The role of microRNA

in zebrafish central nervous system

regeneration

Jez Supreme

Experimental and Regenerative Neurosciences, School of

Animal Biology

This thesis is presented for the degree of Master of

Philosophy at The University of Western Australia,

August 2016

2

Abstract

Zebrafish have the ability to regenerate damaged parts of their central nervous system

and regain functionality. However, the molecular and cellular mechanisms involved

remain unclear. Here we test the hypothesis that gene regulatory mechanisms,

specifically microRNAs, are instrumental in orchestrating regenerative responses in

zebrafish. We used microarrays to analyse and integrate the mRNA and microRNA

(miR) expression profiles of zebrafish retina after optic nerve crush to identify potential

regulatory mechanisms that underpin central nerve regeneration. We used bioinformatic

analysis to identify candidate miRs and selected miR-223 for further analysis. In order

to downregulate miR223 we injected an inhibitor (i-miR), scrambled control, or vehicle

into the zebrafish eye immediately following an optic nerve crush. For proof of

principle, we validated the efficacy of miRNA injection for miR-223 by quantifying the

expression of miR-223 and its gene targets 2 days post injury. For all injection groups

(miR223, scrambled, vehicle), we assessed retinal ganglion cell axon regeneration

(distance and density) at two time points (3 and 7 days post-injury) using

immunohistochemistry. qPCR revealed the miR-223 inhibitor to be target-specific,

resulting in downregulation of miR223 levels and of target genes at 3 days post crush.

In addition, there appeared to be a delay in RGC axon regeneration with axons in the

miR injected groups failing to cross the chiasm. The density of RGC axons in the optic

tract was also reduced compared to controls at 3 days. However, for all fish, injection of

the inhibitor did not alter the distance reached by regenerating RGC axons at 7 days

post crush. Our results remain inconclusive about the role for miR-223 in zebrafish

RGC regeneration. However, the specificity of the miR targeting technique provides a

framework for future studies to investigate not only the cellular processes required for

CNS regeneration, but also how these mechanisms might be regulated to promote

successful repair and return of function in the injured mammalian brain.

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Table of contents

ABSTRACT 1

ACKNOWLEDGEMENTS 6

STUDENT CONTRIBUTION DECLARATION 7

CHAPTER 1: LITERATURE REVIEW 8

1.1 CENTRAL NERVOUS SYSTEM 8 1.1.1 OVERVIEW 8 1.1.2. CNS DAMAGE 9 1.1.2.1. CNS Injury 9 1.1.2.2. Early phase vs. Secondary injury 10 1.1.2.3. Neurodegenerative Disease 10 1.2. SPONTANEOUS NEUROREGENERATION IN VERTEBRATES 11 1.2.1. OVERVIEW 11 1.2.2. THE OPTIC NERVE AS CNS MODEL 12 1.2.3. OPTIC NERVE REGENERATION IN VERTEBRATES 13 1.2.4. FACTORS PREVENTING SPONTANEOUS NEUROREGENERATION IN MAMMALS 14 1.2.5. ADVANCES IN STIMULATING SPONTANEOUS MAMMALIAN NEUROREGENERATION 16 1.3. PROCESSES LINKED WITH NEUROREGENERATION 17 1.3.1. INFLAMMATION 17 1.3.2. DEVELOPMENT AND REGENERATION 18 1.4. MICRORNAS AND GENE REGULATION 18 1.4.1. THE C-VALUE PARADOX 18 1.4.2 MIRNA 19 1.4.3. MIRNA NUMBER INCREASES IN LINE WITH NEURAL COMPLEXITY 20 1.4.4. MICRORNA IN NEUROREGENERATION & DEVELOPMENT 21 1.5. MODEL SPECIES IN STUDIES OF OPTIC NERVE REGENERATION 22 1.5.1 ZEBRAFISH 22 1.5.2. RATS 23 1.6. RATIONALE OF THE THESIS 23 1.7. AIMS 25 1.8. CONCLUSION AND SIGNIFICANCE 26

CHAPTER 2: METHODS 28

2.3. EXPERIMENTAL DESIGN AND ANIMAL NUMBERS 28 2.4 LNA OLIGONUCLEOTIDES 29 2.5 OPTIMISATION OF THE INJECTION PROTOCOL 30 2.6 INTRAVITREAL INJECTION – FINAL PROTOCOL 31 2.7 EYE AND RETINA REMOVAL FOR RNA EXTRACTION 32 2.8 RNA AND MIRNA EXTRACTION 32 2.9 MIRNA QUANTIFICATION 33 2.10 MRNA QUANTIFICATION ERROR! BOOKMARK NOT DEFINED. 2.11 FISH PERFUSION AND DISSECTION FOR IMMUNOHISTOCHEMISTRY 35 2.12 CRYOSECTIONING 37 2.13 IMMUNOHISTOCHEMISTRY 38 2.14 MEASUREMENT OF REGENERATION 40

CHAPTER 3: RESULTS 42

3.1 SHORT TERM PROOF OF PRINCIPLE STUDY 42 3.2 LONG TERM REGENERATION STUDY 45

CHAPTER 4: DISCUSSION 47

4

4.1. AN INSUFFICIENT CHANGE IN MIRNA EXPRESSION. 47 4.3. LACK OF ACCURACY IN MEASURING REGENERATION, DUE TO POOR TISSUE QUALITY. 48 4.4. CONTEXT AND SIGNIFICANCE OF MY STUDY 49

REFERENCES 56

Table of Figures

FIGURE 1.2. PRELIMINARY MICROARRAY DATA OF RETINAL CHANGES

IN BOTH ZEBRAFISH AND RAT. 24

FIGURE 2.1: MIR-223 EXPRESSION – CONCENTRATION OPTIMISATION 30

FIGURE 2.2: MIR-223 EXPRESSION - INJECTION TRIAL 31

FIGURE 2.3: VENTRAL VIEW OF THE ZEBRAFISH BRAIN 36

FIGURE 2.4: LAYOUT OF OPTIC NERVE FOR CRYOSECTIONING 37

FIGURE 2.5. METHOD OF TECTUM MEASUREMENTS 41

FIGURE 3.1: AXON REGENERATION 7 DAYS POST-OPTIC NERVE

CRUSH 43

FIGURE 3.2: REGENERATING AXONS 7 DAYS POST-INJURY 45

FIGURE 3.2. EXTENT OF REGENERATION 7 DAYS AFTER CRUSH 46

List of Tables

TABLE 2.1: SUMMARY OF ANIMAL NUMBERS USED IN THE STUDY 29

TABLE 2.2: MIRNA REVERSE TRANSCRIPTION (RT) MASTER MIX 34

TABLE 2.3: MIRNA PCR CYCLE PROGRAM 34

TABLE 2.4: MIRNA QPCR MASTER MIX 35

TABLE 2.5: MIRNA QPCR CYCLE PROGRAM 35

TABLE 2.6: TARGET GENE RT MASTER MIX ERROR! BOOKMARK NOT

DEFINED.

TABLE 2.7: TARGET GENE PCR CYCLE PROGRAM ERROR! BOOKMARK

NOT DEFINED.

TABLE 2.8: MIR-223 TARGET GENES ERROR! BOOKMARK NOT DEFINED.

TABLE 2.9: TARGET GENE QPCR MASTER MIX ERROR! BOOKMARK NOT

DEFINED.

5

TABLE 2.10: TARGET GENE QPCR CYCLE PROGRAM ERROR! BOOKMARK

NOT DEFINED.

TABLE 3.1: QUALITATIVE ANALYSIS OF REGENERATING AXONS IN

DISTANCE AND DENSITY 44

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Acknowledgements

First, and most importantly, I need to give more thanks than I can ever express to my

primary supervisor, A/Prof Jenny Rodger. Through all the trials and tribulations of this

work she has never been anything but utterly, utterly supportive, intelligent, creative,

kind and generous with her time, expertise and support. Similarly, A/Prof Kim Carter

not only shepherded me through the perils of my honours year, but also introduced me

to Jenny and massively contributed to this project coming together. Without him, none

of this could have happened. Thanks also must go to the esteemed and impressive

Winthrop Professor Alan Harvey for his expert viewpoints in discussion of this project;

both in its initial stages and in critical assessment of its flaws. There were many people

at EaRN who helped this work come together. Specifically, a large measure of thanks

goes to Marissa Penrose, whose help with so many of the technical aspects cannot be

understated, and to Carole Bartlett & Michael Archer – thank you for being available to

assist me in the laboratory whenever I needed the help. So much of this project was

built on the work of others: Jenny, Kim & Alan of course, but also on the work of

masters student Jenny Ilgen and, absolutely critically and most of all, Paula Fuller-

Carter, whose brainchild this must rightly be called.

To my fellow students, all of whom are so much more talented and driven than I: kudos

to you. Particularly to Kalina Makowiecki, who made being her officemate not only a

joy, but a continual source of inspiration as she worked tirelessly in her own doctoral

work.

My candidature was financially supported by an Australian Postgraduate Award &

UWA top-up scholarship, and I was grateful to receive a travel grant from the school of

Animal Biology to travel to the Australian EMBL Symposium in my first year to learn

from some of the most impressive scientists in the country.

Finally, I must give my most heartfelt thanks to my partner and the love of my life:

Nicole. You have been a source of strength, friendship, inspiration and support. I have

no idea where I would be without you, but I would be so much the worse for your

absence from my life. You are my everything.

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Student contribution declaration

The examination of the thesis is an examination of the work of the student. The work

must have been substantially conducted by the student during enrolment in the degree.

Where the thesis includes work to which others have contributed, the thesis must

include a statement that makes the student’s contribution clear to the examiners. This

may be in the form of a description of the precise contribution of the student to the work

presented for examination and/or a statement of the percentage of the work that was

done by the student.

In addition, in the case of co-authored publications included in the thesis, each author

must give their signed permission for the work to be included. If signatures from all the

authors cannot be obtained, the statement detailing the student’s contribution to the

work must be signed by the coordinating supervisor.

Chapter 1: Literature review.

This literature review was written by the student with feedback from and discussion

with his supervisors.

JZ contribution: 100%

Chapter 2: Methods

The methods section includes data on qPCR analysis of miRNA levels performed by a

German exchange student Ms Jennifer Illgen. Ms Illgen, Ms Paula Fuller-Carter and Ms

Marissa-Penrose-Menz assisted with surgical procedures and animal monitoring.

JZ contribution: 75%

Chapter 3: Results

Results were collected and analysed by JZ with assistance from German exchange

student Ms Jennifer Illgen for the 3 day regeneration timepoint.

JZ contribution: 80%

Chapter 4: General discussion

This chapter was written by the student with feedback from and discussion with his

supervisors.

JZ contribution: 100%

Student Signature

………………………………………………………………………………………….

Coordinating Supervisor Signature.

..……………………………………………………………………

8

Chapter 1: Literature review

1.1 Central Nervous System

1.1.1 Overview

The Central Nervous System (CNS) in vertebrates consists of the brain and the spinal

cord. The brain is the seat of cognition, emotions, and sensorimotor processing

(Fahrback, 2013) and the spinal cord, made up of axons and nerve cells, carries

information between the brain and the rest of the body to control function (Watson,

Paxinos, & Kayalioglu, 2009). The CNS is therefore the foundation on which our

essential selves are built; the conduit and storehouse for both our behavioural and

cognitive biology. Thus, its normal functioning is of prime importance to human health.

Following damage, however, the adult CNS has an extremely limited ability to

regenerate (Huebner & Strittmatter, 2009; Ramon & Cajal, 1928). A major hallmark of

CNS injury and disease is long-term disability, which severely impacts not only on the

affected individuals, but the wider economy (Access-Economics, 2007, 2009; Findley,

2007). The ability to induce regenerative properties in the adult CNS would be

incredibly important to the human civilisation.

In this introduction, I will explore the variability of spontaneous CNS regeneration

within the vertebrate phylum, and review how phylogenetic comparative investigation

can be used to identify the key molecular mechanisms underpinning differences in

regenerative capacity. This will be done through the use of molecular biology,

bioinformatics and neuroscience, in order to identify possible mechanisms through

which we may successfully induce neuroregeneration in mammals.

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1.1.2. CNS damage

1.1.2.1. CNS Injury

Damage to the CNS, such as traumatic brain injury, cerebral ischemia, and Spinal Cord

Injury (SCI) is a major cause of death and disability in the adult population (Feigin,

2005; Javouhey, Guérin, & Chiron, 2006; Wyndaele & Wyndaele, 2006). Whether

acquired through insult or disease, CNS injury is not only a leading cause of major

human suffering, but also significantly impacts the economy through the need for

increased care, complex treatments, and the loss of ability to work. In the U.S.A. alone,

270 000 people live with spinal cord injury (SCI) and ~12 000 new injuries are reported

annually (DeVivo, 2012). This is not a small concern: worldwide, approximately 2.5

million people live with SCI and 130000 new cases are reported each year (Thuret,

Moon, & Gage, 2006).

In 2007, acquired brain injury severe enough to limit participation in the workforce was

reported to affect 1 in 45 of all Australians, with more than 75% of the affected below

the age of 65 (Disability in Australia, Disability in Australia: acquired brain injury,

2007). While most SCI occurs in those aged 18-35, in that same year 20,000 children

were reported to have suffered an acquired brain injury, and the increasing lifespan of

the population has been associated with increasing incidence of acquired brain injury

due to falls (Bramlett & Dietrich, 2004; Sun et al., 2011). While the long-term economic

and social costs of CNS damage are high, the impact on the individual is far more

severe; there are few options left to someone suddenly robbed of their ability to walk or,

in the case of quadriplegics, to even move their arms (Disability in Australia, Disability

in Australia: acquired brain injury, 2007).

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1.1.2.2. Early phase vs. Secondary injury

Beyond the initial insult to the CNS, such acquired damage can often lead to secondary

injury (reviewed in Oyinbo, 2011). The early phase of injury is marked by disruption of

the blood-brain barrier, reduced or altered blood flow, as well as neuronal and/or glial

damage (Bramlett & Dietrich, 2004). The secondary phase brings increased

inflammation, which can often lead to additional damage and further cell death

(National Center for Injury Prevention and Control, 2001; Hinson, Rowell, & Schreiber,

2015; Liverman, Altevogt, Joy, & Johnson, 2005; Wyss-Coray & Mucke, 2002).

1.1.2.3. Neurodegenerative Disease

In addition to acquired injury through damage, more than 600 disorders are known to

affect the nervous system (Brown, Lockwood, & Sonawane, 2005). Neurodegenerative

disorders are those hereditary and/or sporadic conditions characterised by progressive

worsening nervous system dysfunction (reviewed in Brown et al., 2005). Often

associated with atrophy of the central or peripheral structures, they include conditions

such as Alzheimers disease and multiple sclerosis (Saba Sheikh, Safia, Ejazul Haque, &

Mir, 2012). While their aetiology differs from directly acquired injury, the mechanisms

share some overlap, such as through inflammation leading to secondary damage, and an

increased rate of neuronal cell death (Hinson et al., 2015; Oyinbo, 2011; Wyss-Coray &

Mucke, 2002). As of 2012, such neurodegenerative diseases afflict more than 30 million

people worldwide (Saba Sheikh et al., 2012).

These diseases are usually age-dependent, meaning that increasing lifespans across the

world are contributing to a rising prevalence (Khoo & Kopan, 2004; Roser, 2015;

Tzourio et al., 1997). This is an especially pertinent fact in regards to densely populated

countries in which the standard of living (and therefore both health and life expectancy)

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are rapidly increasing, such as in China and India (Banister, Bloom, & Rosenberg,

2010; Panigrahi, 2014).

The economic costs generally increase in line with disease severity. In the UK, the

impact of Parkinson’s disease in 2007 alone is estimated to be somewhere between 449

million and 3.3 billion pounds (Findley, 2007; Morrow, 2014). While Parkinson’s

disease is the second most common neurodegenerative disease, the impact of more than

600 NDs worldwide is clearly huge.

1.2. Spontaneous neuroregeneration in vertebrates

1.2.1. Overview

Within the vertebrate phylum there is a range of complexity in the construction of the

CNS. Interestingly, there appears to be an inverse relationship between neurocomplexity

and spontaneous neuroregeneration (Figure 1) (Beazley & Dunlop, 2000; Kaslin, Ganz,

& Brand, 2008). The teleost fish, whose CNS architecture is some of the simplest within

the vertebrates, show a strong ability to regenerate from injury, being capable of adult

neurogenesis and regeneration in the brain and other parts of the CNS (Kaslin et al.,

2008).

Figure 1.1. Spontaneous neuroregeneration within vertebrates is inversely

correlated with relative neurological and evolutionary complexity.

Fish recover almost completely from crush injury to the optic nerve, and are

demonstrated to have significant and spontaneous regeneration from major spinal cord

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injury (Beazley & Dunlop, 2000; Becker, Wullimann, Becker, Bernhardt, & Schachner,

1997; Zupanc & Sîrbulescu, 2011). Reptiles and amphibians, which possess

intermediate neurocomplexity, show intermediate levels of spontaneous regeneration

(Beazley & Dunlop, 2000; Dunlop et al., 2004). Mammals, which possess the most

complex vertebrate CNS architecture, show the least ability to spontaneously

neuroregenerate; CNS injury results only in the induction of brief, abortive and

ultimately unsuccessful regenerative processes (Ferguson & Son, 2011; Huebner &

Strittmatter, 2009; Silver & Miller, 2004).

1.2.2. The Optic Nerve as CNS model

Investigating the CNS is inherently difficult, as any damage to this integral system can

preclude survival. The optic nerve, however, is a part of the CNS that does not present

this issue.

Anatomically and developmentally, the optic nerve is an extension of the central

nervous system; it may not be the proverbial window to the soul but does provide an

excellent view of the CNS (London et al., 2012). The optic nerve exhibits CNS

characteristics: host to specialized immune responses similar to those in the brain and

spinal cord (London et al., 2012), a failure to exhibit robust regeneration in mammals, in

possession of a blood-brain barrier and containing non-neuronal supporting cells (Berry

et al., 2008). Further, the architecture and cell-type functionalities of retinal neurons

have been well defined over decades of investigation, mutations and injuries to the

visual system are non-lethal under laboratory conditions (which permits detailed

phenotypic examination) and the retina is relatively easy to access (reviewed in

Sundermeier and Palczewski, 2012). Finally of particular benefit to this phylogenetic

work, the physical architecture, histology, circuitry and biochemistry is highly

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conserved among most vertebrates (Chan et al., 2009; Fadool & Dowling, 2008; Lamb,

Collin, & Pugh, 2007; Mahony, Corcoran, Feingold, & Benos, 2007).

1.2.3. Optic nerve regeneration in vertebrates

For the teleosts, such as goldfish and zebrafish, axotomy of the ON leads to complete

regeneration of the RGCs and a return to full function (Matsukawa, Arai, Koriyama,

Liu, & Kato, 2004). In zebrafish ON transection, the regenerating RGCs completely

traverse the tectum 25 days post-transection (Kaneda et al., 2008). Within 7 days,

regenerating axons have begun to traverse the anterior part of the tectum and at least

partial recovery of visual function is recovered as early as 14 days post-injury (Kaneda

et al., 2008). In a crush model, over 90% of axons are reported to reach the tectum

within the first week post-injury (Zou, Tian, Ge, & Hu, 2013). By contrast, in mammals,

such rats and humans, there is almost no spontaneous regeneration (Berkelaar, Clarke,

Wang, Bray, & Aguayo, 1994; Gao et al., 2012). In rat ON axotomy through

transection, most RGCs survive to 5 days post-injury, however they then experience a

massive die-off, with around 50% RGC death by 7 days post-injury (Berkelaar et al.,

1994). Axotomy through ON crush results in most RGCs apoptotically dying by

approximately 2 weeks after injury and no return to function or notable regeneration

(Villegas-Perez, Vidal-Sanz, Rasminsky, Bray, & Aguayo, 1993).

Regeneration of the optic nerve in vertebrates follows the same trend as the overall

CNS, in that there remains an inverse correlation between neurocomplexity and

spontaneous regeneration. Following optic nerve damage, zebrafish and amphibian

regeneration is robust (Beazley and Dunlop, 2000; Zupanc and Sîrbulescu, 2011).

Regeneration still occurs in many lizard species, but with significant errors in

pathfinding and retinotopic mapping (Dunlop et al., 2004). In mammalian vertebrates,

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such as rats and humans, the ability of the CNS to grow and path-find after damage

appears to be developmentally lost, meaning that in adults, aside from slight and

abortive induction of neuroregenerative processes, successful CNS regeneration is

essentially absent (Beazley and Dunlop, 2000; Vajn et al., 2013).

Even within spontaneously neuroregenerating vertebrates, such as the teleosts,

successful regeneration of damage to the optic nerve is highly dependent on the extent,

type and positioning of the insult (Harvey et al., 2006). For multiple reasons, not least of

which is the disruption of the blood-brain barrier, ‘cut’ injuries in which the axons are

entirely severed and the myelin sheath of the optic nerve is broken are far less

successfully repaired than ‘crush’ injuries, in which the axons of the optic nerve are

severed but the sheath is left intact (Reier & de Webster, 1974). Further, the distance

from the eye in which the damage occurs is a relevant factor to CNS repair; greater

distance results in less successful repair of damage (Berkelaar et al., 1994; Weibel,

Cadelli, & Schwab, 1994).

1.2.4. Factors preventing spontaneous neuroregeneration in mammals

In mammals, the CNS fails to regenerate due to both intrinsic and extrinsic inhibitory

factors. Extrinsic inhibitory factors include: CNS myelin, which collapses the tips of

growing axons on contact (Schnell & Schwab, 1993; Wang et al., 2002); inhibitory glial

scarring that forms at CNS injury sites (Benowitz & Yin, 2007; Silver & Miller, 2004);

and a lack of neurotrophic support within the CNS (Harvey, Ooi, & Rodger, 2012; Jin,

Fischer, Tessler, & Houle, 2002; Lu & Tuszynski, 2008).

The intrinsic growth capacity of axons changes over time; Retinal Ganglion Cells (RGCs)

younger than embryonic day 21 show rapid axonal extension, while RGCs older than 2

15

days postnatal fail to extend (Benowitz & Yin, 2007). This shift appears to require direct

contact with amacrine cells (Goldberg, Klassen, Hua, & Barres, 2002). The intrinsic

regenerative capacity relies heavily on gene transcription and protein translation

(reviewed in (Wang & Jin, 2011)). For example, RGCs express a wide range of proteins

during developmental connection formation, like GAP-43, which becomes

downregulated as mature connections form. Successfully regenerating neurons (like the

sensory neurons of the peripheral sensory ganglia, or fish CNS neurons) strongly

upregulate GAP-43, whereas mammalian RGCs show only a small transient upregulation

after axotomy (Skene, 1989). It has been reported that limited regeneration of the dorsal

root ganglions can be promoted in adult mice through the co-expression of GAP-43 and

CAP-23 (Bomze, Bulsara, Iskandar, Caroni, & Pate Skene, 2001), that increased GAP-

43 expression is associated with macrophage-activation-mediated RGC regeneration in

rats (Botstein & Risch, 2003) and that overexpression induces nerve sprouting in adult

mice (Aigner et al.). However, other studies have shown that transducing RGCs to express

GAP-43 alone does not improve regeneration (Hellstrom & Harvey, 2011; Leaver, Cui,

Bernard, & Harvey, 2006). Further, the overexpression of GAP-43 can potentially result

in pathological outcomes (Hocquemiller et al., 2010). There remain considerable

questions as to how the intrinsic growth capacity of RGCs are modulated.

The intrinsic state of the RGC is crucial to understand, as it dictates the response to

extrinsic factors (Benowitz & Yin, 2007). For example, elevated intracellular cAMP

levels are generally required for RGCs to respond to cell survival and axon outgrowth-

inducing factors, but once a mammal reaches adulthood these levels are low, contributing

to the lack of regenerative ability (Benowitz & Yin, 2007; Hellström & Harvey, 2014).

In contrast, cAMP levels in fish RGCs increase during regeneration and return to normal

levels once regrowth is complete (Rodger, Goto, Cui, Chen, & Harvey, 2005).

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1.2.5. Advances in stimulating spontaneous mammalian neuroregeneration

While recent work has shown it possible to stimulate pro-regenerative responses in the

mammalian retina through various strategies, such as the addition of subtoxic

concentrations of excitatory amino acids, specific molecules like oncomodulin (Harel et

al., 2012), growth factors, or the stimulation/repression of Transcription Factors (TFs)

(Benowitz & Yin, 2007), this has not led to significant recovery of function in the limited

regeneration achieved (Karl & Reh, 2010). With even the combination of the existing

approaches failing to bring about a full, functional recovery, the puzzle appears to be

missing necessary elements for solution.

There remain further avenues through which neuroregeneration in mammals might be

enhanced. The induction of some aspects of developmental gene expression, pro-

regenerative gene pathways and/or the mimicking of genetic regulation seen in the more

plastic vertebrate neural systems might all yield valuable additional pieces towards

solving the problem (Benowitz & Popovich, 2011; Fischer, Petkova, Thanos, &

Benowitz, 2004; Glass, Saijo, Winner, Marchetto, & Gage, 2010). The regulatory aspect

is particularly compelling, as genes upregulated during teleost CNS regeneration are

common to mammals, suggesting the disparity in regeneration is the result of

differential gene expression rather than species-specific genes (Blackmore, 2012; Hui et

al., 2014).

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1.3. Processes linked with neuroregeneration

1.3.1. Inflammation

In teleosts, damaged RGCs either survive, or die only in small numbers by apoptosis

(Murray & Edwards, 1982). By contrast, CNS lesions in mammals lead to injured cells

undergoing both apoptosis and necrosis (Kerr, Seorl, Harmon, & Bishop, 1987).

Necrosis generally leads to tissue inflammation and the formation of glial scars, which

inhibit regeneration (Zhang, Krebs, & Guth, 1997).

In fish, the immune response is rapid and localized. Cell apoptosis is followed by the

appearance of innate immune cells, neutrophils and macrophages, post-lesion (Zupanc

et al., 2003), which are associated with rapid clearing of astrocytes and

oligodendrocytes from the lesion site, preventing the formation of an astrocytic scar

(Nona, 1998). Neutrophil infiltration is the first response to inflammation within 12-

24h (Kurimoto et al., 2013; Schnell, Fearn, Klassen, Schwab, & Perry, 1999; Stirling,

Liu, Kubes, & Yong, 2009). Next, macrophages invade the injury zone to clear axonal

debris and myelin (Blaugrund, Duvdevani, Lavie, Solomon, & Schwartz, 1992).

In rats, however, the inflammatory response to an optic nerve crush shows a small and

steady increase in macrophages over the first 5 days (Perry, Brown, & Gordon, 1987). It

is known that macrophages release trophic factors and that may play a beneficial role in

nerve regeneration; specifically, there is evidence that macrophage-derived factors and

oncomodulin promote regeneration in rat models (Kurimoto et al., 2013; Yin et al.,

2003). For example, activating macrophages with the pro-inflammatory agent Zymosan

following an optic nerve crush in rats promoted axon regeneration through a peripheral

nerve graft, suggesting that macrophages in fact support optic nerve regeneration(Yin et

18

al., 2003). Therefore, there seems to be a correlation between poor regenerative capacity

of the CNS and limited number of immune cells in the region following injury.

1.3.2. Development and regeneration

During development of the CNS, axons grow and path-find, forming connections as a

result of complex, multifaceted gene expression. In the formation of the optic nerve, for

instance, the growth cones make rapid adjustments based on feedback from their

surroundings (Erdogan, Ebbert, & Lowery, 2016). Once reaching the tectum, retinotopic

mapping of the axons to form useful connections is based on both attraction and

repulsion, and highly modulated gene expression (McLaughlin & O'Leary, 2005;

Tamariz & Varela-Echavarría, 2015)

Successful CNS regeneration, such as in zebrafish optic nerve regrowth, inducts a local

gene expression profile similar to that seen during development, however with notable

differences, primarily because axons are regrowing through a mature brain environment

(Munzel et al., 2012; Ramachandran, Reifler, Parent, & Goldman, 2010). Beyond

inducing cell survival and regrowth, re-creating this mapping in adult mammals may

require the mimicking of some, but not all, of the gene expression profile seen in the

region during development.

1.4. microRNAs and gene regulation

1.4.1. The c-value paradox

The c-value is the term for genome size in an organism. One of the surprising

discoveries in the study of evolutionary genetics was that the size of the genome does

not scale in line with the ‘complexity’ of a species (Gregory, 2005). The discovery of

noncoding DNA, illuminating the fact that the sheer gene number does not itself

necessarily dictate genome size, went a small way to explaining this paradox. However,

19

the number of genes is also not strongly correlated with the complexity of an organism

(Bird, 1995). More recent work has demonstrated that an increase in the regulatory

complexity and apparatus correlates much more closely with complexity than does

simple gene number (Fritzsch, Jahan, Pan, & Elliott, 2015).

1.4.2 miRNA

Most of the information in the vertebrate genome is involved in complex regulatory

processes, many of which underpin development and brain function. Key players in this

process are non-coding RNAs (described by large consortia such as ENCODE and

FANTOM), which play a significant role in many key biological processes. One of the

most intensely studied groups of these non-coding RNAs are microRNAs. microRNAs

(miRNAs) were first discovered in 1993, but not reported to definitively act in

biological regulation until the early 2000s (Almeida, Reis, & Calin, 2011). These small

(~22 nts), noncoding RNA sequences have since been shown to act in the regulation of

almost all protein-coding transcripts in animals (Berezikov, 2011). They act as guide

molecules in RNA silencing, downregulating expression of their targets as ‘fine-tuning’

regulators; modulating expression to a smaller degree than do other methods, such as

larger RNA molecules; they act as a rapidly activated ‘spigot’ to adjust expression

through downregulation, rather than as an on/off switch (Almeida et al., 2011). A given

miRNA binds through perfect/imperfect binding, and may target many different genetic

regions with varying strength, or act in combination with transcription factors to

regulate entire pathways as ‘master regulators’ (van Rooij, 2011). One miRNA can

target hundreds of genes and their regulatory models are complex (Chiu, Alqadah, &

Chang, 2014; Corrada, Viti, Merelli, Battaglia, & Milanesi, 2011). Further, there is

often a redundancy of targeting, meaning that for some regions, knockout of just a

single miRNA may not be sufficient to meaningfully change expression (Fischer,

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Handrick, Aschrafi, & Otte, 2015). The evolutionary importance of microRNAs as

regulatory molecules is reflected in their strong sequence conservation between species

(Berezikov, 2011). Compellingly, there is a greater divergence in microRNA expression

between tissues than between species, and further, there are more distinct microRNAs

expressed in the brains of vertebrates than in any other tissue, highlighting the

evolutionary conservation of microRNAs in brain development and function (Mattick,

2011). In neurons, microRNAs regulate many fundamental processes including

differentiation, axonal growth, synaptogenesis, and plasticity (Manakov, Grant, &

Enright, 2009). microRNA implication in neurological diseases, combined with their

remarkable specificity for individual signalling pathways, has led to the development of

microRNA-based CNS therapeutics (Madathil, Nelson, Saatman, & Wilfred, 2011),

with microRNAs found to be versatile and reversible regulators of gene expression in

neurons (Chiu et al., 2014).

An intriguing and compelling aspect of microRNAs is their ability to regulate other

transcriptional regulators, particularly transcription factors (TFs), which themselves

play an important role in CNS development and regeneration (Tedeschi, 2011). The

high conservation between species observed for TFs, as seen for microRNAs, supports

the idea that microRNAs and TFs co-evolved (Chen & Rajewsky, 2007). MicroRNAs

appear to target TFs more than other gene types (Dannemann et al., 2012), whilst

microRNA genes are preferentially regulated by TFs, indicating an intricate, complex

and synergistic mechanism for gene regulation (Krol, Loedige, & Filipowicz, 2010).

1.4.3. miRNA number increases in line with neural complexity

The number of miRNA present and active within the CNS of vertebrates follows the

same general trend in neural complexity (Figure 1). This suggests that this regulatory

21

apparatus is an important part of a developing nervous system, and contributes to its

ability to gain complexity. Key characteristics of miRNA, covered earlier, make them

well suited to regulate the complex events of brain development.

miRNA are important gene regulators within the CNS. These small, noncoding RNAs

are found in almost all eukaryotic cells, and abundantly expressed in the CNS

(Benowitz & Yin, 2007; Lu & Tuszynski, 2008; Madathil et al., 2011). Many show

specificity of tissue and developmental stage expression, with the suggestion of unique

functions in the retina and other ocular tissues (Liu et al., 2009). Their ability to induce

and regulate entire pathways of expression means their modulation may represent the

key to generating functional recovery from CNS damage in mammals.

1.4.4. MicroRNA in Neuroregeneration & Development

It is primarily the epigenetic processes (e.g. DNA methylation, chromatin remodelling,

noncoding RNAs, RNA & DNA editing) that shape development, differentiation and

plasticity in the nervous system (Mattick, 2011). In the brain, animals (particularly

primates) have evolved considerable adaptability within RNA regulatory systems

(McNeill & Van Vactor, 2012). Predicted to regulate synaptogenesis and neural

development (reviewed in Xu, 2009), miRNA have been described as the ‘prime movers’

shaping the epigenetic landscape of the CNS (Manakov et al., 2009).

Essential regulatory elements during development (reviewed in Sibley & Wood, 2011), a

number of specific miRNA may be important for spontaneous CNS repair. In particular,

one miRNA, miR-223, was identified in our previous work in zebrafish (Fuller Carter et

al., 2015; described in detail in section 1.6: Rationale) and has been shown to have a

number of gene targets important for neuroregeneration. It has been implicated in

22

preventing neuronal cell death following transient global ischemia (Rita & Robert, 2010),

is upregulated in response to spinal cord injury (SCI) and plays a role in regulating

neutrophils (Harraz, Eacker, Wang, Dawson, & Dawson, 2012), suppressing

proinflammatory macrophage activation (Izumi et al., 2011).

1.5. Model species in studies of optic nerve regeneration

In order to facilitate identification of the important molecules and processes involved in

human health and disease, model species should have a useful phenotype and well

characterised genomes (Li, Yang, & Zhong, 2015). Here, I study regulation of gene

expression in zebrafish, which display successful regeneration with full return of visual

function (Becker & Becker, 2007). I have chosen to study zebrafish because their

genome has been completely sequenced and annotated, with continuous ongoing

revision. In addition, their microRNA genetic make-up is relatively well described and

annotated. Although insights into the requirements for successful regeneration could be

obtained from a comparison of reptiles, which have varied regenerative responses

(Dunlop et al., 2004), little is known about reptilian genomes. Furthermore, within-class

comparisons have limited ability to identify functional conserved non-coding sequences,

due to high sequence similarity (Ahituv, Rubin, & Nobrega, 2004). For this reason, the

present thesis will focus on mammal-fish comparisons.

1.5.1 Zebrafish

One of the great benefits of the zebrafish as an animal model in terms of genetic

investigation is that they have a fully sequenced and well annotated genome (D. G.

Howe et al., 2013; K. Howe et al., 2013). The species has been used by a large number

of biological investigations over the last decades, and has been well characterised. In the

case of this specific investigation, many of the genes inducted by CNS injury are

23

virtually identical to the human orthologues (K. Howe et al., 2013). As with most

species, the knowledge base concerning the microgenome (or, the genome of the

microRNA) lags behind that of the base DNA. While this does represent an additional

challenge to phylogenetic investigation of miRNA in zebrafish specifically, much of the

microgenome has been reported within the literature and there are powerful online tools

with which to support such study (eg. TargetScanFish; (Cho et al., 2005; Grimson et al.,

2007)). There are additional benefits to the use of zebrafish in a laboratory setting, as

they have not only been used in previous neuroregeneration studies (enabling

comparison to the existing literature and benefits to the planning of specific

experimentation), but are easy to care for, inexpensive and easy to acquire, as well as

being in possession of a fairly rapid growth cycle (Cho et al., 2005; Jiao et al., 2005).

1.5.2. Rats

The ultimate goal of medical research is to take the lessons we learn and apply it to

human health outcomes. As a mammalian model, rats are a good proxy for human

studies. While there are clear differences between rats and humans, rats present, in

contrast to primates, for examples, a much better studied and well-understood model, as

well as being more cost-effective and less ethically problematic (Iannaccone & Jacob,

2009). Their genome has been very well investigated and annotated, and their

microgenome is relatively well known (Gibbs et al., 2004; Minami et al., 2014). As with

zebrafish, rats are heavily reported in the literature of neuroregeneration studies,

facilitating comparison and interpretation.

1.6. Rationale of the thesis

The experimental design of this thesis was informed by the outcome of a bioinformatics

analysis of mRNA and miRNA expression in zebrafish eye following an optic nerve

24

crush (Fuller-Carter et al., 2015). We performed a pilot study of gene expression

microarrays in rat and zebrafish retina at 3 days following an optic nerve crush injury,

identifying differentially regulated microRNAs and genes (including TFs) potentially

contributing to the successful regenerative response in zebrafish.

Figure 1.2. Preliminary microarray data of retinal changes in both zebrafish and rat.

Differentially expressed

microRNAs, genes, and

transcription factors after

optic nerve crush. Up (↑)

and down (↓) represent

direction of change.

Transcription factors were

identified by GO terms

associated with DNA-

transcription processes.

Data were collected from

n=4 pooled retinae (each

pool=4 animals) for control

vs. crush, in each species.

An initial species comparison revealed 657 differentially expressed genes in the

zebrafish compared to 593 differentially expressed genes in the rat (log fold change

1.5; adjusted p-value <0.05; Figure 2). Many of these genes were also identified in

previous mRNA screens (Agudo et al., 2008; McCurley & Callard, 2010; Veldman,

Bemben, Thompson, & Goldman, 2007). Further analysis identified miR-223 and

miR29b to be significantly up-regulated in zebrafish and down-regulated in rat. The

predicted targets of these miRs based on inverse expression patterns and bioinformatic

prediction software are involved in axonal outgrowth and neuronal plasticity. The

relationship between miR-223 and these predicted targets was validated in cell culture

(Fuller-Carter et al., 2015) and here I further investigate the role of miR223 in optic

nerve regeneration in zebrafish.

A.

A.

25

1.7. Aims

Investigate the effects of specific miRNA on CNS regeneration in vertebrates

In this work I will explore the effects on neuroregeneration in zebrafish of modulating

expression of miR223. My results will inform future studies to conversely modulate the

miR223 in rats in order to promote mammalian neuroregeneration. More broadly, my

results will also provide a framework to explore the role of other miRNAs in optic nerve

regeneration.

Aim 1: To determine whether injection of miRNA inhibitors into the eye in vivo in

zebrafish can downregulate the target miRNA

As this is a methodological aim, the outcomes will be described in chapter 2: Methods.

Aim 2: To investigate the effects on retinal ganglion cell regeneration zebrafish of

inhibiting our target miRNA

The intervention (covered within the experimental chapter in more detail) consists of a

complete of the optic nerve of the right eye, approximately 3 mm from the eye, so as to

completely sever the axons of the optic nerve while leaving the myelin sheath intact as a

path for regenerative growth (and to minimise secondary damage due to inflammation

and disruption of the blood-brain barrier). Immediately after injury, I will inject a miR-

specific inhibitor which binds to and ‘knocks down’ the miR223. Zebrafish will be

sacrificed at two timepoints: an early timepoint (2-3 days) to confirm knockdown of

miR and target gene expression, and a late timepoint (7 days) to examine the effects on

RGC axon regeneration. After sacrifice, the zebrafish will be dissected, optic nerves and

brain preserved and sectioned for histochemical analysis to determine the extent of

regrowth and effects of miR knockdown on the axonal regeneration.

26

1.8. Conclusion and significance

There are myriad interconnected signalling pathways involved in neuronal survival and

regeneration and it is not clear which ones are the best targets for therapeutic

interventions (Benowitz & Yin, 2007). By using a comparative species approach, our

lab previously identified miRNAs that differentially expressed in zebrafish and rats.

Here we will assess the ability of microRNAs to mediate rapid, specific and adaptive

changes in gene expression that may drive CNS regeneration.

Our approach of using miRNAs to gain insight into regulation of gene expression

reflects the current understanding that most differences between species comes down to

differences in the timing and location of gene expression, not the existence of unique

genes (Carroll, 2008). The emerging field of miRNAs is likely to provide insights into

gene regulatory mechanisms that underpin the differences in regenerative ability across

the vertebrate phyla, differences which have intrigued researchers for over 100 years.

Moreover, the use of miRNAs which affect the expression of multiple genes, potentially

overcomes the requirement for combinatorial therapies with associated combinatorial

side effects (Benowitz & Yin, 2007). Furthermore, our study of targets downstream of

miR-223 will allow us to refine any potential therapeutic intervention to minimize side

effects and maximize efficacy.

Manipulating levels of miRNAs is an exciting therapeutic concept that is being trialed

in many diseases, and miRNAs have been used as therapeutic agents in the experimental

treatment of cancer (Roshan, Ghosh, Scaria, & Pillai, 2009; Schratt, 2009). However,

very little work has been done on the potential for miRNAs to treat neurological

conditions. Nonetheless, miRNAs are abundantly expressed in the vertebrate and

27

specifically the human brain, emphasizing their importance in regulating appropriate

gene expression for complex connectivity and function.

28

Chapter 2: Methods

2.1 Animals and anaesthesia

Common longfin adult zebrafish (Danio rerio), 2–4 cm in body length, were obtained

from commercial suppliers, kept in gravel-bottomed tanks containing aerated,

dechlorinated tap water in a controlled temperature room at 220C on a 12-h light/dark

cycle, and fed five times a week with dried goldfish pellets. For surgery and intravitreal

injections, zebrafish were anaesthetised by immersion in 0.3% MS222 solution,

buffered with bicarbonate soda (0.6g MS222 and 0.6g NAHCO3 in 200mL deionized

H2O). For terminal anaesthesia the [MS222] was 0.6%, with the same concentration of

NAHCO3. Procedures conformed to the NHMRC guidelines for the use of animals and

were approved by the Animal Ethics Committee of The University of Western

Australia.

2.2 Optic nerve crush & Intravitreal injections

The right eye was deflected forward and connective tissue removed to expose the optic

nerve that was crushed with watchmaker's forceps with pressure applied for 10 seconds,

1 mm from the back of the eye; the procedure severs all RGC axons but leaves the nerve

sheath intact as a conduit for regeneration (Meyer & Kageyama, 1999). The eye was

then placed back into the socket.

2.3. Experimental design and animal numbers

Animal numbers are summarized in table 2.1.

29

Experimental groups: Fish received an optic nerve crush and were injected with (1) a

miR223 inhibitor, (2) a scrambled control sequence, (3) a vehicle control, or (4) no

injection.

Proof of principle short term (2-3 days) injection study: Retinas from 3 fish were pooled

to give sufficient RNA for analysis, and nine fish were used per group, resulting in 3

samples per group. For immunohistochemistry (IHC) analysis of nerves at 3 days, each

group contained 3 fish.

RGC regeneration long term (7 day) study: Brains were collected for

immunohistochemistry from 10 fish per group. All tissue from an initial experiment was

lost due to a freezer breakdown in 2015 and these animals were repeated a second time

with n=6-9 per group. Due to lack of time, only brains were analysed by

immunohistochemistry for RT97 and eyes and nerves were retained for future analysis.

Table 2.1: Summary of animal numbers used in the study

Short term Long term

2 days (RNA) 3 days (Histology) 7 days (Histology)

miRNA validation

36

NA

NA

Histology 1 (lost

due to freezer

failure)

NA

12

40

Histology 2

NA

12

40

2.4 LNA oligonucleotides

The zebrafish-specific LNA miR-223 inhibitor (i-miR) and scrambled negative control

were ordered from Exiqon (Denmark). The miR-223 inhibitor specifically binds to

30

endogenous mature miR-223 sequences, whilst the scrambled negative control has non

known binding partner in zebrafish. Each lyophilized LNA oligo (5.0nmol) in was

resuspended in ddH2O to various concentrations. The oligo sequences for LNAs were as

follows: i-miR223 sequence 5’-3’: GGGTATTTGACAAACT; scrambled sequence 5’-

3’: ACGTCTATACGCCCA.

2.5 Optimisation of the injection protocol

Review of the literature for appropriate doses of miR inhibitors revealed a concentration

of 250µM (0.125nmol) significantly decreased miR expression while control miRs

(scrambled) at this concentration had no effect (Sano et al., 2012). After testing

concentrations ranging from 500µM to 30µM, we found that a concentration of 100µM

(0.05nmol in 0.5ul) of the miR inhibitor (i-miR) significantly decreased miR-223 levels

but scrambled control had no effect (Fig. 1).

Figure 2.1: miR-223 Expression – Concentration Optimisation

Different concentrations were tested to find the optimal concentration. 30, 60, 200, 250,

and 500µM concentrations of the inhibitor had no effect on miR223 levels. Although

300 and 400µM decrease the miR-223 expression, I found that at 100µM the decrease

was more stable and consistent. Therefore, I used a concentration of 100µM for all

injections in this study.

31

When compared to a crush control, the glass micropipette increased miR-223 expression

to the same extent as the Hamilton syringe (Fig. 2.2), but the glass micropipette was

easier to stabilize whilst injecting. I therefore used a glass micropipette for all injections

in this study.

Figure 2.2: miR-223 Expression - Injection Trial

Two different injection techniques were trialed to determine a tool that induces the least

amount of lens damage at the time of injection following an optic nerve crush. A crush

control, where only the optic nerve was crushed, was used to compare the miR-223

expressions after injection. Although the injections procedures gave similar results, the

glass micropipette was used due to ease of handling.

2.6 Intravitreal Injection – final protocol

Injections were made with a 10µl Hamilton syringe connected to a glass micropipette

via tubing. The tubing was prefilled with mineral oil to ensure the exact amount of oligo

was injected. A dorsal eye incision was made with a 30-gauge needle to insert the

syringe into the eye. It has been shown by several groups that damage to the lens can

occur during injections in mammals, hence the needle was carefully placed in front of

32

the lens to avoid contact with the lens itself or the retina(D. Fischer, P. Heiduschka, &

S. Thanos, 2001; Fischer, Pavlidis, & Thanos, 2000; Leon, Yin, Nguyen, Irwin, &

Benowitz, 2000). Experiments in our lab found the maximum volume that could be

injected into the zebrafish eye was 0.5µl. Therefore 0.5µl of the miR-223 inhibitor (i-

miR) or the negative control (scrambled) was injected into the vitreous. A fine tube was

placed into the mouth of the fish to flush tank water through to accelerate reanimation.

2.7 Eye and Retina Removal for RNA extraction

Retinae were collected for RNA extraction. The fish was anesthetised in 0.3% MS222.

Using a binocular microscope, the eye was cut out with forceps and scissors by first

tearing the connective tissue around the eye and then by cutting the optic nerve and

removing the eye from the eye socket. To cut the cornea around the lens, an incision

across the lens was made with a 30g needle. The retina was then isolated by using

forceps to tear apart the eye, and remove the lens, sclera and retinal epithelial pigment.

The retina was placed into 400µl RNA Later, a RNA stabilisation solution, and kept in

4°C overnight before being transferred into -80°C for storage.

2.8 RNA and miRNA Extraction

The pooled zebrafish retinas were homogenized in 1ml Trizol using a syringe (22g then

27g). The homogenate was then allowed to sit for ~3min at room temperature and 200µl

chloroform was added. The Eppendorf tube was shaken for 15sec and then allowed to

sit for another ~3min at room temperature. The samples were centrifuged at 12,000g for

20min at 4°C. Next, the upper aqueous phase was transferred to a new Eppendorf tube

without disturbing the interphase or organic layers (~450µl). 500µl of room temperature

isopropanol was added to the supernatant, mixed and then allowed to precipitate at room

33

temperature for 10min. The samples were spun for 20min at 12,000g at 4°C and the

supernatant removed. The pellet was washed 2x with 500µl of ice-cold 80% ethanol

(EtOH), mixed with a finger flick and centrifuged again at 12,000g for 5min at 4°C. To

concentrate the RNA, 5 volumes of 100% EtOH, 1/10th volume 3M sodium acetate

(NaOAc) and 1µl glycogen were added to the sample, mixed thoroughly and incubated

at -80°C overnight. After incubation, the samples were centrifuged at 12,000g for 20min

at 4°C and the supernatant removed. Next, the pellets were washed two times with

500µl of ice-cold 80% EtOH and centrifuged at 12,000g for 5min at 4°C. The pellets

were air-dried for 5-10min and 20-30µl of RNase free H2O was added. Before the RNA

concentration was determined using a Nanodrop (Thermo Scientific) the samples were

frozen at -20°C for ~15min and then resuspended. The 260/280 and 260/230 ratios were

observed to make sure that the samples were not contaminated (protein, salt, phenol,

etc.).

2.9 miRNA quantification

microRNA RT and qPCR for miR-223 and U6 was performed using Taqman miRNA

assay kits (Applied Biosystems). Each kit contains a miR-specific stem-loop primer to

reverse transcribe the mature miR sequence, and a miR-specific fluorogenic probe to

quantify the mature miR by qPCR.

For the RT PCR about 10ng RNA was used for each sample, if necessary the RNA was

diluted (1/10). The samples were prepared on ice as followed, 7µl of the master mix

(H2O, 100mM dNTPs, RT Enzyme, 10x Buffer, RNase Inhibitor) (Table 2.2), 5µl of

RNA (up to 10ng RNA + H2O), and 3µl of 5x RT Primer were aliquoted into 0.2ml

tubes to a total volume of 15µl. The RT Primers used were miR 223 and U6. U6 is a

small nuclear RNA which is used as control. The samples were gently mixed and

incubated for 5min on ice before starting the PCR cycle (Table 2.3).

34

Table 2.2: miRNA Reverse Transcription (RT) Master Mix

Master Mix 1x

100mM dNTPs 0.15µl

RT Enzyme (Multiscribe) 1.00µl

10x Buffer 1.50µl

RNase Inhibitor 0.19µl

H2O 4.16µl

Final Volume 7.00µl

Table 2.3: miRNA PCR Cycle Program

Cycle Temperature + Time

Reverse Transcription to

cDNA

16°C for 30min

Amplification 42°C for 30min

Termination 85°C for 5min

Cooling of Sample 4°C forever

For qPCR, the Taqman-based detection uses a 5’ fluorogenic-labeled probe to identify

specific amplification products by using quenchers on the 3’ ends which first inhibit

fluorescence and then emits fluorescence as soon as it is separated from the reporter

dye. For the microRNA qPCR each sample was tested in triplicate with a final volume

of 20µl. The Taqman Universal Master Mix was combined with RNase free H2O, the

35

miR-223 RT 20x Primer, and the cDNA from the RT-PCR (Table 2.4). The samples

were amplified in a quantitative PCR (qPCR) reaction (Table 5). A water sample was

used as a negative control.

Table 2.4: miRNA qPCR Master Mix

Master Mix 1x 3x (w 20% excess)

Taqman Universal MM

(no UNG)

10.00µl 36.00µl

H2O 7.67µl 27.60 µl

RT 20x Primer 1.00µl 3.60µl

cDNA 1.33µl 4.8µl

Final Volume 20.00µl 72.00µl

Table 2.5: miRNA qPCR Cycle Program

Cycle Temperature + Time

UNG Enzyme Activation 1x 50°C for 2min

Hot-Start Activation 1x 95°C for 10min

Denaturation 95°C for 15sec

Annealing/Elongation 95°C for 1min

2.11 Fish Perfusion and dissection for immunohistochemistry

For immunohistochemistry (IHC) assays, the brain together with the optic nerve and the

eyes were dissected. Before the dissection, the fish was anesthetised in MS222 (0.3%)

and then perfused with 4% paraformaldehyde (PFA). An incision was made above the

ventral fin and cut along the midline up to the heart. The ribcage was cut to get better

40x

36

access to the heart. The tissue enclosing the heart was also removed. A 30g needle

attached to a syringe was then inserted into the ventricle of the heart and 0.65% saline

slowly injected to remove the blood in the blood vessels. The 4% PFA solution was

then injected into the ventricle to fix the brain tissue for dissection and histological

analysis. After the perfusion the fish head was cut off and placed into 400µl 4% PFA

and stored overnight in 4°C.

To gain access to the brain, firstly the jaw as well as the surrounding tissue had to be

removed. The ribcage was cut through to remove the tissue. Once the skull was cut

open, the muscles connecting the brain to the eyes were removed. The skin on the dorsal

side of the head and all of the mandibular cartilage was removed. Following the

dissection, the eyes were removed from the brain and optic nerve whereas the crush site

was kept on the optic nerve (Fig.3). The optic nerve, together with the brain was stored

in 4% PFA by 4°C. The optic nerves and chiasm were removed from the brain before

cryosectioning for antibody (AB) staining.

Figure 2.3: Ventral View of

the Zebrafish Brain

The zebrafish eye is

connected to the optic nerve.

At the optic chiasm, the

nerve crosses over to the

contralateral hemisphere

where it connects to the optic

tectum via the optic tract.

The crush (clear strip in the

optic nerve corresponding to

discontinuous axons) was

performed with fine forceps

on the right optic nerve right

after the eye before the optic

chiasm.

crush site

Optic tectum

Optic tract

Eye

Optic nerve

37

2.12 Cryosectioning

A cryostat, Leica CM1900, was used to section the zebrafish optic nerve for

immunohistochemistry. The cryostat was held at a temperature of -20°C to maintain

specimens frozen for cutting. A metal chuck was mounted with O.C.T. (optimal cutting

temperature) compound, an embedding medium for frozen tissue specimens to ensure

optimal cutting temperature. The metal chuck was placed in the cryostat to freeze and a

few sections were cut to smoothen the surface. The sample was soaked in O.C.T. and

then placed onto the metal chuck and again coated with O.C.T.. The zebrafish optic

nerve was placed with the ventral side

Figure 2.4: Layout of Optic Nerve for Cryosectioning

The optic nerve was positioned on the chuck with the dorsal side upwards and the crushed

nerve on the right.

downwards, so that it was sectioned dorsal to ventral (Fig. 2.4). Once frozen, the chuck

was mounted on the microtome, an ultrafine slicer, and the tissue was cut into 14

microns sections. The tissue sections were picked up with double subbed (100ml H2O,

Anterior

Posterior

38

0.5g gelatin, 0.05g chromium (III) potassium sulphate (CrK(SO4)2)) superfrost slides

(Menzel Gläser, Lomb Scientific Pty LTD). The slides were kept in -20°C before being

used for IHC.

2.13 Immunohistochemistry

Fish were terminally anaesthetised with [0.6%] MS222 and perfused transcardially with

saline followed by 4% paraformaldehyde. Eyes and brains were dissected, wherever

possible preserving the ON intact, and post-fixed in 4% paraformaldehyde overnight at

40C. Gross dissections were made the following day and finer dissections made over

the subsequent week. After 1 week storage at 40C in 4% PFA the brains, eyes and ONs

were transferred to 30% sucrose in phosphate buffered saline (PBS, pH 7.2) and stored

at 40C for minimum 24 hrs, in order to cryoprotect them prior to cryosectioning. Tissue

was embedded in tissue-tek medium for sectioning. Brains were sectioned horizontally

at 14 um to visualize the rostro-caudal tectal axis. ON were sectioned horizontally at 14

um. Slides were left to air dry on a heating block set to 400C and then initially stored at -

200C, and subsequently moved to storage at -800C. Prior to use, sections were removed

from -80o C and air-dried for 1-2 hours at room temperature.

Two different inmmunohistochemical approaches were used in an effort to reduce the

levels of background staining and auto-fluorescence. For nerves, a fluorescent

secondary antibody was used to detect primary antibody (RT-97) staining. However,

due to high background in some of the tissue, a colorimetric method using horseradish

peroxidase and diaminobenzidine (DAB) was used for staining the brains as this method

can increase sensitivity while retaining low background. Unfortunately, background

39

staining was also present in brain tissue (see results section). Both protocols are

described below.

For nerves, slides were washed for ~5min in 1x PBS in a glass container. They were

then dried and a hydrophobic pen used to surround the tissue sections so that

incubations could proceed directly on the slide. The tissue was permeablised in PBS-T

(0.2% Triton) for 10min to allow further reagents to infiltrate. A blocking solution

consisting of 10% NDS (normal donkey serum) in 0.1% BSA (bovine serum albumin)

in PBS-T was applied to the slides at room temperature in a humidified chamber for 2

hours to avoid non-specific binding of the antibody. Next, the first antibody (Table 10)

was diluted with blocking solution accordingly and then applied and incubated

overnight at 4°C in a humidified chamber. Following the incubation the tissue was

washed 3x in 1x PBS for 5-10min and the appropriate alexa-fluor labeled second

antibody (1:600) as well as Hoechst (1:1500), for nuclei staining, were applied for 2

hours at room temperature. Afterwards the tissue was washed 3x in 1x PBS for 5-

10min, again. The slides were then air dried and mounted: ~80µl Fluoromount-G was

applied onto a 40mm coverslip at the side and spread whilst putting down the slide

slowly from one side to the other and avoiding any bubbles during this process. The

sections were examined under a Nikon Eclipse 80i fluorescence microscope.

For brains: Tissue was rehydrated in PBS containing 0.2% tritonX100 for 10 minutes;

endogenous peroxidases were inhibited by incubation with PBS containing 0.9% H2O2

for 10 minutes; sections were rinsed in PBS and incubated in blocking solution (10%

horse serum, 0.1% bovine serum albumin) for 2 hours in a humidified chamber at room

temperature. Brain sections were then incubated with RT-97 (1:200, in blocking soln.

mouse human, EMD Millipore) to reveal regenerating retinal ganglion cell axons,

40

overnight at 40C, in a humidified chamber. Antibody binding was visualized using a

biotin-streptavidin-HRP system (Vectastain ABC, Vector Laboratories) and a diamino-

benzidine (DAB)-metal complex (Thermo Scientific). Slides were rinsed in PBS,

dehydrated by increasing alcohol concentrations, cleared in xylene and mounted in

‘Entellen new’ (Merck Millipore) in preparation for microscopy. Control sections were

processed in the absence of primary antibody.

2.14 Measurement of regeneration

Sections of optic nerve (short term study only).

The absolute distance from the crush site to the farthest labelled axon, as well as the

distance from the chiasm to the farthest labelled axon were analysed. In addition, a

qualitative approach was used to rate the amount of regeneration: +++ - robust

regeneration, optic tract filled. ++ - sparse regeneration , optic tract half filled. + -

regeneration stopped at chiasm with only sparse axons in the tract. Due to the small

number of samples (2-3 per group due to the accidental damage or loss of the very small

nerve tissue in several of the experimental groups), statistical analysis was not

attempted on either of these methods.

Sections of brain (optic tectum: long term regeneration study only)

To chart the rate of axon regeneration the distance of the leading regenerating axons

from the tract/tectal border was measured in sections spanning the dorsal-ventral extent

of the tectum and expressed as a % of total tectal length (Fig. 5). As there was visible

(though lesser) staining in the control tectum, in cases where there was no staining

visible in either tectum the sections were not used for analysis. Analysis was undertaken

at a final magnification of 200x under white light. Images were taken at a final

magnification of 100x. The program ‘ImageJ’ (Abramoff, Magalhaes, & Ram, 2004)

41

was used to measure the total length of the tectum (Fig. 5), as well as determine the

length of regeneration (Fig. 2.5).

Figure 2.5. Schematic of measurements taken for extent of regeneration

The percentage regeneration for all sections on each side was averaged to determine the

‘slide regeneration’. Some fish were poorly perfused, resulting in tissue damage during

sectioning and poor immunostaining. These animals were not included in the analysis.

Values from all sections from a single animal were averaged to determine the

percentage axon regeneration per animal, and then averaged within each group. Final

animal numbers included in the analysis were as follows: for i-miR223 (n=5); for

scrambled (n=4); for crush/pierce control (n=5).

42

Chapter 3: Results

Results of the optimization of miR inhibitor injection are reported in the methods

section as these reflect technical aspects of the work. Data reporting the effect of i-miR

injection on RGC axonal regeneration are presented here.

The regeneration of RGC axons in zebrafish is characterised by the appearance of

regenerating axons at the lesion site 2 days post-injury, and extending into the optic

tract by 3-4 days post-injury (Becker & Becker, 2007). This is followed by further

growth into the optic tectum by about 7 days post-injury (Becker & Becker, 2007). In

this experiment, all control samples exhibited the expected timecourse of regeneration,

validating our approach.

3.1 Short term proof of principle study

The extent of regeneration was examined immunohistochemically at 3 days post-injury.

All fish showed regenerating RGC axons extending beyond the lesion site and into the

chiasm. The distance from the chiasm to the farthest regenerating axon appeared to be

lowest in the miR223 injected group (Fig. 3.1) but no statistical analysis could be

performed due to low numbers in the experimental groups.

43

Figure 3.1: Axon Regeneration 3 Days Post-Optic Nerve Crush

The y-axis represents the distance per mm2 travelled by regenerating axons from the crush

site. The absolute distance from the crush site to the tip of the farthest regenerating axon,

was slightly lower in the presence of the inhibitor compared to crush and scrambled

controls. The “Control injury” group represents fish crush injury but no injection.

This quantitative result was supported by the qualitative analysis of the distance and

density of regenerating axons (Table 3.1). In all control samples the majority of

regenerating axons was found at the outside of the optic nerve and tract, presumably

leaving the inside filled with cell debris. Furthermore, two control fish showed an

abundance of regenerating axons at the chiasm and all of them showed a greater

regeneration than the inhibitor samples (Fig.3.2 A-C). In contrast, the presence of the

inhibitor produced a sudden stop of regenerating axons after the optic chiasm, (2/2 fish)

(Fig3.2 D). The density of regenerating axons was difficult to quantify due to variable

tissue quality and there was no obvious difference between groups.

44

Table 3.1: Qualitative Analysis of Regenerating Axons in individual fish

Density

Crush2 ++ (mostly outside)

Crush3 +++( mostly outside)

Control injury3 ++ (mostly outside in tract; more at

chiasm)

Scrambled1 +++ (mostly outside in tract; more at

chiasm)

Scrambled2 +++ (mostly outside)

Scrambled3 +++ (patchy, mostly outside)

i-miR1 + (mostly outside)

i-miR2 + (more at chiasm)

+++ - strong in optic tract, filled

++ - sparse in optic tract, half filled

+ - stopped after chiasm, very sparse in optic tract

45

Figure 3.2: Regenerating Axons in the optic nerve and tract 3 Days Post-Injury

The regenerating axons of the scrambled control (A) are very abundant beyond the

crush site (X) and at the chiasm (Ch) and reach into the optic tract (Ot). The control

injury (B), as well as the crush control (C) show the same distance for axon regeneration

as the scrambled control (A). However, the regenerating axons are less dense and the

majority of the axons are found the outside of the nerve. In presence of the inhibitor (D)

the regenerating axons make a sudden stop after the optic chiasm but maintain a high

density at the chiasm. Scale bar: 500 µm.

3.2 Long term regeneration study

The first cohort of 48 fish were processed for optic nerve crush, miR or control

injections and perfused and cryoprotected. However, due to a freezer breakdown in the

summer of 2015-2016, the tissue thawed and proved to be unusable for

immunohistochemical analysis. The experiment was repeated with a lower number of

animals due to limitations of time and resources and the data collected are shown below.

Some problems with tissue quality and high background staining in some fish again

meant that analysis was limited and interpretation must be carried out with caution.

Examples of histology are shown in Figure 3.3. In all groups, RGC axons had

.

X

Ch

Ot

46

regenerated to occupy roughly 25-30% of the optic tectum by 7 days post crush (Figure

3.4). ANOVA showed that there was no significant difference between groups (p=

0.058).

Figure 3.3 Histology showing extent of regeneration 7 days after crush

Immunohistochemistry showing the extent of optic nerve regeneration in zebrafish

following control (pierce crush; A), i-mir223 (B) or scrambled control (C). Axons have

entered the rostral tectum (shown by *) and extend roughly ¼ of the full tectal extent

(limit of regeneration identified under 40x magnification and indicated by an arrow).

Scale bar: 500 µm

Figure 3.4. Quantification of the extent of regeneration 7 days after crush

There was no significant difference in the extent or distance of regeneration between

experimental groups. Groups: ‘crushpierce’: control, ‘i-miR’: targeted disruption of

miR-223, and ‘scrambled’: control for imiR-223 injection.

i-miR, n=5,

24.68%

scrambled, n=3,

23.60%

crushpierce,n=5,

28.70%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Pe

rce

nta

ge

te

ctu

m r

eg

en

era

ted

Regeneration of zebrafish tectum after ON crush

A B C

* * *

47

Chapter 4: Discussion

The aim of this experiment was to perform in vivo knockdown in the retina of the prime

candidate CNS-associated miRNA, miR-223, following an optic nerve rush in zebrafish,

in order to prevent optic nerve regeneration. Locked Nucleic Acid ‘anti-miRs’ can bind

to miRNA in vivo and cause its degradation, thus preventing their activity (Boon et al.,

2013). In this work we used an anti-miR targeted to suppress miR-223 in the eye after

an optic nerve crush in zebrafish. We first provided a proof of principle that injection of

a miR inhibitor reduced the levels of miR-223 and its target genes in the zebrafish

retina. Immediately following optic nerve crush we performed an injection of this ‘anti-

miR’; a ‘scramble anti-miR’ and mechanical equivalent intervention were used as

negative controls to assess the outcome on RGC axon regeneration.

These results indicate that knockdown of miR-223 alone is insufficient to change

regeneration in Danio rerio optic nerve injury. Possible reasons why experimental

groups did not show a clear different to the controls are discussed below.

4.1. An insufficient change in miRNA expression.

While the validation study did show a significant change in miRNA expression after

injection of the anti-miR, this was validated to only to 3 days post-injection, and the

data did indicate a trend at this time towards returning to pre-injection expression levels.

This could mean that while regeneration in the experiment was tracked for 1 week, the

miR-223 inhibition was only effective for the first half of that time. Further, it is

possible, given that miR-expression in general is known to be extremely dynamic and

variable over time, that the timepoints in which miR-223 most strongly regulates

48

regeneration of the optic nerve may not fall within the initial 3 days post-injury. This

could be addressed by using viral vectors to maintain sustained expression levels over

several weeks. AAV vectors have been proven to be an effective tool for overexpressing

and inhibiting miRNAs (Grobetal et al., 2014).

4.2 Insufficient change in gene expression.

It may be that the inhibition of ONLY miR-223 did not adequately upregulate its gene

targets. It was discovered on further research that the secondary target miRNA from the

dataset, miR-29b, in fact has some overlapping gene targets with miR-223. This would

suggest that in the suppression of miR-223 alone, miR-29b may provide ‘redundancy’

of gene regulation, downregulating expression of those same targets despite miR-223’s

lack of activity. This could be addressed by creating more experimental groups, in

which not only would miR-223 activity be suppressed in isolation, but also miR-29b in

isolation, and both miRNAs in combination. Before undertaking this, the predicted

targets of miR-29b would need to be experimentally validated (especially in the case of

those involved with cell survival and regeneration), and its knockdown in vivo

demonstrated.

4.3. Lack of accuracy in measuring regeneration, due to poor tissue quality.

The scope of this study was limited by the significant loss of an entire cohort of

experimental tissue at the end of my first year. Despite repeating the entire experiment,

my immunohistochemical analysis remained difficult to interpret with confidence due to

consistently high levels of background staining, regardless of the protocols and

detection methods we attempted, suggesting that tissue quality and problems with

histological processing caused significant technical limitations. In future, this could be

49

resolved by using a neuronal tracer to label regenerating RGCs without the need for

antibody detection. Preliminary studies in the lab after my experiments were completed

suggest that DiI (1,1’-dioctadecyl-3,3,3’,3’-tetramethylindocarbocyanine perchlorate)

injected into the eye can be used to label RGCs, and that this label can subsequently be

detected in the optic nerve, tract and tectum, although even using this method,

background auto-fluorescence levels remained high. Alternative mounting medias and

careful storage of tissue at constant temperature may further improve the quality of

histology.

4.4 Context and significance of my study

In humans, damage to the adult CNS has an extremely limited ability to regenerate

(Huebner & Strittmatter, 2009; Ramon & Cajal, 1928). CNS injury through insult or

disease is a leading cause of not only major human suffering, but of significant

economic impacts through the need for increased care, treatment and loss of ability to

work (Access-Economics, 2009; Findley, 2007). In the U.S.A. alone, 270 000 people

live with spinal cord injury (SCI) and ~12 000 new injuries are reported annually

(DeVivo, 2012; Thuret et al., 2006). It is therefore greatly important to carry out

research in discovering new therapeutic options to repair the damaged CNS.

This thesis builds on numerous findings within the field of CNS regeneration in

vertebrates. These have collectively demonstrated many examples of small, incremental

steps towards inducting successful regeneration of the central nervous system (Dietmar

Fischer, Peter Heiduschka, & Solon Thanos, 2001; Hellstrom & Harvey, 2011; Leaver

et al., 2006; Sindhu, Peter, Kathryn, & Bernard, 2011; Yin et al., 2003). While much of

the work to promote CNS regeneration in mammals has attempted to either mimic or

50

co-opt the mammalian peripheral nervous system’s regenerative ability and apply that to

the CNS, my thesis took an alternative approach by examining successful spontaneous

CNS regeneration in other vertebrates and applying those findings to mammals. While

the specific outcomes of this project were inconclusive, it has put in place the

framework for an improved study design which could more effectively investigate the

role of microRNA in CNS regeneration.

As briefly mentioned in the introduction, and as our primary rationale for a comparative

approach between vertebrate regeneration phenotypes, it may be that the variable

regeneration seen across phyla is in part the result of a causal relationship between

neurocomplexity and spontaneous neuroregenerative ability, whereby the increasingly

interrelated and subtle elements of a complex, fine-tuned and highly evolved CNS

inhibit its spontaneous regeneration after acquired injury, as a form of ‘evolutionary

collateral damage’. As seen in Figure 1, vertebrates which regenerate their CNS

completely (e.g. teleosts), mostly (e.g. amphibians) and those in which such

regeneration is extremely limited or abortive (e.g. mammals) lie along an increasing

trend line of neurocomplexity. This follows logically, as a more complex system would

be more challenging to regulate into a ‘regenerative state’ than a simpler one. This

could help explain why those vertebrates with simpler CNS makeups are better able to

spontaneously regenerate damage to them (Dunlop et al., 2004; Vajn, Plunkett,

Tapanes-Castillo, & Oudega, 2013).

But why would evolutionary pressures lead to a LOSS of spontaneous CNS

regeneration? One of the major determinants of the success of humans as a species is

our large, complex brain (Sherwood, Subiaul, & Zawidzki, 2008). The ability to enact

cognition at a high level thus provides a strong selector for evolutionary fitness and

51

reproductive advantage. This is true in terms of sexual selection, species survival (e.g.

through advanced language) and overall individual survival, though this latter may be

substantially less true in a globalised world (Arden et al., 2015; Miller, 2000; Sherwood

et al., 2008). Thus, our evolution has favoured increasing neurocomplexity. However,

given that natural selection only acts on traits which manifests prior to reproduction and

rearing of the young, and given that the ability to regenerate damage to the CNS would

only come into play in the case of rare injury or a later-in-life CNS disease, one can

surmise that the traits of spontaneous CNS repair are not strongly selected for. This may

well have led to its being lost in tandem with increasing vertebrate neurocomplexity.

This possibility further supports an investigation in miRNA as potentially inhibitory to

regeneration in mammals, as increasingly neurocomplex vertebrates have a much larger

complement of this regulatory element and they have been reported to have significant

effects in neural development (Bian & Sun, 2011; He & Hannon, 2004; Heimberg,

Sempere, Moy, Donoghue, & Peterson, 2008).

The pilot study conducted by Fuller-Carter et. al. (Fuller-Carter et al., 2015) using

microarray expression data from retina of zebrafish and rat at 3 days post ON crush

post-injury, identified a list of ‘top candidate’ miRNA (and their respective validated

gene targets) which could play a role in CNS regeneration. The analysis used

bioinformatics techniques to investigate gene ontology and networks, in combination

with the gene expression data indicating upregulated and downregulated genes during

regeneration. Thus, the study attempted to identify miRNA which could plausibly

influence known or suspected neuroregenerative processes and were differentially

expressed between these species. While several miRNA within zebrafish were identified

to be plausibly involved in regeneration; the top 2 candidates were miR-223 and miR-

29b.

52

miR-223 acts in the regulation of genes involved with inflammation, which has

been reported to both enhance and hinder the regenerative process (Haneklaus,

Gerlic, O'Neill, & Masters, 2013; Kyritsis et al., 2012; Wyss-Coray & Mucke,

2002). It has also been reported to inhibit calcium influx in neurons, which plays

a role both in regeneration and in prevention of cell death (Ferguson & Son,

2011; Harraz et al., 2012; Rehder, Jensen, & Kater, 1992).

miR-29b has been reported to prevent apoptosis and become activated during

neuronal maturation (Kole, Swahari, Hammond, & Deshmukh, 2011; Y. Zhang

et al., 2014). The miR-29 family directly targets at least 16 genes involved with

the extracellular matrix (reviewed in) (Fu, Zhou, Cheng, Liao, & Zhou). It is

also associated with neurodegenerative disease (reviewed in (Bicchi, Morena,

Montesano, Polidoro, & Martino, 2013; Villa et al., 2013).

miR-223 and miR-29b expression levels have been observed to be associated in

muscle tissue, suggesting that they may act synergistically (Kin et al., 2012).

This possibility is supported by evidence that these two miRNAs act together to

regulate cyclin T1 protein levels (Chiang, Sung, & Rice, 2012; Rottiers & Näär,

2012).

The functional characterisation of miRs through bioinformatics-based investigation is

by necessity a ‘best-guess’ with a number of challenges (Vlachos et al., 2015; Witkos,

Koscianska, & Krzyzosiak, 2011). This is in part due to the fact that there is no ‘gold

standard’ tool or collection of tools and that miRNA databases (particularly in

zebrafish) are substantially lacking in experimentally validated miRNA and targets (Cho

et al., 2005; Grimson et al., 2007). Even most validated miRs within a zebrafish dataset

have ‘predicted’ gene targets only (Cho et al., 2005; Grimson et al., 2007). This

necessitates further experimental validation on the part of a laboratory investigating the

53

potential effects of any specific miRNA. There are substantial limitations to using

alternate software tools/approaches and taking the ‘intersect’ of results (meaning that

only results which are indicated in both or multiple approaches are taken as ‘valid), as

this tends to vastly under-report likely miRNA and their gene targets (Tabas-Madrid,

Muniategui, Sánchez-Caballero, Martínez-Herrera, Sorzano, Rubio, & Pascual-

Montano, 2014). Further, using a ‘union’ methodology, in which two or more

approaches are used and results from both datasets are combined tends to vastly over-

report these results (Tabas-Madrid et al., 2014). However, there are workflows designed

to combat these limitations (Karbiener, Glantschnig, & Scheideler, 2014), and within

the context of this work we are reasonably confident in the predictions made.

A much more comprehensive approach than the use of microarrays would have been

complete miRNA sequencing from the tissue, however this is much more expensive

(Zhao, Fung-Leung, Bittner, Ngo, & Liu, 2014). This approach leads to unbiased

detection of novel transcripts (microarrays require species- and transcript-specific

probes in order to indicate their presence) as well as enhanced detection of genes,

transcripts and differential expression (Pritchard, Cheng, & Tewari, 2012) . It also

avoids issues of cross-hybridisation between probes and their limited detection range, as

well as those of probe redundancy and annotation (Zhao et al., 2014). Essentially,

microarrays tend to find examples of transcripts we are already aware of and miss those

which may be novel. RNA-Seq also provides for increased detection of rare and low-

abundance transcripts, though of course in this study a low-abundance transcript would

be unlikely to have a significant biological effect, and entirely novel transcripts would

be very difficult to justify investigating as their target genes would not be known and

therefore difficult if not impossible to quantify as likely/unlikely to influence

regeneration beyond simple changes in expression levels.

54

These microarray-derived results were somewhat confounded by using miRNA derived

from the whole eye, where this work focused on RGC axonal growth specifically.

However, RGCs represent less than 0.1% of all cells in the retina and changes in gene

expression within this population may be swamped if the whole retina is collected (this

may have contributed to the low number of differentially regulated genes we observed

in our pilot study; (Nadal-Nicolás et al., 2009). While it is possible to sort RGCs based

on the expression of cell surface markers, the lengthy process of antibody binding and

FACS or magnetic bead sorting is likely to induce changes in gene expression that are

irrelevant to the regenerative process we are examining. W/Prof Harvey developed a

physical isolation method in which the RGC layer is scraped from frozen retinal

sections and RNA extracted following standard procedures (LeVaillant et al., 2016).

Although this preparation still contains a mixed population (60% RGCs & 40%

amacrine cells in rats (Perry, 1981), similar numbers in fish (Zhang, Bonilla, Zhang, &

Leung, 2014), it represents a significant improvement over previous studies, which

extracted mRNA from the entire retina and included photoreceptors, interneurons, glial

cells and others.

There is an argument to be made for using whole-eye derived samples in the

experiment, as gene expression surrounding the axonal regeneration may well play a

part, such as inducing inflammation, which brings with it pro-regenerative factors such

as macrophage-derived oncomodulin (Yin et al., 2006). On the other hand, the close-

range nature of miRNA action would suggest that a more targeted approach would

result in identification of miRNA targets more likely to play a more direct and

significant role in RGC regeneration, and thus more likely to result in changed regrowth

after intervention. Another concern with this analysis is the small sample size, however

55

once more this was a cost-based compromise and difficult to avoid without significantly

more funding. Furthermore, the use of different techniques of analysis (both inverted

expression between regenerative and non-regenerative phenotypes and bioinformatics-

based predicted targets) resulted in several targets of high confidence, and the validation

of miR-223 action within the tissue post-selection alleviated any remaining concerns.

Overall, while these results are ultimately inconclusive, this work has paved the way for

a more rigorous repetition of the study, which could lead to validated method of

modulating regeneration-based gene expression in zebrafish and its extrapolation to

benefitting regeneration of the mammalian CNS.

Future directions

A key aspect of both miRs identified in the comparative bioinformatics analysis was

that both play a role in regulation of the immune response. My thesis primarily

investigated the effect of inhibiting miR223 on axonal regeneration per se, however, it

would also be of interest to examine whether miR223 affected the immune response

after optic nerve crush. As briefly outlined in the introduction, inflammation, as part of

the inducted immune response following CNS injury, appears in mammals to have a

complicated relationship with regeneration. A number of studies have reported that

localised inflammation can act to increase the regenerative properties of the CNS,

however there is an equally compelling body of evidence to suggest a negative impact

of inflammation on repair (Mietto, Mostacada, & Martinez, 2015). There are clear

differences between zebrafish and rats in terms of their inflammatory (and general

immune response) in the case of ON crush injury (Benowitz & Popovich, 2011; Filbin,

2006; Kyritsis, Kizil, & Brand, 2014; Kyritsis et al., 2012; Yin et al., 2009). In teleosts

like zebrafish, the RGCs do not die in large numbers, and those that do generally follow

56

the cell death path of apoptosis (McCurley & Callard, 2010). By contrast, mammalian

ON crush injuries result in large numbers of RGC death by both apoptosis and necrosis

(Berkelaar et al., 1994). Necrosis, in which the cell content leak out into the surrounding

areas, inducts significantly more inflammation, and the formation of glial scars, which

inhibit regeneration (Fawcett, Schwab, Montani, Brazda, & MÜller, 2012; Filbin,

2006). The immune response in the case of zebrafish is rapid and localised and may

promote regeneration (Kyritsis et al., 2012; Nona, 1998). In rats, the response is slower,

more generalised, and more extreme (Mietto et al., 2015). Ultimately, it may be that

miR-223 modulates regeneration indirectly by regulating and coordinating the immune

response. As shown by Jenny Ilgen’s work in her 2015 thesis (Ilgen, 2015), macrophage

and neutrophil recruitment to the vicinity of an optic nerve crush in zebrafish does

appear to be affected by this molecule. Given inflammation’s clear, though complex,

involvement in the regenerative process it may be only due to the limitations of this

study that a real effect by miR-223 suppression was dissipated by the 7 day timepoint.

My work has identified a number of improvements such a subsequent investigation

might make in order to explore the role of miR-223 (and miR-29b) in the future.

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