Upload
duongnga
View
215
Download
2
Embed Size (px)
Citation preview
www.sciencemag.org/cgi/content/full.1233665/DC1
Supplementary Materials for
Type I Interferon Suppresses Type II Interferon–Triggered Human
Anti-Mycobacterial Responses
Rosane M. B. Teles, Thomas G. Graeber, Stephan R. Krutzik, Dennis Montoya, Mirjam
Schenk, Delphine J. Lee, Evangelia Komisopoulou, Kindra Kelly-Scumpia, Rene Chun,
Shankar S. Iyer, Euzenir N. Sarno, Thomas H. Rea, Martin Hewison, John S. Adams,
Stephen J. Popper, David A. Relman, Steffen Stenger, Barry R. Bloom, Genhong Cheng,
Robert L. Modlin*
*To whom correspondence should be addressed. E-mail: [email protected] Published 28 February 2013 on Science Express
DOI: 10.1126/science.1233665
This PDF file includes:
Materials and Methods
Figs. S1 to S22
References
1
Supplementary Materials for
Type I interferon suppresses Type II interferon-triggered human anti-
mycobacterial responses
Rosane M.B. Teles, Thomas G. Graeber, Stephan R. Krutzik, Dennis Montoya, Mirjam
Schenk, Delphine J. Lee, Evangelia Komisopoulou, Kindra Kelly-Scumpia, Rene Chun,
Shankar S. Iyer, Euzenir N. Sarno, Thomas H. Rea, Martin Hewison, John S. Adams,
Stephen J. Popper, David A. Relman, Steffen Stenger, Barry R. Bloom, Genhong Cheng
and Robert L. Modlin
correspondence to: [email protected]
This PDF file includes:
Materials and Methods
Figs. S1 to S22
Materials and Methods
Patients and clinical specimens
Patients with leprosy were classified according to the criteria of Ridley and
Jopling (30). The designation of tuberculoid leprosy (T-lep) included patients that were
classified clinically as borderline tuberculoid, “BT”, and the designation of lepromatous
leprosy (L-lep) only included patients classified as “LL”. All T-lep and L-lep skin biopsy
specimens were taken at the time of diagnosis, prior to initiating treatment. Reversal
reaction (RR) skin biopsy specimens were considered upgrading reactions; consistent
with activation of cell-mediated immune responses against M. leprae towards the
2
tuberculoid pole (usually this reaction occurs during treatment, but can also occur
spontaneously). Specimens were embedded in OCT medium (Ames, Elkhart, IN), snap
frozen in liquid nitrogen and stored at -80C. All leprosy patients were recruited with
approval from the Institutional Review Board of University of Southern California
School of Medicine and the Institutional Ethics Committee of Oswald Cruz Foundation,
as well as the University of California, Los Angeles.
Antibodies and cytokines
Antibodies used for immunohistochemistry were as follows: CD3, CD163 and
CD209 (BD Pharmingen, Franklin Lakes, NJ), IFN-β and IFNAR1 (PBL Interferon
Source, Piscataway, NJ), CD14 and IL-10 (Invitrogen, Carlsbad, CA and BD
Biosciences, San Diego, CA) and IgG controls (Sigma, St. Louis, MO). The following
human recombinant cytokines were used for in vitro assays, IFN- β (PBL Interferon
Source), IFN-γ (BD Biosciences) and IL-10 (R&D Systems, Minneapolis, MN).
Blocking antibodies included anti-IL-10 (BD Pharmingen) and anti-IFNAR2
(Calbiochem, San Diego, CA).
Microarray data analysis
Gene expression profiles of mRNAs derived from skin biopsy specimens of 24
leprosy patients (T-lep, n = 10; L-lep, n = 6; RR, n = 7) were determined using
Affymetrix Human U133 Plus 2.0 microarrays and analyzed as previously described (31).
Principal component analysis (PCA) was performed using Partek v6.4. Unsupervised
clustering analysis of genes with coefficient of variance ≥ 1.0 and intensity average ≥100
3
was performed using Cluster and Treeview (32) and further biofunctional analyses were
performed using Ingenuity Pathways Analysis Software (IPA). The raw gene expression
data analyzed in this study are available online through the Gene Expression Omnibus
database (http://www.ncbi.nlm.nih.gov/geo/) accession number GSE17763.
In a separate experiment, CD14+ monocytes were enriched by negative selection
of PBMC from four healthy donors using EasySep (Stem Cell Technologies, Vancouver,
Canada). The negatively selected cells were analyzed by flow cytometry and found to be
>90% CD14+. The monocytes were cultured in the presence or absence of lL-10
(10ng/ml) for 24h. Gene expression profiles of mRNAs derived from the untreated or
treated monocytes were determined as described above. Expression Omnibus database
(http://www.ncbi.nlm.nih.gov/geo/) accession number is GSE43700.
Identification of IFN regulated genes
Supervised analyses were performed to identify Type I and Type II IFN regulated
genes. Differentially expressed genes between T-lep and L-lep leprosy groups were
identified by pairwise comparison using the criteria of a p ≤ 0.05 and fold change (FC) ≥
1.5. A list of genes specifically induced or repressed by only IFN-, IFN-β or IFN-γ was
derived from the gene expression profile data of IFN-treated PBMC (6). These IFN
downstream gene targets were then integrated with the leprosy lesion microarray data to
determine the differential expression of IFN-regulated genes in different disease forms.
A second IFN-oriented analysis was performed using the IFN target genes as defined by
the interferome database (7). Two microarrays using peripheral blood of patients with
tuberculosis, active and latent tuberculosis (TB1) (3) and active tuberculosis patients and
4
healthy donors (TB2) (12) were also compared with the microarray data derived from
IFN-stimulated PBMC (6). Type I interferon suppresses Type II interferon-triggered
human anti-mycobacterial responses. Enrichment analysis of the overlap in IFN target
genes between the different leprosy and TB datasets was performed using the
hypergeometric distribution to control for differences in the overall number of
differentially expressed genes. The hypergeometric distribution (hypergeometric test) is
equivalent to the one-tailed version of Fisher's exact test. These tests determine the
degree the observed amount of enrichment is greater than expected, and together these
are two of the most common enrichment statistics used in bioinformatic analyses (33,
34). For the IFN-specific enrichment statistical analysis of Figure 1C and 1E, IFN-
induced and -repressed genes were individually analyzed for each group (as shown in
Supplemental Figure 2 and 6) and statistical analysis was performed using a one-tailed
Fisher’s exact test and Bonferroni multiple hypothesis testing correction. The IFN
summation score was calculated using a gene voting approach based on the sum of the
signed log ratio relative expression of the IFN-β specific and IFN-γ specific induced
(positive in the summation) and repressed (negative) genes in each individual lesion.
Noisy and non-discriminatory genes were excluded from the IFN summation scores,
namely genes that did not show differential expression in either direction between the
patient subtypes (ANOVA p-value > 0.05). IFN-β specific genes in common between L-
lep lesions and active TB blood, TB1 and TB2, were integrated with the IL-10 vs. media
monocyte gene expression profile. A flow diagram for the gene expression profile and
integrative genomics analyses is shown in Supplemental Figure 1.
5
Immunoperoxidase labeling and confocal microscopy.
Frozen tissue sections were blocked with normal horse serum before incubation
with monoclonal antibodies (mAbs) for 60 min, followed by incubation with biotinylated
horse anti-mouse IgG for 30 min. Slides were counterstained with hematoxylin and
mounted in crystal mounting medium (Biomeda, Foster City, CA) and were visualized
using the ABC Elite system (Vector Laboratories, Burlingame, CA).
To colocalize cytokines with specific cell markers two-color immunofluorescence
with confocal microscopy was used. Immunofluorescence was performed by serially
incubating cryostat tissue sections with mouse anti-human mAbs of different isotypes,
anti-CD3 (IgG1), anti-CD14 (IgG1), anti-CD163 (IgG1), anti-CD209 (IgG2b), anti-IFN-
β (IgG1 and IgG2a) and anti-IL-10 (IgG1) followed by incubation with isotype-specific,
fluorochrome (A488 or A568)-labeled goat anti-mouse immunoglobulin antibodies
(Molecular Probes, Carlsbad, CA). Controls included staining with isotype-matched
antibodies as described previously (35). Nuclei were stained with DAPI (4',6'-diamidino-
2-phenylindole). Double immunofluorescence of skin sections was examined using a
Leica-TCS-SP MP inverted single confocal laser-scanning and a two-photon laser
microscope (Leica, Heidelberg, Germany) at the Advanced Microscopy/Spectroscopy
Laboratory Macro-Scale Imaging Laboratory, California NanoSystems Institute,
University of California at Los Angeles.
Bacterial and human cell culture and treatment
M. leprae was grown in the footpad of nu/nu mice, as described previously (36)
and was provided by Dr. James L. Krahenbuhl of National Hansen's Disease Programs,
6
Health Resources Service Administration, Baton Rouge, LA. Sonicated M. leprae was
provided by Patrick Brennan of the Department of Microbiology, Immunology &
Pathology, Colorado State University, Fort Collins, CO.
Whole blood from healthy donors was obtained with informed consent (UCLA
I.R.B. #92-10-591-31). PBMCs were isolated using Ficoll (GE Healthcare, Piscataway,
NJ) gradient centrifugation. Monocytes were purified by plastic adherence for two hours
in RPMI 1640 (Invitrogen) supplemented with 1% fetal calf serum (Omega Scientific,
Tarzana, CA). Non-adherent cells were removed via vigorous washing and adherent cells
were cultured in RPMI supplemented with antibiotics and 10% fetal calf serum, or 10%
vitamin D-sufficient (100 nM) human serum for antimicrobial peptide gene expression
studies or M. leprae infection studies. Human adherent monocytes were cultured in
RPMI with 10% FCS (Omega Scientific) in the presence or absence of live M. leprae
(MOI 10:1), sonicated M. leprae (10μg/ml) for 6h and 24h for IFN-β mRNA detection by
qPCR and IFN-β and IL-10 protein detection by ELISA, respectively. In addition,
neutralizing anti-human IFNAR2 (10μg/ml; Calbiochem) or a isotype control were used
in combination with live M. leprae (MOI 10:1) or sonicated M. leprae (10μg/ml) for 24h,
then supernatants were collected for measurement of IL-10 by ELISA. Human adherent
monocytes were cultured in RPMI with 10% FCS (Omega Scientific) in the presence or
absence of IFN-β (200U/ml) for 24h and supernatants were collected for IL-10 detection
by ELISA. In a separate set of experiments, monocytes were stimulated with IFN-β
(200U/ml), IFN-γ (273U/ml) or IL-10 (10ng/ml). After stimulation the cells were
cultured for 3h or 24h. In addition, neutralizing anti-human IL-10 (10μg/ml; BD
7
Pharmingen) or isotype control was used in combination with IFN-γ and IFN-β for 24h
and total RNA was isolated to measure antimicrobial pathway gene expression levels.
Real-time quantitative PCR (qPCR)
Total RNA was isolated from 10 L-lep, 10 T-lep and 10 RR skin lesions, and
cDNA was prepared as described previously (37). TaqMan gene expression assays were
used for detection of IFN-β, IFN-γ, IFNAR1, IL-10, OAS1, OAS2 and GAPDH
(glyceraldehyde-3-phosphate dehydrogenase; Applied Biosystems, Foster City, CA).
The relative quantities of the gene tested per sample were calculated against the GAPDH
mRNA using the CT formula as previously described (11).
To analyze cytokine and antimicrobial peptide mRNA levels of human
monocytes, total RNA was isolated, cDNA synthesized and qPCR performed to measure
IFN-β, cathelicidin (CAMP), CYP27B1, DEFB4, VDR and h36B4 as previously reported
(15). The relative quantities of the gene tested per sample were calculated against h36B4
using the delta cycle threshold formula as previously described (38). The data were
normalized to the media control samples.
Antimicrobial assays
To measure IFN-induced antimicrobial activity in M. leprae-infected monocytes,
we adapted the previously described real time PCR based method for the assessment of
bacterial viability, which compares 16S RNA levels to genomic DNA levels (15, 21).
Given that M. leprae itself induced IFN-β, monocytes were pre-treated with IFN-γ, and
then infected with M. leprae at an MOI of 10:1 overnight. This resulted in the infection
8
of approximately 80% of the monocytes at 2.1 ± 0.4 bacteria per cell. Subsequently, the
monocytes were treated with various cytokines and M. leprae viability was measured
after five days. Monocytes were isolated as described above, pre-treated with IFN-γ
(273U/ml) for 24 h and infected overnight with M. leprae at an MOI of 10:1 followed by
stimulation with IFN-β (200U/ml), IFN-γ (273U/mL), IL-10 (10ng/ml), VDR antagonist
ZK 159 222 (VAZ) (10−8
M) or medium for three days. We have used VAZ previously
to establish the role of the VDR in the host antimicrobial response (1, 11, 16). Monocyte
viability was measured before infection and five days after infection by Trypan blue
exclusion and was always ≥90%. In addition, neutralizing anti-human IL-10 antibody
was added before M. leprae infection and in combination with IFN-γ and IFN-β post-
treatment. Total RNA and DNA was isolated as previously described (15). cDNA was
synthesized from the total RNA as described (11) for both human and bacterial mRNAs.
The bacterial 16S rRNA and genomic element DNA (RLEP) levels were then assessed
using real time PCR. In order to normalize for the total number of monocytes present in
the culture, 36B4 was also evaluated. Comparison of the bacterial DNA to the
mammalian 36B4 levels was used to monitor infectivity between all the conditions in the
assay as well as PCR quality. The 16S rRNA and genomic DNA values were calculated
using the CT analysis, with the bacterial DNA value serving as the housekeeping
gene. The M. leprae 16S rRNA and M. leprae repetitive genomic element (RLEP)
primers used were as previously described (15, 21).
ELISA
9
Secreted IFN-β and IL-10 proteins in the supernatant were measured using
VeriKineTM
Human Interferon-Beta ELISA Kit (PBL Interferon Source), and IL-10
antibody pair (Invitrogen) following manufacturer protocols.
Measurement of vitamin D metabolism
Human monocytes were treated with IFN-γ (500U/ml), IL-10 (10ng/ml) and IFN-
γ+ IL-10 in 10% FCS for 48h, followed by incubation with a radiolabeled metabolite of
cholecalciferol (D3), 25 (OH)D3 for 5h in serum-free media. The measurement of
25(OH)D3 bioconversion to 1,25(OH)2D3 or 24,25(OH)2D3 was performed by HPLC as
previously described (17).
Statistical analysis
Results are reported as pooled data from an entire series of experiments, and
described as mean ± the SEM unless otherwise indicated. GraphPad Prism 5 software
was used for testing of parametric distribution and statistical analysis. We applied the log
transformation (log(x+1)) and performed Kolmogov Smirnov normality test and equality
of variances test (Bartlett's test) on the transformed values to verify whether the data were
parametrically distributed. For comparison between three different groups found to have
a parametric distribution, statistical analysis was performed by one-way analysis of
variance ANOVA followed by the Newman-Keuls multiple comparison post test. For
comparison between three different groups found to have a nonparametric distribution,
statistical analysis was performed by Kruskal-Wallis analysis of variance by ranks test
followed by Dunn's multiple comparison test. The two-tailed student’s t-test was used
10
when individual comparisons between two groups were performed. Individual details of
statistical analyses are explained in the figure legends.
11
Fig. S1.
Leprosy test set23 leprosy skin biopsies10 T-lep, 6 L-lep and 7 RR
GSE17763
L-lep vs. T-lep vs. RRdifferential gene expression
(p < 0.05, fold > 1.5)
PCA and clustering analysisFigure 1A and 1B
IFN-induced gene expression profiles in PBMCWaddell et al., 2010
GSE17762
Determined genes that were specifically modulated by IFN- , IFN-b and IFN-g
and examined their expression in
leprosy lesionsFigures 1C and 1D
TB patients whole blood gene expression profiles
TB 1: active vs. latent (Berry et al., 2010)
GSE19491
TB 2: active vs. normal (Maertzdorf et al. 2012)
GSE 34608
Determined genes that were specifically modulated by IFN- , IFN-b
and IFN-g and examined their expression in TB patients blood
Figure 1E
Published TB gene expression datasets
Identification of IFN-b specific genes in blood in common between L-lep, and active tuberculosis (TB1 and TB2) profiles
Integrative genomics
CD14+ monocytesIL-10 gene expression profile
IL-10 vs. media
GSE 43700
Determined which of the IFN-b specific genes expressed in common between L-lep, active
TB1, and TB2, were also induced by IL-10
Figure 1F
Integrative genomics
Validation leprosy lesions
qPCR10 T-lep, 10 L-lep and 10 RR
Figure 2A and 3A
Immunohistochemistry4 T-lep, 4 L-lep and 4 RR
Figure 2B, 2C, 3B, 3C and 3D
Integrative genomics
Supplemental Figure 1. Flow diagram for analysis of gene expression profiles.
12
Fig. S2
0
10
20
30
40
IFN-
induced genes in PBMC repressed genes in PBMC
# g
en
es
ex
pre
ss
ed
in
le
sio
ns
# g
en
es r
ep
ressed
in
lesio
ns
Sig
ne
d lo
g1
0 e
nri
ch
me
nt
p-v
alu
e
IFN-b IFN-g IFN- IFN-b IFN-g
IFN-
induced genes in PBMC repressed genes in PBMC
IFN-b IFN-g IFN- IFN-b IFN-g
L-lep
T-lep
L-lep
T-lep
L-lep
T-lep
L-lep
T-lep
0
10
20
30
40
Sig
ned
lo
g10 e
nri
ch
men
t
p-v
alu
e
Supplemental Figure 2. Type I and Type II IFN specific genes had
a differential distribution in leprosy skin lesions. IFN-, IFN-b and
IFN-g -specif ic genes (induced or repressed) identif ied in healthy
human PBMC were integrated with leprosy lesion transcripts (6 L-lep
and 10 T-lep; fold change ≥ 1.5 and p ≤ 0.05). Dotted lines indicate
hypergeometric enrichment p-value of 0.05 (log p=1.3). Bonferroni
multiple hypothesis test correction was applied for each group.
-2
-1
0
1
2
3
4
5
6
I FNa I FNb I FNg
0
1
2
3
4
5
6
I FNa I FNb I FNg
13
Fig. S3
IFN-b (only) IFN- (only)
IFN-g (only)
L-lep33
13 76
100
00
0
3
1 1 1
3
7 10
00
0
T-lep
RR
Inducible genes
IFN-b (only) IFN- (only)
IFN-g (only)
L-lep24
6 34
000
00
0
0
0 0 0
5
9 52
00
0
T-lep
RR
Repressed genes
Supplemental Figure 3. Venn Diagram of IFN-, IFN-b and
IFN-g specific genes in leprosy lesions. IFN-, IFN-b and IFN-g
specif ic genes induced or repressed in L-lep, T-lep and RR
lesions (6 L-lep, 10 T-lep and 7 RR; FC≥ 1.5, p≤ 0.05).
14
Fig. S4.
>4 4-2.5 >4 4-2.5
L-lep/T-lep T-lep/L-lep
*
0
2
4
6
*
Interferome data baseF
old
en
ric
hm
en
t in
le
sio
n
(ob
serv
ed
/exp
ecte
d)
FC:
IFN type I
IFN type I/II
L-lep T-lep
IFN type I
IFN type I/II
L-lep T-lep
>4 4-2.5 >4 4-2.5
L-lep/T-lep T-lep/L-lep
Supplemental Figure 4. Type I regulated genes upregulated in
L-lep lesions. Type I and Type II regulated genes were classif ied in
the leprosy lesion transcripts using Interferome database (6 L-lep
and 10 T-lep; fold change ≥ 2.5 and p ≤ 0.05). Dotted lines indicate
either the expected fold enrichment of one (upper panel), or the
hypergeometric enrichment p-value of 0.05 (log p=1.3, lower panel).
Bonferroni multiple hypothesis test correction was applied for each
group.
-8
-6
-4
-2
0
2
4
6
8
>4 >2. 5 >4 >2. 5
L- l ep T- l ep
Fo
ld e
nri
ch
me
nt/
de
-en
ric
hm
en
t(l
og
p-v
alu
e)
15
Fig. S5.
IFN-g
IFN-b
MS4A7IFNGR1GLIPR1ALOX5IGHG1CYBAGPR35IGF2BP3SERPINB6KRR1MAN1A2
Expression in leprosy lesions
Repressed by IFN in control PBMC
IFN-b
T-lep L-lep RR
Expression in leprosy lesions
Induced by IFN in control PBMC
MS4A7CCRL2LILRB1CD163MARCKSITGAXCCR1MXL1CENTA2GNPDA1LYNC3AR1NEK4RRBP1SNX2CD59ALOX5B3GNT2NBNTANKRIPK3ANXA4PFKFB3SDSFPRL1CCL4, TLR1CEP110TARP
T-lep L-lep RR
NLRP1GSTM5UBDMMP25VSNL1LTMK2GBP1GBP2GBP6CYP24A1CYP27B1VDRCCL21CXCL2CXCL11
Regulatory cytokines
Antimicrobial
chemokines
IFN-g GBP family
Vit D genes
PRR receptors
Type I IFN
signature genes
B cell genes
OAS1OAS2MX2IFNAR1TLR4TLR7IL-10IL-27CD80CD83CD86TGFBR1BCL2L1XIAPBLNKBAFFVAV1
Costimulatory
molecules
IFN-b
Supplemental Figure 5. IFN-b and IFN-g specific genes distribution in leprosy lesions. IFN-b and IFN-g
induced and repressed specif ic genes distribution in 6 L-lep, 10 T-lep and 7 RR lesions (FC≥ 1.5, p≤ 0.05).
Genes listed in black are common between T-lep and RR lesions. IFN-b induced genes upregulated in L-lep
include Type I interferon genes, PRR receptors, regulatory cytokines and B cells genes. IFN-g induced genes
upregulated in T-lep and RR include GBP family, vitamin D (Vit D) genes and antimicrobial chemokines.
16
Fig. S6
0
5
10
15
20
25
30
I FNa onl y I FNb onl y I FNg onl y
TB ACT
TB LTN
repressed genes in PBMC# g
en
es r
ep
ressed
in
lesio
ns
IFN- IFN-b IFN-gIFN-
induced genes in PBMC
# g
en
es
ex
pre
ss
ed
in
le
sio
ns
IFN-b IFN-g0
5
10
15
20
25
30
I FNa onl y I FNb onl y I FNg onl y
TB ACT
TB LTN
Supplemental Figure 6. Type I and Type II IFN specific genes
distribution in the blood of active and latent tuberculosis. IFN-,
IFN-b and IFN-g -specif ic genes (inducible or repressed) identif ied in
healthy human PBMC were integrated with tuberculosis whole blood
transcripts (fold change ≥ 1.5 and p ≤ 0.05). Dotted lines indicate
hypergeometric enrichment p-value of 0.05 (log p=1.3). Bonferroni
multiple hypothesis test correction was applied for each group.
Sig
ned
lo
g10 e
nri
ch
men
t p
-valu
e
IFN-
induced genes in PBMC
IFN-b IFN-g-2
0
2
4
6
8
10
12
I FNa I FNb I FNg
TB ACT
TB LTN
repressed genes in PBMC
IFN- IFN-b IFN-gSig
ned
lo
g10 e
nri
ch
men
t p
-valu
e
-2
0
2
4
6
8
10
12
I FNa I FNb I FNg
TB ACT
TB LTN
17
Fig. S7
IFN- IFN-b IFN-g
Fo
ld e
nri
ch
me
nt
(ob
se
rve
d/e
xp
ec
ted
)
IFN- IFN-b IFN-gSig
ne
dlo
g1
0 e
nri
ch
me
nt p
-valu
e
0
0.5
1
1.5
2
2.5
3
I FNa I FNb I FNg
TB LTN
TB ACT
-2
0
2
4
6
8
10
12
I FNa I FNb I FNg
TB LTN
TB ACT
Induced IFN-b specific genes
L-lep TB1
20
20
TB2
14 16
14
16
3
Total induced genes
L-lep TB1
790
3205
TB2
888 720
254
470
977
ELF1
IL-27
MS4A7
NBN
OAS2
SSB
USP15
CCR1
CD59
CD163
FPR2
PFKFB3
TANK
TLR1
TLR4
TLR7
IL-1
0 p
rofi
le
(A) (B)
Supplemental Figure 7. Common Type I IFN signature in the blood of active TB patients and L-lep
lesions. (A) Enrichment analysis of overlap between IFN-specif ic genes and tuberculosis whole blood
transcripts associated with disease state (active (ACT), latent (LTN); fold change ≥ 1.5 and p ≤ 0.05).
Dotted lines indicate either the expected fold enrichment of one (upper panel), or the hypergeometric
enrichment p-value of 0.05 (log p=1.3, lower panel). Bonferroni Multiple HypothesisTest correction was
applied for each group. (B) Venn diagrams show the total number of signif icantly (p < 0.05) induced genes
and IFN-b-specif ic induced genes between L-lep, TB1 (UK cohort) and TB2 (Germany cohort) datasets.
Hypergeometric distribution-based enrichment analysis was performed to determine signif icance of IFN-b
genes induced in all three datasets; p < 0.007. Common genes between the three datasets were
compared with genes induced by IL-10 in a human monocyte dataset. Genes in red are also induced by
IL-10, and this overlap with IL-10 is greater than expected (9 of 16 common IFN-b- specif ic induced genes,
compared to 138 of 470 total common induced genes, hypergeometric p-value = 0.02).
18
Fig. S8
Supplemental Figure 8: Controls for immunoperoxidase detection.
Isotype control for IFN-b and IL-10 (IgG2a), isotype control for IFNAR1 (IgG1),
and the macrophage marker CD68 as a positive control. Data are
representative of four biopsy specimens for each group.
IgG2a
IgG1
CD68
T-lep L-lep RR
19
Fig. S9
CD14
IFN-b
Merge
CD209
Merg
e
IFN-b
Merge Merge
IFN-b
IFN-b
CD163
CD3
Supplemental figure 9. IFN-b colocalize with macrophage markers in L-lep
lesions. Co-expression of IFN-b (green) with M markers (CD14, CD163 and
CD209; red) and T cell marker (CD3; red), cellular nuclei were visualized using
DAPI. Data are representative of four individual L-lep biopsy specimens.
20
Fig. S10
Supplemental Figure 10. Isotype controls for IFN-b and cell markers
in L-lep lesions. Co-expression of isotype control for IFN-b (IgG2a, green)
with isotype control for CD14,CD3 and CD163 (IgG1, red) or isotype control
for CD209 (IgG2b, red). Cellular nuclei were visualized using DAPI. Data
are representative of four L-lep biopsy specimens.
IgG1
IgG2a
Merge
IgG2b
IgG2a
Merge
21
Fig. S11
CD163
IFN-b
Merge
IFN-b
CD209
Merge
Supplemental Figure 11. IFN-b and cell markers colocalization in T-lep lesions. CD3+, CD163+ and
CD209+ cells were detected, but few IFN-b+ cells. Co-expression of IFN-b (green) with T cells marker (CD3, red)
and M markers (CD163 and CD209, red). Cellular nuclei were visualized using DAPI. Data are representative
of four T-lep biopsy specimens.
Merge
CD3
IFN-b
22
Fig. S12
Supplemental Figure 12. mRNA levels of Type I IFN genes
are higher in L-lep vs. T-lep. Total mRNA was isolated f rom
10 L-lep, 10 T-lep and 10 RR skin lesions, and OAS1 and
OAS2 mRNA levels were analyzed by TaqMan qPCR. The
mRNA levels were normalized to GAPDH levels. Statistical
signif icance was calculated using one–way ANOVA followed
by Newman-Keuls multiple comparison Test for OAS1 and
Kruskal-Wallis followed by Dunn's multiple comparison test for
OAS2. ** p≤ 0.01; * p≤ 0.05.
OAS1 mRNA
T-lep L-lep RR
0
20
40
60
Rela
tive Q
uan
tifi
cati
on
** *
OAS2 mRNA
T-lep L-lep RR0
50
100
150
200
250
Rela
tive Q
uan
tifi
cati
on
** *
23
Fig. S13
CD163
IL-10
Merge
CD209
IL-10
Merge
FCD3
Merge
IL-10
Supplemental figure 13. IL-10 colocalize with macrophage markers in L-lep lesions. Co-expression
of IL-10 (green) with M markers (CD14, CD163 and CD209; red) and the T cell marker (CD3; red).
Cellular nuclei were visualized using DAPI. Data are representative of four individual L-lep biopsy
specimens.
24
Fig. S14
IgG1
IgG2a
IgG2b
IgG2a
Supplemental Figure 14. Isotype controls for IL-10 and cell markers in
L-lep lesions. Co-expression of isotype control for IL-10 (IgG2a, green)
with isotype control for CD3 and CD163 (IgG1, red) or isotype control for
CD209 (IgG2b, red). Cellular nuclei were visualized using DAPI. Data are
representative of four L-lep biopsy specimens.
MergeMerge
25
Fig. S15
Supplemental Figure 15. Isotype controls
for IL-10 and IFN-b in L-lep lesions. Co-
expression of isotype control for IL-10 (IgG2a,
red) with isotype control for IFN-b (IgG1,
green). Cellular nuclei were visualized using
DAPI. Data are representative of four L-lep
biopsy specimens.
IgG1
IgG2a
Merge
26
Fig. S16
Supplemental Figure 16. IFN-b
induces IL-10 in human monocytes.
Cells were stimulated with IFN-b
(200U/ml) for 24h and IL-10 protein
levels were detected by ELISA. Data
are represented as mean SEM, n=6.
Statistical signif icance was calculated
by two-tailed Student’s t-test. ** p≤ 0.01.
0
20
40
60
80
100
120
media IFN-b
IL-10 (pg/ml)**
27
Fig. S17
IL-10 (pg/ml)
IFNAR2 IgG2a_
IFNAR2IgG2a_
mLEP live IFN-b
0
20
40
60
80
100
120
140
mLEP 10: 1 mLEP 10: 1+aI FNAR2 mLEP 10: 1+IgG2a I FNB I FNB+aI FNAR2 I FNB+I gG 2a
Donor 1 Donor 2
Supplemental Figure 17. Blocking of IFNAR2 decreased the ability of live
M. leprae to induce IL-10. Human monocytes were stimulated with live mLEP
(MOI 10:1) alone or in combination with anti-human IFNAR2 antibody or isotype
control for 24h. IL-10 protein levels were detected by ELISA. Graphs show
results f rom two dif ferent donors.
0
20
40
60
80
100
120
140
mLEP 10: 1 mLEP 10: 1+aI FNAR2 mLEP 10: 1+IgG2a I FNB I FNB+aI FNAR2 I FNB+I gG 2a
IL-10 (pg/ml)
IFNAR2 IgG2a_
IFNAR2 IgG2a_
mLEP live IFN-b
28
Fig. S18
0
500
1000
1500
2000
0 5000 10000 15000
R = -0.43
0
500
1000
1500
2000
0 4000 8000 12000
R = -0.64
IL-1
0(A
U)
IL-1
0(A
U)
L-lep
T-lep
RR
CYP27B1 (AU) VDR (AU)
Supplemental Figure 18. Vitamin D associated gene
mRNA levels inversely correlate with IL-10 mRNA levels.
Correlation of CYP27B1 or VDR and IL-10 detected by
microarray (arbitrary units) for individual samples in three
leprosy groups (L-lep, n=6; T-lep, n=10 and RR, n=7)
29
Fig. S19
CYP27B1 mRNA (FC)
IFN-g
+IFN-b
IFN-g
+IL-10 IFN-g + IFN-b
0
0.5
1
1.5
2
2.5
3
M edi a I FNG G +I FNB G +I L- 10 aI L- 10+G +I FNB I gG 1+G +IFNB
media IFN-g IgG1 IL-10
* *
*
*
VDR mRNA (FC)*
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
M edi a I FNG G +I FNB G +I L- 10 aI L- 10+G +I FNB I gG 1+G +IFNB
media IFN-g IFN-g
+IFN-b
IFN-g
+IL-10
IgG1 IL-10
IFN-g + IFN-b
* **
Supplemental Figure 19 . IFN-b and IL-10 antagonize the ability of IFN-g to induce
vitamin D genes. Human monocytes were stimulated with IFN-g alone or in
combination with IFN-b or IL-10, anti-human IL-10 antibody was added in the monocyte
culture in combination with IFN-g and IFN-b for 24h. RNA was isolated and the CYP27B1
and VDR mRNA levels were detected by qPCR. Data are represented as mean SEM,
n=7. Statistical signif icance between two groups was calculated by two -tailed Student’s
t-test. * p≤ 0.05.
30
Fig. S20
0.0
0.5
1.0
1.5
2.0
media IL-10 IFN-g IFN-g+ IL-10
25D3→24,25D3 (fmol / 106 cells / hr)
**
*
Supplemental Figure 20. IFN-g reduces the inactive
form of Vitamin D3. Human monocytes were treated
with IL-10, IFN-g and IFN-g + IL-10 for 48h followed by
incubation with radiolabeled metabolite cholecalciferol
(D3), 25(OH)D3 for 5 h in serum-free media. The
ability to convert 25(OH)D3 to 24,25(OH)2D3 was
measured by HLPC. Enzymatic conversion data are
represented as mean SEM and shows three separate
donors, each studied in triplicate. Statistical
signif icance was calculated by one-way ANOVA
repeated measures test and comparison between two
groups was conf irmed by the post test, Newman-Keuls
Multiple Comparison Test. * p≤ 0.05.
31
Fig. S21
IL-10IFN-bmedia
M.leprae viability (AU)
Supplemental Figure 21. IFN-b and IL-10
do not affect M. leprae viability. Human
monocytes were infected overnight with live
mLEP (MOI 10:1), followed by treatment
with IFN-b (200U/ml) or IL-10 (10ng/ml) for
4 days. Viability of mLEP was calculated by
the ratio of bacterial 16S RNA and DNA
(RLEP) by qPCR. Data are represented as
mean SEM, n=7.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
32
Fig. S22
CYP27b1
25D
1,25D
Cath. DEFB4
Antimicrobial
activity
VDR
IFN-g
CYP27b1
25D
1,25D
Cath. DEFB4
Pathogenesis
VDR
IFN-g IFN-b
IL-10
Supplemental Figure 22 :IFN-b suppresses IFN-g induced
antimicrobial activity. A summary diagram indicating i) the
IFN-g-inducible antimicrobial pathway (blue), ii) the IFN-b
inducible pathway (red), and iii) parts of the IFN-g-inducible
antimicrobial pathway that are blocked by IFN-b (grey).
References and Notes
1. M. Fabri et al., Vitamin D is required for IFN-gamma-mediated antimicrobial activity
of human macrophages. Sci. Transl. Med. 3, 104ra102 (2011).
doi:10.1126/scitranslmed.3003045 Medline
2. R. M. O’Connell et al., Type I interferon production enhances susceptibility to Listeria
monocytogenes infection. J. Exp. Med. 200, 437 (2004).
doi:10.1084/jem.20040712 Medline
3. M. P. Berry et al., An interferon-inducible neutrophil-driven blood transcriptional
signature in human tuberculosis. Nature 466, 973 (2010).
doi:10.1038/nature09247 Medline
4. M. Yamamura et al., Defining protective responses to pathogens: cytokine profiles in
leprosy lesions. Science 254, 277 (1991). doi:10.1126/science.1925582 Medline
5. M. Yamamura et al., Cytokine patterns of immunologically mediated tissue damage. J.
Immunol. 149, 1470 (1992). Medline
6. S. J. Waddell et al., Dissecting interferon-induced transcriptional programs in human
peripheral blood cells. PLoS ONE 5, e9753 (2010).
doi:10.1371/journal.pone.0009753 Medline
7. S. A. Samarajiwa, S. Forster, K. Auchettl, P. J. Hertzog, INTERFEROME: the
database of interferon regulated genes. Nucleic Acids Res. 37, (Database issue),
D852 (2009). doi:10.1093/nar/gkn732 Medline
8. T. R. Golub et al., Molecular classification of cancer: class discovery and class
prediction by gene expression monitoring. Science 286, 531 (1999).
doi:10.1126/science.286.5439.531 Medline
9. S. S. Iyer, A. A. Ghaffari, G. Cheng, Lipopolysaccharide-mediated IL-10
transcriptional regulation requires sequential induction of type I IFNs and IL-27
in macrophages. J. Immunol. 185, 6599 (2010). doi:10.4049/jimmunol.1002041
Medline
10. M. Rayamajhi, J. Humann, K. Penheiter, K. Andreasen, L. L. Lenz, Induction of IFN-
αβ enables Listeria monocytogenes to suppress macrophage activation by IFN-γ.
J. Exp. Med. 207, 327 (2010). doi:10.1084/jem.20091746 Medline
11. P. T. Liu et al., Toll-like receptor triggering of a vitamin D-mediated human
antimicrobial response. Science 311, 1770 (2006). doi:10.1126/science.1123933
Medline
12. J. Maertzdorf et al.; TBornotTB Network, Common patterns and disease-related
signatures in tuberculosis and sarcoidosis. Proc. Natl. Acad. Sci. U.S.A. 109, 7853
(2012). doi:10.1073/pnas.1121072109 Medline
13. C. L. Cooper et al., Analysis of naturally occurring delayed-type hypersensitivity
reactions in leprosy by in situ hybridization. J. Exp. Med. 169, 1565 (1989).
doi:10.1084/jem.169.5.1565 Medline
14. D. Montoya et al., Divergence of macrophage phagocytic and antimicrobial programs
in leprosy. Cell Host Microbe 6, 343 (2009). doi:10.1016/j.chom.2009.09.002
Medline
15. P. T. Liu et al., MicroRNA-21 targets the vitamin D-dependent antimicrobial
pathway in leprosy. Nat. Med. 18, 267 (2012). doi:10.1038/nm.2584 Medline
16. P. T. Liu et al., Convergence of IL-1beta and VDR activation pathways in human
TLR2/1-induced antimicrobial responses. PLoS ONE 4, e5810 (2009).
doi:10.1371/journal.pone.0005810 Medline
17. S. R. Krutzik et al., IL-15 links TLR2/1-induced macrophage differentiation to the
vitamin D-dependent antimicrobial pathway. J. Immunol. 181, 7115 (2008).
Medline
18. J. S. Adams, M. A. Gacad, Characterization of 1 alpha-hydroxylation of vitamin D3
sterols by cultured alveolar macrophages from patients with sarcoidosis. J. Exp.
Med. 161, 755 (1985). doi:10.1084/jem.161.4.755 Medline
19. K. Edfeldt et al., T-cell cytokines differentially control human monocyte
antimicrobial responses by regulating vitamin D metabolism. Proc. Natl. Acad.
Sci. U.S.A. 107, 22593 (2010). doi:10.1073/pnas.1011624108 Medline
20. P. Salgame et al., Differing lymphokine profiles of functional subsets of human CD4
and CD8 T cell clones. Science 254, 279 (1991). doi:10.1126/science.1681588
Medline
21. A. N. Martinez et al., Molecular determination of Mycobacterium leprae viability by
use of real-time PCR. J. Clin. Microbiol. 47, 2124 (2009).
doi:10.1128/JCM.00512-09 Medline
22. G. Guarda et al., Type I interferon inhibits interleukin-1 production and
inflammasome activation. Immunity 34, 213 (2011).
doi:10.1016/j.immuni.2011.02.006 Medline
23. A. Novikov et al., Mycobacterium tuberculosis triggers host type I IFN signaling to
regulate IL-1β production in human macrophages. J. Immunol. 187, 2540 (2011).
doi:10.4049/jimmunol.1100926 Medline
24. K. D. Mayer-Barber et al., Caspase-1 independent IL-1beta production is critical for
host resistance to mycobacterium tuberculosis and does not require TLR signaling
in vivo. J. Immunol. 184, 3326 (2010). doi:10.4049/jimmunol.0904189 Medline
25. S. Roy et al., Association of vitamin D receptor genotype with leprosy type. J. Infect.
Dis. 179, 187 (1999). doi:10.1086/314536 Medline
26. G. Herrera, Vitamin D in massive doses as an adjuvant to the sulfones in the
treatment of tuberculoid leprosy. Int. J. Lepr. 17, 35 (1949). Medline
27. P. F. Barnes et al., Cytokine production at the site of disease in human tuberculosis.
Infect. Immun. 61, 3482 (1993). Medline
28. C. E. Barry, 3rd et al., The spectrum of latent tuberculosis: rethinking the biology and
intervention strategies. Nat. Rev. Microbiol. 7, 845 (2009). Medline
29. N. R. Gandhi et al., Extensively drug-resistant tuberculosis as a cause of death in
patients co-infected with tuberculosis and HIV in a rural area of South Africa.
Lancet 368, 1575 (2006). doi:10.1016/S0140-6736(06)69573-1 Medline
30. D. S. Ridley, W. H. Jopling, Int. J. Lepr. 34, 255 (1966).
31. J. R. Bleharski et al., Use of genetic profiling in leprosy to discriminate clinical forms
of the disease. Science 301, 1527 (2003). doi:10.1126/science.1087785 Medline
32. M. B. Eisen, P. T. Spellman, P. O. Brown, D. Botstein, Cluster analysis and display
of genome-wide expression patterns. Proc. Natl. Acad. Sci. U.S.A. 95, 14863
(1998). doi:10.1073/pnas.95.25.14863 Medline
33. S. B. Plaisier, R. Taschereau, J. A. Wong, T. G. Graeber, Rank-rank hypergeometric
overlap: identification of statistically significant overlap between gene-expression
signatures. Nucleic Acids Res. 38, e169 (2010). doi:10.1093/nar/gkq636 Medline
34. W. Huang, B. T. Sherman, R. A. Lempicki, Bioinformatics enrichment tools: paths
toward the comprehensive functional analysis of large gene lists. Nucleic Acids
Res. 37, 1 (2009). doi:10.1093/nar/gkn923 Medline
35. M. T. Ochoa, A. Loncaric, S. R. Krutzik, T. C. Becker, R. L. Modlin, “Dermal
dendritic cells” comprise two distinct populations: CD1+ dendritic cells and
CD209+ macrophages. J. Invest. Dermatol. 128, 2225 (2008).
doi:10.1038/jid.2008.56 Medline
36. R. Lahiri, B. Randhawa, J. Krahenbuhl, Application of a viability-staining method for
Mycobacterium leprae derived from the athymic (nu/nu) mouse foot pad. J. Med.
Microbiol. 54, 235 (2005). doi:10.1099/jmm.0.45700-0 Medline
37. D. J. Lee et al., Integrated pathways for neutrophil recruitment and inflammation in
leprosy. J. Infect. Dis. 201, 558 (2010). doi:10.1086/650318 Medline
38. L. Monney et al., Th1-specific cell surface protein Tim-3 regulates macrophage
activation and severity of an autoimmune disease. Nature 415, 536 (2002).
doi:10.1038/415536a Medline