significance is denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001). <OOR denotes out of the detection range.
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97
Figure 4-13 Histogram showing the concentrations of hematopoietic factors CSF2, CSF3 and IL-3 in the fetal membranes, placenta, decidua and myometrium of pregnant CD-1 mice that received saline and oral GR-1 at 109 cfu (Set 3).
Results are mean values ± SEM and expressed in pg/mL. There are two treatment groups in the intrauterine tissues: saline (white) and GR-1 109 cfu (dark grey). There are two treatment groups, saline (white, n=7) and GR-1 at 109 cfu (dark grey, n=5) in the fetal membranes. There are 6 samples in the saline group and 6 samples in the GR-1 group for the placenta, decidua and myometrium. Comparison between the two groups was assessed with Mann-Whitney test. Statistical significance is denoted with different letters and with asterisks (*p<0.05; **p<0.01; ***p<0.001).
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IL-3
FetalMembranes
Placenta MyometriumDecidua
0
25
50
75
100C
once
ntra
tion
(pg/
mL)
CSF2
FetalMembranes
Placenta MyometriumDecidua
* a b
** a b
* a b
Saline GR-1 10
9 cfu
98
Figure 4-14 Stacked barplots showing the vaginal and cecal bacterial compositions of pregnant CD-1 mice that received either oral saline or GR-1.
Each bar represents the vaginal or cecal microbiota of a single mouse and corresponds to the identification number labeled below each bar. Bacterial order found in >1% abundance are represented by a unique color, and orders that have <1% abundance are pooled into a single fraction at the top of the bar in dark blue.
Vaginal Saline
Vaginal GR-1 109 cfu
Cecal Saline
Cecal GR-1 109 cfu
n=6 n=7 n=6 n=6
99
Figure 4-15 Scatterplot showing the Shannon diversity index (SDI) of the vaginal and cecal microbiota of pregnant CD-1 mice.
Results are mean values ± SD and expressed in SDI ratios. Comparisons between the saline and GR-1 groups in the vaginal and in the cecal tissues, as well as between the two saline groups were assessed with Mann Whitney’s test. Statistical significance is denoted with an asterisk (*p<0.05).
0
1
2
3
Shan
non
Div
ersi
ty In
dex
Saline (Vaginal)
Saline (Cecal)
GR-1 (Vaginal)
GR-1 (Cecal)
*
n=6 n=7 n=6 n=6
100
Table 4-1 Delivery outcome of pregnant CD-1 following different treatments in Set 1.
Preterm delivery is defined as delivery of at least one pup within 48 hours of intrauterine injection of LPS. For the delivery outcome results, the LPS 25µg group was compared with each of the following four groups using Fisher’s exact test (sham, saline, 109 cfu, and LPS 25µg + GR-1 109 cfu group with 11 animals in each group). The LPS 50µg group was compared with each of the following four groups using Fisher’s exact test (sham, saline, 109 cfu, and LPS 50µg + GR-1 109 cfu group with 11 animals in each group). Statistical significance is denoted with different letters.
Group
No. of animals delivered
preterm�
No. of animals delivered
term��
Sham
0 a�
11 a�
Saline
0 a�
11 a�
GR-1 109 cfu
0 a�
11 a�
LPS 25 µg�
4 b�
7 b�
LPS 25 µg + GR-1 109 cfu�
7 b�
4 b�
LPS 50 µg�
11 c�
0 c�
LPS 50 µg + GR-1 109 cfu�
11 c�
0 c�
101
Table 4-2 Litter size and fetal weight of live term neonates born to pregnant CD-1 mice at term that received different treatments in Set 1.
Litter size and fetal weight data are expressed in mean values ± SEM. One-Way ANOVA followed by Tukey test was used to compare the groups with one another (p>0.05). Pregnant mice in the LPS 25µg group (4 out of 11), LPS 25µg+ GR-1 109 cfu group (7 out of 11), LPS 50µg group (11 out of 11) and the LPS 50µg + GR-1 109 cfu group (11 out of 11) delivered preterm and there were no surviving pups.
Group
Litter size�
Weight per pup
(gram)�
P-value�
Sham
12.5±0.37 (n=11)�
1.70 ±0.09 (n=11)�
> 0.05�
Saline
12.7 ±0.47 (n=11)�
1.84 ±0.13 (n=11)�
> 0.05��
GR-1 109 cfu
12.5 ±0.43 (n=11)�
1.73 ±0.11 (n=11)�
> 0.05��
LPS 25 µg�
11.4 ±0.61 (n=7)�
1.51 ±0.14 (n=7)�
> 0.05��
LPS 25 µg + GR-1 109 cfu�
12.3 ±0.48 (n=4)�
1.80 ±0.04 (n=4)�
> 0.05��
LPS 50 µg�
-�
-�
> 0.05��
LPS 50 µg + GR-1 109 cfu�
-�
-�
> 0.05��
102
Table 4-3 Hours to delivery, litter size and fetal weight of neonates born to pregnant CD-1 mice that received saline or oral GR-1 (Set 2).
Results are mean values ± SEM and expressed in hours (n=11 per group). One-Way ANOVA followed by Tukey test was used to compare the groups with one another.
Group
Hours to delivery
Litter size�
Weight per pup (gram)�
P value�
Sham
106 ± 3.3�
12.4 ± 0.36��
1.68 ± 0.08��
> 0.05�
Saline
106 ± 3.3��
12.1 ± 0.53�
1.84 ± 0.13�
> 0.05��
GR-1 109 cfu
100 ± 3.0��
12.2 ± 0.44 �
1.63 ± 0.11�
> 0.05��
GR-1 109 cfu
99 ± 2.4��
12.5 ± 0.53�
1.45 ± 0.10��
> 0.05��
GR-1 1010 cfu
101 ± 3.3��
12.5 ± 0.45�
1.69 ± 0.11��
> 0.05��
103
Table 4-4 Summary table of cytokines and chemokines in the maternal plasma, amniotic fluid and intrauterine tissues following varying doses of oral GR-1 treatment.
An upward arrow indicates a significant increase and a downward arrow indicates a significant decrease following GR-1 treatment, when compared to mice that received saline. A dash (-) denotes no significant difference is observed. The numerical value in brackets indicates the dose of GR-1 at which significance is achieved. (8) 108 cfu; (9) 109 cfu; (10) 1010 cfu.
Pro-inflammatory
cytokines
Maternal Plasma
Amniotic Fluid
Fetal Membranes
Placenta Decidua Myometrium
IL-1α - - - - - ! (9)
IL-1β - - - - - -
IL-6 - ! (10) - - - -
IL-17 - - - ! (9) - -
IL-12p40 ! (10) - - - - -
IL-12p70 - - " (9) - - -
TNFα ! (8,9) - - ! (9) - -
IFNγ - ! (10) - - - -
Anti-inflammatory
cytokines
Maternal Plasma
Amniotic Fluid
Fetal Membranes
Placenta Decidua Myometrium
IL-2 - - ! (9) - - -
IL-4 - - " (9) - - ! (9)
IL-10 - - ! (9) - - " (9)
IL-13 - - - - - -
Chemokines Maternal Plasma
Amniotic Fluid
Fetal Membranes
Placenta Decidua Myometrium
CCL2 - ! (10) - - - -
CCL3 - ! (10) - - - -
CCL4 - ! (10) - - - -
CCL5 - ! (10) ! (9) - - " (9)
CCL11 - ! (10) - - - -
CXCL1 - - - - - -
Hematopoietic Factors
Maternal Plasma
Amniotic Fluid
Fetal Membranes
Placenta Decidua Myometrium
CSF2 - - - - - -
CSF3 - - - - - -
IL-3 - - ! (9) ! (9) - " (9)
104
Table 4-5 Maternal plasma progesterone concentrations in pregnant CD-1 mice with varying dose of GR-1 (Set 3)
Results are mean values ± SEM and expressed in ng/mL (n=6 per group). Comparison within groups was assessed with Kruskal Wallis test followed by Dunns post-hoc test (p > 0.05).
Treatment
Saline
GR-1 108 cfu
GR-1 109 cfu
GR-1 1010 cfu
Progesterone concentration
39.5 ± 4.4 50.9 ± 4.4 48.6 ± 4.9 47.1 ± 7.0
105
Table 4-6 Bacterial groups unique to the cecal and vaginal tissues of saline-treated pregnant CD-1 mice.
Presence of the bacteria is denoted with + while absence of the bacteria is denoted with –.
Bacterial Group cecal
(saline) vaginal (saline)
Actinobacteria;Actinobacteria;Actinomycetales;Corynebacteriaceae;Corynebacterium - + Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Micrococcus - + Firmicutes;Bacilli;Bacillales;Bacillaceae1;Anoxybacillus - + Firmicutes;Bacilli;Bacillales;Bacillaceae1;Geobacillus - + Firmicutes;Bacilli;Bacillales;Staphylococcaceae;Staphylococcus - + Proteobacteria;Betaproteobacteria;Hydrogenophilales;Hydrogenophilaceae;Hydrogenophilus - + Proteobacteria;Betaproteobacteria;Hydrogenophilales;Hydrogenophilaceae;Petrobacter - + Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria - + Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Acinetobacter - + Proteobacteria;Gammaproteobacteria;Pseudomonadales;Pseudomonadaceae;Pseudomonas - + Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces - + Actinobacteria;Actinobacteria;Actinomycetales;Microbacteriaceae;Microbacterium - + Actinobacteria;Actinobacteria;Actinomycetales;Nocardioidaceae;Marmoricola - + Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Rothia - + Actinobacteria;Actinobacteria;Coriobacteriales;Coriobacteriaceae;Atopobium - + Bacteroidetes;Sphingobacteria;Sphingobacteriales;Cytophagaceae;Hymenobacter - + Deinococcus-Thermus;Deinococci;Thermales;Thermaceae;Thermus - + Firmicutes;Bacilli;Bacillales;Bacillales_IncertaeSedisXI;Gemella - + Firmicutes;Bacilli;Lactobacillales;Aerococcaceae;Aerococcus - + Firmicutes;Bacilli;Lactobacillales;Enterococcaceae;Enterococcus - + Proteobacteria;Alphaproteobacteria;Rhizobiales;Methylobacteriaceae;Methylobacterium - + Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Shigella - + Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Actinobacillus - + Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Psychrobacter - + Firmicutes;Bacilli;Bacillales;Alicyclobacillaceae;Alicyclobacillus + - Actinobacteria;Actinobacteria;Coriobacteriales;Coriobacteriaceae;Slackia + - Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXIII;Clostridiaceae + - Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Ruminococcus + - Firmicutes;Clostridia;Halanaerobiales;Halobacteroidaceae;Halobacteroidaceae + - Firmicutes;Clostridia;Thermoanaerobacterales;Thermoanaerobacteraceae;Moorella + -
106
Table 4-7 Bacterial groups present in both the cecal and vaginal tissues of saline-treated pregnant CD-1 mice.
Bacterial Group cecal
(saline) vaginal (saline)
Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidaceae;Bacteroides + + Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Barnesiella + + Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Candidatus + + Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Gram-negative + + Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonadaceae + + Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas + + Bacteroidetes;Bacteroidia;Bacteroidales;Rikenellaceae;Alistipes + + Bacteroidetes;Sphingobacteria;Sphingobacteriales;Sphingobacteriaceae;Parapedobacter + + Deinococcus-Thermus;Deinococci;Deinococcales;Deinococcaceae;Deinococcus + + Firmicutes;Bacilli;Bacillales;Bacillaceae1;Bacillus + + Firmicutes;Bacilli;Bacillales;Paenibacillaceae1;Paenibacillus + + Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus + + Firmicutes;Bacilli;Lactobacillales;Leuconostocaceae;Leuconostoc + + Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Lactococcus + + Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus + + Firmicutes;Clostridia;Clostridiales;Clostridiaceae1;Clostridium + + Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXII;Fusibacter + + Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXII;Peptostreptococcaceae + + Firmicutes;Clostridia;Clostridiales;Eubacteriaceae;Acetobacterium + + Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Clostridiales + + Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Clostridium + + Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Eubacterium + + Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Lachnospiraceae + + Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Oribacterium + + Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Ruminococcus + + Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Shuttleworthia + + Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Clostridiales + + Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Clostridium + + Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Lactobacillales + + Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Clostridium + + Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Turicibacter + + Proteobacteria;Betaproteobacteria;Burkholderiales;Sutterellaceae;Parasutterella + + Proteobacteria;Deltaproteobacteria;Desulfovibrionales;Desulfovibrionaceae;Bilophila + + Proteobacteria;Gammaproteobacteria;Oceanospirillales;Halomonadaceae;Haererehalobacter + + Proteobacteria;Gammaproteobacteria;Oceanospirillales;Halomonadaceae;Halomonas + + Tenericutes;Mollicutes;Acholeplasmatales;Acholeplasmataceae;Flavescence + + Verrucomicrobia;Opitutae;Opitutales;Opitutaceae;Opitutus + + Verrucomicrobia;Verrucomicrobiae;Verrucomicrobiales;Verrucomicrobiaceae;Akkermansia + +
107
Table 4-8 Bacteria at different taxonomic levels that have statistically significant higher abundance in the vaginal tissues than in the cecal tissues of saline-treated pregnant CD-1 mice.
Results are mean values ± SD and expressed in centered logarithm transformed ratios. Comparison between the saline (vaginal) group (n=6) and saline (cecal) group (n=6) was assessed with Mann-Whitney test. Statistical significance is denoted with different letters (p<0.05).
Bacteria Taxonomy Saline (vaginal) Mean %
Abundance
Mean Relative abundance (ratio)
Diff
Fold Changes
(2 -diff) Saline (vaginal)
Saline (cecal)
ORDER Lactobacillales 13.2±12.1 7.3±3.2 a 3.3±1.5 b -4.0 16 Pseudomonadales 4.0±3.9 5.5±0.9 a -5.1±3.8 b -10.6 1552 Actinomycetales 7.7±10.0 5.3±1.9 a -4.0±3.1 b -9.3 630 Enterobacteriales 11.3±24.1 3.5±6.4 a -3.8±2.6 b -7.3 158 Hydrogenophilales 1.6±2.4 2.4±2.7 a -5.1±2.3 b -7.5 181 Neisseriales 0.4±0.9 -0.6±3.0 a -5.1±3.5 b -4.5 23 Xanthomonadales 0.2±0.2 -1.1±4.1 a -5.1±2.7 b -4.0 16 Chromatiales 0.5±0.9 -1.3±3.9 a -5.1±2.1 b -3.8 14 FAMILY Bacillaceae1 12.2±15.7 7.9±2.8 a -1.2±1.4 b -9.1 549 Propionibacteriaceae 2.7±2.3 4.8±2.2 a -2.9±1.5 b -7.7 208 Staphylococcaceae 2.2±2.2 4.8±1.6 a -4.1±1.7 b -8.9 478 Moraxellaceae 3.0±3.7 4.3±3.2 a -4.1±4.7 b -8.3 315 Comamonadaceae 1.5±1.3 4.3±2.4 a -4.1±4.6 b -8.4 338 Corynebacteriaceae 3.9±3.3 a -4.1±4.0 b -8.0 256 Hydrogenophilaceae 1.6±2.4 3.1±2.7 a -4.1±2.2 b -7.2 147 Micrococcaceae 0.1±0.2 1.8±1.0 a -4.1±3.5 b -5.8 56 Pseudomonadaceae 0.3±0.3 1.7±2.4 a -4.1±3.0 b -5.8 56 Burkholderiales incertae_sedis
0.2±0.3 0.5±2.0 a -4.1±2.7 b -4.5 23
GENERA Anoxybacillus 2.2±1.2 6.0±1.3 a -4.1±2.4 b -10.1 1097 Staphylococcus 2.2±2.2 5.6±1.7 a -4.1±2.0 b -9.7 832 Acinetobacter 2.5±3.5 4.6±3.2 a -4.1±6.0 b -8.6 388 Hydrogenophilus 1.5±2.4 3.5±2.8 a -4.1±2.4 b -7.6 194 Corynebacterium 4.0±8.4 3.0±4.9 a -4.1±5.2 b -7.1 137 Pseudomonas 0.1±0.1 2.5±2.5 a -4.1±3.3 b -6.5 91 Micrococcus 0.1±0.1 1.5±1.0 a -4.1±3.8 b -5.6 49 Petrobacter 0.1±0.0 0.9±1.8 a -4.1±3.2 b -5.0 32 Neisseria 0.4±0.9 0.8±3.0 a -4.1±3.7 b -4.9 30 Geobacillus 0.2±0.5 0.5±2.7 a -4.1±2.7 b -4.6 24
108
Table 4-9 Bacteria at different taxonomic levels that have statistically significant higher abundance in the cecal tissues than in the vaginal tissues of saline-treated pregnant CD-1 mice.
Results are mean values ± SD and expressed in centered logarithm transformed ratios (n=6 per group). Comparison between the saline (vaginal) group (n=6) and saline (cecal) group (n=6) was assessed with Mann-Whitney test. Statistical significance is denoted with different letters (p<0.05).
Bacteria Taxonomy
Saline (vaginal) Mean %
Abundance
Mean Relative abundance Diff
Fold Changes
(2diff) Saline (vaginal)
Saline (cecal)
ORDER Bacteroidales 7.1±9.0 5.2±2.2 a 10.2±1.3 b 5.0 32.2 Clostridiales 4.0±3.3 4.9±2.0 a 9.3±1.6 b 4.4 20.7 Deinococcales 0.5±0.6 1.2±2.1 a 6.0±1.4 b 4.8 27.6 Acholeplasmatales 0.1±0.3 -2.1±4.2 a 4.6±3.9 b 6.8 109.7 Opitutales 0.1±0.2 -4.2±3.3 a 2.2±2.6 b 6.4 84.7 FAMILY Lachnospiraceae 2.7±1.8 5.0±2.3 a 10.0±1.7 b 4.9 30.6 Porphyromonadaceae 5.6±8.1 4.9±3.5 a 10.5±1.4 b 5.5 46.5 Paenibacillaceae1 0.9±0.7 3.5±2.0 a 7.0±1.4 b 3.6 11.7 Bacteroidaceae 0.8±0.7 3.2±1.5 a 9.1±1.9 b 5.9 59.0 Ruminococcaceae 0.7±1.1 2.7±1.7 a 6.7±1.2 b 4.0 15.6 Deinococcaceae 0.5±0.6 1.8±2.1 a 7.0±1.5 b 5.2 35.8 Clostridiaceae1 0.3±0.3 1.5±1.7 a 6.0±3.0 b 4.6 23.9 Rikenellaceae 0.2±0.1 0.7±1.9 a 6.4±4.1 b 5.8 53.9 Prevotellaceae 0.5±0.6 0.6±3.6 a 7.0±1.6 b 6.4 83.4 Acholeplasmataceae 0.1±0.3 -1.5±4.4 a 5.7±3.9 b 7.2 142.3 Sutterellaceae 0.1±0.3 -2.6±3.5 a 3.7±3.7 b 6.4 83.0 Opitutaceae 0.1±0.2 -3.5±3.4 a 3.3±2.7 b 6.8 109.9 GENERA Barnesiella 3.4±5.6 4.8±3.2 a 9.4±1.1 b 4.6 25.0 Bacteroides 0.8±0.7 4.0±1.6 a 9.1±1.6 b 5.1 35.1 Clostridiales 0.6±0.9 2.8±2.3 a 7.0±1.2 b 4.2 18.0 Deinococcus 0.5±0.6 2.6±2.2 a 7.0±1.3 b 4.4 21.3 Porphyromonadaceae 0.2±0.3 2.0±1.9 a 5.1±3.8 b 3.0 8.2 Candidatus 0.4±0.8 0.5±3.6 a 6.5±1.7 b 6.0 63.4 Porphyromonas 0.1±0.1 -0.3±2.5 a 4.7±0.7 b 5.0 32.2 Alistipes 0.1±0.1 -1.2±3.4 a 5.4±3.3 b 6.6 96.6 Parasutterella 0.2±0.3 -1.9±3.4 a 3.7±3.4 b 5.6 49.4
109
Table 4-10 Bacteria at different taxonomic levels that decreased significantly with oral GR-1 treatment in the vaginal tissues of pregnant CD-1 mice.
Results are mean values ± SD and expressed in centered logarithm transformed ratios. Comparison between the saline group (n=6) and GR-1 group (n=7) was assessed with Mann-Whitney test. Statistical significance is denoted with different letters (p<0.05).
Bacteria Taxonomy
Saline Mean %
abundance
Mean Relative abundance
Diff
Fold Changes
(2diff) Saline GR-1
ORDER Bacillales 15.4±14.4 7.8±2.6 a 5.1±0.4 b -2.7 0.16 Pseudomonadales 4.0±3.9 5.5±0.9 a 1.3±3.8 b -4.2 0.05 Burkholderiales 2.2±1.8 4.5±1.4 a 2.5±1.4 b -2.1 0.24 Hydrogenophilales 1.6±2.4 2.4±2.7 a -0.6±2.3 b -3.0 0.12 FAMILY Bacillaceae1 12.2±15.7 7.9±2.8 a 3.3±1.4 b -4.5 0.04 Propionibacteriaceae 2.7±2.3 4.8±2.2 a 2.1±1.5 b -2.7 0.15 Staphylococcaceae 2.2±2.2 4.8±1.6 a 2.5±1.7 b -2.4 0.19 Comamonadaceae 1.5±1.3 4.3±2.4 a -1.7±4.6 b -6.1 0.01 Micrococcaceae 0.1±0.2 1.8±1.0 a -3.1±3.5 b -4.9 0.03 Burkholderiales_incertae_sedis 0.2±0.3 0.5±2.0 a -4.8±2.7 b -5.2 0.03 GENERA Anoxybacillus 2.2±1.2 6.0±1.3 a 2.1±2.4 b -4.0 0.06 Staphylococcus 2.2±2.2 5.6±1.7 a 2.9±2.0 b -2.6 0.16 Micrococcus 0.1±0.1 1.5±1.0 a -2.7±3.8 b -4.2 0.05 Petrobacter 0.1±0.0 0.9±1.8 a -3.7±3.2 b -4.6 0.04 Geobacillus 0.2±0.5 0.5±2.7 a -4.0±2.7 b -4.5 0.05
110
Table 4-11 Bacteria at different taxonomic levels that increased significantly with oral GR-1 treatment in the vaginal tissues of pregnant CD-1 mice.
Results are mean values ± SD and expressed in centered logarithm transformed ratios (saline group: n=6; GR-1 group: n=7). Comparison between the saline group (n=6) and GR-1 group (n=7) was assessed with Mann-Whitney test. Statistical significance is denoted with different letters (p<0.05).
Bacteria Taxonomy
Saline Mean %
abundance
Mean Relative abundance Diff
Fold Changes
(2diff) Saline GR-1
ORDER Bacteroidales 7.1±9.0 5.2±2.2 a 7.6±1.3 b 2.4 5.13 Clostridiales 4.0±3.3 4.9±2.0 a 7.2±1.6 b 2.3 4.90 FAMILY Bacteroidaceae 0.8±0.7 3.2±1.5 a 6.2±1.9 b 2.9 7.72 Halomonadaceae 0.0±0.1 -2.8±2.5 a 1.3±2.1 b 4.0 16.54 GENERA Bacteroides 0.8±0.7 4.0±1.6 a 6.7±1.6 b 2.7 6.43 Clostridium 0.4±0.3 3.1±1.3 a 5.8±0.9 b 2.7 6.38 Porphyromonas 0.1±0.1 -0.3±2.5 a 2.8±0.7 b 3.1 8.35
111
Chapter Five
Effect of oral probiotic Lactobacillus rhamnosus GR-1® and Lactobacillus
reuteri RC-14® on the vaginal microbiota and cervico-vaginal cytokines and
chemokines in low risk pregnant women with an intermediate or high Nugent
score.
I am grateful to the research nurses, Ms Mary-Jean Martin and Ms Tara Maria Rocco, of
Mount Sinai Hospital for the recruitment of participants and the collection of vaginal swabs,
and staff at the Centre for Mother, Infant, and Child Research (Sunnybrook health Sciences
Centre, Toronto, Canada) for randomization of the participants and statistical analyses of
pregnancy outcomes. I would like to thank Dr. Laurent Briollais for his advice on statistical
analyses as well as members of the CIHR Vaginal Microbiome (VOGUE) team for the
discussion of idea and finding. I would also like to thank Dr. Gregory Gloor for his advice on
the analyses of sequencing data and for his help on filtering and organizing the data into
operational taxonomic unit tables. I would like to express my gratitude to Dr. David Carter
at the Robarts Research Institute (London, Ontario, Canada) for performing the Illumina
sequencing. I would like to thank Ms Shannon Seney, Mr Rod McPhee and Ms Amy
McMillan for providing the Nugent scores.
112
Chapter 5
5. Effect of oral probiotics Lactobacillus rhamnosus GR-1® and
Lactobacillus reuteri RC-14® on the vaginal microbiota and
cervico-vaginal cytokines and chemokines in low risk pregnant
women with an intermediate or high Nugent score.
5.1 Introduction
A healthy human vaginal microbiota, characterized by the dominance of Lactobacillus spp.,
plays an important role in reproductive health and disease. Several studies have shown that
lactobacilli prevent the overgrowth of pathogens by secreting antibacterial hydrogen
peroxide, lactic acid, and bacteriocins (Reid and Bocking, 2003b). Bacterial vaginosis (BV),
an altered vaginal microbiota associated with preterm birth (PTB), is characterized by a
depletion of lactobacilli and an overgrowth of facultative anaerobic bacteria such as
Gardnerella vaginalis, Atopobium vaginae, Prevotella spp., Mobiluncus spp. and
Mycoplasma hominis (Donders et al., 2009; Donati et al., 2010). Cytokines and chemokines
play pivotal roles in PTB, and the predominance of pro-inflammatory cytokines over anti-
inflammatory cytokines, observed during an ascending infection, is associated with the early
onset of labor (Keelan et al., 2003; Challis et al., 2009). BV is associated with elevated
vaginal concentrations of pro-inflammatory cytokine Interleukin (IL)-1β and chemokine IL-8,
both of which are elevated in the amniotic fluid and cervical fluid of women with microbial
invasion of the amniotic cavity and preterm delivery (Balkus et al., 2010; Holst et al., 2011).
A Gram stain Nugent score of 7-10 and/or the presence of three of the Amsel criteria is
indicative of BV: a vaginal pH > 4.5, an amine fishy odour when vaginal fluid is mixed with
potassium chloride, the presence of clue cells, or milky homogenous discharge (Nugent et
al., 1991; Reid and Bocking, 2003b).
The use of high throughput sequencing techniques to characterize the human vaginal
microbiota overcomes several limitations of traditional culture-based techniques, including
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the failure to detect uncultivable microorganisms and underestimation of the vaginal
diversity (Gloor et al.. 2010; Hummelen et al., 2010; Srinivasan et al.. 2012). Several studies
have employed sequencing methods to characterize the vaginal microbiota of healthy
pregnant (Romero et al., 2014a; Romero et al., 2014b; Aagaard et al., 2012), and non-
pregnant women (Gloor et al., 2010; Hummelen et al., 2010; Srinivasan et al., 2012). In this
study, I used the Illumina MiSeq sequencing platform to identify phylogenetically diverse
microorganisms to the species level in pregnant women with an intermediate or high Nugent
score, using primers that target V6 region of the 16S ribosomal DNA (rDNA) (Gloor et al.,
2010).
Probiotics are defined as “live microorganisms which, when administered in adequate
amounts, confer a health benefit on the host” (FAO/WHO, 2001). Probiotic lactobacilli,
administered through either the oral or vaginal route, ameliorate BV and replenish
lactobacilli abundance in the vaginal biota of non-pregnant women (Homayouni et al., 2014).
Oral administration of lactobacilli confers additional health benefits, such as reduction of
urinary tract infection (Reid et al., 2015; Reid, 2001a; Walsh et al., 2014). The rationale for
selecting probiotic Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14 (GR-1
and RC-14) to improve the abnormal vaginal biota was derived from a previous study in non-
pregnant women, in which treatment with GR-1 and RC-14 with a similar dosing range (109
cfu) reduced BV occurrence and recurrence (Reid et al., 2003a).
Our previous studies have demonstrated the supernatant of L. rhamnosus GR-1 (GR-1 SN)
possesses anti-inflammatory properties in cultured human intrauterine tissues (Yeganegi et
al., 2009; Yeganegi et al., 2011; Li et al., 2014), mouse macrophages (Kim et al., 2006) and
can reduce inflammation-associated PTB in pregnant mice (Yang et al., 2014b) (Chapter 3).
To date, the effect of oral probiotic supplementation in modulating the vaginal microbiota
and cervico-vaginal cytokines and chemokines in pregnant women diagnosed with an
abnormal Nugent score remains unknown. I hypothesize that pregnant women with an
abnormal Nugent score will revert to a normal Nugent score with oral GR-1 and RC-14
treatment; oral probiotics will dampen the cervico-vaginal concentration of pro-inflammatory
cytokines and chemokines, and will modulate the vaginal microbiota in these women.
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5.2 Materials and Methods
5.2.1 Study Participants
Pregnant women were recruited from low risk antenatal clinics at Mount Sinai Hospital,
Toronto, Canada. Women were over 18 years of age, were prior to 17 weeks of gestation,
had singleton pregnancies, and were able to provide informed consent. Women who had
multi-fetal pregnancies, fetal complications, maternal history of previous PTB, second
trimester loss, significant maternal medical, surgical complications or HIV were excluded. A
Dacron swab was placed in the posterior fornix or lateral vaginal wall (avoiding cervical
mucous) for 10 seconds, and smears applied to the microscope slides were Gram-stained and
scored according to the Nugent criteria (Nugent et al., 1991). A letter of No Objection was
obtained from Health Canada for the use of probiotic lactobacilli and the study was approved
by the Ethics Review Board of Mount Sinai Hospital (Research Ethics Board Approval
Number: 08-005-A).
5.2.2 Study groups and randomization
A total of 328 women were consented and screened between May 2012 and October 2013 for
the presence of an intermediate (4-6) or high (7-10) Nugent score at the time of their routine
vaginal speculum examination between 12 to 16 weeks of pregnancy (on average 13.3 weeks
gestation). Of the 328 women screened, 86 women had a Nugent score ≥ 4 (Figure 5-1). In
order to detect a difference between a BV prevalence of 30% in the probiotic group and 60%
in the placebo group at the end of treatment protocol, a sample size of 40 pregnant women in
each group was needed. Z test was used to determine the sample size with alpha=0.05 and
power =0.8. The sample size was increased to 43 in each group to compensate for 5% of
women lost to follow-up. Following informed consent, they were randomized using a web-
based randomization service to receive by mouth, two identical looking capsules per day
containing either GR-1 and RC-14 (n=43) or placebo (n=43) for 12 weeks. The choice of
oral administration over vaginal administration was based on a previous study in non-
pregnant women, in which treatment with the same lactobacilli strains (GR-1 and RC-14) at
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a similar dose (109 cfu), reduced BV occurrence and recurrence (Reid et al., 2003a). Vaginal
swabs were collected at 13, 28 and 35 weeks gestation and analyzed for Nugent score,
cytokine and chemokines, and vaginal microbiota. The characteristics of women at the time
of randomization (13 weeks gestation) are summarized in Table 5-1. Fourteen women were
lost to follow-up or withdrew from the study, 3 women had taken less than 25% of the 168
capsules over the 12-week treatment period, and there was insufficient sample for analysis in
3 women (Figure 5-1). After excluding these women, there were 32 women in the probiotic
group and 34 women in the placebo group with samples available for the sequencing analysis
(Figure 5-1). There were insufficient samples in 2 additional women for the cytokine protein
measurements, so there were 31 women in the probiotic group and 33 women in the placebo
group with samples available for the cytokine assay (Figure 5-1).
5.2.3 Nugent score
Vaginal swab smears were graded on a 10-point scale based on the presence or absence of
various bacterial morphotypes, including Lactobacillus spp. (gram-positive rods), and
pathogenic Gardnerella vaginalis (small gram-variable rods) and Bacteroides spp. (small
gram-negative rods). A score of 0-3 was considered a normal vaginal microbiota, with high
abundance of Lactobacillus spp.; a score of 4-6 represented an intermediate biota with higher
proportions of non-Lactobacillus morphotypes, and a score of 7-10 was considered BV, with
the near absence of Lactobacillus morphotypes and high abundance of the pathogenic
morphotypes (Nugent et al., 1991). The smears were analyzed by three experienced
observers in Dr. Gregor Reid’s laboratory (Lawson Research Institute, London, Canada).
5.2.4 Probiotic Strains
Lactobacillus rhamnosus, GR-1® and Lactobacillus reuteri, RC-14® (GR-1 and RC-14) and
placebo capsules were provided by Chr Hansen, Denmark. The probiotic capsules contained
at least 5x109 viable cells per capsule (or 2.5x109 cells of GR-1 and 2.5x109 cells of RC-14)
freeze-dried in gelatin capsules each containing 180 mg of powder. Anhydrous dextrose and
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potato starch were used as fillers to adjust for variations in the amount of microbial culture
used, microcrystalline cellulose was used as binder and magnesium stearate was used as
lubricant (manufacturer’s manual).
5.2.5 DNA Isolation and PCR amplification of V6 region of 16S rDNA
Vaginal swabs were equilibrated in 800µL phosphate buffer saline (PBS) on ice and vortexed
for 1 min. The swab was removed and DNA extracted with a Qiagen Stool Extraction Kit
(Appendix III, Qiagen, Toronto, Canada). Bacterial DNA was amplified with barcoded
primers targeting the V6 region of the 16S rDNA (Robarts Research Institute, Western
University, Canada). PCR amplification was performed with colorless GO-Taq hot start
master mix (Promega, Canada) for 25 repeating cycles of 95°C, 55°C and 72°C for 1 minute
each step. The amplified products were quantified using a QuBit broad-range double-
stranded DNA fluorometric quantitation reagent kit (Life technologies, Canada). Samples
were pooled at equal molar concentrations and purified using Wizard PCR Clean-Up Kit
according to manufacturer’s instructions (Promega, Canada).
5.2.6 Sequencing
Barcoded DNA was sequenced in pairs on the MiSeq Illumina platform at the Robarts
Research Institute (Western University, London, Canada). The V6L and V6R
primers included a unique 12bp sequence tag to barcode each sample. The primers used
were: V6L-5′-
ACACTCTTTCCCTACACGACGCTCTTCCGATCTNNNNNNNNNNNNCWACGC
GARGAACCTTACC-3′ and V6R-5′-CGGTCTCGGCATTCCTGCTGAACCGCTCTTCCG
ATCTNNNNNNNNACRACACGAGCTGACGAC-3′, where the italicized sequences are the
Illumina MiSeq sequencing primers and the bold font denotes the universal 16S rRNA gene
primers. The sequence results were provided in the fastq format. All sequences were filtered
and a table of counts was generated for each sample containing sequences grouped at 97%
operational taxonomic unit (OTU) and 100% identical sequence unit identity. The sequences
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were then classified to distinct taxonomic species using the online Ribosomal Database
Project (http://rdp.cme.msu.edu/seqmatch/seqmatch_intro.jsp). Sequences not identical
across all best matches were marked as unclassified.
5.2.7 Protein Extraction and Cytokine/Chemokine Multiplex Assay
Vaginal swabs were equilibrated in Tris-HCl buffer (pH 7.5) with 150 mmol/L NaCl,
1mmol/L phenylmethylsulfonyl fluoride (Sigma), 0.05% Tween-20 (Sigma) and a protease
inhibitor cocktail tablet (Roche) for 30 min at 4 oC and vortexed every 10 min. The swab was
removed and the buffer centrifuged at 16,000 × g for 15 min at 4 oC. The supernatant was
then stored at -80oC in aliquots until further analysis. IL-1 receptor antagonist (IL-1rα), IL-
1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12p70, IL-13, IL-15, IL-17, basic
Fibroblast Growth Factor (bFGF), Colony Stimulating Factor (CSF) 2, CSF3, Interferon
(IFN)-γ, CXCL10, CCL2, CCL3, CCL4, CCL5, CCL11, Platelet-Derived Growth Factor
(PDGF)-bb, Tumor Necrosis Factor (TNF)-α and Vascular Endothelial Growth Factor
(VEGF) were measured with a 27 human multiplex cytokine/chemokine kit according to
manufacturer’s instructions (Appendix I, Biorad, Canada).
5.2.8 Statistical Analyses
Unpaired Student’s t test (two tailed) or Chi-square test was carried out using SigmaStat
(version 3.5) to compare 1) pre-randomization characteristics; 2) pregnancy outcomes; 3)
compliance of women to the treatment protocol; 4) the percentage of women who reversed to
a normal Nugent score between the placebo and probiotic groups; (5) the microbial profiles
between women with an intermediate Nugent score and a high Nugent score, prior to
treatment. Two-Way Repeated Measure ANOVA followed by Holm Sidak method was
carried out using SigmaStat (version 3.5) to test for treatment and gestational effects on
microbial profiles and the concentrations of cytokines and chemokines. For sequencing data,
centered ratio logarithm transformation was performed as described previously (Aitchison,
1986). Briefly, the geometric mean of the proportions of all species detected in a sample was
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computed. A ratio x was determined from the proportion of species i over the geometric
mean. Then, the relative abundance of species i was calculated by taking natural logarithm of
x. Statistical analysis of the sequencing data was carried out using R (version 3.0.1).
Generalized Estimation Equation Model was used for data that did not follow the normal
distribution. Data were adjusted for false discovery rate using Benjamini Hochberg
procedure and an adjusted p-value of p<0.05 was considered statistically significant. Data
were tested for normality and equal variance and were expressed as mean values ± standard
deviation (SD). The Shannon diversity index was calculated by first taking the proportion of
a bacteria species relative to the total number of species detected in a sample, and
multiplying it by the natural logarithm of this proportion. The product was then summed
across all bacteria species, and multiplied by -1 (Magurrant 2003).
5.3 Results
5.3.1 Pre-randomization characteristics The mean maternal age was 33.8 ± 4.2 years old and the mean pre-pregnancy body mass
index was 22.5 ± 3.2 for the women in the probiotic group at 13 weeks gestation, and these
characteristics were not different for the women in the placebo group (34.4 ± 3.3 years old
and BMI: 22.4 ± 3.1) (Table 5-1). In both groups, vaginal swabs used for screening of an
abnormal Nugent score were taken at 13 weeks gestation. Over 55% of the women were
Caucasian in both groups. Other ethnicities included South and East Asian, Black and
Hispanic.
Forty out of the 43 women (93%) in both the placebo and the probiotic groups had a natural
conception (Table 5-1). Seventeen pre-existing conditions were reported in 14 women
randomized to the probiotic group and 27 pre-existing conditions were reported in 21 women
in the placebo group. A total of 16 previous surgeries were reported in 14 women in the
probiotic group and 34 surgeries were reported in 22 women in the placebo group. Fourteen
women randomized to the probiotic group and 22 women in the placebo group were on
medications at the beginning of the treatment protocol. Thirty-five out of 43 women (81.4%)
in the probiotic group and 41 out of 43 women (95.4%) in the placebo group reported
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ingesting probiotic containing fermented food during pregnancy. These characteristics were
not different between the placebo and probiotic groups (p>0.05, Table 5-1).
5.3.2 Pregnancy Outcomes
Antibiotics were taken by 13.9% of the women in the probiotic group and 11.6% of the
women in the placebo group during pregnancy for various indications (p>0.05, Table 5-2).
There was no difference in antibiotic administration during labor in both groups (46.3% in
the probiotic group and 37.2% in the placebo group, p>0.05). 19.5% of the women had
induction of labor and 80.5% of the women had a vaginal delivery in the probiotic group.
These percentages were not different in the placebo group. The mean gestational age at
delivery was 39.1 ± 1.4 weeks in the probiotic group, and this was not different in the
placebo group (39.4 ± 0.9 weeks, p>0.05, Table 5-2). The mean birth weight was 3340 ± 433
grams in the probiotic group, and this was not different in the placebo group (3351 ± 463
grams, p>0.05). There was 1 infant with intrauterine growth restriction (IUGR) in the
placebo group, and 2 infants in the probiotic group delivered at 34 weeks gestation in
association with premature rupture of membranes (Table 5-2). In 1 of these infants, the
Apgar score was less than 7 at 5 minutes. There was no difference in the fetal sex distribution
or cord blood pH between the two groups. There was also no difference in the number of
women who experienced symptoms such as vaginal itching, vaginal discharge and vaginal
odour during the 12-week treatment period between the two groups. There were no adverse
reactions to the probiotics or placebo reported.
5.3.3 Compliance to the treatment protocol
At the end of the 12 week treatment period, there were on average 13 pills (7.7%) left in the
bottles returned by women in the probiotic group and 9 pills (5.4%) remaining in the bottles
returned by women in the placebo group (Table 5-3). Twenty-six out of 32 women (81.2%)
in the probiotic group and 29 out of 34 women in the placebo group (86.3%) had taken more
than 75% of the total pills (168 pills) (p > 0.05, Table 5-3). The remaining women had taken
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more than 50% of the total pills. Three women have taken less than 25% of the total pills and
were excluded from subsequent analyses.
5.3.4 Effect of oral probiotic GR-1 and RC-14 on the Nugent score
The primary outcome of this trial was to evaluate changes in the Nugent score among women
with an abnormal Nugent score after oral probiotic supplementation, in comparison to
placebo-treated women. There were 11 out of 32 women (34.4%) in the probiotic group and
11 out of 34 women (32.3%) in the placebo group, who reversed to a normal Nugent score at
28 weeks gestation (p>0.05, Table 5-4). The percentages were similar in both groups at 35
weeks gestation (p>0.05).
5.3.5 Effect of oral probiotic GR-1 and RC-14 on the vaginal microbiota A total of 93 distinct bacterial species were detected at 13 weeks gestation (Table 5-5). The
most abundant species were Lactobacillus iners, Lactobacillus crispatus, Gardnerella
vaginalis and Atopobium vaginae across pregnancy. Thirty of 66 women had a single
bacterial species (A. vaginae, n=4; L. jensenii, n=1; iners, n=12, L crispatus, n=9 and G.
vaginalis, n=4), which dominated more than 40% of their vaginal microbiota at 13 weeks
gestation (Figure 5-2). In the remaining women, the vaginal microbiota was dominated by a
mixture of different bacterial species. The vaginal microbiota of pregnant women with an
intermediate Nugent score (n=42) and those with a BV Nugent score (n=24) at 13 weeks
gestation are shown in Figure 5-3. The vaginal microbiota at the time of study entry (13
weeks gestation) were not different between these women (p > 0.05, Table 5-5) and
therefore, these results were pooled for all in subsequent analyses.
The vaginal microbiota of pregnant women who received placebo (n=34) and those who
received probiotics (n=32) at 13, 28 and 35 weeks gestation are shown in Figure 5-4. There
was no difference in the vaginal microbiota between pregnant women in the placebo and
probiotic groups at the end of the 12-week treatment protocol (28 weeks gestation), or at 35
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weeks gestation (Table 5-6 and Table 5-7). There was no difference in the vaginal microbiota
between the placebo and probiotic groups when data were grouped by ethnicity, pre-
pregnancy BMI or when women whose vaginal microbiota were dominated by Lactobacillus
spp were excluded (data not shown).
Lactobacillus rhamnosus was detected in 98% of the women (65 out of 66 women) at 13
weeks gestation, and its abundance did not alter with probiotic treatment. There were two
women in the probiotic group who delivered at 34 weeks gestation in association with
premature rupture of membranes. In one of these women, her vaginal microbiota was
dominated by L. jensenii, and following probiotic treatment, her vaginal biota became more
heterogeneous, with increased abundance of species including L. gasseri, G. vaginalis and
Prevotella bivia (Figure 5-4). The other woman had a heterogenous vaginal microbiota
initially, and with probiotic treatment, L. cripatus dominated her vaginal microbiota (Figure
5-4).
The relative mean abundance of 12 species including L. iners, L. acidophilus, G. vaginalis
and A. vaginae decreased at 28 weeks and/or 35 weeks of gestation in the placebo group
and/or the probiotic group, compared to 13 weeks of gestation (Table 5-6). In contrast, the
relative mean abundance of 9 species increased across pregnancy (Table 5-7). There was no
difference in the Shannon diversity index between the probiotic and placebo groups at 13, 28
or 35 weeks gestation (Figure 5-5).
5.3.6 Effect of GR-1 and RC-14 on the concentrations of cervico-vaginal
cytokines/chemokine
The cervico-vaginal concentrations of cytokines and chemokines at the time of study entry
(13 weeks gestation) were not different between pregnant women diagnosed with an
intermediate or BV Nugent score (p>0.05, data not shown). Therefore, these data were
combined in subsequent analyses. The concentration of cytokines and chemokines were not
different between placebo (n=34) and probiotic-treated (n=32) women at 13, 28 or 35 weeks
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gestation (p>0.05, Table 5-8).
Levels of pro-inflammatory cytokines IL-1β, IL-6, IL-12p70, IL-17, IFN-γ, TNFα, anti-
inflammatory cytokines IL-9, IL-13, chemokines IL-8, CXCL10, CCL11, CCL2, CCL3,
CCL4, CCL5, and growth/hematopoietic factors VEGF, PDGFbb, bFGF, CSF2 and IL-7 did
not change throughout pregnancy (p>0.05, Table 5-8). The concentrations of the anti-
inflammatory cytokine IL-4 in the placebo group and IL-10 in both probiotic and placebo
groups increased slightly at 28 weeks gestation, but were not different at 35 weeks gestation,
when compared to 13 weeks gestation (p<0.05, Figure 5-6). Concentration of the
hematopoietic factor CSF3 decreased at 28 weeks in the probiotic group and at 35 weeks
gestation in the placebo group, when compared to 13 weeks gestation (p<0.05, Figure 5-6).
Concentrations of IL-2, IL-5, IL-15 and IL-1ra were outside the detection limit.
5.4 Comment In this prospective, randomized, double blinded, and placebo-controlled trial, there was no
difference in the pre-randomization characteristics, pregnancy outcomes and compliance to
the treatment protocol between pregnant women in the placebo and the probiotic groups.
Pregnant women were initially classified by their Nugent scores as either BV or Intermediate.
However, since the vaginal microbiota of pregnant women diagnosed with a BV Nugent
score did not differ from women with an intermediate Nugent score at 13 weeks gestation,
we grouped these women for subsequent analyses. Furthermore, lactobacilli dominated the
vaginal microbiota in more than one third of the pregnant women with an abnormal Nugent
score, at 13 weeks gestation. Retrospectively, it was observed that some slides were of poor
quality and the presence of peripheral blood mononuclear cells made scoring the slides
difficult. The Nugent scoring system may not be the ideal approach for the diagnosis of
asymptomatic BV although at the time this study was started, this was the gold standard. It
has been shown that a DNA level of ≥109 copies/mL for G. vaginalis and ≥108 copies/mL
for A. vaginae has a 95% sensitivity and positive predictive value, and 99% specificity and
negative predictive value for the diagnosis of BV, which are higher than has been reported
using the Nugent score (Menard et al., 2008).
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There was no difference between pregnant women randomized to the probiotic group and the
placebo group with regards to their mean maternal age, pre-pregnancy BMI, ethnicity
distribution, mode of conception, and intake of antibiotics and/or fermented food during
pregnancy. There was no difference in the vaginal microbiota between probiotic-treated and
placebo-treated pregnant women at the end of the 12-week treatment period, nor at 35 weeks
gestation. This was evident as well when I excluded women with high lactobacilli abundance
in their vaginal microbiota prior to treatment (18 women in the placebo group and 22 women
in the probiotic group). I based my probiotic dosage on a previous study in non-pregnant
women, which demonstrated oral supplementation of GR-1 and RC-14 at 109 cfu restores the
indigenous lactobacilli in women with recurrent BV (Reid et al., 2003a). Since this study was
started, it has been demonstrated that pregnant women have a higher abundance of several
Lactobacillus spp including L. crispatus, L. gasseri and L. jensenii, and a more resistent
microbiota than non-pregnant women (Romero et al., 2014a; Aagaard et al., 2012). It is
plausible the current dose (5 x 109 cfu) may not be sufficient to alter the vaginal microbiota
in pregnant women, and that a higher dose is required.
In this longitudinal study, I characterized the vaginal microbiota in pregnant women with an
abnormal Nugent score throughout pregnancy and observed that the vaginal microbiota is not
static across gestation, in agreement with a previous study in pregnant women with a healthy
vaginal biota (Romero et al., 2014b). Specifically, I observed a decline in the relative
abundances of A. vaginae, A. rimae and G. vaginalis consistent with previous observations in
pregnant women with a healthy biota (Romero et al., 2014b). In contrast to studies that target
the V1-V3 (Romero et al., 2014b) and V3-V4 (Ling et al., 2010; Srinivasan et al.. 2012)
regions of the 16S rDNA, I did not observe a change in the relative abundance of Gemella
and Sneathia sanguinegens, and I did not detect the presence of Eggerthella
spp., Parvimonas micra, BV associated bacteria 1 (BVAB1), BVAB2 or Ureaplasma
parvum. The use of primers that targeted the V6 region in this study may have under-
estimated the presence of these bacteria (Gloor et al., 2010; Hummelen et al., 2010). Using
sequencing primers that target the cpn60 gene, it is possible to measure the abundance of
Mollicutes, including Mycoplasma hominis, Ureaplasma parvum, and Ureaplasma
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urealyticum in non-pregnant women (Chaban et al., 2014) as well as in pregnant women with
an abnormal vaginal biota at 13 weeks gestation (Hill et al, unpublished data).
The relative abundance of L. iners and L. acidophilus across gestations decreased in this
study, in contrast to a previous report that found an increase in the relative abundance of
several Lactobacillus spp (L. crispatus, L. jensenii, L. gasseri and L. vaginalis) with
advancing gestational age in women with a healthy biota (Romero et al., 2014b). It is
important to distinguish that women in this study had an abnormal biota, which did not
resolve in 65% of the women by 35 weeks gestation.
Previous studies in term cultured human intra-uterine tissues and in pregnant mice have
demonstrated that Lactobacillus rhamnosus GR-1 supernatant possesses anti-inflammatory
properties (Yeganegi et al., 2009; Yeganegi et al., 2011; Yang et al., 2014b; Li et al., 2014).
In this study, oral GR-1 and RC-14 did not alter the cervico-vaginal concentrations of
cytokines or chemokines. It is known that in non-pregnant women, exogenous lactobacilli
colonization is transient (Gardiner et al., 2012). Alternatively, a higher dose of live
lactobacilli is needed to produce sufficient bioactive metabolites to achieve similar effects in
humans. Thirdly, it is possible that an underlying state of inflammation is required before
lactobacilli exert an anti-inflammatory effect.
There was a shift towards an anti-inflammatory environment across gestation as evident by
an increase in IL-4 and IL-10 concentrations at 28 weeks gestation. The levels of cervico-
vaginal IL-4 and IL-10 were in comparable range with previous studies (Nenadic and
Pavlovic, 2008; Chandiramani et al., 2012), and these observations are consistent with the
hypothesis that a dampening of inflammation is important to the maintenance of uterine
quiescence (Challis et al., 2009).
CSF3, which is important in placentation, neutrophil progenitors proliferation, differentiation
and survival, decreased with advancing gestational age. CSF3 has also been shown to
possess anti-inflammatory properties in cultured human placental trophoblast cells (Yeganegi
et al., 2011). However, elevated maternal CSF3 concentrations have been associated with
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spontaneous PTB in humans (Whitcomb et al., 2009). Taken together with the observations
in this study, CSF3 appears to be anti-inflammatory and a decline in the cervico-vaginal
concentration of CSF3 at 35 weeks gestation may promote the inflammatory responses that
eventually lead to the initiation of labor.
There was 1 infant with intrauterine growth restriction (IUGR) in the placebo group, and 2
infants in the probiotic group were delivered at 34 weeks gestation in association with
PPROM. In 1 of those infants, the apgar score was less than 7 at 5 minutes. There was no
difference in fetal sex distribution between placebo-treated and probiotic-treated pregnant
women. There were neither adverse side effects nor alterations in pregnancy outcomes with
probiotic treatment, in agreement with a recent meta-analysis of randomized clinical trials,
which demonstrated the use of probiotics Lactobacillus is safe during pregnancy (Dugoua et
al., 2009).
This study provides a longitudinal overview of vaginal microbiota and cervico-vaginal
cytokine profiles throughout pregnancy, which may serve as a baseline for future clinical
trials that assess the efficacy of probiotic administration to pregnant women. In contrast to
my initial hypotheses, at the current dose (5 x 109 cfu) and duration (12-weeks), oral GR-1
and RC-14 does not alter the Nugent score, vaginal microbiota or cervico-vaginal cytokine
profiles in pregnant women with an abnormal Nugent score. Future trials should consider
using a higher lactobacilli dose or for a longer duration that includes women with high-risk
pregnancies. Future metabolomic studies investigating the function of bacterial species might
shed light to the clinical relevance of the changes in various bacterial species observed as
pregnancy progress.
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Figure 5-1 Consort flow chart of pregnant women enrolled in the study.
Excluded (n= 242) ♦!!Normal Nugent Score ♦ 2 women with high Nugent score declined to be randomized
(n=38) ♦!!!1 withdrawal ♦!!!4 lost to follow up
Probiotics (n=43) GR-1 and RC-14
5 X 109 viable cells
(n=38) ♦!!!5 lost to follow up
Placebo (n=43)
!
Randomized (n= 86) Nugent score ≥ 4
(n=32) ♦!!!4 lost to follow up ♦ !!2 non-compliant or insufficient samples
28 weeks gestation
12 weeks, Twice a day orally
Enrolment (n = 328) 13 weeks gestation
(n=34) ♦!4 non-compliant or insufficient samples
35 weeks gestation
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Figure 5-2 Stacked bar plot showing the vaginal microbiota clustered by bacteria similarity in pregnant women prior to treatment, at 13 weeks gestation (n=66).
Each bar represents the vaginal microbiota of a single woman and corresponds to the participant identification (ID) number labeled in the dendogram, clustered using average linkage cluster analysis. Species found in >1% abundance are represented by a unique color. Species with <1% abundance in the sample are pooled into a single fraction at the top of the bar in grey color. Women who have a single bacterial species which dominated more than 40% of their vaginal microbiota are identified with a color dot below their identification number that corresponds to the dominant species (Dark green, Atopobium vaginae, n=4; Very light blue, Lactobacillus (L.) jensenii, n=1; blue, L. iners, n=12; light blue, L crispatus, n=9 and red, Gardnerella vaginalis, n=4). Black rectangles are used to denote women with a BV Nugent score and white rectangles are used to identify women with an intermediate Nugent score.
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V1_
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V1_
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V1_
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V1_
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V1_
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0.0
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Mic
robi
ota
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128
Figure 5-3 Stacked bar plots showing the vaginal microbiota clustered by bacteria similarity in pregnant women with a BV (n=24) or an intermediate (n=42) Nugent score prior to treatment, at 13 weeks gestation.
Each bar represents the vaginal microbiota of one woman and corresponds to the identification number labeled in the dendogram, clustered using average linkage cluster analysis. A unique color is used to represent species found in >1% abundance. Species with <1% abundance are pooled into a fraction at the top in grey color.
BV (Nugent score of 7-10)
Intermediate (Nugent score of 4-6)
129
Figure 5-4 Stacked bar plots showing the vaginal microbiota across pregnancy clustered by bacteria similarity in pregnant women who received either placebo (n=34) or probiotic (n=32) treatment.
Each bar represents the vaginal microbiota of a single woman and corresponds to the identification number labeled in the dendogram, clustered using average linkage cluster analysis. Species found in >1% abundance are represented by a unique color and species that has <1% abundance are pooled into a single fraction at the top of the bar in grey color. Women were aligned in the same vertical column at 13, 28 and 35 weeks of gestation. Women who have undergone preterm birth (PTB) (n=2) in the probiotic group are denoted with white squares.
Black&**&discussion&about&Black&and&PTB??&
28 wks gestation
35 wks gestation
V1_
099
V1_
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PTB &
V1_1
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V1_3
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V1_2
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V1_2
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V1_3
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V1_2
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V1_2
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V1_2
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V1_2
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V1_0
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V1_3
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V1_0
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V1_1
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V1_1
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V1_0
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V1_1
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V1_1
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V1_2
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V1_3
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V1_1
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V1_1
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V1_0
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V1_2
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V1_3
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V1_0
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V1_3
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V1_2
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V1_2
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V1_1
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V1_1
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V1_2
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V1_3
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78
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99
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Micro
biota
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on
13 wks gestation
Placebo (n=34) &
Probiotics (n=32) &
130
Figure 5-5 Scatterplot showing the Shannon Diversity Index (SDI) across gestations in pregnant women who received either placebo or probiotic treatment.
Results are mean values ± SD and expressed in ratios. Comparisons between the probiotic (n= 32) and placebo (n= 34) groups at 13, 28 and 35 weeks gestation were assessed with Two Way Repeated Measure ANOVA followed by Holm-Sidak post hoc test (p>0.05).
13w 28w 35w 13w 28w 35w0
1
2
3
4
Sha
nnon
Div
ersi
ty In
dex
Placebo Probiotics
131
Figure 5-6 Scatterplots showing the concentrations of cervico-vaginal cytokines IL-4, IL-10 and CSF3 across gestation in pregnant women who received either placebo or probiotic treatment.
Results are mean values ± SD and expressed in picogram per milliliter. Comparison between the placebo group (n=33) and the probiotic group (n=31) was assessed with the Generalized Estimation Equation model in R.
IL-4
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Placebo Probiotics
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cent
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L)
Placebo Probiotics
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-250
0
250
500
750
1000
Con
cent
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Placebo Probiotics
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132
Table 5-1 Characteristics of pregnant women randomized at 13 weeks gestation.
Comparison between the probiotic group (n=32) and the placebo group (n=34) was performed with Student’s t-test or Chi-square (p>0.05).
Ethnicity is based on 32 women in the placebo group and 34 women in the probiotic group.
133
Table 5-2 Pregnancy outcomes. Comparison between the probiotic group (n=32) and the placebo group (n=34) was performed with Student’s t-test or Chi-square (p>0.05).
1 Antibiotics included penicillin, teva-cloxacillin, erythromycin, amoxicillin, macrobid, clindamycin, biaxin, ciprofloxacin, cephalexin and topical metronidazole. 2 The woman also had oligohydramnios. 3 Two women (not included in n=41) delivered at 34 weeks gestation in association of premature rupture of membranes.
Probiotic Group n = 41
Placebo Group n = 43
Antibiotics during pregnancy 1 6 (13.9%) 5 (11.6%)
Antibiotics during labour and delivery 19 (46.3%) 16 (37.2%)
Induction of labor 8 (19.5%) 9 (20.9%)
Mode of Delivery Vaginal
Spontaneous Assisted
C-section Emergency
Labour Elective
Repeat Abnormal presentations
33 (80.5%)
28/33 (84.9%) 5/33 (15.2%)
8 (19.5%)
6/8 (75.0%) 6/6
2/8 (25.0%) 2/2 1/2
34 (79.1%)
28/34 (82.4%) 6/34 (17.7%)
9 (20.9%)
2/9 (22.2%) 1/2
7/9 (77.8%) 6/7 1/7
Gestational age at delivery (weeks) 39.1 ± 1.4 39.4 ± 0.9
Birth weight (g) 3340 ± 433.68 3351 ± 463.49
IUGR Severe (<3rd centile) 2 0 1 (2.3%)
Preterm birth ( < 37 weeks gestation) 3
2 0
Apgar score <7 at 5 minutes 1 (2.4%) 0
Fetal Sex Male Female
19 (46.3%) 22 (53.7%)
24 (55.8%) 19 (44.2%)
Cord blood pH 7.26 ± 0.07 7.26 ± 0.08
134
Table 5-3 Compliance of women in the probiotic and placebo groups. Comparison between the probiotic group (n=32) and the placebo group (n=34) was performed with Student’s t-test (p>0.05).
Compliance Probiotic Group n = 32
Placebo Group n = 34
Number of pills remaining in bottle at the end of 12 weeks of treatment (range)
13 (0 - 28) 9 (0 - 26)
Number of women who took > 50% of total pills in bottle ( < 84 pills remaining) Number of women who took > 75% of total pills in bottle ( < 42 pills remaining)
6 (18.8%)
26 (81.2%)
5 (14.7%)
29 (86.3%)
135
Table 5-4 Nugent scores of pregnant women across pregnancy in the probiotic and placebo groups.
Comparison between the probiotic group (n=32) and the placebo group (n=34) was performed with Student’s t-test (p>0.05).
Nugent Score Probiotic Group n = 32
Placebo Group n = 34
P value
13 weeks gestation • BV
• Intermediate flora • Normal
11 (34.4%)
21 (65.6%) 0
13 (38.2%)
21 (61.8%) 0
> 0.05
> 0.05
28 weeks gestation • BV
• Intermediate flora
• Normal
11 (34.4%)
10 (31.3%)
11 (34.4%)
4 (11.8%)
19 (55.9%)
11 (32.3%)
> 0.05
> 0.05
> 0.05
35 weeks gestation • BV • Intermediate flora
• Normal
8 (25.0%)
12 (37.5%)
12 (37.5%)
10 (29.4%)
12 (35.3%)
12 (35.3%)
> 0.05
> 0.05
> 0.05
136
Table 5-5 The relative to mean abundance of vaginal bacterial species in pregnant women with a BV (7-10) or an intermediate (4-6) Nugent score at 13 weeks gestation.
Results are mean values ± SD and expressed in centered logarithm transformed ratios. Comparison between the BV (n=24) and Intermediate (n=42) groups was performed with Student’s t-test (p >0.05). Species BV Intermediate Species BV Intermediate
Gardnerella vaginalis 10.9±2.1 10.1±2.5 Anaerococcus hydrogenalis -1.6±1.4 -1.0±1.4 Atopobium vaginae 9.9±2.1 8.8±2.2 Gemella asaccharolytica -1.6±2.3 -2.1±0.9 Lactobacillus iners 9.8±2.6 10.6±2.3 TM7 phylum -1.6±2.5 -1.5±1.5 Lactobacillus crispatus 8.6±2.3 10.3±2.6 Bifidobacterium bifidum -1.7±2.1 -2.1±0.9 Lactobacillus jensenii 7.1±2.6 8.0±2.8 Peptoniphilus lacrimalis -1.8±1.0 -2.0±1.0 Veillonellaceae bacterium 6.9±3.3 4.6±2.1 Varibaculum cambriense -1.8±1.2 -1.6±1.1 Lactobacillus acidophilus 6.3±3.0 6.9±2.3 Staphylococcus epidermidis -1.8±1.4 -0.9±1.2 Lactobacillus gasseri 5.6±1.8 6.9±2.5 Arthrobacter albus -1.9±1.0 -1.6±1.1 Bifidobacterium breve 4.9±2.9 5.0±2.9 Facklamia hominis -1.9±1.0 -1.6±1.0 Bifidobacterium longum 4.2±2.7 2.7±3.1 Corynebacterium appendicis -1.9±1.0 -1.9±0.9 Atopobium rimae 3.8±2.8 2.0±1.6 Veillonella parvula -1.9±1.0 -1.8±1.3 Dialister micraerophilus 3.8±2.4 2.4±1.5 Clostridiales coagulans -1.9±1.1 -1.8±0.9 Prevotella timonensis 3.5±2.9 2.3±1.8 Prevotella corporis -1.9±1.2 -2.0±0.8 Dialister propionicifaciens 2.9±2.8 1.4±1.5 Mobiluncus curtisii -1.9±1.2 -1.9±0.9 Bacillus cereus 2.5±3.2 2.7±2.4 Corynebacterium coyleae -1.9±1.2 -1.9±0.9 Lactobacillus rhamnosus 2.3±1.7 1.9±1.7 Corynebacterium amycolatum -2.0±1.0 -1.6±0.9 Lactobacillus vaginalis 2.2±1.9 3.5±2.7 Campylobacter ureolyticus -2.0±1.0 -1.9±0.9 Prevotella bivia 2.1±3.0 0.7±1.8 Corynebacterium mucifaciens -2.0±1.1 -1.9±0.8 Streptococcus agalactiae 2.1±2.1 2.6±2.4 Peptostreptococcus anaerobius -2.0±1.1 -2.0±0.8 Desulfotomaculum halophilum 1.6±3.3 0.6±1.9 Porphyromonas asaccharolytica -2.0±1.3 -1.9±0.8 Prevotella amnii 1.3±4.2 -0.1±2.0 Brevibacterium ravenspurgense -2.0±1.4 -2.0±1.0 Enterobacter cloacae 1.1±2.9 1.1±1.8 Bifidobacterium dentium -2.0±1.6 -1.9±1.5 Escherichia coli 1.1±2.5 1.3±1.9 Anaerococcus murdochii -2.1±0.9 -2.0±0.6 Lactobacillus delbrueckii 0.9±3.3 0.5±2.5 Anaerococcus prevotii -2.1±0.9 -2.0±0.9 Sneathia sanguinegens 0.9±3.2 0.1±1.9 Lactobacillus sp.TS2gene -2.1±1.0 -1.8±1.2 Leuconostoc mesenteroides 0.8±3.3 1.3±2.5 Anaerococcus obesiensis -2.1±1.1 -1.6±1.4 Leptotrichia amnionii 0.8±3.3 0.0±1.9 Campylobacter rectus -2.1±1.1 -2.2±0.8 Lactococcus lactis 0.8±2.9 0.8±2.3 Anaerococcus tetradius -2.1±1.2 -2.0±1.2 Streptococcus anginosus 0.6±1.8 0.8±1.6 Propionimicrobium lymphophilum -2.1±1.2 -2.1±0.9 Alloscardovia omnicolens 0.5±3.0 0.2±2.5 Erythrobacter flavus -2.1±1.9 -1.2±2.7 Lactobacillaceae bacterium 0.5±3.0 0.9±3.0 Anaerococcus lactolyticus -2.2±0.9 -2.2±0.6 Corynebacterium jeikeium 0.0±1.4 -0.1±1.5 Bifidobacterium adolescenti -2.2±1.7 -1.8±1.5 Peptoniphilus|s|sp. S9 -0.1±1.6 -0.4±1.3 Actinomyces europaeus -2.3±0.9 -2.0±0.8 Prevotella bacterium -0.2±2.7 -0.6±1.5 Sideroxydans lithotrophicus -2.3±0.9 -2.2±0.6 Finegoldia magna -0.3±1.6 0.1±1.1 Clostridiales bacterium -2.4±0.8 -1.9±0.8 Streptococcus sobrinus -0.3±2.1 -1.0±1.5 Porphyromonas bennonis -2.4±0.9 -2.1±0.8 Morganella morga -0.4±2.7 -0.2±1.9 Prevotella denticola -2.4±1.2 -2.3±0.7 Streptococcus thermophilus -0.5±2.6 0.3±2.1 FirGemella haemolysans -2.4±1.2 -2.1±1.3 Bifidobacterium adolescentis -0.8±2.1 -1.0±2.1 Vulcanibacillus modesticaldus -2.5±0.8 -2.2±0.9 Prevotella micans -0.8±2.3 -1.5±1.3 Prevotella disiens -2.5±1.1 -1.9±1.3 Corynebacterium sundsvallense -1.0±1.5 -0.8±1.5 Lactobacillus brevis -2.5±1.2 -2.0±1.4 Lactobacillus coleohominis -1.1±2.2 -0.6±2.1 Cryptobacterium curtum -2.5±1.5 -2.1±1.3 Streptococcus pneumoniae -1.2±1.4 -0.2±2.3 Tannerella forsythia -2.6±0.7 -2.3±0.5 Corynebacterium pseudogenitalium -1.2±1.6 -0.9±1.7 Actinobaculum massiliense -2.6±0.9 -2.2±0.9 Prevotella melaninogenica -1.2±1.9 -1.0±1.8 Globicatella sanguinis -2.7±0.9 -2.3±0.7 Actinomyces neuii -1.3±2.7 -1.5±1.1 Helcococcus sueciensis -2.7±0.9 -2.3±0.6 Fusobacterium nucleatum -1.6±1.2 -1.6±1.1
137
Table 5-6 The relative to mean abundance of vaginal bacteria species that decreased across gestation in pregnant women treated with placebo or probiotics. Results are mean values ± SD and expressed in centered logarithm transformed ratios. Comparisons between the placebo (n=34) and probiotic (n=32) groups at 13, 28 and 35 weeks gestation were assessed Generalized Estimation Equation model in R. Statistical significance within the placebo group (a’, b’ and c’) and within the probiotic group (a, b, and c) was denoted with different letters (p < 0.05).
Placebo Group (n=32) Probiotic Group (n=34)
Species 13 wks 28 wks 35 wks 13 wks 28 wks 35 wks p-value
Lactobacillus iners 10.7±2.7 a’ 10.5±2.5 a’ 10.1±2.5 b’ 9.8±2.1a 9.8±2.5 a 9.5±2.4 a 6.5E-03
Gardnerella vaginalis 10.3±2.4 a’ 10.0±2.2 a’ 9.3±2.4 b’ 10.5±2.4 a 9.9±2.4 b 9.6±2.5 b 2.1E-09
Atopobium vaginae 9.4±2.2 a’ 9.3±2.2 a’ 8.8±2.2 b’ 9.0±2.3 a 8.6±2.4 b 8.7±2.4a,b 1.8E-03
Lactobacillus acidophilus 6.6±2.6 a’ 5.7±2.7 b’ 5.3±2.7 c’ 6.8±2.5 a 6.4±2.4 a 6.4±2.4 a 5.6E-07
Atopobium rimae 2.8±2.2 a’ 2.3±2.3 a’ 1.6±2.3 b’ 2.5±2.3 a 1.9±2.0 b 1.7±2.6 b 1.7E-05
Bacillus cereus 2.8±2.5 a’ 1.6±2.4 b’c’ 1.9±2.2 c’ 2.5±2.9 a 1.5±2.9 b 1.7±2.9 b 1.3E-08
Lactobacillaceae bacterium 1.6±3.2 a’ -0.7±1.4 b’ -1.3±1.5 c’ -0.2±2.5 a -1.2±1.6 b -1.4±1.2 b 7.9E-11
Escherichia coli 1.2±1.8 a’ -0.7±1.7 b’ -0.2±2.1 b’ 1.3±2.5 a -0.4±2.1 b 0.0±1.9 b 1.8E-10
Desulfotomaculum halophilum 1.4±2.6 a’ 0.4±2.6 b’ -0.8±2.4 c’ 0.5±2.5 a -0.9±2.1 b -1.1±2.3 b 1.9E-11
Streptococcus thermophilus -0.3±2.3 a’ -2.4±1.3 b’ -2.4±1.6 b’ 0.2±2.3 a -1.7±1.6 a -2.3±1.6 a 5.6E-17
Erythrobacter flavus -1.7±2.4 a’ -3.0±1.1 b’ -3.1±1.4 b’ -1.4±2.6 a -2.6±1.7 b -2.9±1.6 b 5.6E-14
Prevotella denticola -2.5±0.8 a’ -2.8±1.8 a’ -3.4±1.0 b’ -2.2±1.0 a -2.7±1.2 a,b -3.1±1.1 b 2.5E-07
138
Table 5-7 The relative to mean abundance of vaginal bacterial species that increased across gestation in pregnant women treated with placebo or probiotics.
Results are mean values ± SD and expressed in centered logarithm transformed ratios. Comparisons between the placebo (n=34) and probiotic (n=32) groups at 13, 28 and 35 weeks gestation were assessed Generalized Estimation Equation model in R. Statistical significance within the placebo group (a’, b’ and c’) and within the probiotic group (a, b, and c) was denoted with different letters (p < 0.05).
Placebo Group (n=32) Probiotic Group (n=34)
Species 13 wks 28 wks 35 wks 13 wks 28 wks 35 wks p-value
Corynebacterium pseudogenitalium -0.9±1.5a’ 0.4±1.6 b’ 1.0±1.8 c’ -1.1±1.8 a 1.0±2.4 b 1.0±1.7 b 1.7E-16
Facklamia hominis -1.6±1.0 a’ -1.4±1.4 a’ -0.8±1.8 b’ -1.8±1.1 a -0.9±1.6 b -1.0±1.6 b 4.2E-05
Corynebacterium amycolatum -1.9±0.9 a’ -1.1±1.5 b’ -0.5±1.8 c’ -1.6±1.0 a -0.7±1.7 b -0.3±1.1 b 8.1E-10
Clostridiales coagulans -1.8±0.9 a’ -1.0±1.7 b’ -0.3±2.0 c’ -1.9±1.0 a -1.3±1.8 b -1.3±1.7 b 2.9E-07
Varibaculum cambriense -1.7±1.0 a’ -0.4±1.8 b’ 0.0±1.7 b’ -1.6±1.3 a -0.7±1.5 b -0.5±1.8 b 5.1E-12
Campylobacter ureolyticus -2.0±0.9 a’ -1.8±1.7 b’ -1.1±1.5 b’ -1.6±1.6 a -1.6±1.6 a -1.4±2.1 b 4.3E-06
Corynebacterium coyleae -2.2±1.4 a’ -1.1±2.4 b’ -1.4±2.4 b’ -2.1±1.1 a -1.7±1.6 b -1.7±1.5 b 1.9E-03
Prevotella disiens -0.9±1.5 a’ 0.4±1.6 b’ 1.0±1.8 b’ -1.1±1.8 a 1.0±2.4 a 1.0±1.7 a 2.8E-04
Cryptobacterium curtum -1.6±1.0 a’ -1.4±1.4 a’ -0.8±1.8 b’ -1.8±1.1 a -0.9±1.6 a -1.0±1.6 b 5.3E-09
139
Table 5-8 Summary table of cervico-vaginal cytokines and chemokines across gestation in pregnant women who received either placebo or probiotic treatment.
Results are mean values ± SD and expressed in picogram per milliliter. Data have equal variance but were not normally distributed. Comparison between the placebo group (n=33) and the probiotic group (n=31) was assessed with the Generalized Estimation Equation model in R. Statistical significance within the placebo group (a’, b’ and c’) and within the probiotic group (a, b, and c) is denoted with different letters (p<0.05).
Placebo Group (n = 33) Probiotic Group (n = 31)
13 wks 28 wks 35 wks 13 wks 28 wks 35 wks
IL-1β 121.3±186.6 a’ 80.7±171.6 a’ 72.2±166.8 a’ 199.7±404.2 a 66.4±143.3 a 82.3±113.2 a
IL-2 0.6±0.7 a’ 0.6±0.6 a’ 0.4±0.5 a’ 0.4±0.6 a 1.2±2.8 a 0.6±0.6 a
IL-4 0.6±0.4 a’ 0.8±0.4 b’ 0.7±0.4 a’, b’ 0.8±0.4 a 1.3±1.2 a 0.7±0.4 a
IL-5 0.3±0.3 a’ 0.4±0.5 a’ 0.4±0.3 a’ 0.6±1.2 a 1.1±2.1 a 0.5±0.3 a
IL-6 15.1±30. 5 a’ 4.1±5.6 a’ 3.4±5.0 a’ 36.0±71.1 a 6.3±10.7 a 5.3±8.0 a
IL-7 56.0±121.4 a’ 34.6±33.7 a’ 29.9±37.1 a’ 55.4±117.5 a 90.4±269.4 a 29.3±36.2 a
IL-8 1453.9±2230.1 a’ 1155.8±2716.0 a’ 604.4±985.1 a’ 2068.0±4658.2 a 418.2±442.6 a 855.0±1258.5 a
IL-9 7.9±16.2 a’ 4.6±4.1 a’ 4.5±6.7 a’ 6.4±12.1 a 16.5±57.3 a 3.8±3.8 a
IL-10 8.4±2.9 a’ 10.0±2.7 b’ 9.0±3.6 a’,b’ 8.4±3.2 a 11.0±4.6 b 9.9±2.4 a,b
IL-12p70 57.8±89.8 a’ 55.0±47.0 a’ 44.6±38.1 a’, 50.3±72.7 a 90.0±217.5 a 41.4±22.1 a
IL-13 4.7±8.8 a’ 3.4±2.1 a’ 3.3±3.0 a’ 5.1±9.8 a 9.7±27.8 a 3.1±2.8 a
IL-15 1.0±1.1 a’ 1.3±1.5 a’ 0.8±0.9 a’ 1.0±1.0 a 1.6±1.6 a 0.8±0.9 a
IL-17 4.3±2.7 a’ 5.0±2.6 a’ 3.7±1.8 a’ 4.3±2.6 a 7.7±7.1 a 3.8±1.8 a
CCL2 10.7±17.4 a’ 8.4±4.3 a’ 6.8±4.6 a’ 10.6±13.3 a 11.6±10.2 a 9.5±8.5 a
CCL3 1.9±1.5 a’ 1.5±1.0 a’ 1.6±1.8 a’ 3.7±6.1 a 1.7±1.4 a 1.6±0.9 a
CCL4 9.1±9.5 a’ 5.6±8.8 a’ 5.0±13.4 a’ 21.1±48.8 a 3.8±3.3 a 6.3±7.6 a
CCL5 32.8±134.4 a’ 3.8±1.5 a’ 2.9±1.4 a’ 10.0±33.8 a 4.4±3.1 a 3.3±1.5 a
CCL11 11.2±19.4 a’ 14.6±36.7 a’ 7.2±9.6 a’ 6.6±11.8 a 24.8±78.1 a 11.0±12.7 a
CSF2 15.1±13.2 a’ 12.1±7.0 a’ 9.4±7.1 a’ 13.0±12.0 a 21.9±45.6 a 9.2±6.4 a
CSF3 131.9±156.2 a’ 58.1±129.8 a’, b’ 44.2±81.1 b’ 204.6±253.5 a 60.5±109.5 b 73.4±122.0 a
CXCL10 1346.5±3779.0 a’ 639.9±762.5 a’ 309.7±354.0 a’ 512.7±1064.9 a 682.6±1371.7 a 581.2±866.2 a
TNF-α 31.4±55.3 a’ 33.1±41.7 a’ 24.7±30.2 a’ 31.6±30.6 a 56.8±84.7 a 31.6±27.9 a
IFN-Υ 49.0±45.9 a’ 73.5±46.4 a’ 62.0±55.1 a’ 80.4±68.4 a 127.4±110.9 a 67.3±54.4 a
PDGF-bb 74.4±133.1 a’ 45.6±60.0 a’ 33.2±41.6 a’ 64.7±136.2 a 90.8±249.4 a 31.6±34.5 a
bFGF 5.1±7.0 a’ 4.2±2.5 a’ 3.6±2.5 a’ 4.4±3.0 a 6.9±12.5 a 3.4±1.3 a
VEGF 2982.6±4491.4 a’ 3666.5±4247.7 a’ 3541.9±4860.3 a’ 3883.9±8847.3 a 2856.4±2362.8 a 2623.1±2070.7 a
140
Chapter Six
General Discussion
141
Chapter 6
6. General Discussion
A disruption to the balance between pro-inflammatory cytokines and anti-inflammatory
cytokines that favours an inflammatory milieu underlies the pathogenesis of infection/
inflammation associated preterm birth (PTB) (MacIntyre et al., 2012). A disturbance of the
vaginal microbiota such as that observed in bacterial vaginosis (BV) also contributes to an
increased risk of PTB (Donders et al., 2009). Limited knowledge is available regarding the
use of probiotic lactobacilli as a prophylactic treatment for PTB. In this thesis, I assessed the
effect of probiotic lactobacilli and its supernatant on the incidence of PTB and the immune-
regulatory role of lactobacilli using pregnant mice. I also examined the effect of oral
lactobacilli on the cervico-vaginal cytokines in pregnant women with an abnormal Nugent
score. The effect of lactobacilli on the vaginal microbiota in both mice and pregnant women
was also investigated.
I specifically studied 1) the effect of Lactobacillus rhamnosus GR-1 (GR-1) live bacteria
and its supernatant (GR-1 SN) on the prevention of LPS-induced PTB in pregnant CD-1
mice; 2) the effect of GR-1 and GR-1 SN on the systemic and intra-uterine cytokine and
chemokine profiles in pregnant CD-1 mice; 3) the effect of L. rhamnosus GR-1 and L.
reuteri RC-14 (GR-1 and RC-14) live bacteria on the cervico-vaginal concentrations of
cytokines and chemokines in pregnant women with an abnormal Nugent score; 4) the
potential of using GR-1 to modulate the mouse vaginal microbiota; and 5) the potential of
using GR-1 and RC-14 to alter the vaginal microbiota of pregnant women with an abnormal
Nugent score.
I found that pre-treatment with GR-1 SN, but not with GR-1 live bacteria, reduces the
incidence of inflammation (LPS)-induced PTB in pregnant CD-1 mice. I also observed that
GR-1 SN and GR-1 live bacteria differentially modulate the systemic and intrauterine
murine immune responses (Figure 6-1). I then investigated whether GR-1 live bacteria itself
142
has an immune-regulatory role in pregnant mice. The effects of oral GR-1 live bacteria
systemically, as reflected by changes in the maternal plasma and locally within the intra-
uterine tissues, are mainly pro-inflammatory. I observed elevations in the pro-inflammatory
cytokines TNFα, IL-6, IL-12p70, IL-17 and IFN-γ, and chemokines CCL2, CCL3, CCL4
and CCL5 with live bacteria administration. In contrast, GR-1 SN alone did not have any
effect on pro-inflammatory cytokines or chemokines. The effect of GR-1 SN is primarily
anti-inflammatory, with GR-1 SN alone increasing the placental anti-inflammatory
cytokines IL-10 and IL-4 in pregnant CD-1 mice. This is consistent with previous in vitro
studies, in which GR-1 SN increased the production of IL-10 in cultured human placental
trophoblast cells (Yeganegi et al., 2010) and decidual cells (Li et al., 2014). Furthermore, I
found that GR-1 SN dampens LPS-induced increases in pro-inflammatory cytokines and
chemokines in pregnant mice (Figure 6-2). This differential effect on inflammatory
mediators is in keeping with observations in previous studies, which have shown that the
cell-free culture supernatant (CFS) of Bifidobacterium breve CNCM I-4035 is more
effective than its live bacteria counterpart at suppressing the secretion of pro-inflammatory
cytokines and chemokines in human dendritic cells (DCs) challenged (Bermudez-Brito et
al., 2013). It has been shown that the maternal DCs surface expressions of co-stimulatory
molecules CD86 and CD80 and antigen presenting molecule (HLA-DR) are reduced during
pregnancy, suggesting DCs may be important in the immune tolerance of a semi-allogeneic
fetus (Bachy et al., 2008). DCs treated with CNCM I-4036 live bacteria alone secrete
inflammatory cytokines IL-1β, IL-6, IL-8, IL-12 and TNFα while CFS alone decreased the
secretion of IL-8 and IL-12p40 (Bermudez-Brito et al., 2014). B. breve live bacteria alone
are more potent stimulators of the pro-inflammatory cytokines and chemokines than its
supernatant (Bermudez-Brito et al., 2013). Furthermore, B. breve CNCM I-4035 supernatant
dampens the secretion of pro-inflammatory cytokines IL-1β, IL-6, IL-12p40, and
chemokines MCP-1, MIP-1α and RANTES, while B. breve live bacteria increase the
production of these chemokines in response to a challenge with Salmonella (Bermudez-Brito
et al., 2013).
GR-1 live bacteria increased the concentration of CCL2 and IFN-γ in pregnant CD-1 mice
both of which promote pathogen elimination. CCL2 is also responsible for the recruitment
143
of monocytes and their differentiation into macrophages (Mak, 2006). Furthermore, CCL2
enhances the phagocytic activity of macrophages. And IFN-γ possesses anti-pathogenic and
anti-proliferative properties (Mak, 2006). IFN-γ has also been shown to reduce the
expression of COX-2 and PGE2 in term and preterm placenta (Hanna et al., 2004). Taken
together with the findings that GR-1 SN has anti-inflammatory properties, I speculate that
the secreted metabolites in the GR-1 SN limit the inflammatory mediators produced by its
live bacteria counterpart; while at the same time, the anti-infective properties of GR-1 live
bacteria are maintained.
Lipoteichoic Acid (LTA), which is present on the cell surface of gram-positive lactobacilli,
is immune-stimulatory through activation of the Toll-like receptor (TLR) 2 pathway in a
murine model of colitis (Grangette et al., 2005). Enhanced anti-inflammatory activity has
been found in a murine model of colitis when LTA is substituted (D-alanylation) or removed
(Grangette et al,. 2005; Claes et al., 2010; Mohamadzadeh et al., 2011). It has been
suggested that the active moiet(ies) responsible for the anti-inflammatory properties of B.
breve CNCM I-4035 supernatant are likely proteins (Bermudez-Brito et al., 2013). These
results suggest that soluble active metabolites, produced by GR-1 live bacteria and released
into the supernatant, have anti-inflammatory properties, and GR-1 live bacteria and its
supernatant exert their immune-regulatory effects via activation of signaling pathways.
Previous studies have shown that the oral administration of Lactobacillus rhamnosus can
influence body sites distant to the gut, such as the respiratory tract (Villena et al., 2012), the
skin (Tanaka et al., 2009), and the heart of murine animals (Gan et al., 2014). Oral
probiotics can modulate murine intestinal mucosal immune responses (Ogita et al, 2015) as
well as systemic immune responses (Forsythe et al., 2012). Furthermore, it has been shown
that the serum and intestinal fluid cytokine profiles are similar to each other after the oral
administration of L. rhamnosus CRL 1505 in mice (Villena et al., 2012). Although orally
administered L. rhamnosus GR-1 to pregnant CD-1 mice did not change the cecal
microbiota, I did observe a change in the systemic and intrauterine production of cytokines
and chemokines, as well as a change in the vaginal microbiota. It is possible that GR-1
passing through the mouse gut induces the intestinal mucosa to secrete signaling molecules
144
into the systemic circulation, which then exert immune-regulatory effects within the intra-
uterine tissues and amniotic fluid. I did not detect a change in Lactobacillus rhamnosus
abundance in the mouse vaginal microbiota with oral administration of GR-1 live bacteria.
Therefore it is plausible that the secreted signaling mediators, rather than GR-1 live bacteria
travel directly to the mouse vagina, that causes changes in the vaginal environment and
results in an altered vaginal microbiota in pregnant CD-1 mice. It is also possible that the
Ion Torrent sequencing method that I utilized in these experiments is not sufficiently
sensitive enough to detect small changes, if present, in Lactobacillus rhamnosus abundance.
The oral probiotic combination L. rhamnosus GR-1 and L. reuteri RC-14 (GR-1 and RC-
14) did not alter the cervico-vaginal cytokine concentrations in low risk pregnant women
with an abnormal Nugent score. This is in contrast to the findings in pregnant mice, in which
I found oral GR-1 live bacteria induced both systemic and intrauterine inflammatory
cytokines. There are a number of possible explanations for these differences. Firstly, the
effects of lactobacilli could be species specific. It is also possible that unlike in the mouse
study, in which I used lipopolysaccharide to induce inflammation, pregnant women in our
randomized controlled trial had low risk pregnancies with no evidence of clinical or
subclinical inflammatory processes. A combination of probiotic strains (GR-1 and RC-14)
was used in the studies with pregnant women, whereas a single strain (GR-1) was used in
pregnant mice. Further investigations in pregnant mice using GR-1 and RC-14 could provide
additional insights in to the potential efficacy of multi-strain probiotic preparations, and
whether a multi-strain (GR-1 and RC-14) or a single strain (GR-1) would be more beneficial
in pregnant women.
I have also found that oral GR-1 and RC-14, at the dose given in these experiments, did not
alter the vaginal microbiota in pregnant women with an intermediate or BV Nugent score.
This finding is in contrast to previous studies in non-pregnant women that reported oral GR-
1 and RC-14 reduce BV recurrence by restoring the indigenous lactobacilli (Reid et al.,
2003a). This difference could be due to differences in the hormonal environment and/or the
vaginal microbial stability between pregnant and non-pregnant women. High levels of
estrogen during pregnancy likely accounts for a higher abundance of Lactobacillus spp.
145
observed in pregnant women when compared to non-pregnant women (Romero et al.,
2014a), since higher estrogen leads to an increase in mucosal glycogen production, whose
metabolized substrates support vaginal lactobacilli colonization (Spear et al., 2014).
Furthermore, it has been shown that the vaginal microbiota composition of pregnant women
is more stable than non-pregnant women (Romero et al., 2014a). The vaginal microbiota of
pregnant women may thus be more resilient to changes caused by additional exogenous oral
lactobacilli. The probiotic dosage chosen for our study (5 X 109 colony-forming units/ cfu)
was based on previous studies in non-pregnant women (Reid at al., 2003). It is possible that
a higher dose is needed to colonize the vagina of pregnant women.
The administration of GR-1 live bacteria or GR-1 SN alone does not change the normal
gestational length, fetal weight nor litter size in pregnant CD-1 mice. In women, there were
no adverse reactions reported following ingestion of GR-1 and RC-14. Gestational age at
delivery, birth weight, and cord blood pH were not different between neonates born to
placebo and probiotics GR-1 and RC-14 treated mothers. These findings are in agreement
with a previous study that reviewed 37 studies of prenatal probiotics, and found no evidence
of adverse maternal or neonatal outcomes (VandeVusse et al., 2013). We screened women
for an abnormal Nugent score prior to randomization since the presence of an abnormal
vaginal biota such as BV is associated with a 1.4-fold increased risk of PTB. This study is
the first to our knowledge to investigate the effect of probiotic lactobacilli on the vaginal
microbiota and cervico-vaginal cytokine profiles across gestation in pregnant women who
had an abnormal Nugent score initially.
There are a few limitations to consider when interpreting the findings presented in this
thesis. In the mouse studies, I observed that different batches/ bottles of LPS with the same
catalogue number can have different potency; thus, giving variable preterm delivery (PTD)
rate. For instance, 125 µg of LPS was required to result in 100% PTB in the mouse study
that evaluated the GR-1 SN effect alone (Chapter 3); whereas 50 µg of LPS was sufficient to
cause 100% PTB in the mouse study that evaluated the effect of GR-1 live bacteria (Chapter
4). Although the same batch of LPS was used within each set of experiments, two different
batches of LPS were used overall. In addition, separate control experiments were used for
146
each set. I noted a difference in the baseline concentration of progesterone between the two
series of mouse experiments. In the GR-1 SN alone study, baseline progesterone
concentrations were 68 ± 4.6 ng/mL whereas in the GR-1 live bacteria study it was 40 ± 4.4
ng/mL There are a number of factors that could contribute to this difference, including the
fact that the time of day that the mice were sacrificed was different; mice in the GR-1 SN
study were sacrificed half a day earlier than the mice in the GR-1 live bacteria study. The
mice in the GR-1 SN study received saline via intra-peritoneal injection, whereas those mice
in the GR-1 live bacteria study received saline through oral gavage. Different types of
procedure might place different levels of stress on the animals, which may alter the baseline
hormonal concentrations. In the human study, compliance to the treatment protocol was
determined by counting the numbers of pills remaining in the bottle returned at the end of
the study. The study could be strengthened if stool samples were also collected and
subjected to quantitative PCR amplification to quantify the amount of GR-1 and RC-14
present.
Future experiments are needed to identify the active moiety(ies) responsible for the anti-
inflammatory properties of Lactobacillus rhamnosus GR-1 supernatant. The supernatant
could first be fractionated into lipid, proteins and LTA components and tested in pregnant
mice to evaluate which component(s) is associated with the inflammatory dampening effect.
If it were the protein component, further fractionation based on the molecular weights of the
proteins could be performed using Fast Protein Liquid Chromatography. Fractions that have
similar inflammatory dampening effects as the crude GR-1 SN in pregnant mice could then
be subjected to mass spectrometry to identify the active moiety(ies). This would allow
concentration of the fraction, which could potentially enhance the anti-inflammatory
properties.
Other experiments could include identifying the differential underlying mechanisms by
which L. rhamnosus GR-1 live bacteria and its supernatant exert their effects in pregnant
mice. The LTA component of GR-1 live bacteria could also be removed to evaluate
whether it is responsible for the inflammatory stimulating effect of GR-1 live bacteria.
Furthermore, knockout pregnant mice lacking the gene(s) for various TLRs could be used to
147
identify the signaling pathways responsible for the actions of GR-1 live bacteria and its
supernatant. Further mechanistic pathways downstream of the TLRs could also be evaluated
given that previous studies have demonstrated that GR-1 SN increases the production of
anti-inflammatory cytokine IL-10 through the JAK/STAT and MAPK pathways in cultured
human trophoblast cells (Yeganegi et al., 2010).
Since GR-1 SN has also previously been shown in vitro to reduce the synthesis of
prostaglandins (PGs), future experiments could be performed to investigate the effect of GR-
1 SN in vivo on other mediators of parturition including PGs, PTGS, PGDH and MMPs in
pregnant mice. Myometrial concentrations of pro-inflammatory cytokines increase in both
infection (LPS)-induced PTL and non-infection (RU-486, a progesterone antagonist)
associated PTL in pregnant CD-1 mice (Shynlova et al., 2013). LPS induces an increase in
the mRNA levels of various pro-inflammatory cytokines in the myometrium of pregnant
CD-1 mice as early as 2 hours after intrauterine LPS administration (Shynlova et al., 2014).
This initial outburst of pro-inflammatory cytokines may contribute to luteolysis and cause
progesterone withdrawal via activation of the NF-κB pathway (Vrachnis et al., 2012). In this
study, the anti-inflammatory effect of GR-1 SN was independent of circulating maternal
progesterone concentrations. Future experiments giving GR-1 SN to RU486-treated
pregnant mice would provide evidence whether GR-1 SN dampens the initial pro-
inflammatory cytokine outburst or targets progesterone withdrawal and its associated
increase in pro-inflammatory cytokines.
Given that the litter size and the fetal weight of pups did not change with GR-1 SN
treatment, future experiments could be performed to evaluate the health of mouse neonates
born to mothers that received GR-1 live bacteria and/or its supernatant. Intra-uterine
infection/ inflammation has been associated with an increased prevalence of adverse
neurobehavioral outcomes such as cerebral palsy in exposed offspring in the human (Yoon
et al., 2000; Wu, 2002) as well as fetal neuronal abnormalities in mice (Burd et al., 2010). In
this thesis, I found that GR-1 SN dampens LPS-induced systemic and intra-uterine
inflammation in pregnant mice; future studies could be performed to evaluate the potential
of GR-1 SN at reducing inflammation (LPS)-induced fetal brain injury in pregnant mice.
148
In future clinical trials, pregnant women with high-risk pregnancies based on a previous
PTB or short cervix in conjunction with bacterial vaginosis could be recruited to investigate
the effect of oral GR-1 and RC-14. The vaginal microbial profile of pregnant women lacking
Lactobacillus spp could also be used in conjunction with the Nugent score to identify
women most likely to benefit from probiotics. Supplementation with probiotics is also
known to improve intestinal dysbiosis (de Moreno de Blanc and LeBlanc, 2014) and
mucosal immunity (Wan et al., 2015), and probiotics are widely used for non-pregnancy
related conditions. Alterations of the intestinal biota in turn may be important in the
pathogenesis of other pregnancy complications such as preeclampsia, intrauterine growth
restrictions or miscarriage (Zhang et al., 2015). In order to confirm that oral probiotics
colonize the gut of pregnant women, stool samples from the mothers could be collected to
evaluate the gut microbiome. Compared to other body sites (skin, nose, vagina and gut), the
human placenta is most similar to the oral microbiome, which suggests a hematogenous
route of pathogenic transmission to the intrauterine cavity may be important (Aagaard et al.,
2014) It has been previously observed that the relative abundance of Actinomycetales and
Alphaproteobacteria are increased in the preterm placenta compared to the term placenta
(Aagaard et al., 2014). Furthermore, the commensal bacterial species of the human oral
microbiome, F. nucleatum, has been associated with intrauterine infections (Han et al.,
2009). Therefore, crosstalk may exist between multiple bacterial communities in pregnant
women and it is important to take into consideration other microbiome sites in future clinical
studies.
The research findings in this doctoral thesis provide evidence to the efficacy of
Lactobacillus rhamnosus GR-1 supernatant, but not the live bacteria, to reduce LPS-induced
PTB and inflammation in pregnant mice. I have also shown that GR-1 live bacteria can
modulate both systemic and intrauterine cytokines as well as the vaginal microbiota of
pregnant mice. These findings provide further support for the potential benefit of lactobacilli
supernatant in the prevention of inflammation-associated conditions during pregnancy
including PTB.
149
Figure 6-1 Changes in sytemic and intrauterine cytokines after treatment with Lactobacillus rhamnosus GR-1 supernatant or live bacteria.
Cytokines with a downward arrow decreased significantly following GR-1 treatment, when compared to mice that received saline. All other cytokines increased significantly following GR-1 treatment.
Amniotic Fluid
Myometrium
Placenta
Fetal Membranes
GR-1 SN GR-1 live bacteria
Maternal Plasma
IL-12p40 TNFα
Maternal Plasma
No change
IL-4 IL-10
CCL2, 3, 4, 5, 11
CCL5 CCL5 !!
IL-10 IL-10 IL-4
!!IL-4 !!
IL-12p70
IL-17 TNFα IL-1α
IL-6 IFNγ !!
150
Figure 6-2 LPS-induced sytemic and intrauterine cytokines that were dampened with GR-1 supernatant pretreatment.
Cytokines increased with LPS alone were shown on the left. On the right side of the figure, cytokines with a downward arrow decreased significantly with GR-1 supernatant pretreatment following subsequent LPS challenge, when compared to mice that received LPS alone. All other cytokines were not different between LPS group and LPS+GR-1 group.
LPS LPS + GR-1 SN
Amniotic Fluid
Myometrium
Placenta
Fetal Membranes
IL-1β IL-6 IL-12p40 IL-12p70 TNFα IL-17 CCL3 CCL4 CCL5
IL-1β IL-6 IL-12p40 IL-12p70 TNFα IL-17 CCL3 CCL4 CCL5
!!
!!
IL-1β IL-6
IL-12p40 IL-12p70
TNFα IL-17
CCL3,4,5
IL-1β IL-6
IL-12p40 IL-12p70
TNFα IL-17
CCL3,4,5
!!
!!!!!!
Maternal Plasma IL-1β IL-6
IL-12p40 IL-12p70
TNFα IL-17
IL-1β IL-6
IL-12p40 IL-12p70
TNFα IL-17
!!!!!!
!!
CCL3 CCL4 CCL5
Maternal Plasma CCL3 CCL4 CCL5
!!!!
IL-6 TNFα CCL3 CCL4 CCL5
IL-6 TNFα CCL3 CCL4 CCL5
!!!!
!!
151
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152
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Appendices
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List of Appendices Appendix I Cytokine and Chemokine Assay Protocol
1. Dilute 10x beads with assay buffer to 1x concentration.
2. Add 50 µL of 1x beads to each well of a 96 well plate.
3. Wash the plate twice with 100 µL of wash buffer.
4. Dilute samples with sample diluent in a 1:4 ratio for plasma samples and in a 1:1
ratio for all other samples.
5. Add 50 µL of standards, blank (diluent) or samples to each well in duplicate.
6. Cover the plate with a plastic film and then with aluminum foil and incubate on
shaker (850 rpm) for 30 minutes at room temperature.
7. Wash the plate thrice with 100 µL of wash buffer.
8. Dilute 10x detection antibody with antibody diluent to 1x concentration.
9. Add 25 µL of 1x detection antibody to each well.
10. Cover the plate with a plastic film and then with aluminum foil and incubate on
shaker (850 rpm) for 30 minutes at room temperature.
11. Wash the plate thrice with 100 µL of wash buffer.
12. Dilute 100x streptavidin-PE with assay buffer to 1x concentration.
13. Add 50 µL of 1x streptavidin-PE to each well.
14. Cover the plate with a plastic film and then with aluminum foil and incubate on
shaker (850 rpm) for 10 minutes at room temperature.
15. Wash the plate thrice with 100 µL of wash buffer.
16. Re-suspend the beads in each well with 125 µL assay buffer.
17. Cover the plate with a plastic film and then with aluminum foil and incubate on
shaker (850 rpm) for 30 seconds at room temperature.
18. Proceed to read the plate on Bioplex machine.
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Appendix II Progesterone EIA Assay Protocol
1. Reconstitute the progesterone AChE Tracer with 6 mL of EIA buffer.
2. Reconstitute the progesterone EIA antiserum with 6 mL EIA buffer.
3. Set-up the plate to include 2 wells for Blank, 2 wells for non specific binding (NSB),
3 wells for Maximum binding (B0), 1 well for Total activity (TA).
4. Add 100 µL of EIA buffer to NSB wells.
5. Add 50 µL of EIA buffer to B0 wells.
6. Add 50 µL of standards and samples to each well in duplicate.
7. Each sample is assayed at three dilutions and each dilution is assayed in duplicate.
8. Add 50 µL of diluted progesterone AChE to each well except the TA and the blank
wells.
9. Add 50 µL of diluted progesterone EIA antiserum to each well except the TA, the
NSB and the blank wells.
10. Cover the plate with a plastic film and incubate for 1 hour at room temperature on
shaker at 300 rpm.
11. Empty the wells and rinse 5 times with 200 µL of wash buffer.
12. Reconstitute Ellman’s reagent with 20 mL of UltraPure water.
13. Add 200 µL of Ellman’s reagent to each well.
14. Add 5 µL of tracer to the TA wells.
15. Cover the plate with a plastic film and then with aluminum foil. The plate is left in a
dark room to develop on a shaker (300 rpm) for 60 to 90 minutes.
16. Read the plate at a wavelength between 405 nm to 420 nm.
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Appendix III PowerSoil®DNA Isolation Kit Protocol
1. Add vaginal or cecal tissues into PowerBead Tubes and vortex to mix.
2. Add 60 µl of Solution C1 cell lysis buffer. Secure the tubes horizontally on a vortex
pad with tape and vortex at maximum speed for 10 minutes.
3. Centrifuge the tubes at 10,000x g for 30 sec at 25oC and transfer 500 µl of the
supernatant to a clean 2 ml tube.
4. Add 250 µl of Solution C2 inhibitor removal buffer, vortex for 5 sec and incubate at
4°C for 5 min.
5. Centrifuge the tubes at 25°C for 1 min at 10,000 x g and transfer 500 µl of the
supernatant to a clean 2 ml tube.
6. Add 200 µl of Solution C3 inhibitor removal buffer, vortex for 5 sec and incubate at
4°C for 5 min. Repeat Step 5.
7. Add 1200 µl of Solution C4 containing high concentration of salt to bind DNA, and
vortex the tube for 5 seconds.
8. Load 600 µl onto a Spin Filter, centrifuge at 25°C for 1 min at 10,000 x g, and
discard the flow through. Repeat Step 9 twice.
9. Add 500 µl of Solution C5 ethanol containing buffer, centrifuge at 25°C for 30 sec at
10,000 x g and discard the flow through.
10. Centrifuge again at 25°C for 1 min at 10,000 x g.
11. Place the spin filter in a clean 2 ml tube and add 100 µl of Solution C6 sterile elution
buffer and centrifuge at at 25°C for 30 sec at 10,000 x g.
12. Store the DNA in the tube at -80oC until further analysis.
181
Appendix IV Copyright from New England Journal of Medicine
182
Appendix V Copyright from Frontiers of Immunology
183
Appendix VI Copyright from American Journal of Obstetrics and Gynecology
