Astroglial Plasticity within the Rat Orofacial Primary Motor Cortex … · 2019-11-15 · ii Astroglial Plasticity within the Rat Orofacial Primary Motor Cortex Induced by Endodontic

Astroglial Plasticity within the Rat Orofacial Primary Motor Cortex Induced by Endodontic Treatment versus Tooth

Extraction

by

Jacqueline Lopez Gross

A thesis submitted in conformity with the requirements

for the degree of Master of Science in Endodontics

Faculty of Dentistry

University of Toronto

© Copyright by Jacqueline Lopez Gross 2018

ii

Astroglial Plasticity within the Rat Orofacial Primary Motor Cortex

Induced by Endodontic Treatment versus Tooth Extraction

Jacqueline Lopez Gross

Master of Science in Endodontics

Faculty of Dentistry

University of Toronto

2018

Abstract

Objective: To optimise the CLARITY technique that renders brain tissue optically transparent,

immunolabelling and light-sheet microscopy for 3D-characterisation of astroglial

cytoarchitecture and morphology within the orofacial primary motor cortex of rats

receiving endodontic versus tooth extraction treatment.

Methods: Rats received either extraction, endodontic-, sham- or no-treatment of the right

maxillary molar teeth. After one week, 2 mm-thick brain sections of the orofacial primary motor

cortex were cleared and immunolabelled with astroglial markers. 3D-images were acquired with

light-sheet microscope and Imaris software was used to characterise and quantify cytoarchitecture

and morphological features of astroglial processes.

Results: As compared with endodontic-, sham- and no-treatment, tooth extraction produced

significantly thinner and straighter astroglial processes within layer-I of a laminar motor cortex.

Conclusion/significance: Tooth extraction but not endodontic treatment induces astroglial

plasticity within the rat primary motor cortex that controls orofacial motor functions. Astroglia

may be a therapeutic target for preventing/curing postoperative motor impairments.

iii

Acknowledgments

First, I would like to express my gratitude to Dr. Limor Avivi-Arber, who captivated me with her

passion for neuroscience and guided me with her expertise to accomplish every step of this

assignment. Thank you for challenging me with a very demanding project that felt like learning a

new language and required all my brain cells to work in coherence beyond expectations. Thank

you for exposing me to novel cutting-edge experiments and techniques that blew out my brain

with excitation and satisfaction. I am extremely grateful and honoured by your commitment and

patience. I could not ask for a better supervisor and role model.

I would like to thank Dr. Bettina Basrani, my Program Director, for her support and

encouragement throughout my studies. Thanks are due to the valuable inputs from Dr. Pavel

Cherkas that helped me better understand this project; I appreciate his kind editorial efforts and

wise advice as an endodontist and neuroscientist. I would also like to thank my thesis examiners

Dr. Boris Kablar and Ze’ev Seltzer whose comments have further improves the clarity of my

thesis.

The burden of the highly demanding experiments, imaging and data analysis was lessened

substantially by the support and friendship of Dr. Maryam Zanjir, Idan Yona, Ho Jung Hwang

(Amelia), Imran Alidina and Caitlin Sherry. Thank you, guys.

I am also grateful to Kristin Overton and Ailey Crow from Dr. Carl Deisseroth’s Lab at Stanford

University, California, USA; Kim Lau and Paul Paroutis from the Imaging Facility at SickKids

Hospital, Toronto, Canada; Irene Constantini from the European Laboratory for Non-linear

Spectroscopy at the University of Florence, Italy; Yosuke Niibori from Dr. Paul Frankland’s Lab,

Faculty of Pharmacy, University of Toronto; Sayed Abdullah from the Integrated Nanotechnology

and Biomedical Sciences Laboratory, University of Toronto, and to Nikolaos Ziogas from Dr.

Vassilis Koliatsos’s Laboratory, John Hopkins Medicine. Their availability and valuable

information helped us optimise the CLARITY technique and 3D imaging with the light-sheet

microscope. I would also like to thanks Bitplane Imaris support team, Daniel Miranda and

Mathew Gastinger for the hours of on-line support.

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Lastly, but most importantly, I would like to express my gratitude to my parents and my parents

in-law, my sisters and sisters in-law, my brothers and brothers in-law, and in particular my very

dear daughter, Ana, and husband, Alejandro, whose love and support have helped me accomplish

this thesis. I dedicate this thesis to my family.

This work was funded by the Faculty of Dentistry Bertha Rosenstadt Fund, Foundation for

Endodontics, Alpha Omega Foundation of Canada, Canadian Academy of Endodontics, Shimon

Friedman and Calvin Torneck Endowment Fund, and the International College of Prosthodontists.

This project also received the AAE/Dentsply Sirona Resident Award for the best Oral Research

Presentation at the 2018 American Association of Endodontics Annual Meeting, and the

International College of Prosthodontists Research Travel Award to present this work at the 2019

annual meeting in Amsterdam, The Netherlands.

v

Table of Contents Acknowledgments ................................................................................................................... iii

Table of Contents ..................................................................................................................... v

List of Tables ......................................................................................................................... viii

List of Figures ......................................................................................................................... ix

List of Abbreviations ............................................................................................................. xiv

Chapter 1 .................................................................................................................................. 1

Introduction ......................................................................................................................... 1

1.1 Overview .................................................................................................................... 1

1.2 Main Somatosensory and Motor Innervation of Orofacial Tissues ........................... 3

1.2.1 Sensory Receptors ............................................................................................ 3

1.2.2 Major Somatosensory Afferent Pathways ........................................................ 4

1.2.3 The Orofacial Primary Motor Cortex: Neuronal Cytoarchitecture, Connectivity and Major Motor Efferent Pathways .......................................... 7

1.2.4 Clinical Implications ...................................................................................... 10

1.2.4.1 Consequences of Endodontic Treatment and Tooth Extraction ...... 10

1.3 Motor Cortex Neuroplasticity Induced by Altered Sensory Inputs and Motor Function ................................................................................................................... 11

1.3.1 Clinical Significance of Motor Cortex Neuroplasticity ................................. 12

1.4 Glial Cells ................................................................................................................ 14

1.4.1 Astroglial Cells: Cytoarchitecture and Morphology ...................................... 15

1.4.2 Astroglial cells: Role in Regulating Neuronal Function ................................ 16

1.4.3 Astroglial Plasticity ........................................................................................ 18

1.5 The CLARITY Technique ....................................................................................... 18

1.6 Light-Sheet Fluorescence Microscopy ..................................................................... 20

1.7 Statement of the Problem, Hypothesis and Objectives ............................................ 21

1.8 General Aim ............................................................................................................. 22

vi

1.9 Hypothesis ................................................................................................................ 22

1.10 Specific Aims ........................................................................................................... 23

Materials and Methods ...................................................................................................... 24

2.1 Animals .................................................................................................................... 24

2.2 Study Groups and General Study Design ................................................................. 25

2.3 Animal Experiments ................................................................................................. 26

2.3.1 Anaesthesia and Aseptic Procedures .............................................................. 26

2.3.2 Tooth Extraction, Pulpectomy and Sham Operations .................................... 26

2.3.2.1 Tooth Extraction .............................................................................. 27

2.3.2.2 Endodontic Treatment ...................................................................... 27

2.3.2.3 Sham Operation ............................................................................... 27

2.3.2.4 Postoperative Care ........................................................................... 28

2.4 The CLARITY Immunhistochemistry Technique ................................................... 29

2.4.1 Hydrogel Monomer Perfusion-Infusion ......................................................... 29

2.4.1.1 Brain Dissection ............................................................................... 31

2.4.1.2 Hydrogel Tissue Embedding ............................................................ 32

2.4.2 Hydrogel Tissue Hybridisation ...................................................................... 32

2.4.3 Passive Tissue-Clearing of Membrane Lipids ............................................... 33

2.4.3.1 Buffer Wash and Storage ................................................................. 33

2.4.4 Immunolabelling: Optimisation Protocol for Whole-Tissue .......................... 34

2.4.4.1 Whole-Tissue Immunolabelling Protocol ........................................ 34

2.4.5 Optical Clearing and Refractive Index Matching .......................................... 35

2.4.6 Whole Tissue Imaging ................................................................................... 38

2.4.6.1 Mounting Cleared Tissue for Light-Sheet Microscopy ................... 38

2.4.6.2 The Region of Interest ..................................................................... 38

2.4.6.3 Image Acquisition ............................................................................ 39

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2.4.7 Image Processing ............................................................................................ 41

2.4.7.1 Identification of Layer I ................................................................... 41

2.4.8 Quantification of Morphological Parameters of Astroglial Processes ........... 41

2.4.8.1 Morphological Parameters ............................................................... 42

2.5 Data Analysis and Sample Size Calculation ............................................................ 43

2.6 Excluded Data .......................................................................................................... 43

Results ............................................................................................................................... 46

3.1 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex .............. 46

3.2 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment ............................................ 51

Discussion .......................................................................................................................... 53

4.1 3D Visualisation of Astroglia with CLARITY ........................................................ 53

4.2 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex .............. 55

4.3 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment ............................................ 57

4.3.1 Clinical Implications ...................................................................................... 59

4.4 Study Limitations and Future Directions ................................................................. 60

Conclusions ....................................................................................................................... 63

References ......................................................................................................................... 64

viii

List of Tables

Table 1. List of Solutions, ingredients and manufacturer. ........................................................... 31

Table 2. List of conjugated antibodies used for immunolabelling. ............................................. 35

Table 3. Testing options for optical clearing and refractive index matching .............................. 37

Table 4. Summary of study groups, number of animals included or excluded from the study and

the reason for exclusion. ....................................................................................................... 45

ix

List of Figures

Figure 1. Illustration of main pathways showing projections of trigeminal (V) primary afferents

from the oral cavity via the trigeminal ganglion to second-order neurones in the trigeminal

brainstem sensory nuclear complex, and from there, to higher levels of the brain including the

thalamus and cerebral cortex. Vc - subnucleus caudalis, Vi – subnucleus interpolaris, Vo –

subnucleus oralis. Reprinted with permission from the Journal Critical Reviews in Oral Biology

and Medicine, Sessle B, Copyright (2000) (Sessle, 2000)………………………………………..6

Figure 2. On the right are cortical motor maps illustrating the motor representation areas of the

jaw-opening (anterior digastric) and tongue-protrusion (genioglossus) muscles within the rat left

orofacial sensorimotor cortex. The motor representations are superimposed on Nissl-stained

coronal hemisections of the left hemisphere at anteroposterior (AP) planes 2.4, 2.7, 3.0, 3.3, 3.6,

and 3.9 mm anterior to Bregma. On the left are corresponding schematic diagrams from

Swanson’s Atlas of the rat brain (Swanson, 2004) which indicate the different cortical layers in

Arabic numbers (3,4,5,6). Top right of the figure is a sagittal view diagram of the rat brain.

Reprinted with permission from John Wiley and Sons, Journal of Comparative Neurology, Brain

maps 4.0—Structure of the rat brain: An open access atlas with global nervous system

nomenclature ontology and flatmaps, Swanson L, Copyright (2018)……………………………..9

Figure 3. Image of GFAP-labelled astroglial cell within layer 5 of a mouse orofacial primary

motor cortex obtained by 3D imaging of a 40 µm – thick brain section with a spinning disk

confocal microscope (63x/1.3; water). GFAP - Glial fibrillary acidic protein, a specific marker of

astroglial cytoskeleton (Unpublished data)………………………………………..…………….16

Figure 4. Schematic representation of the ‘tripartite synapse’, neuron – astroglia – neuron.

Reprinted by permission from Springer Nature: Nature Neuroscience: Glia — more than just brain

glue, Allen N; Barres, B, Copyright (2009) (Allen and Barres, 2009)…………………………..17

Figure 5. A-C. Layout of the light-sheet Z.1 fluorescence microscope. The objective lens and

detection beam-path are perpendicular to the illumination beam-path. A laser light that is formed

into a thin sheet of light illuminates the fluorescently-labeled tissue from either one or two sides.

x

This illumination excites only fluorophores within the focal plane of the detection objective. All

fluorescent signals are collected on a camera-based detector. D-E. The light-sheet is generated

either statically by using a cylindrical lens or dynamically by high-frequency scanning of a laser

beam. Reprinted by permission from Zeiss……………………………………………………...21

Figure 6. Experiment time-line. Rats were monitored on a daily basis from the date of arrival at

the vivarium until perfusion day. Weight (yellow arrow) was measured on arrival, after

acclimation period and on the day of perfusion. Treatment (endodontic treatment, tooth extraction

or sham operation) were carried out following a 1-week acclimation (green band). Analgesics and

anti-inflammatory drugs were administered up to three days postoperatively (pink band).

Perfusion was performed on day 7 after treatment (blue band)………………………………….26

Figure 7. A. Mouth opening. B. Maxillary molar teeth. C. Extraction sockets of right maxillary

molar teeth. D. Access cavities for dental pulp extirpation of right maxillary molar teeth. E.

Radiographic image of the right maxillae showing maxillary molar teeth after pulpectomy and

restoration of access cavity with a temporary filling material. F. Radiographic image of the right

maxillae showing extraction sockets…………………………………………………………….28

Figure 8. Overview of the CLARITY technique. Step 1- Hydrogel monomer perfusion-infusion:

An optically transparent porous matrix composed of formaldehyde (red), acrylamide and

bisacrylamide (hydrogel) monomers (blue), and thermally-triggered initiators, perfusion-infused

into the brain tissue at 4 oC. The formaldehyde forms crosslinks with the tissue, and covalent links

(electron sharing) between the hydrogel monomers and tissue-proteins, nucleic acids and other

biomolecules. Step 2- Hydrogel tissue embedding: At 37 oC, the tissue-bound monomers

polymerise and create a hydrogel mesh–tissue hybrid that provides physical support to tissue

structure. Step 3- Passive clearing of membrane lipids: Passive clearing removes lipids and

molecules that remained unbound to the hydrogel. While detergent (sodium dodecyl sulfate, SDS)

micelles diffuse passively through the tissue, they capture and clear out lipid of the tissue. The

hydrogel–tissue hybrid keeps biomolecules and fine cytoarchitectural features of the brain intact,

including neuronal and glial proteins. Despite clearing, some light-scattering remains due to

heterogeneous distribution of proteins and nucleic acid complexes in the hybrid. Step 4: Standard

immunolabelling of cells or molecules. Step 5- Optical clearing and refractive index matching:

Immersion in 2,2'-thiodiethanol (TDE) solution for: optical clearing; tissue shrinkage to

xi

compensate for clearing-induced tissue expansion; refractive index homogenization. Step 6-

Image acquisition: Light-sheet microscopy to visualise cells in intact thick tissue. Adapted by

permission from Springer Nature: Nature Methods. CLARITY for mapping the nervous system,

Chung, K; Deisseroth, K, Copyright (2013) (Chung and Deisseroth, 2013)......…………………30

Figure 9. A. A whole brain after hybridisation. Dotted lines mark the region of 2 mm-thick

coronal section containing the orofacial primary motor cortex. B. Rostral view of a 2 mm-thick

coronal section. C. Rostral view of a 2 mm-thick coronal section after 7 days of passive clearing.

D. Rostral view of a 2 mm-thick coronal section following ~15 days of clearing; the tissue appears

clear and ‘see-through’. Notice the significant increase in the size due to swelling that occurred

during the passive clearing………………………………………………………………….…...33

Figure 10. Refractometer. Prior to the light-sheet imaging, a refractometer was used to ensure

that the Refractive Index (RI) of the 63% TDE immersion solution matches the refractive index

of the light-sheet imaging objective (i.e., 1.45)………………………………………………….37

Figure 11. The region of interest (small yellow square) selected for scanning with the light-sheet

20X CLARITY objective spanned from the cortical surface at ~4 mm lateral to midline (red line)

and included a total area of 438.9 μm x 438.9 μm x 1 mm………………………………………39

Figure 12. A. A glass capillary is attached to the caudal aspect of the 2 mm-thick brain section.

Red arrow is pointing at the area were the ROI is located. B. The glass capillary with the brain

section are attached to the Zeiss light-sheet Z1 microscope and positioned in front of the camera

(red arrow). C. Outside view of the Zeiss light-sheet Z1 microscope…………………………..40

Figure 13. A. 3D image of 1 mm-thick cortical tissue showing the features used to select the

region of interest within layer I: the pia mater, composed of NeuN+ flat-shape nuclei (red), the

glia limitans identified as a continuous layer of high intensity GFAP+ astroglial cells, cortical

layer I is characterised by a rich network of GFAP+ processes while layers II/III below show a

significantly larger number of NeuN+ nuclei and sparse GFAP+ cells. B. Illustrates the region of

interest within layer I selected for subsequent morphometric analysis of GFAP+ processes.

Bottom yellow line marks the approximate border between layer I and layers II/III. Top yellow

line marks an approximate border between layer I and the glial limitans. C. Bitplane Imaris

xii

software masked the GFAP+ processes (white) within the region of interest for subsequent

morphometric analysis…………………………………………………………………………..42

Figure 14. A. 3D image of 1 mm-thick brain tissue from a rat that underwent inadequate perfusion

and subsequent immunolabelling with GFAP marker in green. White arrows show >6 µm-thick

GFAP+ structures consistent with blood-filled blood vessels (scale 100 μm). B. Enlarged insert

from figure A. C and D. 3D image of 1 mm-thick brain tissue which underwent immunolabelling

with GFAP marker in green. Image shows bright and dark stripe artifacts which are a common

occurrence in light-sheet microscopy (scale 100 μm). C. A lateral view. D. A superior view……44

Figure 15. A. A 2D image of a Nissl-stained coronal section through the orofacial sensory-motor

cortex of a Sprague Dawley rat at ~ 3 mm anterior to Bregma. Superimposed are the jaw (red)

and tongue (blue) motor representation areas as we have previously mapped and documented. B.

A schematic diagram obtained from Swanson’s Atlas of the Rat Brain). Reprinted with permission

from John Wiley and Sons, Journal of Comparative Neurology, Brain maps 4.0—Structure of the

rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps,

Swanson L, Copyright (2004) (Swanson, 2004), which corresponds to the histological section in

A, indicating the different cortical layers numbered with Roman numerals from superficial to deep

(I-VI). C. A 3D image of a 438.9 µm x 438.9 µm x 1 mm (scale 50 μm) brain tissue showing the

superficial cortical layers I and II/III as well as the pia mater and glia limitans. White arrow

pointing at the pia mater, composed of NeuN+ flat-shape nuclei (red). Juxtaposing below the pia

is the glia limitans (white arrow), which comprises a continuous layer of high intensity GFAP+

astroglial cell bodies and processes. (GFAP+: immunoreactive glial fibrillary acidic protein;

NeuN+: neuronal nuclei)……………………………………………………………………..…47

Figure 16. A. Superior view of glia limitans superficialis showing high-intensity GFAP+ cells

(green; soma and processes). Superior view of a blood vessel (white arrow) penetrating the cortex;

and NeuN+ neuronal nuclei (red). (scale 50 μm) B. Lateral view of a blood vessel (white arrow)

penetrating the cortical parenchyma surrounded by GFAP+ astroglial cells (green) forming the

glia limitans perivascularis; NeuN+ neuronal nuclei are marked in red (scale 50 μm). C. Schematic

representation of the superficial membranes of the cortex showing that the glia limitans (green)

lies between the pia mater and the cerebral cortex. D. 40 µm thick image showing GFAP + cells

xiii

(green) within the superficial layer of motor cortex forming glia limitans, DAPI (blue) labelling

of any nucleus within the cortex and the pia mater above the glia limitans (scale 50 μm).……..48

Figure 17. A. GFAP+ cells covering the cortical surface area form the glia limitans superficialis

and GFAP+ cells surrounding blood vessels form the glia perivascularis. B. Enlarged insert from

Figure A showing the glia limitans perivascularis (scale 50 μm)……………………………….49

Figure 18. A. A 3D image of a 1 mm-thick cortical tissue showing cells immunolabelled with

GFAP (GFAP+, green), a specific marker of astroglial cytoskeleton, NeuN (NeuN+, red), a

specific marker of neuronal nuclei, and DAPI (blue), a non-specific marker of cell nuclei. B. Same

image as in A showing GFAP+ cells. C. Same image as in A showing NeuN+ cells (scale 100

μm)………………………………………………………………………………………………50

Figure 19. Mean diameter (A) and straightness (B) of astroglial processes. Diameter data is

presented as group-means and SEM; Straightness data is presented as group-medians and SEM.

Tooth extraction was associated with a significantly smaller diameter and straighter astroglial

processes………………………………………………………………………………………...51

Figure 20. A. Percent volume of all GFAP-labelled cells. B. Ratio of surface area to volume of

all GFAP-labelled cells. C. Total length of all GFAP-labelled processes. Data presented as group-

means and SEM………………………………………………………………………………….52

xiv

List of Abbreviations

3D Three dimension

AP anteroposterior

ANOVA Analysis of variance

CLARITY Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-compatible Tissue-

hYdrogel

CNS Central nervous system

DAPI 4′,6-diamidino-2-phenylindole

DNA Deoxyribonucleic acid

E.G. Ex grata

ETC electrophoresis for tissue clearing

GABA Gamma-aminobutyric acid

GB Gigabyte

GFAP Glial fibrillary acidic protein

GC-genu of corpus callosum

GG Genioglossus

GHz Gigahertz

Glt1 Glutamate transporter

HP Hewllet packard

I.E., Id est

I.M. Intramuscular

NA Numerical aperture

NaOCL Sodium hypochlorite

NeuN Neuronal nuclei marker

PBS Phosphate buffered saline

PBST Phosphate suffered saline- triton

PBT Phosphate borate triton

Post-op Post-operative

RAM Random access memory

RI Refractive index

ROI Region of interest

RPM Rounds per minute

xv

SDS Sodium dodecyl sulfate

TDE 2,2'-thiodiethanol

VII Facial nerve

IX Glossopharyngeal nerve

X Vagus nerve

1

Chapter 1

Introduction

1.1 Overview Many patients who undergo tooth extraction and endodontic treatments suffer from acute

orofacial sensory (e.g., pain) and/or motor (e.g., jaw movement, biting, chewing) impairments.

Clinicians often fail to adequately manage these impairments and prevent the development of

chronic conditions (e.g., phantom sensation or pain) because the underlying mechanisms are still

poorly understood (Klineberg et al., 2014; Kumar et al., 2018; Nixdorf et al., 2010b; Nixdorf et

al., 2010c; Renton, 2011). While the underlying mechanisms are poorly understood, they may

involve the orofacial primary motor cortex, the main brain region involved in the generation and

modulation of orofacial motor functions. It is important to emphasise that somatosensory inputs

from the orofacial region (e.g., oral mucosa, teeth) provide somatosensory feedback and

feedforward information that is crucial for modulating the orofacial movements. Since these

movements rely on sensory inputs, they are referred to as sensory-motor movements. Current

literature has shown in rodents that changes in sensory inputs to the motor cortex, or altered motor

functions, can induce functional neuroplastic changes in the orofacial primary motor cortex. For

example, noxious stimulation of the orofacial tissues (including tooth pulp) as well as other

intraoral manipulations such as orthodontic treatment, tooth trimming or extraction, and dental

implant surgery can all induces changes in neuronal activity and circuitry (Adachi et al., 2007;

Avivi-Arber et al., 2010b, 2015a,b; Awamleh et al., 2015; Pun et al., 2016; Sood et al., 2015; Yao

and Sessle, 2018; for review see Avivi-Arber et al., 2011d; Avivi-Arber and Sessle, 2018; Sessle

et al., 2013b). Such neuroplastic changes may contribute to the restoration of sensory-motor

functions (i.e., adaptive neuroplasticity), but may also contribute to the development and

maintenance of impaired sensory-motor behaviours including chronic pain (i.e., maladaptive

neuroplasticity). It has also been reported that the neuroplastic changes may involve and depend

on the functional integrity of non-neuronal astroglial cells since application of an astroglial

inhibitor to the surface of the orofacial primary motor cortex can reverse the neuroplasticity

induced by the noxious stimulation of the dental pulp (Awamleh et al., 2015). However, it is

unclear what the exact cortical site of action of the astroglial inhibitor was in the cited study.

2

Nevertheless, it likely diffused into the cortex to exert its effects at least on astroglial cells within

the superficial cortical layers. Indeed, Laskawi et al. showed that peripheral nerve injury induces

astroglial plasticity within layers I/II of the primary motor cortex (Laskawi et al., 1997). Peripheral

injuries (e.g., noxious stimulation of the dental pulp, orofacial nerve injury or inflammation) can

also result in structural and functional astroglial plasticity within other cortical and subcortical

regions characterised by progressive changes in the number, morphology, function, and gene

expression of astroglia within trigeminal subnucleus caudalis, thalamus and primary

somatosensory cortex (for review see Chiang et al., 2012). In fact, it has been shown that

functional astroglial plasticity is tightly coupled to structural astroglial plasticity (Liddelow and

Barres, 2015). However, no study has addressed whether endodontic treatment (i.e., dental pulp

extirpation) and tooth extraction induce structural plasticity in astroglial cells within the orofacial

primary motor cortex. Better understanding of the role and involvement of astroglia in orofacial

sensory-motor functions after dental manipulation is of clinical significance since it can assist in

the development of improved therapeutic approaches, such as targeting astroglia within the

orofacial primary motor cortex, to prevent or cure orofacial sensory-motor impairment (Hamby

and Sofroniew, 2010; Kimelberg and Nedergaard, 2010; Liddelow and Barres, 2015, 2017).

Conventional immunohistochemistry has long been a fundamental technique in neuroscience

research to explore morphological features of neuronal and non-neuronal cells in consecutive thin

(µm) brain sections. Major advancements in recent years have led to the development of the novel

CLARITY technique (i.e., Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-

compatible Tissue-hYdrogel) that renders the brain optically transparent, and along with

immunolabelling and subsequent novel 3D imaging and automated detection of brain cells, allows

quantification of morphological features of cells within thick (mm) brain sections or even at the

whole-brain level (Chung and Deisseroth, 2013; Chung et al., 2013; Zheng and Rinaman, 2016).

However, no study has utilised the novel CLARITY technique to investigate morphological

features of astroglial processes within the superficial layer of the orofacial primary motor cortex

and their plasticity following intraoral injury.

Thus, the general aim of the present thesis was to use an animal model and the novel CLARITY

technique for 3D characterisation of astroglial cytoarchitecture and quantification of

3

morphological changes in astroglial cells within thick brain sections of the orofacial primary

motor cortex of rats receiving tooth extraction or endodontic treatment.

1.2 Main Somatosensory and Motor Innervation of Orofacial Tissues

1.2.1 Sensory Receptors Sensory receptors are specialised nerve endings in peripheral tissues that are activated by external

stimuli such as mechanical [touch, pressure, vibration and proprioceptive (i.e., muscle tension and

length)], chemical, thermal (cold, warm) or nociceptive stimuli. Receptor activation generates

action potentials that propagate through the primary afferent nerve fibre to the brainstem (or spinal

cord) and higher brain centres to generate sensations and also to modulate motor functions (see

below). Teeth and orofacial tissues, in general, are characterised by a high density of receptors

that contribute to the high sensitivity of these tissues (Byers, 1984; Fried, 2014; Sessle, 2006;

Sessle, 2011a).

The dental pulp has a rich innervation density of free nerve endings sensitive to mechanical,

thermal, chemical and noxious stimuli (Byers, 1984; Fried K., 2014; Haggard and de Boer, 2014;

Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011a). The periodontal

ligaments that attach the tooth roots to the surrounding alveolar bone are rich in nociceptors and

specialised mechanoreceptors distributed along the roots of the teeth. The mechanoreceptors also

function as proprioceptors providing information about the amount, speed and direction of

occlusal forces (Haggard and de Boer, 2014; Linden, 1990; Miles et al., 2004; Roth and Calmes,

1981; Sessle, 2006; Sessle, 2011a). Skin and mucosa have free nerve endings and specialised

mechanoreceptors that also function as proprioceptors that are activated in response to

deformations of underlying muscles during muscle contractions and jaw movements (Haggard

and de Boer, 2014; Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011a).

Muscle spindle and golgi tendon, as well as joints, have specialised receptors that function as

proprioceptors. Proprioceptors of skin, mucosa, muscle and joints provide information about joint

angle, muscle length, muscle tension and jaw position in space. However, it is important to note

that many orofacial muscles, including jaw-opening and facial expression muscles, have very few

4

or no muscle spindles and golgi tendon organs (Haggard and de Boer, 2014; Lazarov, 2007; Miles

et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011a).

1.2.2 Major Somatosensory Afferent Pathways The trigeminal nerve is the main cranial nerve carrying somatosensory and proprioceptive primary

afferent neurones projecting from orofacial receptors to the central nervous system. It has three

sensory branches: the ophthalmic branch (superior) that provides sensory innervation to most of

the scalp, forehead, and front of the head; the maxillary branch (middle) provides sensory

innervation to the cheeks, nostrils, upper lip and maxillary bone, soft tissues and teeth; and the

mandibular branch (inferior) provides sensory innervation to the anterior two thirds of the tongue,

lower lip, and mandibular bone, soft tissues, and teeth. In addition, the mandibular division also

carries efferent motor fibres to the jaw muscles of mastication (see below). Other cranial nerves

are involved in the innervation of other orofacial tissues. For example, the glossopharyngeal (IX)

and the vagus (X) nerves innervate the posterior tongue, larynx, pharynx and ears; and the facial

nerve (VII) innervates the tongue (taste), ears and periauricular skin (Haggard and de Boer, 2014;

Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011b).

Most of the somatosensory and all the proprioceptive primary afferent nerve fibres innervating

the orofacial area project in a somatotopic manner along the trigeminal nerve branches to

terminate mainly in the ipsilateral trigeminal brainstem sensory nuclear complex which consists

of the trigeminal main sensory nucleus as well as the trigeminal spinal tract nucleus that is further

subdivided into subnuclei oralis, interpolaris and caudalis (Fig. 1). Touch, pressure, and vibration

inputs from soft tissues (e.g., tongue, skin, mucosa) and periodontal ligaments as well as dental

pulp, and some proprioceptive inputs from periodontal ligaments are conveyed to the central

nervous system via large-diameter, low threshold and fast-conducting Aβ primary afferent nerve

fibres. Nociceptive and thermoceptive inputs from the soft tissues as well as the periodontal

ligament and dental pulp are conveyed via small-diameter, high threshold and slow-conducting

Aδ and C primary afferent nerve fibres. Proprioceptive inputs from jaw muscles and other

orofacial muscles are conveyed via Aα primary afferent nerve fibres (Haggard and de Boer, 2014;

Miles et al., 2004; Roth and Calmes, 1981; Sessle, 2006; Sessle, 2011b).

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The cell bodies of the somatosensory primary afferent nerve fibres are located in sensory ganglia

associated with the cranial nerves VII, IX and X. Generally, primary afferents can diverge and

converge to terminate in multiple subnuclei of the trigeminal brainstem sensory nuclear complex.

Primary afferent nerve fibres conveying touch inputs have their cell bodies located in the

trigeminal ganglion and they synapse mainly on second-order neurones within the principal

sensory nucleus and subnucleus oralis. The majority of these fibres ascend to the thalamus

bilaterally in a somatotopic manner via the dorsal trigeminothalamic tract (i.e., dorsal trigeminal

lemniscus). Primary afferent nerve fibres conveying nociceptive and temperature inputs also have

their cell bodies in the trigeminal ganglion, but they synapse mainly on second-order neurones

within the subnucleus caudalis as well as subnucleus interpolaris. The majority of these fibres

cross to the opposite side and ascend to the thalamus via the ventral trigeminothalamic tract (i.e.,

anterior trigeminal lemniscus) ( Haggard and de Boer, 2014; Miles et al., 2004; Roth and Calmes,

1981; Sessle, 2006; Sessle, 2011a).

Proprioceptive inputs from masticatory muscles as well as the periodontal ligament have their cell

bodies either in the trigeminal ganglion or in the mesencephalic nucleus. Proprioceptive primary

afferents with cell bodies in the trigeminal ganglion synapse on second-order neurones within the

principal sensory nucleus and subnucleus oralis. The majority of the proprioceptive primary

afferents with cell bodies in the mesencephalic nucleus synapse on alpha motor neurones within

the trigeminal motor nucleus. Alpha motor neurones project to and activate masticatory muscle

and thus proprioceptive inputs from the orofacial region can directly and reflexively impact

orofacial motor responses (for reviews, see Avivi-Arber and Sessle, 2018; Haggard and de Boer,

2014; Miles et al., 2004; Paxinos, 2004; Roth and Calmes, 1981; Sessle, 2000).

Thalamic neurones project in a somatotopic manner from the main thalamic sensory nuclei to the

primary somatosensory cortex where conscious somatosensory perception is processed.

Consequently, inputs from the different body parts are organised within the primary

somatosensory cortex in a somatotopic manner known as the somatosensory representation map

or somatosensory homunculus. Body parts that are next to each other in the periphery are also

represented next to each other in the primary somatosensory cortex and the larger the innervation

density of a body part the larger the representation. Thus, the orofacial tissues, including teeth and

jaw muscles have large representations within in the primary somatosensory cortex.

6

A large amount of sensory inputs also projects to the primary motor cortex either through the

primary somatosensory cortex or directly from thalamic sensory and motor nuclei. Somatosensory

and proprioceptive inputs from the oral region, including the teeth, provide feedback and

feedforward information necessary for modulating muscle activity and muscle forces (see below)

(for detailed review see Avivi-Arber, 2009, 2011b, 2018; Haggard and de Boer, 2014; Miles et

al., 2004; Paxinos, 2004; Sessle, 2000; Sessle et al., 2013b)

Figure 1. Illustration of main pathways showing projections of trigeminal (V) primary afferents from the oral cavity via the trigeminal ganglion to second-order neurones in the trigeminal brainstem sensory nuclear complex, and from there, to higher levels of the brain including the thalamus and cerebral cortex. Vc - subnucleus caudalis, Vi – subnucleus interpolaris, Vo – subnucleus oralis. Reprinted with permission from the Journal Critical Reviews in Oral Biology and Medicine, Sessle B, Copyright (2000) (Sessle, 2000).

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1.2.3 The Orofacial Primary Motor Cortex: Neuronal Cytoarchitecture, Connectivity and Major Motor Efferent Pathways

The primary motor cortex is the main brain region involved in the initiation and modulation of

muscle contraction and body movements. Within the primary motor cortex , the orofacial primary

motor area is involved in the initiation and modulation of muscle contraction in the orofacial

region that can give rise to bilaterally coordinated orofacial movements including elemental

movements such as jaw-opening, jaw-closing, tongue-protrusion and tongue-retrusion, as well as

semi-automatic rhythmic movements such as mastication and swallowing (for reviews, see Avivi-

Arber et al., 2011d, 2018; Sessle et al., 2013b)

Neurones within the primary motor cortex are organised in five histologically-defined horizontal

layers numbered with Roman numerals from superficial to deep layers (I, II, III, V and VI), each

with a characteristic cytoarchitecture and connectivity. Since the motor cortex lacks a prominent

granular layer IV which characterises the granular primary somatosensory cortex, it is referred to

as the ‘agranular’ cortex. This region corresponds macroscopically and histologically to the

coronal sections in Swanson’s rat brain atlas that are at 2.5 – 4.0 mm anterior to Bregma (Fig. 2)

(Swanson, 2004; for reviews see Asanuma, 1989; Avivi-Arber et al., 2010b, 2010c, 2015b;

Awamleh et al., 2015; DeFelipe et al., 2002; Donoghue, 1982; Kaas, 1991). Layer I lies directly

below the pia mater and the glia limitans (see below). It contains only few scattered neurones but

is abundant in horizontal reciprocal axonal projections relaying information to/from multiple

cortical (e.g., primary somatosensory cortex) and subcortical (e.g., thalamus) regions. These

axons synapse on terminals of apical dendrites of pyramidal neurones from layers III and V (see

below) (Mohan et al., 2015).

Layer I also has a small number of inhibitory neurones with GABA as their primary

neurotransmitter. Layers II-VI consist of pyramidal neurones (i.e., cortical efferent) and non-

pyramidal stellate neurones (i.e., intracortical inter-neurones). The cell bodies of the pyramidal

cells are most prominent in layers III and V. Layer III is the major target for interhemispheric

corticocortical afferents and the main source for corticocortical efferents. Layers V-VI give rise

to all of the principal cortical efferent projection to brainstem motor neuronal and inter-neuronal

regions involved in orofacial muscle control. The major descending pathway that can initiate and

influence motor activity in orofacial muscles is the so-called ‘pyramidal tract’ (i.e., ‘corticobulbar

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tract’) with pyramidal cell bodies located mainly in layers V-VI, and efferent axons projecting

bilaterally but mainly contralaterally to synapse and activate motor neurones within the brainstem

motor nuclei. In turn, the axons of the motor neurones project via the ipsilateral motor root of the

trigeminal mandibular branch to synapse and activate the masticatory muscles including the jaw-

closing (masseter, temporalis, medial pterygoid) and jaw-opening (mylohyoid, digastric, lateral

pterygoid) muscles (Burish et al., 2008; Chen, 2004; Douglas and Martin, 2004; Iyengar et al.,

2007; Kaas et al., 2006; Mao et al., 2011; Neafsey et al., 1986; Roberts, 1986; Takata and Hirase,

2008).

Although pyramidal tract neurones can project directly to brainstem motor nuclei to directly

activate motoneurones, most of the projections related to masticatory jaw movements are

multisynaptic and project to brainstem motoneurones through other cortical or subcortical relay

regions including brainstem pre-motor inter-neurones located bilaterally at the brainstem reticular

formation regions, nucleus of the solitary tract, inter- and supra- and juxta-trigeminal regions

surrounding the trigeminal motor nucleus and mesencephalic nucleus. These brainstem pre-motor

neurones are part of the Central Pattern Generator circuitry which is a complex network of

excitatory and inhibitory inter-neurones that synapse and activate or inhibit alpha-motor neurones

within the trigeminal and other cranial nerve motor nuclei (for review, see Aroniadou and Keller,

1993; Huntley, 1997; Sessle, 2000; Sessle et al., 2013b; Westberg and Kolta, 2011)

Several features characterise the primary motor cortex in general. Nearby corticobulbar tract

neurones responsible for the contraction of different body muscles maintain their somatotopic

organisation along their efferent projection pathways. Thus, muscles that are next to each other in

the body have adjacent motor representations in the primary motor cortex known as the ‘motor

homunculus’ or ‘motor representation map’. Muscles that are involved in more complex and finer

movements have a larger motor representation within the primary motor cortex and the orofacial

muscles occupy a large motor representation area within the primary motor cortex known as the

orofacial primary motor cortex. Similar to the motor homunculus in humans, in rats, motor

representations of the body are organised in a so-called motor ‘ratunculus’ and the jaw and tongue

muscles have large motor representations within the orofacial primary motor cortex. The cortical

areas (i.e., motor representations) devoted to the motor output of each muscle in the body can be

identified, delineated and mapped by systematic spatial application of low-intensity electrical

9

currents to the cortex and recording of evoked electromyographic activity in body muscles (Fig.

2) Asanuma, 1989; Avivi-Arber et al., 2010c, 2015b; Donoghue, 1982; Neafsey et al., 1986).

It is important to note that those brain regions involved in the generation and control of orofacial

movements, including the orofacial primary motor cortex brainstem Central Pattern Generator

and motor nuclei, receive a large amount of somatosensory inputs from both sides of the orofacial

region including the teeth which can assist but also interfere with jaw movements (for review, see

Avivi-Arber, 2009, 2018; Paxinos, 2004; Sessle, 2000; 2006; Sessle et al., 2013b).

Figure 2. On the right are cortical motor maps illustrating the motor representation areas of the jaw-opening (anterior digastric) and tongue-protrusion (genioglossus) muscles within the rat left orofacial sensorimotor cortex. The motor representations are superimposed on Nissl-stained coronal hemisections of the left hemisphere at anteroposterior (AP) planes 2.4, 2.7, 3.0, 3.3, 3.6, and 3.9 mm anterior to Bregma. On the left are corresponding schematic diagrams from Swanson’s Atlas of the rat brain (Swanson, 2004) which indicate the different cortical layers in Arabic numbers (3,4,5,6). Top right of the figure is a sagittal view diagram of the rat brain. Reprinted with permission from John Wiley and Sons, Journal of Comparative Neurology, Brain maps 4.0—Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps, Swanson L, Copyright (2018).

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1.2.4 Clinical Implications During orofacial motor functions, such as mastication and speech production, a large number of

receptors of different types (e.g., nociceptors, thermoreceptors, chemoreceptors,

mechanoreceptors and proprioceptors) and from different orofacial tissues (e.g., skin, mucosa,

muscles, joints and teeth) are activated simultaneously and sequentially to generate patterns of

somatosensory afferent inputs to the central nervous system. Since facial and jaw-opening

muscles have significantly fewer or no muscle spindle proprioceptors, the periodontal

proprioceptors as well as the skin and joint mechanoreceptors play a crucial role in providing

peripheral feedback and feedforward information that is essential for accurate performance of

discrete as well as the complex rhythmic movements of the jaw during chewing, speaking and

other orofacial motor functions. The bilateral direct projections of primary afferent proprioceptive

neurones from jaw muscles (e.g., masseter) and periodontal ligaments to brainstem motor nuclei

are also crucial for simultaneous bilateral modulation of the masticatory muscles and for eliciting

jaw-opening and jaw-closing reflexes to protect the teeth from injury during biting, or protecting

the jaws from excessive stretching (for review see Haggard and de Boer, 2014; Paxinos, 2004;

Sessle et al., 2013b; Trulsson and Essick, 2004).

1.2.4.1 Consequences of Endodontic Treatment and Tooth Extraction The most obvious consequence of endodontic treatment is the loss of somatosensory inputs from

dental pulp primary afferent neurones (i.e., denervation) and subsequent loss of tactile,

temperature and nociceptive perception from the dental pulp. On the other hand, tooth extraction

results in denervation of both pulpal, periodontal and gingival primary afferent neuron resulting

in loss of somatosensory as well as proprioceptive inputs. Thus, tooth extraction may also impact

proprioception including perception of spatial orientation of the jaws during function and the

ability to modulate the amount of muscle force being employed during jaw movements and biting

(Trulsson and Essick, 2004).

A common consequence of both endodontic treatment and tooth extraction is the occurrence of

acute pain caused by the tissue injury and subsequent inflammatory processes that activate the

wounds and their peripheral nociceptive neurones as well as their intact neighbour neurones (Al-

Khateeb and Alnahar, 2008; Holland, 1995; Sessle, 2011a). While in most patients, postoperative

11

analgesia is effective in resolving acute pain, in a significant number of patients undergoing

endodontic treatment (5-12 %) or tooth extraction (~3%) the acute pain may develop into a

chronic pain condition. For example, Polycarpou et al. reported that 12 % of the patients receiving

endodontic treatment developed chronic pain, and Nixdorf et al. reported that in up to 5.5 % of

the endodontically treated teeth pain persisted for at least 6 months (Nixdorf et al., 2010a;

Polycarpou et al., 2005). Of note, pain by itself can cause an altered pattern of muscle activity as

well as altered cognitive motor behaviour such as favouring chewing on the painless side (Avivi-

Arber and Sessle, 2018; Lund, 2011; Sessle, 2006; Svensson and Graven-Nielsen, 2001).

Tooth extraction and subsequent reduced number of occluding pairs of teeth (but not endodontic

treatment) may also alter a subject’s preferred chewing side and alter the patterns of jaw

movements during mastication (Miehe et al., 1999; Shiraishi et al., 2017). This may affect

proprioceptive as well as mechanoreceptive inputs from muscles and other orofacial tissues

involved in jaw movements including teeth and missing teeth. Noteworthy is that even in subjects

treated with dental implant to replace the missing teeth, chewing efficiency and the ability to

adjust biting forces and muscle activity in relation to the food hardness, do not match those of

subjects with natural dentition; this may be related to the lack of periodontal ligament and sensory

inputs from periodontal receptors (for reviews see Avivi-Arber and Sessle, 2018; Trulsson and

Essick, 2012b).

Thus, any change to the dentition induced by dental treatments, including endodontic treatment

or tooth extraction, may activate or eliminate mechanoreceptive, proprioceptive and nociceptive

inputs from the teeth and surrounding tissues, and may thereby impact peripheral feedback and

feedforward information necessary for the regulation of muscles’ activity and associated

masticatory movements and biting forces.

1.3 Motor Cortex Neuroplasticity Induced by Altered Sensory Inputs and Motor Function

Numerous studies focusing on spinally-innervated tissues in animals and humans have shown that

the primary somatosensory and motor cortices involved in processing and controlling sensory-

motor functions of the limbs have a remarkable capacity to continuously form new neuronal

12

connections and re-wire their neuronal circuitry via functional and structural changes (i.e.,

neuroplasticity) in response to persistent modifications in sensory inputs and altered motor

function (Buonomano and Merzenich, 1998; Ebner, 2005). These neuroplastic changes may have

a fast- or slow-onset and may be short-lived or long-lasting. Different mechanisms may underlie

the different forms of neuroplasticity at different points of time and some may be involved

simultaneously. Fast-onset neuroplasticity, such as following peripheral denervation, can occur

within minutes and may be associated with potentiation of previously existing synapses via

unmasking of existing intracortical excitatory synaptic connections which are usually ineffective

because of inter- and intra-hemispheric lateral (e.g. GABAergic) inhibition (Farkas et al., 2000;

Jacobs and Donoghue, 1991). Long-lasting neuroplasticity may be related to enhanced or

diminished gene expression (Kleim et al., 1996), or generation of new receptors, new dendritic

branching and synapses, and even new neuron and subsequent new neuronal circuitry (Greenough

et al., 1985; Jones et al., 1996; Kleim et al. 1996, 2002, 2004; Monfils et al., 2004. Long-term

potentiation of synaptic efficacy may play a role at early and late phases of cortical neuroplasticity

(for reviews, see Boroojerdi et al., 2001; Kaas, 1991; Navarro et al., 2007).

1.3.1 Clinical Significance of Motor Cortex Neuroplasticity Most of our knowledge on motor cortex neuroplasticity comes from studies focusing on the limbs.

These studies have revealed that neuroplasticity is a crucial mechanism that can determine how

subjects adapt their motor behaviours to varying conditions, and how they learn or re-learn new

motor behaviours following injury (e.g., limb amputation) and/or rehabilitation (e.g., limb

prostheses). However, neuroplasticity may also reflect maladaptation that leads to a variety of

chronic motor as well as sensory dysfunctions (e.g., phantom limb sensation or pain, muscular

dystonia and dystrophy). Noteworthy is that the knowledge gathered from these studies in animals

and humans has influenced modern limb rehabilitation approaches which now include

neurobiologically-based approaches (for reviews, see Avivi-Arber et al., 2011b; Kleim and Jones,

2008; Sessle et al., 2013b). For example, pairing limb rehabilitation training with cortical

electrical stimulation as compared with training alone, can better enhance motor recovery

following injury (Adkins et al., 2008; Brown, 2006; Frost et al., 2003).

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The capacity of the orofacial motor cortex to undergo functional and structural neuroplasticity is

less well-documented. Nevertheless, as with limbs motor functions, orofacial motor cortex

neuroplasticity is considered a crucial mechanism underlying orofacial motor adaptation

following intraoral injury or dental treatment, and maladaptive neuroplasticity may underlie

orofacial motor as well as sensory impairments such as phantom pain or sensation, phantom bite,

embouchure dystonia and temporomandibular disorders (Avivi-Arber et al., 2011b, 2018; Sessle

et al., 2013b). Recent electrophysiological studies in rats have shown that various intraoral

manipulation that can conceivably change sensory inputs from the orofacial tissues or alter the

chewing patterns, are associated with extensive neuroplasticity manifested as reorganisation of

jaw and tongue motor representations within the orofacial primary motor cortex (Avivi-Arber et

al., 2010b,c, 2015b; Awamleh et al., 2015; Pun et al., 2016; Sood et al., 2015). For example, acute

noxious stimulation of the dental pulp or the tongue in rats and humans have been associated with

decreased orofacial motor cortex excitability (Adachi et al., 2007; Awamleh et al., 2015;

Boudreau et al., 2007; Pun et al., 2016). In addition, it has been shown in humans, that pain can

interfere with the successful performance of a learned tongue protrusion task (Boudreau et al.,

2007). These studies suggest that the decreased cortical excitability is a mechanism contributing

to motor limitation as a protective mechanism to prevent further damage to the affected tissues

and facilitate tissue and motor recovery (for review see Avivi-Arber et al., 2011c; Sessle, 2006;

Sessle et al., 2013b).

Unilateral extraction of the rat mandibular incisor tooth was associated, one week later, with

functional neuroplasticity manifested as reorganisation of jaw and tongue motor representations

within the orofacial primary motor cortex, including a significantly increased number of jaw and

tongue sites and a significantly decreased onset latency of evoked tongue activity (Avivi-Arber et

al., 2010a). In contrast, maxillary molar tooth extraction was associated with a significant and

sustained (1-2 months) decreased number of jaw and tongue motor representations and increased

cortical excitability (Avivi-Arber et al., 2011a, 2015b). Tooth extraction can also induce structural

changes in the brain. For example, a magnetic resonance imaging (MRI) study has shown that

tooth extraction can induce widespread volumetric changes in the brain manifested as decreased

or increased volumes within several brain regions involved in processing motor information as

well as somatosensory, cognitive and emotive information (Avivi-Arber et al., 2017). Learning a

new orofacial motor task, such as tongue-force training in rats, can also induce orofacial motor

14

cortex neuroplasticity manifested as increased excitability of the primary motor cortex but with

no apparent reorganisation of the tongue motor representation (Guggenmos et al., 2009). In

contrast, training humans and non-human primates in a novel tongue-protrusion task does produce

reorganisation of the tongue motor representation in the orofacial primary motor cortex,

manifested as a significantly increased motor representation of the tongue protrusion muscle and

a decreased motor representation of the tongue-retrusion muscle (Svensson et al., 2003; Yao et

al., 2002; for review see Avivi-Arber et al. 2011a,d; Sessle et al., 2013b).

Most significant is that motor cortex neuroplasticity can be reversible. For example, dental

implant treatment that replaces missing molar teeth can reverse the changes induced by the molar

tooth extraction, but dental implants can also produce new changes that do not exist in naïve

animals and which may compensate, for example, for the missing periodontal ligament of the

missing teeth (Avivi-Arber et al., 2015b). It is also significant that motor cortex neuroplasticity

induced by acute noxious stimulation of the tooth pulp can be reversed by the application of an

astroglial inhibitor to the pial surface of the orofacial motor cortex (Awamleh et al., 2015). While

it is unclear what the exact cortical site of action of the astroglial inhibitor was in that study, it

likely diffused from the surface into the cortex to exert its effects at least on astroglial cells within

the superficial cortical layers including glia limitans and layer I. Thus, the following section

discusses astroglial structure, functions and role in motor cortex neuroplasticity.

1.4 Glial Cells Glial cells are the most abundant and diverse cell types in the brain. While there are 100 billion

neurons in the adult human brain, it is estimated that glial cells are 50 times more abundant

(Kettenmann et al., 2008). Glial cells include microglia, astroglia, and oligodendrocyte

(Gundersen et al., 2015) and this section will focus mainly on astroglia.

Oligodendrocytes can sense changes in electrical impulses in neurons and produce myelin sheath

that enwraps neuronal axons in the central nervous system and can thereby modulate the

conduction velocity of action potentials along the axons (Bradl and Lassmann, 2010; Gundersen

et al., 2015).

15

Microglia are innate immune cells in the brain which are capable of phagocytosis and

modulation of repair and scarring processes following central injury resulting in activation and

proliferation of microglia (Allen et al., 2005). Activation and proliferation of microglia have also

been observed in cortical and subcortical regions (e.g., spinal cord, brainstem trigeminal sensory

and motor nuclei) following peripheral injury including orofacial nerve injury, inflammation and

noxious stimulation of the dental pulp (Lee et al., 2010, 2011; Piao et al., 2006; Salter, 2004; Zhao

et al., 2007). Moreover, behavioural and pharmacological studies in rats (e.g., application of

microglial inhibitors to the brainstem) have shown that microglia play a crucial role in the

development of central sensitization and chronic orofacial pain as well as in modulating jaw

reflexes and chewing (Chiang et al., 2011; Hossain et al., 2017; Itoh et al., 2011; Mostafeezur et

al., 2012a,b; Sessle, 2007; Xie et al., 2007).

1.4.1 Astroglial Cells: Cytoarchitecture and Morphology There are several subtypes of astroglia, and their number, structure, morphology and function

depend on the animal species, their subtype, their location in the brain, and the developmental

stage and age of the brain. The majority of astroglial cells have a star-like shape with a cell body

and five to eight major processes, each of which is highly ramified into numerous delicate

processes.

Astroglia in layer I of the mammalian cortex are often referred to as ‘pial astrocytes’ or ‘marginal

glia’ while astroglia in the other cortical layers are collectively referred to as protoplasmic

astroglia (Bushong et al., 2004; Lanjakornsiripan et al., 2018; Pekny and Pekna, 2014). The fine

astroglial processes occupy distinct, non-overlapping domains and are in close proximity to

neuronal synapses. It is estimated that each astroglia can contact tens of thousands of synapses

(Bushong et al., 2002; Hammond, 2008; Nag, 2011) (Fig. 3).

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Figure 3. Image of GFAP-labelled astroglial cell within layer 5 of a mouse orofacial primary motor cortex obtained by 3D imaging of a 40 µm – thick brain section with a spinning disk confocal microscope (63x/1.3; water). GFAP - Glial fibrillary acidic protein, a specific marker of astroglial cytoskeleton (Unpublished data).

1.4.2 Astroglial cells: Role in Regulating Neuronal Function For many years, scientists have thought that the electrically excitable neuronal networks are

connected through chemical synapses and that the surrounding non-neuronal microglial and

astroglial cells provide only immunological and metabolic support to the neuronal functions.

However, it is now clear that glial cells play a critical role in the development and function of

neurons in the brain, and that astroglia, in particular, can sense and modulate neuronal activity

and thereby also play a crucial role in cortical neuroplasticity.

Astroglial processes are in close proximity to neuronal synapses and form the so-called ‘tripartite

synapses’, each composed of one presynaptic and one postsynaptic neuronal terminal surrounded

by astroglial processes. Synapses and astroglial process are directly connected via gap junctions

that allow for bidirectional electrical and metabolic signaling between neurones and astroglia

(Perea and Araque, 2014) (Fig. 4). Moreover, astroglia have receptors for several neuronal

mediators (including glutamate and GABA) and they can remove neurotransmitters from the

17

synaptic extracellular space. Thus, signals between neurones and astroglia occur via ion fluxes or

binding of neurotransmitters and other molecules released to/from astroglia and neuronal

synapses. Astroglial cells also form a rich network of astroglial process that are connected via gap

junctions, but inter-astroglial communication occurs through intracellular waves of calcium and

intercellular diffusion of chemical messengers. Such signals can induce or inhibit the release of

neurotransmitters and thereby affect synaptic transmission. Noteworthy is that in the brain,

astroglia are the sole source (by synthesis) of glutamine, a precursor for the major excitatory

(glutamate) and inhibitory (GABA) neurotransmitters, and inhibition of glutamine synthesis or its

transport from astroglia to neurones can affect synaptic transmission and neuronal excitability

across networks of neurones and astroglia (Araque, 2008; Awamleh et al., 2015; Ben Achour and

Pascual, 2012; Perea and Araque, 2005; Tanaka et al., 1997; Verkhratsky and Butt, 2013;

Verkhratsky and Nedergaard, 2018).

Figure 4. Schematic representation of the ‘tripartite synapse’, neuron – astroglia – neuron. Reprinted by permission from Springer Nature: Nature Neuroscience: Glia — more than just brain glue, Allen N; Barres, B, Copyright (2009) (Allen et al., 2009).

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1.4.3 Astroglial Plasticity Another striking aspect of astroglia is their capacity to undergo short-term and long-term

functional and structural plasticity in response to sustained alterations in sensory stimuli or

trauma, inflammation, ischemia or neurodegeneration (Bernardinelli et al., 2014; Cheung et al.,

2015; Genoud et al., 2006; Perez-Alvarez et al., 2014). Dynamic cellular morphological changes

(see below) may occur in response (i.e., reaction) to increased synaptic activity, or nerve injury

which are temporally coupled with changes in intracellular Ca2+ and the release of gliotransmitters

including glutamate and GABA (Dallerac et al., 2013; Eng et al., 1992; Newman, 2003).

Astroglial structural responses to injury may include: (1) proliferation, movement and

differentiation; (2) upregulation of Glial Fibrillary Acidic Protein (GFAP), the main astroglial

intermediate filament protein used as a specific marker to identify astroglial cytoskeleton,

(Bignami and Dahl, 1977; Garcia-Cabezas et al., 2016); (3) changes in shape, volume,

cytoskeletal organisation, lysosomal fragility, and enzyme content. (Eng et al., 1992; Pekny and

Pekna, 2014; Sun and Jakobs, 2012; Yu et al., 2012).

Similar to neuroplasticity, such a remarkable astroglial plasticity may underlie the functional

adaptation (or maladaptation) of neurones and behaviour following injury and treatment

(Verkhratsky and Nedergaard, 2018). Interestingly, evidence from the last decade has shown that

astroglia in rodent brainstem play a crucial role in acute and chronic orofacial pain conditions,

and that they can undergo functional and structural changes under these conditions (Chiang et al.,

2012, 2007; Mostafeezur et al., 2014; Okada-Ogawa et al., 2015; Sessle, 2007; Tsuboi et al., 2011;

Xie et al., 2007). However, little is known of the effects of tooth extraction and endodontic

treatment on the structure and function of astroglia in the orofacial primary motor cortex.

1.5 The CLARITY Technique Conventional immunofluorescence methodologies have been used for high-resolution

visualisation of structural, morphological, connectivity and organisational features of different

cells in thin (µm) serial sections of the brain. Traditionally, only a certain number of sections are

included for high-resolution imaging and subsequent analysis of specific regions of interest in the

brain. Main disadvantage of this technique is the loss of information and the difficulty to achieve

19

3D high-resolution image of the cytoarchitecture of a whole few millimeter-thick brain tissues.

While inclusion of all sections for 3D reconstruction is available, it requires sophisticated image

stitching techniques and is very labor intensive and expensive, and thus is usually limited to very

small volumes of tissue, measured in a few microns. Moreover, mounting sections on slides

renders the method irreversible and thus the slightest mistake in the process can ruin the whole

samples or even the whole experiment.

Over the last few years, several optical clearing and imaging techniques have been developed to

overcome the limitations of the conventional immunohistochemical techniques. These new

techniques allow for high-resolution 3D cytoarchitectural visualisation of intact, several mm-thick

brain sections, and even a whole intact mouse or rat brain (Chung and Deisseroth, 2013; Chung

et al., 2013; Tomer et al., 2014). One of these clearing techniques is the Clear Lipid-exchanged

Acrylamide-hybridized Rigid Imaging-compatible Tissue-hYdrogel (CLARITY) (Chung and

Deisseroth, 2013; Costantini et al., 2015; Jensen and Berg, 2016; Tomer et al., 2014) (and see:

http://clarityresourcecenter.org; http://wiki.claritytechniques.org).

This technique utilises optically transparent porous hydrogel matrix that is perfusion-infused into

the tissues to provide a substructure that links tissue-proteins, nucleic acids and other

biomolecules together while dissolving and clearing the tissue of its lipid content (See Fig. 8 in

Chapter 2). The resultant hydrogel-tissue hybrid provides physical support to fine structures of

the brain and preserves their cytoarchitecture and molecular information during the subsequent

step in which a chemical detergent is used to clear the tissue from lipids that otherwise would

cause light scattering and prevent penetration of large molecules. This tissue-clearing process

results in an optically-transparent and macromolecule-permeable tissue that allows deep

penetration of light and macromolecules (e.g., antibodies and fluorescent markers); the light can

excite fluorescent-labelled cells and molecules, the signals of which can be captured with a camera

to produce 3D image of thick intact-tissue architecture with minimal light-scatter artifacts.

The original CLARITY technique utilises electrophoresis for tissue-clearing (ETC) to expedite

the lipid removal from brain tissue. For example, a whole mouse brain can be cleared overnight.

However, main disadvantages of ETC include the complexity of the technique, ability to clear a

limited number of brains at one time (i.e., it depends on the number of available electrophoresis

20

systems), and distortion of brain tissue (Tomer et al., 2014; Zheng and Rinaman, 2015). An

alternative to the ETC is the passive tissue-clearing technique that is carried out in a temperature-

controlled shaker. This technique can overcome the limitations of the ETC, and it also eliminates

the need to use electrophoresis equipment (Spence et al., 2014; Tomer et al., 2014; Yang et al.,

2014). Even though passive clearing requires a significantly increased clearing time (e.g., few

months for a whole mouse brain), immunolabelling seems to work best in samples that have been

passively cleared as opposed to ETC (http://wiki.claritytechniques.org).

1.6 Light-Sheet Fluorescence Microscopy Another important advancement in brain imaging was applying light-sheet fluorescence

microscopy to cleared brains (Dodt et al., 2007; Stefaniuk et al., 2016; Tomer et al., 2014). By

scanning the sample volume plane-by-plane instead of point-by-point, light-sheet allows for fast

imaging of large specimens with sufficient resolution for quantitative neuroanatomy (Silvestri et

al., 2015). It utilises a rapid and precise (high spatial and temporal resolutions) visualisation of

multiple fluorescently-labeled components at the tissue, cellular or molecular levels. Another

advantage of the light-sheet is the minimal imaging-related photobleaching (from

http://blogs.zeiss.com) (Selchow, 2013) (Fig. 5). Although light-sheet imaging provides essential

structural information, the images are not pristine and often contains dark stripes (see Chapter 2).

Such artifacts generically arise from either absorbing or scattering structures along the

illumination light path (Becker et al., 2008; Santi, 2011).

21

Figure 5. A-C. Layout of the light-sheet Z.1 fluorescence microscope. The objective lens and detection beam-path are perpendicular to the illumination beam-path. A laser light that is formed into a thin sheet of light illuminates the fluorescently-labeled tissue from either one or two sides. This illumination excites only fluorophores within the focal plane of the detection objective. All fluorescent signals are collected on a camera-based detector. D-E. The light-sheet is generated either statically by using a cylindrical lens or dynamically by high-frequency scanning of a laser beam. Reprinted by permission from Zeiss: https://www.zeiss.com/content/dam/Microscopy/Products/imaging-systems/Lightsheet%20Z1/photonik_intl_2013_01_044_HiRes.pdf

1.7 Statement of the Problem, Hypothesis and Objectives Following tooth extraction and endodontic treatments, many patients will suffer from orofacial

sensory and/or motor impairments for short or long term. While the underlying mechanisms are

unclear, novel data suggest that they may involve the orofacial primary motor cortex, the main

brain region involved in sensory-motor control and integration. Our group has shown that intraoral

manipulations in rodents, such as orthodontic treatment, tooth trimming or extraction, dental

implant surgery and acute noxious stimulation of the dental pulp, can induce functional changes

in the orofacial primary motor cortex and these changes may involve and be dependent on the

functional integrity of astroglial cells. Astroglia regulate neuronal function at synapses, and

astroglial process are directly connected with neurones, allowing bidirectional electrical and

metabolic signaling between neurones and astroglia. It is well documented that changes in

astroglial function are tightly coupled to changes in their morphology and in their expression of

22

GFAP. However, no study has tested whether endodontic treatment versus tooth extraction can

produce morphological changes in astroglial cells within the orofacial primary motor cortex.

Conventional immunohistochemistry uses a certain number of thin (μm) sections out of the whole

specimen. This may result in a loss of information and the inability to achieve 3D high-resolution

image of the cytoarchitecture of a whole few millimeter-thick brain tissue. Moreover, mounting

sections on slides renders the method irreversible and thus the slightest mistake in the process can

ruin the entire samples. Novel optical clearing techniques have been developed to overcome these

limitations. The Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-compatible

Tissue-hYdrogel (CLARITY) technique renders the brain optically transparent and allows for

high-resolution 3D cytoarchitectural visualisation of cellular morphology and spatial interactions

across different cell types within an intact, several mm-thick brain sections, and even a whole

intact mouse or rat brain. This technique has not been utilised previously in oral neurophysiology

research.

Better understanding of the role and involvement of astroglia in orofacial motor functions in

health and disease is of clinical significance since it can assist in the development of improved

therapeutic approaches of orofacial motor impairment such as targeting astroglia within the

orofacial motor cortex.

1.8 General Aim The general aim of the present thesis was to use an animal model and the novel CLARITY

technique for 3D characterisation of astroglial cytoarchitecture and quantification of

morphological changes in astroglial cells within thick brain sections of the orofacial primary

motor cortex of rats receiving tooth extraction or endodontic treatment.

1.9 Hypothesis Extraction but not endodontic treatment of three right maxillary molar teeth induces, within one-

week, changes in the morphological features of astroglial cells within the superficial layer I of the

rat orofacial primary motor cortex.

23

1.10 Specific Aims 1. To use 2 mm-thick coronal brain sections and optimise the novel CLARITY

immunohistochemistry technique to allow for 3D characterisation of astroglial and

neuronal cytoarchitecture and morphology within the superficial layers of the rat orofacial

primary motor cortex.

2. To test if endodontic treatment versus extraction of three right maxillary molar teeth can

induce within one-week changes in the morphological features of astroglial cells in the

superficial layer I of the rat orofacial primary motor cortex.

24

Materials and Methods

All experimental procedures were approved by The University of Toronto Animal Care

Committee, in accordance with the Canadian Council on Animal Care Guidelines and the

regulations of The Ontario Animals for Research Act (R.S.O 1990). The experiments reported

herein followed a strict standard protocol and all experimental procedures were carried out by the

same investigator to ensure consistency and uniformity of the procedures. Data analysis was

carried out in a blinded manner to reduce potential experimenter bias.

2.1 Animals The present study was carried out on young adult male Sprague-Dawley rats (Charles River,

Montreal, QC, Canada). Rats were 225-250 g upon arrival to the vivarium, and 300-340 g on the

day of perfusion. All rats received a basic health assessment upon arrival (weight, skin, eyes, teeth

and fur inspection). Consistent with our published (Avivi-Arber et al., 2010a, 2015b) and ongoing

studies, rats were single-housed (27 x 45 x 20 cm cages) to minimise social effects that might

mask treatment outcome (Devor et al., 2007; Seminowicz et al., 2009). The cages contained a

polyvinyl chloride tube (used as a shelter and a gnawing device) and were stored under the same

temperature (21 ± 1 °C) and humidity (50 ± 5 %) controlled conditions and a 12-hour light/dark

cycle (lights on at 07:00, off at 19:00 h). Consistent with our ongoing studies involving intraoral

manipulations, all rats received mash chow diet and water ad libitum to avoid postoperative

discomfort from biting on a hard diet and to ensure adequate food and drink intake. Consistent

with the literature and our previous studies, since transportation and changes in husbandry

environment are potentially stressful events that can significantly impact animals’ health and

function which may impact treatment effects on brain functions, all rats were subjected to a 7-day

acclimation period (Fig. 7). Rats were monitored daily to assess body weight, food consumption

and any change in their grooming, scratching or exploratory behaviour.

25

2.2 Study Groups and General Study Design

A total number of four rats were used to optimise the CLARITY and immunofluorescence

technique. A total number of 28 rats were used to test whether tooth extraction versus endodontic

treatments can induce, one week later, differential changes in the morphological features of

astroglial cells within the rat orofacial primary motor cortex. The one week time point was chosen

since previous studies have shown that animals develop postoperative perioral hypersensitivity

that peaks between postoperative day four and seven and thereafter subsides and returns to

baseline within 14 days (Lakschevitz et al., 2011).

To prevent allocation bias, rats were randomly allocated into control and experimental groups

(n=7/group). Rats of the extraction (‘Exo’) group received extraction of the three right maxillary

molar teeth and rats of the endodontic (‘Endo’) group received endodontic treatment in the three

right maxillary molar teeth. Rats of the ‘Sham’ group received the same general anaesthesia and

mouth opening as the Exo and Endo groups but without actual tooth extraction or pulpectomy.

Rats of the ‘Naïve’ group received no treatment and no anaesthesia. Consistent with previous

studies and to reduce postoperative pain and inflammation, rats received analgesics and anti-

inflammatory drugs for the first three postoperative days. Rats were perfused on postoperative

day seven (Fig. 6). Brains were extracted and thereafter 2 mm-thick coronal sections containing

the orofacial motor cortex went through clearing and subsequent immunohistochemistry

procedures to label astroglial cells. We also immunolabelled cellular nuclei and neuronal nuclei

to assist in identifying the superficial layer I. 3D imaging was carried out with a light-sheet Z1

fluorescence microscope (Carl Zeiss, Jena, Germany) (20x CLARITY objective). Images were

then processed with Bitplane Imaris software to automatically identify and quantify

morphological features of astroglial processes.

26

Figure 6. Experiment time-line. Rats were monitored on a daily basis from the date of arrival at the vivarium until perfusion day. Weight (yellow arrow) was measured on arrival, after acclimation period and on the day of perfusion. Treatment (endodontic treatment, tooth extraction or sham operation) were carried out following a 1-week acclimation (green band). Analgesics and anti-inflammatory drugs were administered up to three days postoperatively (pink band). Perfusion was performed on day 7 after treatment (blue band).

2.3 Animal Experiments

2.3.1 Anaesthesia and Aseptic Procedures

All surgical procedures were carried out under standard aseptic surgical conditions with

isoflurane/oxygen for general anaesthesia (1-3% Isoflurane; 1L/min mixed with O2)

supplemented with local infiltration of lidocaine hydrochloride 0.1 ml, 2% in 1:100,000

epinephrine (Lignocaine, Lignospan standard®, Septodont, Ontario, Canada) injected to the labial

and palatal sides of the three right maxillary molar teeth. Pulse oximeter monitoring verified that

the heart rate and oxygen saturation levels were within a physiological range (i.e., 333–430

beats/min, 90-100% O2). A controlled heating pad (Model 73A, YSI, Ohio, USA) maintained the

rat core temperature at 37–37.5°C, and their eyes were treated with a lubricating ophthalmic

ointment (Alcon®, Novartis, Canada). All the instruments used during the procedures were

sterilised in an autoclave at 121o C.

2.3.2 Tooth Extraction, Pulpectomy and Sham Operations

Dental surgeries and sham operations were carried while the animal was under general anaesthesia

(see above), lying in a supine position with a mouth being kept opened by pulling down the 2

mandibular incisors with a dental floss. The tongue was fixed to the left cheek with a tape (Fig.

7A). The surgical area was wiped using a cotton applicator soaked with 0.12% chlorhexidine

27

gluconate (Peridex®, 3M ESPE, Canada), and a gauze was placed at the back of the throat to

protect the rat from any aspiration. Thereafter, a local anaesthetic was injected into the palatal

gingivae and buccal vestibule. All surgical procedures were carried out with the aid of an optical

magnification of 4.5x using dental loupes (Orascoptic, Middleton, WI, USA).

2.3.2.1 Tooth Extraction

The marginal gingiva around the three right maxillary molar teeth was gently detached. Then, the

teeth were luxated using modified dental instruments (Avivi-Arber et al., 2015b, 2017).

Hemostasis was achieved by applying pressure to a sterile gauze pressed over the extraction

sockets for a few minutes (Fig. 7C).

2.3.2.2 Endodontic Treatment

Surface disinfection of the three maxillary molar teeth was carried out with 2.5 % sodium

hypochlorite. The area was kept dry by continuous suctioning and application of a cotton roll to

the buccal vestibule. For dental pulp extirpation, occlusal access cavities were drilled using a low-

speed handpiece and a LN 25 carbide bur (Dentsply Maillefer, Ballaigues, Switzerland). Root

canals were identified and cleaned using a filing motion with K-files #10; 21 mm long, bent at

2.5 mm from the tip, (Dentsply Maillefer, Ballaigues, Switzerland) and irrigated with 2.5%

NaOCL under continuous suction (BabySmile S-502 Nasal Aspirator). When there was no more

bleeding from the canals, final irrigation with 2.5 % sodium hypochlorite for 1 minute per tooth

was performed (Fig. 7D). Canals were dried with paper points and the pulp chamber was filled

with an aqueous paste of calcium hydroxide (Vista Dental Products, Racine, WI, USA). The

access cavity was sealed with IRM dental filling (Dentsply Maillefer, Ballaigues, Switzerland).

2.3.2.3 Sham Operation

Sham rats had exactly the same surgical operation as rats of the Exo and Endo groups including

general and local anaesthesia, analgesics and anti-inflammatory drugs, and mouth opening for 30-

60 min, and kept for a similar period of time that was used for the pulpectomy and extraction

28

procedures of the Exo and Endo groups. However, no actual tooth extraction or endodontic

treatment was carried-out in Sham rats.

Figure 7. A. Mouth opening. B. Maxillary molar teeth. C. Extraction sockets of right maxillary molar teeth. D. Access cavities for dental pulp extirpation of right maxillary molar teeth. E. Radiographic image of the right maxillae showing maxillary molar teeth after pulpectomy and restoration of access cavity with a temporary filling material. F. Radiographic image of the right maxillae showing extraction sockets.

2.3.2.4 Postoperative Care

After the surgical operation, rats were placed back into their cage under a heat lamp and monitored

for 30 mins to ensure complete recovery from the general anaesthesia. Rats are known to develop

periapical inflammatory changes after pupal extirpation (Holland, 1995). Whereas after tooth

extraction they may develop postoperative perioral hypersensitivity that peaks between

postoperative day 4 to 7 and thereafter subsides and returns to baseline within 14 days

(Lakschevitz et al., 2011). Therefore, to reduce postoperative pain and inflammation following

the surgical operations, buprenorphine hydrochloride (0.05 mg/kg, s.c., Buprenex, Reckitt

Benckiser Healthcare Ltd, USA) and ketoprofen (5 mg/kg, .c., Anafen ® Injection, Boheringer

Ingelheim, Canada) were administered subcutaneously every 8–12 h during the first three

postoperative days. This postoperative care procedure was consistent with previous studies

(Avivi-Arber et al., 2010a, 2015b; Avivi-Arber et al., 2017). Consistent with previous studies,

rats recovered uneventfully following the endodontic treatment (Erausquin and Muruzabal, 1967;

1968; 1969) and tooth extraction surgery (Avivi-Arber et al., 2015b). Following the operations,

rats showed a normal feeding, grooming, scratching and exploratory behaviours, and a normal

mean of daily rate of body weight gain.

29

2.4 The CLARITY Immunhistochemistry Technique All the procedures described below and summarized in Figure 8 were adapted from the CLARITY

Protocol developed by Karl Deisseroth’s Lab at Stanford University (Deisseroth, 2017; Engberg,

2014). Some modifications were introduced to optimise tissue-clearing and immunolabelling of

astroglial cells as well as neurones within the orofacial primary motor cortex, our region of

interest.

2.4.1 Hydrogel Monomer Perfusion-Infusion General anaesthesia was induced with Ketamine HCl (175 mg/kg, Ketaset®, Ayerst Veterinary

Laboratories, Ontario, Canada; I.M) and Xylazine (25 mg/kg, Rompun®, Bayer, Ontario, Canada).

A deep state of anaesthesia was confirmed by the lack of a twitch in response to a strong pinch of

the hindlimb. The rat was then placed on its back on the dissection pad in a supine position. A

transverse incision was made with scissors first through the skin just below the ribs and then

through the abdominal wall and ribs. Care was taken not to damage large blood vessels or organs

such as the lungs and liver. The pericardium was gently detached from the heart. The anterior wall

of the chest was raised and flipped backwards to keep the heart exposed. A metal perfusion needle

with a ball tip was inserted through the apex of the left ventricle into the aorta. When placed

correctly, the tip of the perfusion needle was visible through the transparent wall of the aorta. The

needle, just below the ball tip, was then secured to the aorta wall with a silk suture. Then, the right

atrium was cut open and 200 mL of ice-cold (4 °C) 1X PBS solution wasere perfused with a

peristaltic pump (10 ml/min, ~5 - 10 min) through the needle and the right aorta to clear all blood

from the capillaries in the brain and other body tissues. This step was followed by perfusion

(10ml/min, ~5-10 min) of 200 ml of ice-cold fixative hydrogel solution (Fig. 8, Table 1).

Adequate perfusion was confirmed by the appearance of a pale-color liver and a stiff tail

(http://wiki.claritytechniques.org).

30

Figure 8. Overview of the CLARITY technique. Step 1- Hydrogel monomer perfusion-infusion: An optically transparent porous matrix composed of formaldehyde (red), acrylamide and bisacrylamide (hydrogel) monomers (blue), and thermally-triggered initiators, is perfusion-infused into the brain tissue at 4 oC. The formaldehyde forms crosslinks with the tissue, and covalent links (electron sharing) between the hydrogel monomers and tissue-proteins, nucleic acids and other biomolecules. Step 2- Hydrogel tissue embedding: At 37 oC, the tissue-bound monomers polymerise and create a hydrogel mesh–tissue hybrid that provides physical support to tissue structure. Step 3- Passive clearing of membrane lipids: Passive clearing removes lipids and molecules that remained unbound to the hydrogel. While detergent (sodium dodecyl sulfate, SDS) micelles diffuse passively through the tissue, they capture and clear out lipid of the tissue. The hydrogel–tissue hybrid keeps biomolecules and fine cytoarchitectural features of the brain intact, including neuronal and glial proteins. Despite clearing, some light-scattering remains due to heterogeneous distribution of proteins and nucleic acid complexes in the hybrid. Step 4- Standard immunolabelling of cells or molecules. Step 5- Optical clearing and refractive index matching: Immersion in 2,2'-thiodiethanol (TDE) solution for: optical clearing; tissue shrinkage to compensate for clearing-induced tissue expansion; refractive index homogenization. Step 6- Image acquisition: Light-sheet microscopy to visualise cells in intact thick tissue. Adapted by permission from Springer Nature: Nature Methods. CLARITY for mapping the nervous system, Chung, K; Deisseroth, K, Copyright (2013) (Chung and Deisseroth, 2013).

31

Table 1. List of Solutions, ingredients and manufacturer.

Formalin and acrylamide are toxic and irritant chemicals. ❌Sodium dodecyl sulfate (SDS), boric acid and TDE are irritant chemicals, therefore all experimental steps utilising these chemicals were carried-out in a fume hood with appropriate personal protective equipment (i.e., gloves, lab coat, safety glasses, and shield).

2.4.1.1 Brain Dissection

Immediately following the perfusion, the fixed brain was extracted from the skull. The skin,

connective tissue and muscles surrounding the skull were cut and removed with scissors and a

rongeur instrument, the first spinal vertebrae was cut out, the spinal cord was cut with the tip of

Use/ Solution Ingredients Manufacturer Perfusate Saline Solution.

- 200 mL (for 1 rat)

1X PBS – 200 mL

Life Technologies

Fixative and substructure Hydrogel Solution.

- 400 mL (for 2 rats)

Acrylamide (40% v/v) - 40 mL Bis-Acrylamide (2% v/v) - 10 mL Buffered Formalin Sol. 10% v/v - 100 mL VA-044 Initiator - 1 g (0.25 w/v) 10 X PBS - 40 ml Deionised water - 210 ml

Bio-Rad Bio-Rad EM Sciences WAKO BioShop

Storage Phosphate Buffered Saline Triton (PBST) 1 L (for 40 brains)

PBS 1X - 1L Triton-X 100 0.1% v/v - 1mL Sodium Azide - 0.1% w/v - 1 gr

Life Technologies BioShop Sigma

Clearing Buffer Solution - 10 L (for 56 brains)

Boric Acid - 123.66 g Deionised water - 2L Sodium hydroxide (NaOH)

– adjust pH to 8.5 Sodium dodecyl sulfate (SDS)❌

– 4% w/v-400mg Deionised water - up to 10 L

BioShop BioShop Invitrogen

Buffer Wash Phosphate Borate Triton (PBT)

- 1L (for 6 brains)

Boric acid - 12.5g ❌ Deionised water - 1L Sodium hydroxide (NaOH)

– adjust pH to 8.5 Triton-X 100 0.1% - 1 mL Sodium Azide 0.1% w/v - 1 g

BioShop BioShop BioShop Sigma

Refractive Index Matching & Optical Clearing 30% 2,2′-Thiodiethanol (TDE ❌

- 100 mL (for 4 brains) 63 % TDE ❌

- 100 mL (for 4 brains)

TDE – 30 mL PBS 1X – 70 mL TDE 63 mL PBS 1X 7mL

Sigma Life Technologies Sigma Life Technologies

32

fine scissors at the level of C2, then the rongeur was used to fracture the zygomatic arches, remove

the auditory meatuses, and then to gently remove the skull from around the brain starting at the

ventral surface of the skull, then going lateral and rostral. Then the brain was gently lifted to allow

for optical chiasm transection and trimming of any dura connecting the brain to the skull.

Thereafter the olfactory nerves were transected, and the brain was gently lifted and removed out

the skull. Special care was taken not to damage the motor cortical areas.

In addition, the rat maxillae were collected into 50 ml Falcon conical tubes containing 10 ml of

10% buffered formalin solution for radiographic evaluation of extraction sites and periapical

tissue (Fig. 7 E, F).

2.4.1.2 Hydrogel Tissue Embedding

Each brain was placed in a 50 ml conical Falcon tube containing 25 mL of ice-cold hydrogel

solution and stored at 4 °C for 7 days to allow further diffusion of the hydrogel solution into the

brain tissue.

2.4.2 Hydrogel Tissue Hybridisation

The Falcon tube with a loosened lid was placed in a desiccation chamber (in a fume hood) hooked

up to a carbon dioxide tank and a vacuum pump (two Falcon tubes at a time). A vacuum was

applied to the chamber for 20 minutes to remove all oxygen (i.e., ‘degassing’) which was then

replaced with inert 100% carbon dioxide gas flowing into the chamber for three minutes. Then,

the Falcon tube was quickly sealed to prevent reintroduction of oxygen. The tube was submerged

in a temperature-controlled 37oC water-bath for 3-4 hours to polymerise and crosslink the

hydrogel matrix.

After polymerisation, the gel was peeled off from the brain with a lint-free tissue paper

(KIMTECH Science®, Kimberly-Clark, Canada) and stored individually in a labelled 50 mL

Falcon tube with PBST solution until ready for sectioning. A mark was made to the right side of

the brain to differentiate it from the left side. We used macroscopic anatomical features of the

brain to determine the location of the orofacial primary motor cortex, corresponding to Swanson’s

33

atlas location ~2 – 4 mm anterior to Bregma (see Chapter 1 Fig. 2) (Swanson, 2004). The 2-

millimeter thick coronal sections containing the orofacial primary motor cortex were cut with a

vibratome 3000 (Model 3000, TPI, Missouri, USA). Each 2-mm thick section was stored in 50 ml

Falcon tube with 25 ml of PSBT solution (Table 1) until ready for passive tissue-clearing.

2.4.3 Passive Tissue-Clearing of Membrane Lipids

Passive clearing of membrane lipids from each of the 2 mm-thick coronal section was carried-out

by sequential immersions in a clearing solution (Table 1) within a 50 mL Falcon tube placed on

a 3D Rotator platform (30 RPM, LAB-LINE) and incubated at 45 °C. The section was first washed

in 50 mL clearing solution for one day, and then for additional two days in fresh clearing solution

to remove excess of formalin, initiator, and hydrogel monomers. Subsequently, 50 ml of fresh

clearing solution was changed every two days. The clearing was checked visually by holding the

container up to the light until all lipids solubilised rendering the tissue completely transparent

(i.e., ‘see-through’ tissue) for microscopy (Engberg, 2014) (Fig. 9). Clearing took approximately

15 days.

Figure 9. A. A whole brain after hybridisation. Dotted lines mark the region of 2 mm-thick coronal section containing the orofacial primary motor cortex. B. Rostral view of a 2 mm-thick coronal section. C. Rostral view of a 2 mm-thick coronal section after 7 days of passive clearing. D. Rostral view of a 2 mm-thick coronal section following ~15 days of clearing; the tissue appears clear and ‘see-through’. Notice the significant increase in the size due to swelling that occurred during the passive clearing.

2.4.3.1 Buffer Wash and Storage

Following clearing, each section was placed in 50 mL buffer wash made of Phosphate Borate

Triton (PBT) solution (Syed et al., 2017) (Table 1) in a Falcon tube placed on a 3D rotator platform

34

(30 RPM, LAB-LINE) at room temperature to wash out SDS micelles. The PBT was replaced

three times per day for two days, and thereafter, the sections were stored in PBT solution at 4 °C

until tissue labelling.

2.4.4 Immunolabelling: Optimisation Protocol for Whole-Tissue

The focus of this step was to optimise the immunolabelling of astroglial cells with a specific glial

fibrillary acidic protein (GFAP) antibody to allow for subsequent characterisation and

quantification of morphological features of astroglia within 2 mm-thick cleared motor cortex brain

sections (Table 2) (Bastrup and Larsen, 2017; Bignami and Dahl, 1977; Chung and Deisseroth,

2013; Chung et al., 2013; Costantini et al., 2015; Eng et al., 2000; Garcia-Cabezas et al., 2016;

Tomer et al., 2014) (http://wiki.claritytechniques.org/index.php/Immunostaining). In addition, we

used and optimised immunolabelling of a neuronal nucleus marker (NeuN) that is known as a

Fox-3 protein, which is expressed exclusively by neurones and plays a role in regulating neuronal

cell differentiation and nervous system development (Kim et al., 2009). NeuN is conventionally

applied to distinguish astroglia from neurones and was used in this study assist in delineating the

cortical layer I (Gusel'nikova and Korzhevskiy, 2015; Mullen et al., 1992).

We also used and optimised the immunolabelling with 4′,6-diamidino-2-phenylindole (DAPI),

which is a blue-fluorescent DNA stain that is commonly used as a nuclear counterstain in

fluorescence microscopy. DAPI has high affinity for DNA and has been used, for example, to

count cells and sort them based on DNA content, or to measure cell apoptosis.

We have used Alexa Fluor-conjugated antibodies as primary antibodies that are already directly

conjugated to a fluorophore-coupled secondary antibody, thus eliminating the need for incubating

the primary antibody with a secondary antibody. This simplified and shortened the

immunolabelling process since there was no secondary antibody incubation step, needing fewer

washing steps. Conjugated antibodies are also cheaper. In addition, to save on material and

incubation time, in the optimisation process we used 200 μm-thin coronal sections.

2.4.4.1 Whole-Tissue Immunolabelling Protocol

The 2 mm-thick sections were cut in the midline to separate the left and right hemispheres. Only

the left hemispheres contralateral to the dental manipulation side were collected for

35

immunolabelling since it has previously been documented that while orofacial muscles and tissues

have bilateral representations within the orofacial motor cortex, the contralateral representations

are significantly more predominant. Moreover, unilateral orofacial manipulations, such as tooth

extraction, induce functional neuroplasticity mainly within the contralateral orofacial motor

cortex (Adachi et al., 2007; Avivi-Arber et al., 2010b, 2015b).

Brain sections were transferred into new 50 ml Falcon tubes containing 0.5 mL PBST solution of

1:70 (7.1µl) anti-GFAP antibody conjugated to Alexa Fluor® 488, anti-NeuN antibody

conjugated to Alexa Fluor® 555 and DAPI (Table 2). Tubes were placed on a rotating platform

(at 30 RPM) and incubated at 37 °C for 6 days. Tissue sections were then washed in PBST at

37 °C for 6 days, changing PBST twice during working hours (i.e., 9 am and 6 pm). From this

stage forward, the Falcon tubes were tightly covered with aluminum foil to protect the

fluorescence antibodies from light and prevent fading (photobleaching) of the fluorophores.

Antibodies come in small amounts within small vials that were centrifuged before aliquoting to

ensure all the material was at the bottom of the vial available for use.

Table 2. List of conjugated antibodies used for immunolabelling.

Antibody Target Manufacture Catalog number

Wavelength Excitation (nm)

Wavelength Emission (nm)

Concentration/ 500 µL PBST

Anti-Glial Fibrillary Acidic Protein (GFAP)

Alexa Fluor® 488 Conjugate

Astroglial filaments

Sigma MAB3402X 493 (Green)

519 (Green)

1:70

7.1 µL

Anti-NeuN clone A60 Alexa Fluor® 555

Conjugate

Neuronal nuclei

Sigma MAB377A5 555 (Red)

565 (Red)

1:70 7.1 µL

4,6-Diamidino-2-

phenylindole dihydrochloride (DAPI)

Nucleic acid all cell

nuclei

AAT Bioquest

17510 (AAT) 356 (Blue)

461 (Blue)

1:70 7.1 µL

2.4.5 Optical Clearing and Refractive Index Matching

A transparent brain tissue immersed in a solution of the same refractive index as its internal

refractive index will appear invisible. Thus, the refractive index of the brain section had to be

36

equilibrated to that of the imaging immersion medium, which in turn had to be matched as closely

as possible to the refractive index of the imaging objective (Richardson and Lichtman, 2015). The

objectives of the light-sheet Z1 fluorescence microscope (Carl Zeiss, Jena, Germany) have a

refractive index 1.45 which is suitable for imaging cleared tissue at a high-resolution.

FocusClear is a recommended immersion solution in the original CLARITY protocol, and in

particular for thick-tissue sections like a whole mouse brain. FocusClear has shown to provide the

optimal optical transparency and maximum imaging depth (Tomer et al., 2014). However, it is an

extremely expensive solution ($180 USD/ 5 ml). Other more affordable solutions with a RI of

~1.45, such as glycerol 87% (Tomer et al., 2014) and 63% 2,2′-thiodiethanol (TDE) (Costantini

et al., 2015; Jensen and Berg, 2017), can also be used but only for imaging thin tissue sections (<

1- 2 mm thick) or for a small imaging depth (http://wiki.claritytechniques.org). Thus, glycerol and

TDE were tested in this study to obtain the best tissue transparency and maximum imaging depth.

GFAP- and NeuN-labelled sections went through serial incubations in series of TDE or glycerol

solutions (Table 3).

For glycerol, the sections were incubated in different concentrations of the solution incrementally.

First, the brain section was placed in 50 mL 25% (vol/vol) glycerol in 1X PBS (Glycerol/PBS)

and stored in a Falcon tube on a 3D rotating platform (30 RPM) at 37 °C for 1 day (~24 hrs).

Then, the sample was transferred to a new Falcon tube containing 50 mL 50% (vol/vol) glycerol

in 1X PBS and stored in the same conditions as before. Lastly, the sample was transferred to a

new Falcon tube containing 87% (vol/vol) glycerol in 1X PBS and stored at the same conditions

as before and imaging was performed the following day (Tomer et al., 2014).

(http://wiki.claritytechniques.org/index.php/Solutions). With glycerol, the sections remained

visually cloudy and this resulted in less penetration depth and less image quality.

For TDE, the sample was immersed in 50 mL of 30% (vol/vol) TDE in 1X PBS (TDE/PBS) (pH

7.5) and stored in a Falcon tube placed on a 3D rotating platform (30 RPM) at 37 °C. The section

remained in the 30% TDE until its internal region got saturated with TDE as evident by its sinking

to the bottom of the tube (~1.5 hrs). Then, the section was immersed in 50 mL 63% (vol/vol) TDE

in the same conditions as before and until the section sunk to the bottom of the tube (~1.5 hrs).

After immersion in TDE, the sections became completely transparent but acquired a yellow hue.

37

Sections also shrunk in TDE which appears to compensate for the swelling occurring following

tissue-clearing (Costantini et al., 2015; Epp et al., 2015).

We found that TDE, as compared with glycerol, provided a simpler and faster procedure for

refractive index matching and optical clearing, and it also allowed for acquiring images with a

deeper penetration depth and a higher resolution. Therefore, 63% TDE was used as the immersion

solution for this study.

To further minimise refractory index mismatch and subsequent optical errors such as spherical

aberrations (https://photographylife.com/what-is-spherical-aberration), and to improve the image

quality and penetration depth, before each brain imaging the refractive index of the immersion

solution (63% TDE) was checked with a refractometer to ensure it is within 1.45 ± 0.03 (Fig. 10).

Figure 10. Refractometer. Prior to the light-sheet imaging, a refractometer was used to ensure that the Refractive Index (RI) of the 63% TDE immersion solution matches the refractive index of the light-sheet imaging objective (i.e., 1.45).

Table 3. Testing options for optical clearing and refractive index matching

Solutions Volume Concentration Rotation Temperature Time

Glycerol/PBS 50 mL 25% 30 RPM 37 °C 24 hrs


38


TDE/ 1X PBS 50 mL 30% 30 RPM 37 °C Until sunk to the bottom of

the tube (~1.5 hrs )

TDE/ 1X PBS 50 mL 63% 30 RPM 37 °C Until sunk to the bottom of

the tube (~1.5 hrs )

2.4.6 Whole Tissue Imaging

2.4.6.1 Mounting Cleared Tissue for Light-Sheet Microscopy

A glass capillary was glued with super-glue to the caudal side of the coronal section at a brain

region distant from the region of interest (i.e., orofacial primary motor cortex) and not within the

centres of light emission planes and objective (Fig. 12). The tip of the capillary was then mounted

to the microscope holder and the brain section was suspended from above into 63% TDE-filled

chamber. This chamber provided the brain section with a stable temperature environment

throughout the imaging process which took about 1/2 hour. For imaging the region of interest in

layer I, the orofacial primary motor cortex was imaged while the coronal slide was submerged

into the mounting solution facing its rostral aspect to the objective. Care was taken not to form air

bubbles in the chamber to avoid light scattering.

2.4.6.2 The Region of Interest

Based on previously published electrophysiology studies (Avivi-Arber et al., 2011b, 2017;

Awamleh et al., 2015) and Swanson anatomical atlas (Swanson, 2004) (Figs. 2, 11), the region of

interest included the superficial layer I at ~ 4 mm from the midline of the whole coronal section

(depicted with a red line) .

39

Figure 11. The region of interest (small yellow square) selected for scanning with the light-sheet 20X CLARITY objective spanned from the cortical surface at ~4 mm lateral to midline (red line) and included a total area of 438.9 μm x 438.9 μm x 1 mm.

2.4.6.3 Image Acquisition

A Zeiss light-sheet Z1 microscope was used for image acquisition with the following

specifications (Fig. 12):

Detection Optics: 20x/1.0 (CLARITY, RI=1.45)

Illumination Optics: 10x/0.2 x 2, 5x/0.1 x 2

Lasers: 405 nm (20mW), 488 nm (50 mW), 561 nm (20 mW), 638 nm (75 mW)

Camera: pCO Edge 5.5 x 2

Max Sample Dimensions: 10 x 10 x 20 (mm)

Field of View (20x): 439 x 439 (μm)

Software: Zeiss Zen Light-sheet 2014

Environmental Control: Zeiss (temperature/CO2)

40

Figure 12. A. A glass capillary is attached to the caudal aspect of the 2 mm-thick brain section. Red arrow is pointing at the area were the ROI is located. B. The glass capillary with the brain section are attached to the Zeiss light-sheet Z1 microscope and positioned in front of the camera (red arrow). C. Outside view of the Zeiss light-sheet Z1 microscope.

Images of the region of interest were acquired with a CLARITY objective (Clr Plan-Neofluor

20x/1.0, RI=1.45 (± 0,03), NA=1. Acquisition parameters were as follow:

Unilateral illumination: Since usually only the left- or right-side illumination provided a better

resolution image of the labelled neurones and astroglia, each plane was illuminated from either

the left or right light source and not both.

A separate track for each laser and camera color was used for each marker; GFAP (green 50),

NeuN (red 50) and DAPI (cyan).

Laser power range: 45- 90%

Exposure time: 29 – 129 ms

Computers used for image acquisition require very large storage space as well as large random-

access memory (RAM) for image processing. The storage space of each acquired image of 2 mm-

thick brain tissue was ~100 GB/scan. This storage volume was too large to be handled by the

computers available at our imaging facility. Therefore, we carried out 2 scans of the region of

interest which included 1 mm3 of the rostral aspect of the region of interest, and then 1 mm3 of

the caudal aspect of the region of interest. We here report data collected from the rostral aspect

only (i.e., ~60 GB/scan).

41

After imaging, the section was stored in PBST at room temperature protected from light.

2.4.7 Image Processing

Image analysis was carried out with Imaris Software 9.2.0 (Bitplane) for 3D reconstruction. The

Z- stacks acquired with the light-sheet microscope Z1 were converted from Zen (.czi) files to

Imaris (.ims) files using the Imaris File Converter x64 9.0.1 application. After background

subtraction and thresholding for the green channel that corresponds to GFAP positive cells

(GFAP+), a systematic region of interest delineating Layer I was cropped from the total volume

of the acquired image.

2.4.7.1 Identification of Layer I Cytoarchitectonic features were used to delineate the border between cortical layer I and layers

II/III. Layers II/III, as compared with layer I, were characterised with a significantly larger number

of NeuN positive (NeuN+) nuclei but only sparse GFAP immunoreactivity. In contrast, layer I

was characterised by a rich network of GFAP+ processes and sparse NeuN immunoreactivity.

The selected region of interest included layer I and excluded the glial limitans due to a

significantly higher GFAP immunoreactivity of the glial limitans that limited the software ability

to trace individual GFAP+ processes (Fig. 13).

2.4.8 Quantification of Morphological Parameters of Astroglial Processes Accurate morphological description of filamentous structures requires ultimate resolution to

capture the finest of structures of interest in our study, i.e., the astroglial processes. Therefore, the

Filament Tracer application of Bitplane Imaris, an advanced software for automatic detection of

filament-like structures, was used for morphometric analysis of astroglial processes in all spatial

directions (Fig. 13 B and C).

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Figure 13. A. 3D image of 1 mm-thick cortical tissue showing the features used to select the region of interest within layer I: the pia mater, composed of NeuN+ flat-shape nuclei (red), the glia limitans identified as a continuous layer of high intensity GFAP+ astroglial cells, cortical layer I is characterised by a rich network of GFAP+ processes while layers II/III below show a significantly larger number of NeuN+ nuclei and sparse GFAP+ cells. B. Illustrates the region of interest within layer I selected for subsequent morphometric analysis of GFAP+ processes. Bottom yellow line marks the approximate border between layer I and layers II/III. Top yellow line marks an approximate border between layer I and the glial limitans. C. Bitplane Imaris software masked the GFAP+ processes (white) within the region of interest for subsequent morphometric analysis.

The tracing was done by applying the threshold-based algorithm that is based on an absolute

intensity threshold of GFAP+ filamentous structures (processes). The analysis took approximately

8 hours per scan.

2.4.8.1 Morphological Parameters

Several statistic values were calculated automatically by the Imaris software and compiled in an

Excel Sheet. For the purpose of our study, values from seven parameters were collected. The term

‘Filament’ is given by the software to the filamentous structures (astroglial processes)

(http://www.bitplane.com/download/manuals/ReferenceManual6_1_0.pdf).

1. Filament Area: the sum of the generated surfaces of a frustum (truncated cone).

2. Filament Length (sum): the sum of the length of all filaments.

3. Filament mean diameter: the mean diameter within a filament. Each point of a filament

line has its individual measured diameter. The diameter is measured as the shortest

distance from the centre line to the surfaces defined by the lower threshold.

4. Filament volume: the sum of the volume of all edges (cones) which compose a filament

5. Filament straightness: h = the distance between two branch points. The filament

straightness is h per length of the filament.

43

6. Volume of the region of interest within layer I; use for subsequent normalization of the

length, surface area and volume of the astroglial processes.

Changes in the complexity of astroglial morphology were determined by calculating the

surface area/volume ratio from the data provided by the software.

2.5 Data Analysis and Sample Size Calculation The densely intermingled GFAP+ processes within layer I of the orofacial primary motor cortex

did not allow analysis of morphological features of GFAP+ processes per individual cell.

Therefore, data analysis was based on automatic software quantification of global morphological

features of GFAP+ processes within the region of interest.

Our published and recent studies indicate large effect size (21-25%) between groups in primary

outcomes. According to G*Power calculation, the minimum sample size required to obtain

statistically significant results for ANOVA test with 80% power and a= 0.05 is n = 7/group, and

for 4 groups a total of 28 rats. The outcome variables were transformed to obtain a normal

distribution. The independent variable was the study group, i.e., Endo, Exo, Sham or Naive. The

dependent variables were: sum of the total surface areas of all GFAP+ filaments, sum of the total

length of all GFAP+ filaments, filaments’ mean diameter, sum of the total volume of all GFAP+

filaments, and median filament straightness. The total volume (%), surface area, and length of

GFAP+ filaments were normalised by the region of interest. Sigma Plot 11 (Systat Software, San

Jose, CA, USA) was used to perform the statistical analysis. One-way ANOVA followed by the

post-hoc Duncan test determined whether the independent variable had an effect on any of the

independent variables. A p-value < 0.05 was considered a statistically significant difference. Data

are presented as means + SEM.

2.6 Excluded Data A total of 32 rats were initially included in the study however, data of 10 rats were excluded

because of animal death during the general anaesthesia (n=2), or inadequate perfusion (n=3)

(Table 4). Inadequate perfusion was associated with bright wide-diameter (> 6 µm) GFAP+

structures consistent with blood-filled blood vessels (Fig. 14 A,B) (Whittington and Wray, 2017).

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Accordingly, for the mean diameter parameter, all the values larger than > 6 µm were not included

for data analysis.

Additional 5 animals from the Naïve (n=3) and Exo (n=2) groups were excluded from the study

due to inadequate quality of the images acquired with the light-sheet microscope. Three images

had bright/ dark stripe artifacts which are a common occurrence in light-sheet microscopy (Power

et al., 2017) (Fig. 14 C,D). One Naïve rat was excluded due to a persistent technical problem with

the statistical data extraction in the Imaris software. Thus, this study reports on a total of 22 rats

with some groups having 5 rats.

Figure 14. A. 3D image of 1 mm-thick brain tissue from a rat that underwent inadequate perfusion and subsequent immunolabelling with GFAP marker in green. White arrows show >6 µm-thick GFAP+ structures consistent with blood-filled blood vessels (scale 100 μm). B. Enlarged insert from figure A. C and D. 3D image of 1 mm-thick brain tissue which underwent immunolabelling with GFAP marker in green. Image shows bright and dark stripe artifacts which are a common occurrence in light-sheet microscopy (scale 100 μm). C. A lateral view. D. A superior view.

45

Table 4. Summary of study groups, number of animals included or excluded from the study and

the reason for exclusion.

Experimental Group

Number of Animals

Included for analysis

Number of Animals

Excluded Reasons for exclusion

Naïve 5 3

- Two animals with bright/dark

stripe artifacts - One animal with unsolved

technical problem in statistical data extraction by Imaris software

Sham 6 2

- One animal with inadequate

perfusion and bright blood-filled blood vessel artifacts

- One animal died during general anaesthesia

Endo 6 2

- Two animal with inadequate

perfusion and bright blood-filled blood vessel artifact

Exo 5 3

- Two animals with bright/dark

stripe artifacts - One animal died during general

anaesthesia

Total

22 10

46

Results

In the present study, we have utilised the CLARITY technique to render 2 mm-thick rat coronal

brain sections optically transparent. We then utilised immunofluorescence labelling with antibody

markers specific to astroglial filaments (GFAP) and neuronal nuclei (NeuN). We subsequently

applied light-sheet microscopy for 3D imaging of a motor cortex region we have previously

defined as the centre of the rat orofacial primary motor cortex. By subsequently employing the

Bitplane Imaris software for 3D reconstruction and morphometric analysis of the GFAP- and

NeuN-labelled cells within the superficial layers I-III of the motor cortex we have identified their

laminar distribution and have also characterised morphological features of astroglial processes

within layer I of naïve rats and rats receiving tooth extraction, endodontic treatment or sham

operation.

3.1 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex

We have identified a laminar cytoarchitecture of the primary motor cortex demonstrated by NeuN-

and GFAP-immunoreactivity (i.e., NeuN+ and GFAP+, respectively). Fig. 15 C shows a 3D

image of a 438.9 µm x 438.9 µm x 1 mm brain tissue from a representative rat immunolabelled

with the NeuN and GFAP markers. The most superficial layer comprised a thin layer of NeuN+

flat-shape nuclei corresponding to the pia mater, i.e., the innermost layer of the meninges. The pia

closely apposed a continuous layer of high-intensity GFAP+ cell bodies and processes, which are

known as the glia limitans superficialis (glial limiting membrane) (also see Fig. 16). This

membrane also surrounds the perivascular space surrounding the cortical parenchymal blood

vessels and is referred to as the glia limitans perivascularis (Fig. 17). Immediately below the glia

limitans is cortical layer I, which comprised a dense network of GFAP + cell bodies and processes,

some of which project to the glia limitans. The immediately adjacent inner cortical layers,

corresponding to cortical layers II/III, comprised an abundant number of NeuN+ round-shaped

nuclei, significantly larger than the number of NeuN+ cells in layer I. In contrast, GFAP+ cells

appear to be significantly more abundant in layer I than in layers II/III. DAPI was able to label (in

blue) nuclei within the cortex and nuclei of the Pia mater located above the glia limitans (Fig. 16

D and Fig. 18 A).

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Figure 15. A. A 2D image of a Nissl-stained coronal section through the orofacial sensory-motor cortex of a Sprague Dawley rat at ~ 3 mm anterior to Bregma. Superimposed are the jaw (red) and tongue (blue) motor representation areas as we have previously mapped and documented. B. A schematic diagram obtained from Swanson’s Atlas of the Rat Brain). Reprinted with permission from John Wiley and Sons, Journal of Comparative Neurology, Brain maps 4.0 - Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps, Swanson L, Copyright (2004) (Swanson, 2004), which corresponds to the histological section in A, indicating the different cortical layers numbered with Roman numerals from superficial to deep (I-VI). C. A 3D image of a 438.9 µm x 438.9 µm x 1 mm (scale 50 μm) brain tissue showing the superficial cortical layers I and II/III as well as the pia mater and glia limitans. White arrow pointing at the pia mater, composed of NeuN+ flat-shape nuclei (red). Juxtaposing below the pia is the glia limitans (white arrow), which comprises a continuous layer of high intensity GFAP+ astroglial cell bodies and processes. (GFAP+: immunoreactive glial fibrillary acidic protein; NeuN+: neuronal nuclei).

48

Figure 16. A. Superior view of glia limitans superficialis showing high-intensity GFAP+ cells (green) (soma and processes). Superior view of a blood vessel (white arrow) penetrating the cortex; and NeuN+ neuronal nuclei (red) (scale 50 μm) B. Lateral view of a blood vessel (white arrow) penetrating the cortical parenchyma surrounded by GFAP+ astroglial cells (green) forming the glia limitans perivascularis; NeuN+ neuronal nuclei are marked in red (scale 50 μm). C. Schematic representation of the superficial membranes of the cortex showing that the glia limitans (green) lies between the pia mater and the cerebral cortex. D. 40 µm thick image showing GFAP + cells (green) within the superficial layer of motor cortex forming glia limitans, DAPI (blue) labelling of any nucleus within the cortex and the pia mater above the glia limitans (scale 50 μm).

49

Figure 17. A. GFAP+ cells covering the cortical surface area form the glia limitans superficialis and GFAP+ cells surrounding blood vessels form the glia perivascularis. B. Enlarged insert from Figure A showing the glia limitans perivascularis (scale 50 μm).

50

Figure 18. A. A 3D image of a 1 mm-thick cortical tissue showing cells immunolabelled with GFAP (GFAP+, green), a specific marker of astroglial cytoskeleton, NeuN (NeuN+, red), a specific marker of neuronal nuclei, and DAPI (blue), a non-specific marker of cell nuclei. B. Same image as in A showing GFAP+ cells. C. Same image as in A showing NeuN+ cells (scale 100 μm).

51

3.2 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment

Tooth extraction (Exo group), had a significant effect on the diameter of astroglial processes

within the orofacial primary motor cortex. The mean diameter of astroglial processes of rats in

the Exo group was significantly smaller than that of rats in the Naïve and Sham groups (ANOVA

F3,21=4.10 p= 0.022; post hoc Duncan’s p=0.005, Sham: p= 0.028, respectively) and small, but

not statistically significant, than that of rats in the Endo group. In contrast, the mean diameter of

astroglial processes of rats of the Endo group was similar to that of rats in the Naïve and Sham

groups (post hoc Duncan’s p=0.148, 0.569, respectively), and was larger, but not statistically

significant than that of rats in the Exo group (post hoc Duncan’s p=0.066) (Fig. 19 A).

Tooth extraction, but not endodontic treatment, also had a significant effect on the straightness of

astroglial processes. In comparison to Naïve and Sham groups, in the Exo group the astroglial

processes were significantly straighter (ANOVA F3,21=3.77 p= 0.030; post hoc Duncan’s p=0.011,

0.032, respectively) (Fig. 19 B).

Figure 19. Mean diameter (A) and straightness (B) of astroglial processes. Diameter data is presented as group-means and SEM; Straightness data is presented as group-medians and SEM. Tooth extraction was associated with a significantly smaller diameter and straighter astroglial processes.

52

No significant differences were found across the study groups in the volume, surface area to

volume ratio, and length of astroglial processes (ANOVA, p > 0.050) (Fig. 20).

Figure 20. A. Percent volume of all GFAP-labelled cells. B. Ratio of surface area to volume of all GFAP-labelled cells. C. Total length of all GFAP-labelled processes. Data presented as group-means and SEM.

53

Discussion

This study has successfully applied, for the first time, the novel CLARITY (Clear Lipid-

exchanged Acrylamide-hybridised Rigid Imaging-compatible Tissue-hYdrogel) technique to

clear a 2 mm-thick section of the orofacial primary motor cortex of adult male Sprague-Dawley

rats. With subsequent immunohistochemistry of the optically cleared brain section and the aid of

light-sheet microscopy, we have successfully obtained, for the first time, large-volume high-

resolution 3D images of astroglia and neurones within the superficial layers (I-III) of a cortical

region we have previously identified as the centre of the orofacial primary motor cortex. This

study has also applied, for the first time, the Imaris software to automatically quantify

morphological features of astroglial processes and test the effects of endodontic treatment versus

tooth extraction on these morphological features. Our novel findings suggest that tooth extraction

has a statistically significant effect, one week later, on the morphological features of astroglial

cells within the superficial layers of the rat orofacial primary motor cortex. Our results indicate

that in comparison with Naïve rats and sham-operated rats, tooth extraction is associated with

thinner and straighter astroglial processes. On the other hand, endodontic treatment has no

statistically significant effect on the morphological features of astroglial cells. The mean diameter

and median straightness of astroglial processes within the primary orofacial motor cortex of rats

receiving endodontic treatment were similar to those in naïve rats and those in rats receiving sham

operation. As discussed below, the differential effects of tooth extraction versus endodontic

treatment on the morphological features of astroglia within the orofacial primary motor cortex

may reflect differences in the rat sensory-motor function and functional adaptation (or

maladaptation) to changes in orofacial sensory-motor functions induced by these treatments.

4.1 3D Visualisation of Astroglia with CLARITY Astroglia communicate with each other and with neurones through an extensive network of

processes that span within and through different regions and layers of the brain (Kettenmann et

al., 2008; Verkhratsky and Butt, 2013; Verkhratsky and Nedergaard, 2018). Exploring their

complex anatomy and connectivity requires 3D imaging of intact thick brain tissues. Conventional

immunohistochemistry relies on a selective selection of a certain number of thin sections

measured in a few μm and up to several tens of μm out of a whole brain specimen. This

unavoidably results in a loss of information and an inability to achieve 3D high-resolution images

54

of complex cytoarchitecture that spans a few millimeters or even centimeters within thick brain

tissues or even the whole brain. Moreover, conventional immunohistochemistry is an irreversible

process involving mounting of brain sections on slides. Thus, the slightest mistake in the process

can ruin the whole sample or even a whole experiment. It also does not allow for re-staining or

additional staining. The CLARITY technique, however, can overcome all these limitations of the

conventional technique. CLARITY is based on the creation of a hydrogel scaffolding that

stabilises the brain tissue and allows for membrane lipids to be removed without losing structural

details and antigenicity of the tissues therein. This results in an intact, optically-transparent brain

tissue that is permeable to large molecules and their chromophores including cellular antibodies

for immunofluorescence labelling. It also facilitates 3D imaging of cells within a whole brain or

thick tissue sections. In addition, there is no need for irreversible mounting, and the cleared tissue

samples can be stored for months and go through multiple rounds of immunostaining with

different fluorophores, which is particularly useful for multiplexing beyond the limits of spectral

separation (i.e., using various fluorophores that absorb and emit light in different parts of the

visible spectrum in order to detect multiple molecules in a tissue) (Miller et al., 2016; Tomer et

al., 2014). In the present study we used and optimised immunostaining with Anti-GFAP, which

is a standard and specific marker of astroglial filaments (Bastrup and Larsen, 2017; Bignami and

Dahl, 1977; Chung and Deisseroth, 2013; Costantini et al., 2015; Eng et al., 2000; Garcia-Cabezas

et al., 2016; Tomer et al., 2014) We also used Anti-NeuN, which is a standard and specific marker

of neuronal nuclei (Gusel'nikova and Korzhevskiy, 2015; Kim et al., 2009; Mullen et al., 1992),

and DAPI, which is a blue-fluorescent stain of nuclear DNA in any cell. Thus, the present study

has successfully applied for the first time the CLARITY technique to optically clear a 2 mm-thick

sections of the orofacial primary motor cortex and has successfully optimised immunostaining of

astroglial cells as well as neurones and cell nuclei.

The novel light-sheet microscope allows for high-speed and high-resolution 3D imaging of a few

millimeters- to a few centimeters-thick intact cleared tissues. Thus, the light-sheet microscopy

can exploit the CLARITY potential for 3D imaging of large populations of cells with complex

cytoarchitecture spanning millimetres or even centimeters within an intact brain tissue (Dodt et

al., 2007; Silvestri et al., 2015; Stefaniuk et al., 2016; Tomer et al., 2014). However, these images

generate an enormous amount of data that cannot be quantified manually. The Bitplane Imaris

software can overcome this problem by allowing automatic identification and quantification of

some morphological features of cells in the brain. Noteworthy is that the present study is the first

55

to utilise the Imaris software for automatic identification and quantification of morphological

features of astroglial processes with the superficial layer I of a 2 mm thick section of the orofacial

motor cortex.

4.2 3D Characterisation of Astroglial and Neuronal Cytoarchitecture and Morphology within the Superficial Layers of the Rat Orofacial Primary Motor Cortex

Our study is the first one showing large-volume (~0.5 x 0.5 x 1 mm3) high-resolution 3D images

of the highly organised laminar cytoarchitecture of the superficial layers of the orofacial primary

motor cortex. Our findings are consistent with the findings of published studies that have utilised

conventional immunohistochemistry and histology. Of particular note is the abundance of

neuronal nuclei within layers II/III and their sparse distribution in layer I. In contrast, the highly

organised astroglial cells are dispersed in layers II/III but abundant in layer I and form a dense

network of processes, some of which project to the most superficial layer of the cortex known as

the glia limitans superficialis (glial limiting membrane). Indeed, other studies have shown that in

cortical layers II and III, the mean astroglia-to-neuron ratio is approximately 1∶5 (Fleischhauer

and Vossel, 1979; Kalman and Hajos, 1989; Takata and Hirase, 2008) and there is 1.6 times higher

density of astroglial cells in layer I than in layers II and III (Takata and Hirase, 2008).

The finding of NeuN+ flat cells in the pia mater corresponds with previously published studies

showing that the meninges, including the pia mater, harbour neuronal precursor cells (Bifari et

al., 2015; Nakagomi and Matsuyama, 2017). Moreover, the pia mater is a highly vascularized

layer (Adeeb et al., 2013) and therefore, the presence of NeuN+ cells in the pia mater might

correspond to the vascular innervation of blood vessels (Pigolkin Yu et al., 1985). Interestingly,

nowadays, it is accepted that the only intracranial structure associated with pain perception (e.g.,

headache) is the dura mater that is innervated by neurones exhibiting properties characteristic to

nociceptors found in other body tissues (Messlinger et al., 2008; Strassman and Levy, 2006).

Nevertheless, recent observations during intracranial brain surgeries in awake humans suggest

that in fact cerebral vessels and the pia mater are sensitive to mechanical stimuli that can induce

acute pain perception in orofacial regions innervated by the trigeminal nerve (Fontaine et al.,

2017, 2018).

56

The glia limitans superficialis is a continuous layer composed of astroglial soma and a dense

meshwork of astroglia processes that are firmly attached to an outer basal lamina that makes

intimate contact with cells of the pia mater (Karasek et al., 2004; Liu et al. 2013). Astroglial

processes tightly ensheath the blood vessels that penetrate into the cortical parenchyma. This

nearly-complete coverage of blood vessels through abundant astroglial endfeets is known as the

‘glia limitans perivascularis’. The glia limitans superficialis is continuous with the glia limitans

perivascularis and together they play a role in the control of the blood-brain barrier (Quintana,

2017). In addition, the perivascular endfeet can release vasoactive substances that can mediate

cerebral ‘functional hyperemia’, i.e., the increased or decreased cerebral blood flow associated

with increased or decreased neuronal activity (Dunn and Nelson, 2014; MacVicar and Newman,

2015).

The finding of a rich network of astroglial cells within the superficial layers of the orofacial

primary motor cortex supports previously published data (Awamleh et al., 2015) suggesting that

superficial astroglial cells are involved in modulating motor cortex functional neuroplasticity (i.e.,

decreased excitability) induced by acute noxious stimulation of the dental pulp. This study has

shown that the application of an astroglial inhibitor to the surface of the orofacial primary motor

cortex can reverse the neuroplasticity induced by the noxious stimulation (Awamleh et al.,

2015). While in this study the exact cortical site of action of the astroglial inhibitor is unclear, it

likely diffused into the cortex to exerted its effects, at least in part, on the astroglial cells within

the superficial cortical layers.

While the present study utilised the CLARITY immunohistochemistry in 2 mm-thick brain tissue

to explore morphological features of marginal astroglial cells within layer I of the orofacial

primary motor cortex, most of the available studies exploring astroglial structure and morphology

have used mice and not rats as well as monkeys and human, and have characterised protoplasmic

astroglia within layer II – VI of different cerebral cortical regions (Miller et al., 2016; Oberheim

et al., 2008, 2009; Rodriguez et al., 2009; Sun and Jakobs, 2010; Wilhelmsson et al., 2004). In

addition, the majority of these studies have utilised the conventional immunohistochemistry

technique using small (mm) and thin (40µm) brain sections which contain only a few astroglial

cells and utilised immunolabelling with different markers of astroglial cells (e.g., S-100, Glt,

ALDA1L, GFAP), high-magnification (60x) imaging techniques and subsequent manual

quantification of morphological features such as total diameter of the labeled astroglia, number of

57

processes, the length of the processes, and the diameter of the soma or the thickest astroglial

process. Therefore, we could not have made any comparison with published data. We have found

that the mean diameter of astroglial processes within layer I ranged from 0.46 – 4.00 µm and the

Mean + SEM was 1.71 + 0.15 µm. Oberheim et al. found in mice that the diameter of the thickest

process measured 2.6 µm + 0.2 µm (Oberheim et al., 2009).

In a recently published study, Miller and Rothstein (Miller et al., 2016) have utilised the

CLARITY technique in transgenic mice expressing the astroglial proteins glutamate transporter

(Glt1) and tdTomato-astros, and further immunolabelled with GFAP. By using single- and multi-

photon microscopy to image 0.5- to 1.0 mm-thick brain tissue, they have characterised the laminar

distribution of the different astroglial markers. However, they have not provided any details

related to the cytoarchitecture and morphological features of the rich network of GFAP+ astroglial

processes within the cortical layer I.

4.3 Morphological Features of GFAP-Immunoreactive Processes: Effects of Maxillary Molar Tooth Extraction versus Endodontic Treatment

Tooth extraction, but not endodontic treatment, had a statistically significant effect on the

morphological features of astroglial cells within the orofacial primary motor cortex. In

comparison with naïve and sham-operated rats, in rats receiving tooth extraction, the astroglial

processes were significantly thinner (smaller mean diameter) and straighter, and they were also

thinner but not statistically significant than those in rats receiving endodontic treatment. There

were no statistically significant differences between rats receiving endodontic treatment and those

receiving sham operation or no treatment (i.e., the Naïve group).

The differences in the effects on cortical astroglial between tooth extraction and endodontic

treatment may be related to differences in the extent of tissue injury, sensory denervation and the

altered motor function. Following tooth extraction, there is major damage to hard and soft tissues

as well as a complete loss of sensory inputs due to the lack of occlusal contacts and the loss of

periodontal as well as pulpal tissues. In contrast, following endodontic treatment, the amount of

tissue injury is significantly smaller, and there is also only a partial loss of occlusal contacts with

no loss of periodontal ligament. Therefore, it is possible that the changes induced by the

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endodontic treatment were not significant enough to result in structural and morphological

changes in astroglial processes, which is consistent with the notion that motor cortex plasticity

emerges in response to significant changes in external factors or experiences including changes

in orofacial sensory-motor functions. However, these differences may also provide evidence that

the orofacial primary motor cortex has the capability to adapt and be modelled in a task-dependent

manner, but they may also suggest the existence of different underlying mechanisms (Ebner,

2005; Haydon et al., 2014; Monfils, 2005; Remple et al., 2001). It is also possible that the changes

induced by endodontic treatment were too small to be detected by our methods. It is important to

consider that the analysed data was underpowered and a large effect (21-25%) was contemplated

for this study (see below study limitations). Another possibility relates to the reliability of our

combined methods (Light-sheet microscope 20x objective and Imaris software) to accurately

image astroglial processes and identify and delineate their boundaries for subsequent analysis of

morphological features.

Similar study limitations to those described above may also account for our findings that neither

tooth extraction nor endodontic treatment had any significant effect on any of the other measured

variables, including volume (%), surface area (normalised), surface area to volume ratio and sum

length of astroglial processes.

Our findings of decreased dimensions of astroglial processes are consistent with a couple of

previously published studies. In a structural magnetic resonance study in rodents, molar tooth

extraction was associated with a significantly decreased volume of the orofacial primary motor

cortex region as well as other cortical regions involved in processing sensory and motor functions

(Avivi-Arber et al., 2017). Our findings are also consistent with electrophysiological studies

showing that molar tooth extraction is associated with decreased jaw and tongue motor

representations in the orofacial primary motor cortex (Avivi-Arber et al., 2015b).

To our best knowledge, no other study has utilised the CLARITY immunohistochemistry to test

the effects of intraoral injury on the morphological features of astroglia within the most superficial

layer I of the orofacial primary motor cortex. Nevertheless, the findings of the present study

appear to be in contradiction to the study by Laskawi et al., who have used conventional

immunohistochemistry in rats who underwent transection of the facial motor nerve that supplies

motor innervation to the facial muscles and vibrissae. The facial nerve transection was associated with

59

increased immunoreactivity of various astroglial antigens in layers I/II and III/V of the primary motor

cortex including S-100 protein which is a Ca2+-binding protein located mainly in the astroglial

cytosol, GFAP which is a cytoskeletal filament protein, as well as connexin 43 which is a gap junction

protein. The increased immunoreactivity occurred within 1 hour following the nerve transection and

lasted for 2 to 5 days (Laskawi et al., 1997). The difference between their findings and ours may be

due to the amount of peripheral injury, type of injured neural structure (motor vs sensory) or the

postoperative time when these changes were sampled.

The findings of the present study of thinner and straighter astroglial cells post-extraction also

contradict the notion that peripheral (e.g., nerve injury) and central (e.g., brain injury) injuries or

neurological diseases (e.g., stroke), always induce astroglial reactivity that manifests in

hypertrophy (i.e., reactive astroglia) within cortical (e.g., sensory and motor cortex) and

subcortical (e.g., brainstem) brain regions. These hypertrophic changes result in upregulation of

GFAP expression, increased volumes of soma and processes and increased immunoreactivity of

astroglial antigens including GFAP. Nevertheless, such changes depend on many factors

including the type of injury and its severity, and brain region (Bernardinelli et al., 2014; Cheung

et al., 2015; Childers et al., 2014; Genoud et al., 2006; Liddelow and Barres, 2015; Miller et al.,

2016; Oliet et al., 2001; Perez-Alvarez et al., 2014; Sun and Jakobs, 2012).

The contradicting findings reported in the present study as compared with those reported by other

studies may be related to different study designs such as animal species, type and location of the

injury, as well as the follow-up time since it has been documented that different brain mechanisms

are involved at different points of time. It may also be related to the types of

immunohistochemistry, imaging and data analysis techniques that were applied in the different

studies.

4.3.1 Clinical Implications It is now clear that astroglia not only provide metabolic support to neurones, but they also play an

integral and essential role in maintaining and participating in neuronal synaptic activity. Astroglia

release and remove neurotransmitters to and from the synaptic cleft, they can also provide

neuronal support and impact synapse formation and synaptic pruning and help maintain blood

flow and blood-brain barrier (Liddelow and Barres, 2015). Significant to the present study,

60

peripheral (e.g., nerve injury) and central (e.g., brain injury) injuries as well as neurological

diseases (e.g., stroke), have been associated with astroglial plasticity manifested as changes in the

structure and function of astroglial cells. Such changes can have a rapid or slow onset and last for

a short duration and/or chronically and may subsequently enhance or impede recovery of sensory-

motor functions following injury or disease (Bernardinelli et al., 2014; Cheung et al., 2015; Chung

and Deisseroth, 2013; Genoud et al., 2006; Liddelow and Barres, 2017; Miller et al., 2016; Oliet

et al., 2001; Perez-Alvarez et al., 2014). However, little is known of the involvement, role and

underlying mechanisms of motor cortex astroglia in mediating neuronal response and sensory-

motor behaviour to peripheral injury including following intraoral injury such as tooth extraction

and/or pulpectomy. Nevertheless, this information is of clinical significance since patients

receiving endodontic treatment or tooth extraction develop postoperative sensory-motor

impairments such as pain and limited or altered jaw movement and altered biting forces (for

reviews see Avivi-Arber et al., 2011d, 2018; Sessle et al., 2013a; Trulsson et al., 2012a).

Moreover, in a significant number of patients these acute impairments may develop into chronic

sensory-motor conditions such as chronic orofacial pain, phantom bite or occlusal dysaesthesia

(Hara et al., 2012; Kelleher et al., 2017; Marbach and Raphael, 2000; Melis and Zawawi, 2015;

Nixdorf et al., 2012; Polycarpou et al., 2005). For example, in 5-12% of the patients undergoing

endodontic treatment and in 3% of the patients receiving tooth extraction, acute pain develops

into a chronic pain condition (Nixdorf et al., 2010b,c; Polycarpou et al., 2005). Thus, a better

understanding of the mechanisms underlying the development, maintenance and resolution of

these conditions is crucial for the development of improved therapeutic strategies that target, for

example, astroglial processes.

4.4 Study Limitations and Future Directions The present study has successfully utilised the CLARITY immunohistochemistry technique in 1-

2 mm-thick brain tissue to characterise cytoarchitecture features of astroglia and neurons within

the superficial layers of the orofacial primary motor cortex as well morphological features of

astroglial processes, and to quantify the effects of tooth extraction versus endodontic treatment on

these features.

The CLARITY immunohistochemistry is a multi-step technique that requires significant

optimisation and thus a large number of factors may affect the accuracy of the outcome. These

61

include quality of the fluorescence images that can be affected by the adequacy of the animal

perfusion, degassing the hydrogel solution to generate as little as possible air bubbles within the

tissue, volumetric changes in the tissue after clearing, the quality and concentration of the

antibodies and their ability to penetrate the full thickness of the brain section to achieve a high

signal-to-background noise ratio and minimise nonspecific antibody binding. In the present study,

although we have strictly adhered to the protocol for all brain samples, technical problems have

precluded the inclusion of all animal samples in the final data analysis, which may have affected

the statistical power.

In general, statistical power is affected by effect size of the intervention and the size of

the sample used to detect effect of treatment. In the present study, a large effect size (21-25%)

was estimated based on our previously published studies, and it is possible that the effect of

endodontic treatment was smaller than the proposed effect size. Due to the exclusion of some rats

from all four groups and the reduction of the sample size to 6 or even 5 animals per group, it is

possible that the study did not have enough power to detect small changes induced by endodontic

treatment.

Another limitation of the study is the use of only one marker of astroglial cells. It is known that

antibodies against GFAP label only the main processes of astroglial cells that contain intermediate

filaments, and it does not label the fine distal processes. It has been suggested that GFAP

delineates only approximately 15% to 20% of the total volume of astroglial cells in the cortex

(Sun and Jakobs, 2012; Verkhratsky and Butt, 2013). Therefore, the use of only one marker of

astroglia may have underestimated the effect of treatments on finer branches of the studied

astroglia, as well as the 3D features quantified in this study. Nevertheless, GFAP is a specific and

well-documented marker of astroglial cells that is conventionally used for immunohistochemical

identification of astroglial cells and for characterisation of morphological changes occurring

following peripheral or central injuries (McKeon et al., 2018; Sofroniew et al., 2010).

Another important limitation to consider is that when excited, red blood cells emit fluorescence

within a wide range of wavelengths including the wavelength of the chromophore used in the

present study to stain GFAP+ cells (488 nm). Therefore, it is difficult to distinguish between fine

blood vessels and astroglial cells (Whittington and Wray, 2017).

62

A common drawback and limitation of the light-sheet microscopy is the appearance of dark and

bright artifactual stripes in the 3D images. These artifacts result from the unilateral illumination

of the brain sections and the existence of optical obstacles (e.g., bubbles) that obscure the light-

sheet and result in light scattering and/or absorption. Since such artifacts could have affected the

accuracy of the morphometric analysis, brains with such artifacts were excluded from the present

study (see Chapter 2).

The use of only male rats precluded any assessment of possible sex differences. Sex differences

were previously documented in rats and humans in the effects of orofacial injury on sensory and

motor functions (Cairns et al., 2001, 2002, 2003; Komiyama et al., 2005). Future studies could

make use of both male and female rats to investigate possible sex differences in the effects of

endodontic treatment and tooth extraction on the morphological features of astroglial cells within

the orofacial primary motor cortex.

Future studies with a larger number of animals that can investigate possible structural changes

following intraoral treatment at different postoperative time points and different cortical and

subcortical brain regions. Thereby add further insights into the differential spatial-temporal

regulation of GFAP after endodontic treatment and tooth extraction.

Enabling scientists to obtain high-resolution volumetric images of thick cleared tissue and the

ability to quantify morphometric features of astroglial cell will likely yield groundbreaking

findings that would improve our understanding of astroglial plasticity in health and disease.

63

Conclusions

Considering the crucial role that astroglia play in supporting and modulating neuronal activity in

health and disease, and since injury and disease can induce rapid and chronic changes in astroglial

structure and function which can either facilitate or impede sensory-motor recovery, developing

novel methods to study astroglial structure is of paramount importance in neurophysiology

research. Thus, our modified and optimised CLARITY immunohistochemistry technique along

with our automatic Imaris software analysis protocol provide a novel tool to characterise astroglial

morphology and plasticity in health and following injury or in disease.

Our novel findings of the laminar organisation of astroglia and neurones within the orofacial

primary motor cortex and that tooth extraction, but not endodontic treatment, produces significant

changes in morphological features of astroglial processes, will facilitate pursuing future research

directions to address the role of astroglia within the orofacial primary motor cortex in normal and

pathological conditions. They also suggest that astroglial cells are a new and promising target for

improved therapeutic interventions and prevention of impaired sensory-motor functions induced

by injury or disease.

64

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