SLPI) in Progranulin Regulation and Neurodegeneration

The Role of Secretory Leukocyte Protease Inhibitor (SLPI) in progranulin regulation and neurodegeneration

2013

By Greg Toulson (B.Sc.)

School of Medicine

A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy (PhD) in the Faculty of Medical and Human Sciences.

Supervisors: Prof. Stuart Pickering-Brown and Prof. Stuart Allan

P a g e | 2

Table of contents:

Table of contents -P.2-

List of figures and tables -P.5-

Abstract -P.8-

Declaration -P.9-

Acknowledgements -P.10-

Commonly used abbreviations -P.11-

Chapter I: Introduction

1.1 An Introduction to FTLD -P.13-

1.2 FTLD Syndromes -P.13-

1.3 The Proteinopathies of FTLD -P.15-

1.4 Microtubule associated protein tau -P.15-

1.5 Tar binding protein 43 and the granulin gene -P.16-

1.6 TDP associated genes: C9Orf72, VCP and TARBP -P.17-

1.7 Fused in Sarcoma and FTLD-UPS -P.18-

1.8 The neurodegenerative disease spectrum -P.19-

1.9 Proposed mechanisms of TDP-43 aggregation -P.19-

1.10 Post transcriptional modification of TDP-43 -P.22-

1.11 TDP-43 proteinopathy based animal models -P.24-

1.12 Progranulin in wound response -P.25-

1.13 Granulin null mice -P.28-

1.14 Secretory Leukocyte Protease Inhibitor -P.28-

1.15 SLPI null mice as a potential FTLD model -P.30-

1.16 Conclusions -P.31-

1.17 Project aims -P.31-

P a g e | 3

Chapter 2: Materials and methods

2.1 Establishing a SLPI null colony -P.35-

2.2 Genotyping of mice -P.35-

2.3 Handling of animals and general test principals -P.37-

2.4 Processing of tissue for biochemical analysis -P.38-

2.5 Cell culture: siRNA, plasmid and enzyme treatment -P.43-

2.6 Antibody characterisation for western-blot -P.43-

2.7 Progranulin ELISA validation -P.44-

2.8 Immunoglobulin clearance of blood plasma -P.46-

2.9 Neutrophil Elastase activity assay -P.46-

2.10 Primary neuronal culture -P.47-

2.11 Wax sectioning and immunohistochemistry -P.48-

2.12 Antibodies used -P.49-

2.13 Statistical analysis -P.49-

Chapter 3: Behavioural evaluation of SLPI null mice

3.1 Introduction -P.51-

3.2 Methods -P.52-

3.3 Open-field arena and Y-maze spontaneous alternation -P.55-

3.4 Social interaction/preference and olfactory discrimination -P.57-

3.5 Tail suspension and Pavlovian fear conditioning -P.61-

3.6 Discussion of behavioural evaluation -P.64-

Chapter 4: Biochemical analysis of SLPI regulation of Progranulin.

4.1 Introduction -P.68-

4.2 Methodology -P.69 -

4.3 Results from Brain homogenate analysis -P.70-

4.4 Results from Lung homogenate analysis -P.71- P a g e | 4

4.5 Results from blood serum analysis -P.73-

4.6 Results from cell culture based analysis -P.76-

4.7 Discussion -P.80-

Chapter 5: Immunohistochemical evaluation of SLPI null brains

5.1 Introduction -P.85-

5.2 Methodology -P.86-

5.3 Pathological examination for FTLD hallmarks -P.86-

5.4 Discussion of immunohistochemical results -P.91-

Chapter 6: Conclusions

6.1 Conclusions -P.94-

6.2 Future experiments -P.97-

Chapter 7: References -P.100-

Chapter 8: Supplementary information -P.116-

Supplementary results -P.121-

P a g e | 5

List of tables and figures

Figure 1.2.1: The current terminology for different FTLD syndromes. -P.14-

Figure 1.3.1: Proteinopathies and nomenclature of FTLD. -P.15-

Figure 1.5.1: The current classification system for FTLD-TDP. -P.17-

Figure 1.9.1: Schematic showing TDP-43 fragments and isoforms. -P.21-

Figure 1.12.1: Proposed inflammatory signalling from progranulin and SLPI. -P.27-

Figure 2.1.1: Genotyping optimisation for SLPI null primers. -P.37-

Figure 2.1.2: Genotyping validation. -P.37-

Figure 2.3.1: Fear conditioning programme used to illicit a Pavlovian response. -P.40-

Figure 2.6.1: Deglycosylation of progranulin using EndoH and PNGase. -P.44-

Figure 2.6.2: T98G lysate probed with progranulin, SLPI and actin. -P.44-

Figure 2.7.1: Standard curve generated from progranulin standard vs. OD405. -P.45-

Figure 2.7.2: Spike assay showing the serial dilution of blood plasma. -P.46-

Figure 2.8.1: Immunoglobulin depletion calibration for progranulin. -P.46-

Figure 2.12: Antibodies used in western blot and IHC. -P.49-

Figure 3.2.1: Sequence of behavioural tests from least stressful to most stressful. -P.52-

Figure 3.2.2: Schematic of the Open-Field arena. -P.54-

Figure 3.2.3: Schematic of the Y-maze arena. -P.54-

Figure 3.2.4: Schematic of the tail suspension test. -P.54-

Figure 3.2.5: Schematic of the social interaction arena. -P.54-

Figure 3.2.6: Schematic of the fear conditioning arena. -P.54-

Figure 3.3.1: Open-field, total distance travelled. -P.55-

Figure 3.3.2: Open-field, percentage time spent in the centre of arena. -P.55-

Figure 3.3.3: Spontaneous alternation of 3xTg mice vs. Non-tg. -P.56-

Figure 3.3.4: Spontaneous alternation of SLPI null vs. WT mice. -P.56-

Figure 3.4.1: Social interaction paradigm, interaction time. -P.57-

Figure 3.4.2: Linear regression analysis of social interaction paradigm. -P.58- P a g e | 6

Figure 3.4.3: Social preference paradigm, interaction time. -P.59-

Figure 3.4.4: Linear regression analysis of social preference paradigm. -P.59-

Figure 3.4.5: Olfactory discrimination task, time spent sniffing. -P.60-

Figure 3.4.6: Linear regression analysis of olfactory discrimination task. -P.60-

Figure 3.5.1: Tail suspension test, time spent immobile. -P.61-

Figure 3.5.2: Linear regression analysis of tail suspension test. -P.61-

Figure 3.5.3: Fear conditioning, Entrainment. -P.62-

Figure 3.5.4: Fear conditioning, Environmental recall. -P.63-

Figure 3.5.5: Fear conditioning, conditioned response recall. -P.63-

Figure 4.3.1: Progranulin western blot of frontal brain homogenate, 20 months. -P.70-

Figure 4.3.2: Progranulin western blot of frontal brain homogenate, 12 months. -P.70-

Figure 4.3.3: Western blot of elastase, SLPI and actin. Elastase activity assay. -P.71-

Figure 4.4.1: Progranulin western blot of lung homogenate, 20 months. -P.72-

Figure 4.4.2: Progranulin western blot of lung homogenate, 12 months. -P.72-

Figure 4.4.3: Western blot of elastase, SLPI and actin. Elastase activity assay. -P.73-

Figure 4.5.1: Progranulin concentration of blood plasma of male mice. -P.73-

Figure 4.5.2: Regression analysis of progranulin, blood plasma of male mice. -P.74-

Figure 4.5.3: Progranulin concentration of blood plasma of female mice. -P.74-

Figure 4.5.4: Regression analysis of progranulin, blood plasma of female mice. -P.75-

Figure 4.5.5: Regression analysis of progranulin, blood plasma, both sexes. -P.75-

Figure 4.5.6: Progranulin western blot of IgG depleted blood plasma. -P.76-

Figure 4.5.7: SLPI and Elastase western blot of plasma and elastase activity assay -P.76-

Figure 4.6.1: Progranulin and SLPI western blot of NE treated T98G media. -P.77-

Figure 4.6.2: Progranulin western blot of NE/DPPI treated T98G media. -P.77-

Figure 4.6.3: Progranulin western blot of DPPI treated, expressed pro-NE. -P.78-

Figure 4.6.4: Progranulin western blot of LPS treated primary neurones. -P.78-

Figure 4.6.5: Progranulin ELISA of LPS treated primary neurones, T=12 hours. -P.79-

Figure 4.6.6: Progranulin ELISA of LPS treated primary neurones, T=24 hours. -P.79- P a g e | 7

Figure 4.6.7: Neutrophil elastase activity of LPS treated primary neurones. -P.79-

Figure 5.3.1: Hippocampal sections stained with glial fibrillary acid protein. -P.86-

Figure 5.3.2: Cortical sections stained with glial fibrillary acid protein. -P.87-

Figure 5.3.3: Hippocampal sections stained with TDP-43. -P.87-

Figure 5.3.4: Cortical sections stained with TDP-43. -P.88-

Figure 5.3.5: Hippocampal sections stained with ubiquitin. -P.88-

Figure 5.3.6: Cortical sections stained with ubiquitin. -P.89-

Figure 5.3.7: Hippocampal sections stained with FUS. -P.89-

Figure 5.3.8: Cortical sections stained with FUS. -P.90-

Figure 5.3.9: Hippocampal sections stained with tau. -P.90-

Figure 5.3.10: Cortical sections stained with tau. -P.90-

Sup. Fig. 1: Immunoglobulin depleted blood plasma of 12 month old, -P.122- alternating male and female samples. Sup. Table 1: 2-way ANOVA, multiple comparisons. Fear conditioning Day 1. -P.122- Sup. Table 2: 2-way ANOVA, multiple comparisons. Fear conditioning Day 1. -P.123- Sup. Table 3: 2-way ANOVA, multiple comparisons. Fear conditioning Day 2. -P.123- Sup. Table 4: 2-way ANOVA, multiple comparisons. Fear conditioning Day 3. -P.124- Sup. Table 5: 2-way ANOVA, multiple comparisons. Fear conditioning Day 3. -P.124-

P a g e | 8

Abstract

Frontotemporal lobar degeneration (FTLD) is an early onset neurodegenerative disorder which selectively destroys frontal and temporal cortical neurones. The resulting damage leads to a range of language and behavioural deficits; however, episodic memory is generally maintained. Around 10% of FTLD cases are caused by progranulin gene mutations that lead to haploinsufficiency and reduced expression of progranulin.

Secretory leukocyte protease inhibitor (SLPI) has been shown to have a key protective effect over progranulin, inhibiting enzymatic cleavage by neutrophil elastase. Previous work demonstrating this role of SLPI is largely from in vitro studies and scenarios with above- physiological SLPI concentrations. To ascertain a role for endogenous SLPI in the regulation of progranulin, a murine SLPI knockout model was used and tonic progranulin measurements taken. No change in circulating progranulin levels were seen in SLPI null mice (at 6, 12 or 20 months of age) when compared to non-transgenic controls, though significant differences were observed between male and female SLPI null animals. Similarly, tissue (brain and lung) levels of progranulin were comparable between wild-type and SLPI null mice, despite the presence of active neutrophil elastase. Behavioural analysis of SLPI null mice revealed no major phenotype when compared to wild- type, over a range of behavioural tests. However primary neuronal cultures taken from SLPI null mice did display an elevated progranulin response to bacterial lipopolysaccharide (LPS). These data suggest that, although SLPI may play a role in progranulin regulation during an inflammatory event, it is unlikely to play a major role in progranulin regulation under basal conditions, as reported previously. Therefore under disease conditions regulation of extracellular progranulin is likely through other modulatory factors that have yet to be described.

P a g e | 9

Declaration

No portion of the work referred to in this thesis has been submitted in support of an application for another degree or qualification from either the University of Manchester or any other university or institute of learning.

I.) The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes.

II.) Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made.

III.) The ownership of certain Copyright, patents, designs, trade marks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions.

IV.) Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=487), in any relevant Thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.manchester.ac.uk/library/aboutus/regulations) and in The University’s policy on Presentation of Theses

P a g e | 10

Acknowledgments

“Team dementia” (past and present) has my unending thanks for dealing with 3 years of stupid questions, small favours, moderate favours and totally unreasonable favours. Nicola Halliwell, Steve Sikkink, Sara Rollinson, Sue Usher and Kate Young have all endured my pestilence well and have made my time in the laboratory an enjoyable one.

My project would have been totally impossible were it not for the mentoring of Janis Callister who deserves not only my thanks, but some kind of monument to be erected in her honour. Thank you for being the ground zero of unrelenting questions, existential doubts and generally sorting things out when it all went horribly wrong.

To my friends Sandy Rolph and Alex Ryan who have been a constant source of inspiration; if inspiration can be defined as rampant alcohol consumption and shouting. Similar thanks goes to Hannah Gornell, Brook Cooper, David Allen, William Montague, Ben Dobres and Taba Easton who have all prevented me from having a psychotic episode over the last 3 and a bit years and instead made it quite fun. Thanks also to Thomas Larrieu and Muna Hilal-Larrieu for a wonderful stay in Bordeaux and the tutoring in behavioural testing.

As always, my mum, dad and sister have been quite simply brilliant; there is absolutely no way I can thank them enough.

Thanks to R & D systems for making antibodies that actually work and to all the other suppliers and facilities that I have used over the years. Thanks also to Ugo Basile and San Diego Instruments for their great equipment and consent to use their images.

The Neuroscience Research Institute have been a brilliant organisation to work with, not only for funding this project but also in introducing me to different aspects of neuroscience and giving me opportunities to display my work. Thanks also to the University of Manchester for 8 incredible years of scientific pursuit, brilliant friends and financial destitution.

My final thanks go to both of my supervisors: Stuart Allan and Stuart Pickering-Brown, who have been incredibly understanding when work wasn’t going well and provided a near encyclopaedic knowledge of science and technical solutions to problems. Generally, thanks for being great to work for.

P a g e | 11

Abbreviations:

AD: Alzheimer’s disease,

ALS: Amyotrophic lateral sclerosis,

ALP: Autophagy-lysosomal pathway, bvFTD: Behavioural-Variant Frontotemporal Dementia,

CHMP2B: Charged multivesicular body protein 2b,

DN: Dystrophic neurites,

FTLD: Frontotemporal Lobar Degeneration,

FUS: Fused In Sacoma,

GRN: Granulin,

IHC: Immunohistochemistry,

KO: Knock-out, lvPPA: logopenic variant PPA,

MAPT: Microtubule Assembly Protein Tau,

NCIs: Neuronal Cytoplasmic Inclusions,

NIIs: Neuronal Intranuclear Inclusions,

PNFA: Progressive Non-Fluent Aphasia,

SLPI: Secretory Leukocyte Protease Inhibitor,

SD: Semantic Dementia,

TDP-43: Tar Binding Protein 43kDa,

TNF: Tumour Necrosis Factor,

TNFR: Tumour Necrosis Factor Receptor,

UBQLN: Ubiquilin-1,

UPS: Ubiquitin Proteosome System.

VCP: Valocin Containing Protein, P a g e | 12

Chapter 1: Introduction

P a g e | 13

1.1: An Introduction to Frontotemporal Lobar Degeneration

Frontotemporal lobar degeneration (FTLD) is an umbrella term used to encompass a spectrum of presenile dementias, which result from a number of underlying pathologies that manifest as focused atrophy of the frontal and temporal cortical areas (Cairns et al., 2007). FTLD can display an autosomal dominant pattern of inheritance (Stevens et al., 1998) and represents one of the three most common causes of dementia in those under the age of 65 years (Harvey et al., 2003 and Borroni et al., 2009). FTLD is classified as a number of different sub-syndromes, each corresponding to a differing set of clinical symptoms. In general, patients experience some form of progressive linguistic decline and/or negative changes to behaviour with a subset of patients also co-exhibiting motor dysfunction (Neary et al., 1998). Despite its prevalence, current available therapies to combat FTLD are limited to only masking some of the behavioural symptoms using anti-depressant medication (such as selective serotonin reuptake inhibitors) and not treating the underlying illness. 1.2 FTLD Syndromes The symptomatic presentation of FTLD can be broadly divided into 2 clinical entities: behavioural variant frontotemporal dementia (bvFTD) and primary progressive aphasia (PPA) (Gorno-Tempini et al., 2011) where the behavioural variant accounts for 56-70% of the total observed FTLD cases (Johnson et al., 2005 & Snowden et al., 2007). Patients with bvFTD display a profound and detrimental change to their behaviour which can include: emotional blunting, disinhibition, reduced social insight, apathy, altered eating habits or the adoption of highly regimented behaviour (Neary et al., 1998).

Figure 1.2.1: The current terminology for different FTLD syndromes and phenotypes.

Although most mental faculties may be retained within bvFTLD; the adoption of dispassionate, inappropriate or socially abrasive tendencies can lead to the exclusion of sufferers from social support networks and society as a whole. In addition to behavioural symptoms, some bvFTD P a g e | 14 suffers can also develop Parkinsonism, marked by uncontrolled muscle movements, limb rigidity and reduced motor speed (Wszołek et al., 2005). A diagnosis of PPA is made if a patient exhibits a specific profile of language dysfunction that progressively worsens over time. After this initial diagnosis a PPA sufferer can then be sub- dived into one of 3 distinct syndromes: Semantic dementia, Progressive nonfluent aphasia (PNFA) or Logopenic variant PPA (lvPPA): a form of Alzheimer’s disease (see figure 1.2.1). Semantic dementia is characterised as the loss of the meaning of words (from which the disorder derives its name), leading to a progressive decline in language comprehension whilst retaining episodic memory (Neary et al., 1998; Gorno-Tempini et al., 2011). A subset of Semantic dementia patients also show deficits within the comprehension of visually based cues like objects or faces, despite the patient retaining the ability to perceive them (Kertesz et al., 2003). While some suffers of Semantic dementia may go on to develop behavioural problems in the later stages of the disease; these are typically less severe than those expressed in bvFTD. Some emotional blunting may also occur (as is observed in bvFTD); however, it appears to be confined to a limited capacity for fear, while other patients display an increased preference for social contact (Snowden et al., 2001). Within a PNFA phenotype, patients retain their ability to comprehend words; however, speech production and grammar deteriorate resulting in an increasingly effortful speech with profound agrammatism. Behavioural symptoms only occur in the latest stages of PNFA and are typically less severe than bvFTD (Buratti and Baralle 2009; Gorno-Tempini et al., 2011). While being caused by (atypical) Alzheimer’s disease, patients with lvPPA display similar speech affects to FTLD. lvPPA is characterised by slow speech speed, deficits within word retrieval and sentence repetition; however, recognition of single words is generally maintained. It is hypothesised that lvPPA is a deficit within the phonologic (the sounding out of words) short term memory; not a semantic or grammatical component (Gorno-Tempini et al., 2008). Each disorder displays characteristic, localised atrophy leading to a loss of specific regional functionality (i.e. area's responsible for language or social insight). PNFA displays a highly asymmetrical pattern of atrophy affecting the left hemisphere, particularly the perisylvian language areas (Mesulam et al., 1982, Neary et al., 1998). Whereas, Semantic dementia exhibits bi-temporal neocortical asymmetric atrophy including the middle and inferior temporal gyri, with the bias of left to right hemispheric atrophy influencing the degree of semantic (left) or visual (right) agnosia (Snowden et al. 2001). Specific behavioural presentations of bvFTD (apathetic, disinhibited and stereotypical phenotypes) correlate well with the observed pattern of atrophy. Degeneration is typically symmetrical, bilateral and confined to the frontal and anterior temporal lobes with additional deterioration of the striatum also occurring in a number of patients (Neary et al., 2000). P a g e | 15

The behavioural phenotype that is observed often correlates with specific underlying genetic mutation: C9Orf72 mutations (detailed in section 1.6) commonly co-exhibit with psychosis or paranoid delusions (Snowden et al., 2013). Conversely, some mutations can result in a range of disease phenotypes: various GRN mutations can manifest as bvFTD, SD or PNFA depending on the individual (Finch et al., 2009).

1.3: The proteinopathies of FTLD

Analogous to the range of different FLTD symptoms, the underlying causes of FTLD are a diverse and interconnected spectrum. Four distinct groups have been described within FTLD based upon which aggregated protein is observed: tau, TDP-43, FUS or ubiquitinated non- specific proteins (See fig 1.3.1) (Cairns et al., 2007 & Mackenzie et al., 2010). The discovery of these proteins has been an extremely long process and has built upon early clinical, histological and genetic studies.

Figure 1.3.1:Proteinopathies and nomenclature of FTLD. Adapted from Mackenzie et al., 2011.

1.4: Microtubule associated protein tau. Around 40% of FTLD suffers have a positive family history for the disease (Chow et al., 1999) making genetic linkage studies a mainstay in the discovery of FTLD related genes. A number of early linkage studies identified chromosome 17q21 -22 as an area of interest (Wilhelmsen et al., 1994). Subsequent sequencing of this region identified mutations within the MAPT gene as being present in many FTLD patients (Hutton et al., 1998, Poorkaj et al., 1998 and Spillantini et al 1998). These MAPT mutations are now known to account for roughly 10% of all FTLD cases and arise from a number of different pathogenic mutations (Seelaa et al., 2008).

MAPT encodes the microtubule associated protein (MAP): tau, an essential component for functional microtubule assembly (Cleveland et al., 1977) and regulator of intercellular trafficking (Ebneth et al., 1998). Prior to the identification of MAPT mutations in FTLD, P a g e | 16 immunohistochemical evidence of hyper-phosphoryled tau was observed in a number of neurodegenerative disease including: Alzheimer's disease (Spillantini et al., 1996), corticobasal degeneration (Mori et al., 1994) and progressive supranuclear palsy (Verny et al., 1998, Pitmann et al., 2005). Although this strongly suggested a pathological role for tau, it was not until causative mutations within the MAPT gene were found that a definitive link could be drawn between mutant tau and neurodegeneration.

The utilisation of tau specific antibodies in immunohistochemical studies has led to the term “Tauopathy” to denote neurodegenerative diseases in which intercellular tau positive deposits can be observed, over 20 of which have now been characterised (Williams 2006). All FTLD disorders in which tau positive aggregates are observed are grouped together and classified as “FTLD-Tau”, See figure 1.3.1 (Mackenzie et al., 2010).

1.5: Tar binding protein: TDP-43 and the granulin gene. Many FTLD families who showed linkage to chromosome 17q21-22 did not display tau pathology (Rademakers et al., 2005) an observation that was explained by the discovery of a second dysfunctional FTLD gene, granulin (GRN), just 1.7 Mb from the MAPT gene (Baker et al., 2006 and Cruts et al., 2006). The GRN gene encodes progranulin (also known as acrogranin and proepithelin), a wound related growth factor (He et al., 2003). Progranulin has been shown to be heavily involved in inflammatory wound response (Zhu et al., 2002) and as a developmental factor in neurogenesis (Suzuki et al., 2009). FTLD cases that arise from GRN mutations do not show tau pathology or reveal any evidence of abnormally localized or aggregated progranulin within inclusion bodies (Mackenzie et al., 2006). However, GRN mutations do lead to the formation of ubiquitinated neuronal cytoplasmic inclusions (NCIs) or neuronal intranuclear inclusions (NIIs) that contain aggregated tar binding protein-43 (TDP-43) (Arai et al., 2006, Neumann et al., 2006). A number of different GRN mutation mechanisms have been observed in FTLD: mutation of the initiation methionine, those which induce nuclear degradation due to the inability of mRNA to leave the nucleus or those which result in nonsense mediated decay of mRNA prior to translation (Baker et al., 2006 and Cruts et al., 2006). Additionally, missense mutations can result in degradation of mutant progranulin protein via the secretory pathway (Schymick et al., 2007, Van der Zee et al., 2007 and Shankaran et al., 2007), while mutations that alter the progranulin signal sequence (Mukherjee et al., 2006) lead to miss-sorting and reduced expression (Shankaran et al., 2007). All reported mutations result in progranulin haploinsufficiency, the transcriptional loss of 1 allele leading to a reduction of progranulin expression. These pathogenic mutations in the GRN gene are thought to account for roughly 10% of all FTLD cases (Seelaa et al., 2008). P a g e | 17

Immunohistochemical classification of FTLD is broadly split between cases that show tau positive aggregates (NCIs, Pick bodies or neurofibrillary tangles); and those that show tau negative, ubiquitin positive aggregates (NIIs, NCIs and dystrophic neuritis) (Cairns et al., 2007). However, (poly) ubiquitination alone does necessarily imply cellular pathology. Ubiquitination is as a post transcriptional modification which can regulate a diverse range of protein functions such as kinase activation, endocytosis and most commonly attributed to being a degradation tag for the ubiquitin proteosome system (UPS) (for review, see Pines and Lindon 2005). The vast majority of tau negative, ubiquitin positive, FTLD cases also show immunoreactivity for TDP-43 (Arai et al., 2006, Neumann et al., 2006). Like Tauopathies; TDP-43 proteinopathy is observed in a number of different neurodegenerative diseases including amyotrophic lateral sclerosis (ALS) (Arai et al., 2006, Neumann et al., 2006) and Alzheimer's disease (Amador-Ortiz et al., 2007). However, GRN mutations are not the only instigator of TDP-43 dysfunction and a number of different genes associated with TDP-43 pathology have now been described. Despite these different underlying causes, all FTLD cases that show TDP-43 dysfunction are categorised as “FTLD-TDP” (Mackenzie et al., 2010) (see figure 1.2). The observed FTLD-TDP pathology is then further sub-classified into types: A, B, C or D; based upon the distribution and appearance of TDP-43 aggregates using IHC (Mackenzie et al., 2011), see figure 1.5.1.

Figure 1.5.1: The current classification system for FTLD-TDP based on aggregate morphology and localisation, adapted from Mackenzie et al., 2011.

1.6: TDP-43 related genes: C9ORF72, VCP and TARBP mutations The first FTLD-TDP related gene to be identified was valosin containing protein (VCP). A number of VCP mutations have now been identified and are thought to instigate FTLD in around a third of carriers (30% penetrance) (Watts et al,. 2004). The VCP protein is thought to be critical in protein degradation via the endoplasmic reticulum associated degradation pathway and the UPS: implying that a loss of VCP function likely inhibits neurones ability to clear aggregated TDP-43 (Weihl et al., 2009). Some VCP mutations are also observed to lead to TDP- 43 dysfunction which manifests as ALS (Johnson et al., 2010). This overlap is observed in a number of different FTLD causative genes, indeed, mutations within the TDP-43 encoding gene itself (TARBP) are capable of instigating TDP-43 pathology, but only manifest as ALS and not FTLD (Van Deerlin et al., 2008; Gendron et al., 2012). P a g e | 18

In 2011, two independent research consortiums using differing experimental methodologies identified a hexanucleotide expansion [GGGGCC]n=500-4000 within the C9Orf72 gene as being the cause of chromosome 9 linked FTLD and ALS (Renton et al., 2011; DeJesus-Hernandez et al., 2011). C9Orf72 repeat expansion carriers who develop FTLD or ALS display a unique pathology whereby phosphorylated TDP-43 aggregates are observed within the cortex, however; they are accompanied by TDP-43 negative neuronal cytoplasmic inclusions within the cerebellum, hippocampus and frontotemporal neocortex. These TDP-43 negative inclusions do however stain positive for ubiquitin (Mahoney et al., 2012; King et al., 2012; Snowden et al., 2011). While research is ongoing to identify a mechanism whereby the hexanucleotide expansion can lead to TDP-43 dysfunction, two important elements have already been identified. Mori and colleagues have identified a sequestration effect that is thought to be instigated by [GGGGCC] mRNA, showing that the repeat region is preferentially bound by a number of RNA-binding proteins. One of these proteins, hnRNP A3, was found to be present in the TDP-43 negative inclusion bodies that could be observed within the hippocampus of 10 (out of a total of 13) C9Orf72 expansion carrying patients (Mori K et al., 2013A). In addition to this sequestrational effect, the repeat region appears capable of initiating non-ATG dependent protein translation, whereby a hairpin is formed by the [GGGGCC] mRNA and initiates translation of a number of dipeptide repeats. Antibodies that are raised against these dipeptides (specifically glycine- alanine, glycine-proline and glycine-arganine) are capable of labelling aggregate bodies within C9Or72 affected individuals, implicating their involvement in neurodegeneration (Mori et al., 2013B, Ash et al., 2013). 1.7: Fused in Sarcoma and FTLD-UPS Around 20% of FTLD cases with ubiquitinated inclusions do not show TDP-43 immunoreactivity (Roeber et al., 2008), however; many of this sub-group do display aggregate immunoreactivity for Fused in Sarcoma (FUS) protein (Neumann et al., 2009). The presence of FUS has also been observed within aggregate bodies of familial of ALS (Vance et al., 2009). One striking feature of FUS is its resemblance to TDP-43, both in structure and it’s in DNA/RNA processing (Lagier-Tourenne and Cleveland 2009). FTLD cases which display FUS immunoreactive aggregates are classified as “FTLD-FUS” (Mackenzie et al., 2011). The final grouping of FTLD cases is reserved for those patients with a pathogenic mutation within the endosomal ESCRTIII-complex subunit: CHMP2B (Skibinski at al., 2005). As with VCP mutations, CHMP2B mutations are thought to inhibit cellular degradation pathways and lead to ubiquitinated aggregate bodies, classified as “FTLD-UPS” (Mackenzie et al., 2011).

P a g e | 19

1.8: The neurodegenerative disease spectrum The discovery of tau, TDP-43 and FUS proteinopathies has highlighted an interlinking web of different neurodegenerative diseases, each with overlapping histologies that manifest as a defined range of disease phenotypes.

As with FTLD; ALS describes a number of different neurodegenerative diseases, all result in muscle weakness and/or spastic paralysis via the degeneration of motor neurones (Brain and Walton 1969). The majority of ALS cases do not show any overt symptoms of dementia, however, around 30-50% are thought to exhibit some subclinical cognitive impairment (Phukan J et al., 2007). While relatively uncommon, the existence of a form of ALS which co-exhibits with FTLD has been known for some time (Neary et al., 1990). Despite this, a definitive link between the pathological mechanisms of ALS and FTLD could only be made following the discovery of TDP-43 aggregates within FTLD and ALS (Arai et al., 2006, Neumann et al., 2006) and later FUS (Neumann et al., 2009 and Vance et al., 2009).

The presence of ubiquitinated TDP-43 aggregates within both FTLD and ALS suggests that a common or overlapping mechanism may be responsible for both diseases; however, it is important to note that mutations responsible for the two diseases can be very different. Genome-wide association studies of ALS reveal no correlation to MAPT (Van Es et al., 2009); whereas a number of mutations which do lead to ALS, such as those within the TDP-43 gene TARBP (Van Deerlin et al., 2008) or SOD1 gene (Rosen et al., 1993) are not observed in FTLD. Although GRN mutations are reported in ~10% of total FTLD cases (Gass et al., 2006); GRN mutations were thought not to cause ALS (Schymick et al., 2007). A recent publication appears to overturn this view by confirming the presence of a GRNA9D mutation within an ALS patient (Cannon et al., 2013). Despite these genetic differences, other commonalities do suggest some shared mechanisms within the two diseases. The presence of FUS aggregates in both ALS (Vance et al., 2009 and Kwiatkowski et al., 2009) and FTLD (Neumann et al., 2009) suggests that some forms of FTLD and ALS are essentially one cohesive entity with mirroring FUS and TDP-43 pathology, which happens to present as a divergent series of clinical and neurological affects. Recent findings within C9Orf72 further substantiate this link. Patients with ALS caused by a C9Orf72 expansion are more likely than other ALS causative mutations to develop FTLD (Byrne et al., 2012; Snowden et al., 2013). Similarly, FTLD cases carrying a C9Orf72 expansion are more likely to co- exhibit ALS than any other FTLD causative mutation (Simon-Sanchez et al., 2012). P a g e | 20

This integrated hypothesis presses the need for both the FTLD and ALS fields to identify the elements that make frontal/temporal neurones vulnerable to neurodegeneration in FTLD, as opposed to motor neurone susceptibility in ALS.

1.9: Proposed mechanisms of TDP-43 aggregation TDP-43 was originally identified due to its ability to bind TAR DNA, a regulatory sequence which is essential for the activation of TAT protein (Ou et al., 1995). Further analysis placed TDP-43 within the hnRNP family of proteins (Krecic and Swanson 1999), containing a glycine- rich region at the C-terminal and two RNA recognition motifs. These RNA binding regions have the ability to bind the common microsatellite region: (GU/GT)n (Buratti and Baralle 2008)and the novel motif: (UG)nUA(UG)m, where an adenine residue is flanked by (UG) repeats (Sephton et al. , 2011 ). A wide array of functions have been attributed to TDP-43 within transcriptional and splicing control, most notably exon skipping control within exon 9 of cystic fibrosis transmembrane conductance regulator (Buratti et al., 2001) and exon 7 of survival of motor neurone protein (Bose et al., 2008). TDP-43 is also known to form complexes with the RNA binding proteins: methyl CpG-binding protein 2 and poly-pyrimidine tract-binding protein 2, both of which are largely up-regulated in neuronal cell types (Sephton et al. , 2011 ). Interestingly, TDP-43 also appears to bind to the 3’UTR of its own RNA transcript thereby increasing transcript stability and instigating an auto-regulatory loop (Ayala et al., 2011 and Polymenidou et al. 2011). In a potentially important link between progranulin and TDP-43, Polymenidou and colleagues have shown that TDP-43 alters GRN mRNA levels and plays a role in splicing regulation of the progranulin binding receptor, sortillin (Polymenidou et al,. 2011).

TDP-43 is essential to cell maintenance and when knocked-down leads to an increase in cyclin dependent kinase 6 (Cdk6) levels. This, in turn, leads to the concurrent phosphorylation of Cdk6 target proteins: retinoblastoma protein (pRb) and pRb2/p130. The effect of this is to decrease the amount of time spent in G0/G1 phase by around 60% and to reduce the stability of the nuclear membrane, thereby increasing apoptosis (Ayala (A) et al., 2008).

One feature common to all FTLD-TDP patients is the presence of a number of different protein species generated from TDP-43. These include a slightly larger 45kDa isoform, due to post transcriptional phosphorylation and ubiquitination (Neumann (B) et al., 2007, Inukai et al., 2008), and a number of C-terminal fragments observed at ~25kDa and 37kDa (Arai et al., 2006 and Neumann et al., 2006) (see figure 1.9.1). These alternative TDP-43 products can be observed in detergent insoluble urea fractions of affected brain regions, signifying highly insoluble, aggregated protein (Cairns et al., 2007). A study by Zhang and colleagues reported that a P a g e | 21 reduction in progranulin expression, achieved via GRN siRNA treatment, leads to cleavage of TDP-43 into two fragments of 37kDa and 25kDa (Zhang et al., 2007). Both caspase-3 and caspase-7 have been shown to be capable of generating these two TDP fragments in vitro, however, caspase-3 seems the more likely in vivo mediator as an increase in caspase-3 activation has been reported to coincide with reduced progranulin levels. This supports an earlier observation of elevated caspase-3 activation in neurones and astrocytes of FTLD patients, even within non-affected brain regions (Su et al., 2000).

The caspase-3 pathway presents a possible mechanism by which reduced progranulin expression could lead to the generation of 25kDa and 37kDa C-terminal fragments that are observed in FTLD-TDP (Arai et al., 2006 and Neumann et al., 2006), though some controversy exists as to the exact effect of reduced progranulin upon caspase-3. Dormann and colleagues have illustrated that, although C-terminal fragments of TDP-43 can be generated by caspase-3 activation with staurosporine, progranulin knock down does not activate caspase-3 or lead to an increase in TDP-43 processing (Dormann et al., 2009). Additionally, knock down of a GRN gene equivalent (granulin B) within zebrafish produces no noticeable change in processing TDP- 43 (Shankaran et al., 2008). This suggests that while caspase-3 may be involved in the generation of pathological TDP-43 fragments, the exact causative link between reduced progranulin and TDP-43 aggregation is still unknown.

Figure 1.9.1: Schematic showing TDP-43 fragments and isoforms. “NLS”: Nuclear localisation signal, “NES”: Nuclear export signal and “Gly.”: Glycine rich region.

Studies using recombinant TDP-43 composed of differing lengths of C or N terminal fragments have shown that certain truncated lengths of TDP-43 have a propensity for generating inclusion bodies. Cells transfected with GFP tagged constructs of C-terminal amino acids: “162-414”, “218-414” and an N-terminal fragment of “1-161” were able to drive the formation of GFP/TDP- 43 positive ubiquitinated protein aggregates. Interestingly, co-transfection using congo red tagged full length TDP-43 shows co-localisation of green (fragment) and red (proxy for endogenous TDP-43) within protein aggregates (Nonako et al., 2009). This suggests that once aggregation has been nucleated by pathogenic fragments, endogenous TDP-43 is then further recruited by the growing protein aggregate. All three constructs which have been shown to be P a g e | 22 able to drive TDP-43 aggregation contain the glycine rich region and both RRMs (although only part of RRM 1 is present in C-Terminal “218-414”), supporting a previous observation by Johnson et al., (Johnson et al., 2008) which showed that C-terminal fragments which contained RRM2 were capable of generating toxic, high order protein aggregates in yeast.

Proposing an alternate, translation driven mechanism for TDP-43 fragment generation, Nishimoto and colleagues, have shown that 37kDa and 25kDa TDP-43 fragments can also be generated by alternate start codons utilising methionine 85 and 162/167 (Nishimoto et al., 2009) (see figure 1.9.1) As with the TDP-43 caspase-3 cleavage products, TDP-43 alternative isoforms (TDP-25iso and TDP-37iso) display altered exon skipping properties and miss- localisation (Zhang et al., 2007 and Nishimoto et al., 2009). The predicted caspase-3 cleavage site that can generate the ~25kDa fragment of TDP-43 is predicted to be “DVMD” at amino acids 219-222 (Zhang et al., 2007), however, Nishimoto et al. hypothesise that this fragment is too small to be the observed endogenous pathogenic fragment and that caspase-3 down-stream effects may instead initiate transcription of TDP-25iso; rather than cleaved form.

TDP-43 is mostly localised to the nucleus, however, a small amount is maintained in the cytoplasm due to constant shuttling across the nuclear membrane (Ayala (B) et al., 2008), implying an active role in the cytoplasm in addition to its role within the nucleus. With the exception of Type D inclusions (which result from pathogenic VCP mutations); FTLD-TDP inclusion bodies are nearly all located in within the cytoplasm and coincide with the apparent depletion of nuclear TDP-43 (Cairns et al., 2007; Mackenzie et al., 2011) This suggests that TDP- 43 translocation to the cytoplasm is extremely important within FTLD-TDP pathology and that nuclear depletion of TDP-43 is a plausible neurodegenerative mechanism.

TDP-43 has two localisation signals: a two part, basic nuclear localisation signal (NLS) at amino acids 82-98 and a hydrophobic nuclear export signal (NES) at 239-250. Recombinant TDP-43 which contains point mutations within (either part of) the NES leads to cytoplasmic depletion of TDP-43 and generates intranuclear inclusion bodies similar to NIIs. Conversely, point mutations introduced into the NLS leads to redistribution of nuclear TDP-43 to the cytoplasm and the formation of cytoplasmic inclusion bodies (Winton et al., 2008). Disruption of localisation signals presents a likely explanation for the abnormal localisation of TDP-43 fragments.

1.10: Post-transcriptional modification of TDP-43 As with most proteins, post-transcriptional modification likely plays an important role in TDP- 43 processing, degradation and aggregation. Systematic phospho-specific antibody screens have identified 5 key serine residues within the C-terminal region, being serines: 379, 403/404, 409/410 as phosphorylation targets. In the same study, it was shown that caesin kinase 1 (CK1) P a g e | 23 treatment is able to drive phosphorylation of TDP-43 and is likely a key mediator of TDP-43 phosphorylation in vivo (Hasegawa et al., 2008). Of the 5 identified serine residues, S409/410 appears to be aberrantly phosphorylated in both ALS and FTLD aggregates, whereas antibodies raised against these epitopes will not stain non-pathological nuclear TDP-43 (Inukai et al., 2008). Analysis of larger patient cohorts has revealed that phosphorylation of S409/410 occurs in all TDP pathologies of ALS and FTLD (Neumann et al., 2009), and that TDP-43 phosphorylation of S403/404 and S409/410 also occurs in a large proportion of Alzheimer's disease and dementia with Lewy bodies (DLB), highlighting TDP-43 phosphorylation as a reoccurring feature of neurodegeneration (Aria et al., 2009).

Phosphorylation of TDP-43 could potentially result in a number of down-stream effects. One suggestive line of evidence shows that double labelling aggregates with the phospho-specific TDP-43 antibody: 1D3 and an anti-ubiquitin antibody reveals co-localisation at fully formed inclusion bodies. However, only 1D3 localises to “pre-inclusion bodies” suggesting that phosphorylation of TDP-43 occurs before ubiquitination and may play a role in driving aggregation (Neumann et al., 2009).

Due to the high degree of ubiquitination of TDP-43, it has long been hypothesised that insufficient protein clearing (via the UPS or Autophagy-lysosomal pathway: ALP) may be responsible for pathological aggregation of TDP-43 within all FTLD-TDP cases. Kim and colleagues (Kim et al., 2008) utilised a yeast two hybrid screen to identify ubiquilin-1 (UBQLN) as an interaction partner with TDP-43, with binding being mediated by the UBA domain of UBQLN. Further co-expression studies in HeLa cells revealed that UBQLN associates to ubiquitinated TDP-43 and that co-overexpression of TDP-43 and UBQLN greatly increases the generation of TDP-43 positive inclusion bodies compared to TDP-43 overexpressing cells alone. Finally, Kim et al. showed that UBQLN association to TDP-43 may be as part of ALP targeting, and that concanamycin A treatment (a vacuoloar-ATPase inhibitor which inhibits the ALP) results in co-aggregation of TDP-43 and UBQLN. Both autophagy and the UPS appear to be important in TDP-43 clearance, as pharmacological inhibition of either the ALP or UPS leads to an increase in TDP fragment generation (Wang et al., 2009).

While TDP-43 aggregation represents a toxic 'gain of function' scenario whereby the presence of inclusion bodies results in cell death; a TDP-43 'loss of function' scenario could also potentially be the major mechanism responsible for neurodegeneration. Supporting the 'loss of function' hypothesis is the observation that, although other hnRNP proteins remain within the nucleus in FTLD-TDP; cytoplasmic aggregation of TDP-43 leads to almost total depletion of nuclear TDP-43 (Neumann (B) et al., 2007). This nuclear depletion would then lead to a loss of critical transcriptional and RNA processing functions that TDP-43 mediates, leading to secondary P a g e | 24 pathology. This scenario is leant further credence by the observation of abnormal nuclear morphology and eventual cellular apoptosis upon TDP-43 knock down (Alaya et al., 2008). It is conceivable that both loss of function for TDP-43 and gain of function via aggregate toxicity occur simultaneously, however, it is unknown which (if either) of the two scenario's contributes most to neuronal degradation within FTLD.

1.11: TDP-43 proteinopathy based animal models A number of different strategies to model TDP-43 dysfunction have been attempted by a number of groups, with mixed success. Stemming from the TDP-43 “loss of function” hypothesis, TDP-43 knockout models present an obvious method to recapitulate FTLD-TDP. Confoundingly, TDP-43 knockout within mice is embryonic lethal (Sephton et al., 2010); whereas heterozygous knockout mice show no measurable reduction in TDP-43 protein expression, though do show some increased muscle weakness with age (Kraemer et al., 2010). Subsequent attempts to use conditional knockout of TDP-43 at 4-6 weeks of age also proved lethal, with animals succumbing to weight loss due to increased fat oxidation (Chang et al., 2010).

Other early attempts to model FTLD-TDP (outside of murine models) utilised transfection of zebrafish with mutant forms of TDP-43 RNA that are causative for ALS (G348C, A315T and A382T): all result in changes to motor neuron morphology and motor dysfunction. However, knockdown of TARDBP also appears to impair motor function, and effect which can be recovered by transfection with wild type; but not mutant: TARDBP RNA. As both knock down and mutant isoforms of TDP-43 have been shown to ablate motor function, both 'a gain of' and loss of' function scenario appears to be feasible within this zebrafish model (Kabashi et al., 2009).

To model a “gain of function” scenario, Wegorzewska and co-workers engineering a mouse line which expresses TDP-43A315T (a causative mutation for ALS) under control of the prion promoter. The resultant mice continue to express endogenous TDP-43 globally, in addition to TDP-43A315T within the brain and spinal-cord. Unlike wild-type TDP-43 over-expressing mice, TDP-43A315T transfected mice show severe motor dysfunction and display a progressive worsening gait culminating in the inability to walk after 4.5 months. Accumulation of ubiquitinated protein was observed throughout cortical layer 5, specifically the motor, orbital, sensory and cingulate cortex, however, no mature inclusion bodies were observed (Wegorzewska et al., 2009).

Expanding upon this work, Swarup and co-workers generated transgenic mice which expressed full length human, wild-type TDP-43 and (ALS causative) TDP-43G348C and TDP-43A315. All three transgenic mice strains displayed motor deficits as assessed by rotorod test and memory P a g e | 25 deficits as assessed by Barnes maze. Interestingly, TDP-43G348C and TDP-43A315 strains displayed evidence of TDP-43 fragment generation consistent with the ~25kda and ~37kDa cleavage products observed in FTLD-TDP, while co-staining for active caspase-3 and TDP-43 appeared colocalized to the same neurones within TDP-43G348C animals (Swarup et al., 2011).

1.12: Progranulin in wound response Over 60 different mutations within the GRN gene have been observed within FTLD (for full list see http://www.molgen.ua.ac.be/FTDMutations/ ) which all lead to haploinsufficiency and a reduction in secreted progranulin (Gass et al., 2006). While caspase-3 mediated effects upon TDP-43 may be controlled by progranulin levels, other factors are likely involved and investigating progranulin's role within neurological systems is a high priority of the FTLD field.

Progranulin is a secreted protein of 593 amino acids, which, due to heavy glycosylation, corresponds to around 90kDa when run on an SDS gel (Zhou et al., 1993); while the murine form is observed at around 80kDa (Petkau et al., 2009). When secreted, progranulin is capable of forming a homodimer which can be observed physiologically within human and mouse blood plasma (Nguyen et al., 2013).

Intact progranulin is comprised of 7.5 repeating globular domains, with each domain containing a cross-linked moeity of 12 cysteines known as a granulin motif (Bhandari et al., 1992). Each granulin motif forms an individual compact globular structure, with the structure of intact progranulin being analogous to “threaded beads on a string” (Hrabal 1996). Processing of progranulin is mediated by proteolytic cleavage by the serine proteases: neutrophil elastase, chymotrypsin (Zhu et al., 2002) and proteinase-3 (Kessenbrock et al., 2008); and the macrophage secreted metalloproteinase: MMP-12 (Suh et al., 2012). Cleavage liberates a number of granulin products, named granulins: A-G and paragranulin (Bhandari et al., 1992) and results in a net increase in proinflammatory signalling. Preliminary work has suggested that each of these granulins may have a distinct signalling function, (Zhu et al., 2002) making it conceivable that they act in concert to produce various aspects of a pro-inflammatory response.

Both intact progranulin and the resultant granulin cleavage products have profound but contrasting effects upon cell regulation, leading to the view of progranulin as a 'non- conventional growth factor' (He and Bateman 2003). Progranulin has been shown to stimulate growth of cultured mouse embryonic fibroblasts (MEFs) in a non-IGF-1 dependent manor (insulin-like growth factor) (Sell et al., 1994). Supportingly, GRN mRNA levels are found to be highest in proliferative cell types such as skin keratinocytes or intestinal deep crypts (Daniel et al., 2000). Cutaneous wounds treated with recombinant progranulin display an increase in neovascularization and heightened accumulation of neutrophils and macrophages. Additionally, P a g e | 26

GRN mRNA's are reported to be up-regulated in keratinocytes, dermal fibroblast and endothelial cells following wounding (He et al., 2003).

To date, two putative Progranulin binding receptors have been identified: sortilin (Hu et al., 2010) and tumour necrosis factor receptor 2 (TNFR2) (Tang et al., 2011). Sortilin appears critical in the regulation of extracellular progranulin expression by mediating progranulin endocytosis and its delivery to the lysosome (Hu et al., 2010). Recent insights into sortilin splicing have revealed potentially important findings that may underpin FTLD-TDP, in that the sortilin splice variant Ex17b is preferentially included into the mRNA transcript in the absence of TDP-43. This splice variant truncates the sortilin receptor, maintaining its ability to bind progranulin however inhibiting its ability to internalise progranulin (Gass et al., 2012). This highlights a mechanism whereby functional TDP-43 depletion (via a mechanism of aggregate sequestration) could further add to extracellular progranulin miss-regulation.

The TNF receptor is integral to inflammatory signalling and activation of the TNF pathway by TNF-alpha stimulation is thought to lie at the top of the inflammatory cascade (Aggawarwal et al., 2003). Tang and colleagues have shown that progranulin binds to TNFR2 both within a yeast two-hybrid assay and by co-immunoprecipitation. They also show that progranulin is capable of inhibiting TNF-alpha activation of T-regulatory cells, implying that progranulin acts as an antagonist for the TNFR2 receptor: occupying the TNF-alpha binding site without activating the TNF signalling cascade.

Secretory leukocyte protease inhibitor (SLPI) has been shown to bind progranulin in a yeast two hybrid system, most likely via association to negatively charged inter-granulin linker regions (Zhu et al., 2002). Additionally, SLPI can bind a number of proteinases which degrade progranulin, most notably neutrophil elastase (Zhu et al., 2002), chymotrypsin (Smith et al., 1985), MMP-12 (Suh et al., 2012); however it does not inhibit proteinase-3 mediated progranulin cleavage (Wiedow et al., 1993). SLPI's ability to form a complex with progranulin and neutrophil elastase inhibits the conversion of progranulin to granulin(s) (Zhu et al., 2002), making SLPI concentration a key modulator of the cellular ratio of progranulin to granulin(s). This effect is thought to be an important switch within wound healing. Immediately following wounding, cleavage of progranulin by elastase and other proteinases instigates a proinflammatory signal as a defence against possible infection. Once the inflammatory response has run its course and wound closure is required, cell proliferation signals such as those provided by intact progranulin are again required. This makes anti-protease activity (such as SLPI’s) a crucial component of the switch back to anti-inflammatory healing (Zhu et al., 2002 and Kessenbrock et al., 2008). P a g e | 27

Proteolysis of progranulin and the release of granulins has been shown to stimulate the production of interleukin-8 (IL-8), specifically, granulin B has been shown to be a potent stimulator of IL-8 production while also inhibiting epithelial cell proliferation (Zhu et al., 2002). IL-8 is a major leukocyte chemoattractant, mediating a pro-inflammatory response that results in increased invasion of neutrophils and T-lymphocytes to the wound site (Wilmer and Luster 1994). Intact progranulin, however, has the opposite effect as it inhibits pro-inflammatory TNF signalling by preventing phosphorylation of the tyrosine kinase: Pyk2 (Zhang et al., 2002), potentially via its TNFR2 antagonistic action (Tang et al., 2011). When the TNF signalling pathway is stimulated, activated PI3K leads to the downstream phosphorylation of Pyk2 (Fuortes et al., 1999). The result of (non-inhibited and activated) TNF signalling is the activation of neutrophils which mount an antimicrobial response by the generation of a reactive oxygen species (respiratory burst) (Dahlgren and Karlsson 1999) and the inflammatory response is initiated. Conversely; inhibition of progranulin cleavage by anti-proteinases such as SLPI, restore intact progranulin signalling: attenuating the TNF pathway while reducing pro- inflammatory granulin signalling (Zhu et al,. 2002).

Figure 1.12.1: Proposed inflammatory signalling from progranulin and SLPI. Progranulin enacts an anti-inflammatory effect when intact (left side of diagram), antagonising the TNF pathway. When cleaved (in the absence of SLPI) TNF pathway inhibition is lifted in addition to pro-inflammatory signalling from granulin proteins.

Using hippocampal brain sections from GRN null mice, Gass and co-workers have shown that progranulin appears to be an important regulator of neurite growth. GRN null primary neurones show significantly reduced branching and neurite outgrowth (compared to wild-type controls); a phenotype that can be recovered upon the expression of progranulin (using viral expression). This demonstration of progranulin cleavage within the hippocampal cultures led Gass and colleagues to suggests that it is the granulin cleavage products and not full length progranulin that mediates this neurite outgrowth. Treatment with recombinant SLPI reduced neurite P a g e | 28 branching and outgrowth to GRN null levels (via its protective effect over progranulin cleavage), whereas; treatment with granulin C and E stimulated neurite outgrowth (Gass et al., 2012). This illustrates that while SLPI may prevent inflammatory signalling, it may also attenuate neuronal branching and neurite outgrowth via a reduction in granulin(s) levels.

The duality of progranulin's role within cell maintenance and inflammatory response allows for the extrapolation of two different (possibly convergent) mechanisms by which altered progranulin levels could lead to neurodegeneration. Within a neuroinflammatory lead scenario: reduced progranulin levels could perturb inflammatory signalling (such as the TNF pathway) which could in turn, lead to intracellular signalling events that result in TDP-43 aggregation (either by reduced TDP-43 clearing or by nucleating its aggregation). In a growth factor lead scenario the loss of progranulin (or granulins) contributions to cell survival would lead to increased cellular apoptosis within affected neurones. Apoptotic signalling or the attenuation of essential cell maintaining signalling could then lead to TDP-43 aggregation.

1.13: Granulin null mice Studies on conditional GRN null mice by Yin and co-workers (Yin (A) et al., 2010) revealed that mice lacking progranulin exhibit a more pro-inflammatory base rate than wild-type animals: producing less IL-10 and more inflammatory cytokines. These GRN null mice also display an increase in neuronal vulnerability, hippocampal neurones appearing to be more susceptible to oxygen and glucose deprivation. When aged to 18 months, these mice displayed widespread microglial and astrocytic activation in addition to moderate accumulation of phosphorylated TDP-43 within the hippocampus, thalamus and cortex. This pathology differs slightly from observations by Ahmed and co-workers, who also found substantial microglial activation (as assessed by Iba1 staining) and a significant increase in ubiquitination within GRN null mice, however; they observed no strong evidence of TDP-43 dysfunction associated to the GRN null phenotype (Ahmed et al., 2010). In a later paper, Yin and co-workers (Yin (B) et al., 2010) employed behavioural tests to show increased depressive behaviour of GRN null mice in tail suspension and forced swimming tests, in addition to increased disinhibition as measured by elevated plus maze. Mirroring FTLD, GRN null mice also showed social deficits as compared to wild-type mice when assessed by a stranger recognition test. In the oldest cohort of mice, aged to 18 months, impaired cognitive ability also became apparent within water maze tests. (A more detailed account of the Murine GRN null behavioural phenotype is given in section 3.1)

P a g e | 29

1.14: The Secretory leukocyte protease inhibitor (SLPI) SLPI is a 11.7kDa cationic secreted protein, comprised of 107 amino acids (Thompson and Ohlsson 1986). The SLPI gene comprises 4 exons and 3 introns and is one of a number of “whey acidic protein (WAP) with four-disulphide core” peptides that are encoded within loci q12 of chromosome 12 (Clauss et al., 2002 and Stetler et al., 1986). The translated SLPI protein assembles into two “WAP/four-disulphide core” motifs forming two compact globular domains that are located at either side of a linker region (Grutter et al., 1986).

SLPI has been shown to inhibit a range of serine proteases including: trypsin, chymotrypsin, tryptase, chymase, neutrophil elastase and cathepsin G (Doumas et al., 2005); and the metalloproteinase MMP-12 (Suh et al., 2012). Systematic residue alterations have revealed that SLPI's inhibition of serine proteases is mediated by leucine-72, located within a putative inhibitory loop region that extends out of domain 2 (Eisenberg et al., 1990). While the C- terminal mediates direct protease inhibition, it has been suggested that the N-terminal domain stabilises any resultant complex formed from a SLPI/neutrophil elastase interaction (Faller et al., 1992).

Structural modelling of the resultant complex formed from SLPI binding to neutrophil elastase theorises an overall increase in positive charge (exposed to the aqueous environment) than either of the two components in isolation (Sullivan et al., 2008). This increase in polarity is believed to result in SLPI/neutrophil elastase complex associating to cellular membranes, sequestering both SLPI and neutrophil elastase.

SLPI is expressed in a range of different tissues, particularly endothelial cells within the lung (Van Seuningen et al., 1995) and is found within various mucosal fluids, such as saliva (Thompson and Ohlsson, 1986), cervical mucus (Denison et al., 1999) and seminal plasma (Ohlsson et al., 1995). Owing to its role within inflammation SLPI, is also highly expressed within neutrophils and macrophages (Doumas et al., 2005).

Prior to cellular processing and secretion as a 11.7kDa protein, cytosolic SLPI consists of a 14kDa precursor protein (Sallenave et al., 1997). This 14 kDa species has been observed to associate to the megakaryocytes and platelet specific microtubule protein: beta-1 tubulin, causing SLPI to localize along microtubules (Schulze et al., 2004). While this situation is specific to beta-1 tubulin containing cells, the intracellular 14kDa species of SLPI may serve additional functions within other cell types relevant to progranulin processing. The SLPI signal sequence is cleaved during cellular processing prior to secretion, likely by a signal peptidase, between glycine-25 and serine-26 (Jacobsen et al., 2008). P a g e | 30

Aside from its role within inflammation, SLPI also displays potent antimicrobial and antiviral properties, to the extent that its high concentration within human saliva is theorised to be the major contributing factor behind the inability of HIV to be transmitted orally (Wahl et al., 1997). This antiviral ability is thought to be mediated by SLPI's disruption of the association between CD4 and scramblase1/4, a key process within phospholipid movement and viral cellular entry (Py et al., 2009). SLPI also increases the levels of glutathione within lung epithelium, in a process that helps mitigate the effects of reactive oxygen species generated in respiratory burst (Gillissen et al., 1993).

In addition to progranulin mediated inflammatory response, SLPI also opposes inflammation via inhibition of nuclear factor kappa B (NF-kB) transcription (Lentsch et al., 1999). Monocytic cell culture treated with lipopolysaccharide (LPS), a potent activator of the NF-kB and TNFα inflammatory pathways, are attenuated by exogenous SLPI treatment. This effect is thought to be caused by cytosolic SLPI signalling which inhibits UPS mediated degradation of IκBβ. The retention of cytosolic IκBβ, maintains the NF-kB complex within the cytoplasm, preventing nuclear translocation and so precluding the transcription of pro-inflammatory genes (Taggart et al., 2002). This attenuation of LPS activation is furthered by findings of Vroling and co-workers, who found that SLPI is capable of reducing LPS activation of bone marrow derived macrophages via inhibition of LPS to CD14 pathway (Vroling et al., 2012).

Work by Zhang and co-workers (Zhang et al., 2002) has further elucidated SLPI's non-protease mediated functions with the discovery that SLPI up regulates Cyclin-D1 transcription, implying an overall affect of cell proliferation which complements its progranulin protective role.

No mutations within the SLPI gene have been reported for either FTLD or affiliated diseases, however, its role in progranulin processing, inflammatory response and interaction with the UPS make SLPI an extremely interesting candidate for study within the context of FTLD.

1.15: SLPI null mice as a potential FTLD model Serial knock out studies on yeast suggest that only around one half of the genes within a genome have any discernible effect upon phenotype once knocked out (Smith et al., 1996), owing to the stability and redundancy inherent within biological systems. Despite this, SLPI knockout mice show heavily inhibited wound healing in addition to increased levels of leukocyte and neutrophil invasion when compared to control animals (Ashcroft et al., 2000). Deficient wound healing in these mice was found to be elevated by administration of neutralising antibodies raised against TGF-beta, prior to cutaneous wounding. Later work by Zhu et al. (Zhu et al., 2002) has shown that exogenous treatment with progranulin can restore deficient wound healing P a g e | 31 within SLPI null mice, implying that excessive progranulin processing, rather than NF-kB signalling, was responsible for the observed phenotype.

SLPI knockout mice display excessive Neutrophil elastase activation, which in turn, alters the ratio of progranulin to granulins (anti-inflammatory vs. proinflammatory signalling) (Zhu et al., 2002). This leads to an increase in chemoattractant signalling, increasing leukocyte and macrophage invasion in addition to activating neutrophils (Ashcroft et al., 2000). This makes SLPI null mice an interesting candidate for an FTLD model not only because of their propensity towards increased inflammatory signalling but also as a plausible method for reducing extracellular, signalling progranulin.

If neurodegenerative markers or phenotypes were observed within these SLPI null mice that was comparable to those seen in GRN null mice, it would lend credence to progranulin having an extracellular signalling role within neurodegeneration. Conversely, if the neurodegenerative markers that have been observed in GRN null mice are not present within SLPI knockout mice, or different pathology is observed, then the importance of intracellular progranulin concentration would be highlighted.

1.16: Conclusions SLPI’s participates in 3 different areas in which it may contribute towards neurodegeneration within the FTLD/ALS spectrum, making it a strong candidate for further study. Gliosis (the activation of glial cells) has long been known to occur within a number of neurodegenerative diseases including FTLD (Frank-cannon et al., 2009). This neuroinflammatory aspect of FTLD may represent a key mediator of neuronal cell death, a view which is supported by recent evidence from GRN null mice (yin et al., 2010 & Ahmed et al., 2010). SLPI’s contribution to inflammation via non-protease inhibitory mechanisms (progranulin independent), such as LPS inhibition or NF-kB modulation (Vroling et al., 2012 & Taggart et al., 2002) may further contribute to this neuroinflammatory scenario, which could then lead to subsequent neuronal cell death. This is supported by the observation that SLPI is up regulated following ischemic stroke (Wang et al., 2003), implying a potentially protective neurological role. SLPI’s modulation of progranulin represents a second mechanism that may be important within the modelling and understanding of FTLD pathology. SLPI knockout mice show deficits within wound healing that are concurrent with reduced progranulin levels in vivo (Zhu et al,. 2002) and represent a feasible method for trying to recapitulate FTLD mutations caused by progranulin haplo-insufficiency. This methodology would also provide a basis for looking at system wide P a g e | 32 effects (such as activated immunoresponse or apoptosis) that globally reduced progranulin levels might have upon TDP-43 (and other FTLD related proteins). Finally, recent findings by Gass and co-workers have identified a third scenario, as SLPI’s protective effect over progranulin appears to have significant effects on neuronal outgrowth/branching via the regulation of granulin production from intact progranulin (Gass et al., 2012). This would imply that SLPI null mice may make an interesting model to study the behavioural phenotype resulting from altered granulin levels, potentially leading to reduced neuronal growth.

1.17 Project aims. Existing work with SLPI null mice has provided evidence of a wound healing deficit that can be restored by exogenous progranulin treatment, implying a mechanism whereby the absence of SLPI leads to excessive progranulin cleavage. If SLPI null mice display excessive progranulin cleavage, they may offer a system in which granulin action can be studied with implications that may be relevant to the FTLD field. To test this hypothesis, measurements of progranulin concentration were taken in a range of tissues and compared to wild-type controls. Behavioural analysis of SLPI null mice was performed to look for neurological evidence of a reduced progranulin phenotype and investigate the wider implications for SLPI within the brain. Finally, SLPI’s progranulin regulatory role was examined in both cultured cell lines and primary mammalian cultures. Preliminary work included cell culture based analysis of SLPI and the evaluation of appropriate antibodies for SLPI detection. This permitted subsequent work, which aimed to map SLPI’s interaction partners, specifically, inhibition of neutrophil elastase cleavage of progranulin. Similarly, different progranulin antibodies were tested in western blotting native and deglycosylated murine progranulin, so that specificity to different glycoforms could be assessed. Once a suitable antibody was found, various tissues taken from age matched Wild-type and SLPI null mice were homogenised and the progranulin content compared. If SLPI exerts a profound progranulin regulatory role, it should be expected that progranulin concentration would be diminished in SLPI null animals. For murine behavioural, tissue and pathological examination to take place, a genotyping strategy had to be developed and then aged match litters of wild-type and SLPI null mice bred. Once these cohorts were established and aged to reasonable time points (6, 12 and 20 months of age), a battery of behavioural tests were performed to assess any neurological affect that might be FTLD relevant. Following behavioural examination, mice were euthanized and histologically examined to identify any neurodegenerative markers that might indicate an FTLD like phenotype. P a g e | 33

SLPI’s protective effect over elastase mediate cleavage of progranulin was also assessed in immortalised cell lines, using a combined approach of siRNA knockdown, over-expression and treatment with recombinant proteins. If existing concepts around SLPI/progranulin regulation are correct, cell lines with (siRNA) knocked down SLPI should elicit reduced progranulin and progranulin which is more susceptible to recombinant neutrophil elastase activity.

P a g e | 34

Chapter 2: Materials and methods

P a g e | 35

2.1: Establishing a SLPI null colony

Background strain: For this study, a background strain of C57Bl/6J (Harlan Laboratories, Bicester, UK)was used. This strain is a widely used and has been used extensively in both behavioural evaluation and in biochemical analysis of their tissue. Known health problems for C57BL/6J include low bone density, age related hearing loss, a susceptibility to obesity, type-2 diabetes and atherosclerosis. For a full characterisation of this strain, see http://jaxmice.jax.org/strain/000664.html.

Breeding strategy: SLPI null animals were obtained from stocks originally established by Ashcroft and colleagues (Ashcroft et al., 2000). SLPI null animals were bred with C57BL/6J stock and the resulting F1 generation back crossed with the parental stock. Backcrossed progeny were then genotyped and the heterozygous animals used as breeding stock. Heterozygous breeding stock were maintained as “Trio’s” of 1 male and 2 female animals, the resulting progeny were then genotyped and the homozygous Wild-type or SLPI null animals housed for study.

Mice were weaned and ear punched at 6-8 weeks and housed in groups of 4-6, sex separated but mixed genotypes. Diet consisted of standardised chow and cages were kept in a standard 12 hour light/dark cycle. Mice were given free access to food and water; except prior to the olfactory discrimination task where food was withheld for 12 hours.

2.2: Genotyping of mice

DNA extraction: Ear-snips were taken after weaning and used to assign a number to each mouse. Ear snips were digested using 100µg/ml proteinase K (Roche, West sussex, UK) in 250µl digestion buffer for 2 hours at 55°C with frequent vortexing. The digestion mixture was then centrifuged for 30 minutes, 14,000 RPM at 4°C: the supernatant taken and added to 500 µl isopropanol and precipitated overnight at -20°C. The following day the isopropanol/digestion mixture was centrifuged for 30 minutes, 14,000 RPM at 4°C and the supernatant discarded. The DNA pellet was then washed twice using 70% ethanol, centrifuging for 10 minutes, 14,000 RPM at 4°C per wash. The final pellet was then air dried at room temperature for 3 hours before being resuspended in 40 µl of T.E buffer and concentration assessed using a nano-drop.

P a g e | 36

Genotyping Primers: For amplification of the SLPI wild-type allele, primers were deigned to amplify flanking regions of the SLPI gene, resulting in a 340bp amplification product. Knockout (SLPI null) mice were generated via the introduction of a neomycin cassette into the start of the SLPI gene preventing translation. For amplification of a SLPI null allele, a primer was designed to bind to the neomycin sequence, which was used in conjunction with the SLPI reverse primer to generate a 420bp amplification product.

SLPI Forward Primer: 5’-CTCTGATGGCCTCATGGTCCTGCC-3’ Neomycin Cassette Forward Primer: 5’-CATCGCCTTCTATCGCCTTCTTGACG-3’ SLPI Reverse Primer (Common): 5’-CAGCCCAAACCATCAGGAGCCCCC-3’

Genotyping reagents and conditions: DNA samples were diluted to 15ng/µl using nuclease free sterile water. 2µl of each DNA sample was added per well, before adding 23µl of a master mix of PCR reagents, which comprised of:

 2.5µl of 10x PCR buffer (Qiagen Ltd. Manchester, UK)  1ul of 1 pM Primer 1 (Invitrogen, Paisley, UK)  1ul of 1 pM Primer 2 (Invitrogen, Paisley, UK)  Specified amount of MgCl2+(Qiagen Ltd. Manchester, UK)  1.75µl of 10mM of dNTP’s (Qiagen Ltd. Manchester, UK)  0.1µl of HotStarttm Taq (Qiagen Ltd. Manchester, UK)  Made up to 23µµl using sterile, nuclease free water.

Cycle conditions:

Genotyping optimisation and validation: Though the wild-type allele PCR consistently amplified a 340bp fragment, the SLPI null PCR did not produce the required band. To optimise the reaction, a titration of magnesium chloride from 0.5 to 4mM was performed at a range of temperatures. Figure 2.1.1 shows the most successful P a g e | 37 amplification conditions with negative controls, lacking template DNA, at maximal magnesium chloride conditions.

Figure 2.1.1: Magnesium chloride and temperature optimisation of SLPI-Null PCR primers.

To allow the same annealing temperature to be used for both genotyping PCR’s, 2mM of magnesium chloride was added to the SLPI null PCR master mix. Figure 2.1.2 shows the validation of the genotyping protocol via the successful identification of 4 wild-type and 4 SLPI null DNA samples. All genotyping necessary for the study was performed in triplicate.

Figure 2.1.2: Genotyping validation using ear snip DNA, C57Bl/6 or homozygous SLPI Null. 2.3: Handling of animals and general testing principles All experiments performed were carried out under United Kingdom Home Office personal and project licences, using protocols which adhered to the UK Animals in Scientific Procedures Act 1986. To minimise anxiety caused by handling, animals were handled for a total of 5 minutes per mouse, each day for 7 days prior to commencement of behavioural testing. Mice were moved into the behavioural testing suite and allowed to acclimatise for 1 hour prior to commencement of any testing. Male and female mice were tested on separate days to prevent scent interference of behaviour, with female mice generally being tested first. P a g e | 38

Lighting was maintained at 150 Lux, all behavioural tests were performed in the second 6 hours of the light cycle and a screen was used to hide the experimenter view of the test mouse. For each behavioural test, arenas and equipment were thoroughly cleaned with 70% ethanol between each test animal to ensure no scents were carried over from different animals. Where randomisation was required for testing purposes, arbitrary numbers were assigned to test arena corners or arms and a random number generator utilized. Where visual assessment of test footage was required, arbitrary and randomised numbering was arranged ahead of time so that genotypes were unknown while scoring.

Behavioural evaluation: Open-field arena Mice were placed facing towards the wall of a square arena (28cm x 28cm x 20cm), corner placement being randomised between trials (see figure 3.1.2). Each trial was given 5 minutes, movement being assessed via video tracking which sub-divided the arena into 16, 7cm x 7cm squares. For time spent in the central area, times were aggregated together from the central 4 squares. Total distance moved was measured over all 16 squares.

Behavioural evaluation: Y-maze spontaneous alternation To ensure adequate visuospatial reference points, cues (geometric shapes) were placed at each arm terminus and on each wall of the testing suite. The test was initiated upon placing the test mouse into a randomised arm of the y-maze, facing towards the wall. A 5 minute trial period was given and movement recorded by a video camera positioned above the maze. Arm entries were assessed by the experimenter, each arm being designated A, B or C (see figure 3.1.3); successful entries requiring the entire body of the mice being inside the specified arm (Mandillo et al,. 2008). On average, a cognitively normal mouse will tend to complete more successful “periods”, sequential visits of each arm (A to B to C or B to A to C etc.) over the total time course. A mouse with a deficit in spatial working memory will tend to re-visit the arm it has just left more often, performing fewer “periods” and scoring closer to the periodicity score that randomised progression would result in.

Behavioural evaluation: Social interaction and social preference The sociability apparatus was provided by Ugo Basil (Milan, Italy) and is comprised of 3 transparent, 20 x 40 x 22 cm chambers that are connected by closable doors (see figure 3.1.5). Within the two outermost chambers, smaller interaction cages (7cm diameter, 15cm high) were placed into a corner in the configuration shown. The test mouse was first placed into the central chamber and allowed to feely explore all 3 chambers for a 10 minute acclimatisation period, during which time the interaction cages were left empty. The test mouse was then coaxed into P a g e | 39 the central chamber and the access doors closed. A stranger mouse (sex and age matched to the test mouse) was then placed into a randomised interaction cage, the access doors then opened and the test mouse allowed free access to all 3 chambers for a further 10 minutes. The test mouse was then again coaxed into the central area, a new stranger mouse placed into the empty cage then the access doors again opened for a further 10 minute test period. To assess interaction time, a camera was suspended over the interaction apparatus and test sessions recorded. Interaction time was assessed visually by the experimenter as being the total time the test mouse was facing towards and in closer proximity to an interaction cage (within several centimetres). Stranger and familiar mice were comprised of either heterozygous stock animals or animals which had already completed the sociability test; no animal was used more than once per day in any aspect of the sociability test.

Behavioural evaluation: Olfactory discrimination Mice were denied access to food for 12 hours prior to testing before being placed into “olfactory isolation” for a total of 50 minutes: cages without bedding and lacking any odour. Mice were transferred between 4 scentless cages, remaining in each for 12.5 minutes before being transferred to the olfaction arena. The 3 chamber sociability apparatus was used for this purpose, one exterior interaction chamber being used for olfactory testing with the access doors closed and a screen placed into the central chamber. A 70mm diameter piece of filter paper was dabbed with either distilled water or sesame seed essence and placed into a corner of the arena for 3 minutes each. Water dabbed filter paper was placed down for the first 3 minutes, followed by sesame dabbed filter paper. A video camera was angled over the filter paper and time spent sniffing defined as time where the distance between the mouth and paper was less that ~3mm.

Behavioural evaluation: Tail suspension Mice were suspended by their tails for a 6 minute trial period, 30 cm from the table top. Mice were secured by their tails to the horizontal arm of a G-clamp stand (Fisher scientific Ltd. Loughborough, UK) using masking tape, to hinder mice climbing their tails; adhesive tape was used backwards so that a flexible joint was made between the tail and the suspension hook. A video camera was used to assess the total amount of time the mouse spends immobile, defined as the total amount of time that the mouse spends without actively moving any part of its body, ignoring any slight residual swinging motion that might persist from previous activity. Mice that climbed their tails for more than 25 seconds were excluded from the analysis.

P a g e | 40

Behavioural evaluation: Fear conditioning Mice were placed into a freeze response chamber (depicted in figure 3.1.6), provided by San Diego instruments (San Diego, US). This apparatus employs an array of infrared beams positioned around the test chamber periphery to detect movement of the mouse. The desired program was entered into San Diego instruments freeze response program, a schematic of the test scheme is shown in figure 2.3.1. Movement was assessed as latency until a light beam was broken within a 30 second time bin. Day 1, Entrainment, was comprised of five, 30 second time bins for acclimatisation. This was then followed by 3 training events comprised of two, 30 second time bins with the light activated (the conditioned stimulus) with a small 0.5mA shock being administered in the second time bin. The following day, recall of the testing arena (environmental recall) was assessed over 16, 30 second time bins. On the third day, recall of the conditioned stimulus was assessed with the arena being disguised to eliminate any environmental recall element. An initial 5 time bins of baseline latency was followed 12 time bins with the light activated (the conditioned response).

Figure 2.3.1: Fear conditioning programme used to illicit a Pavlovian response. Day one showing the entrainment regiment; day two in which the animals recall of the test arena is assessed and day three where the conditioned response is assessed.

2.4: Processing of tissue for biochemical analysis Euthanasia and cardiac perfusion of mice:

Mice were anaesthetised with isoflurane (3%: Baxter, Newbury, UK) in O2 (200ml/min) and N2O (200ml/min), anaesthesia being assured by foot pinch response. Transcardiac perfusion P a g e | 41 with saline was performed to remove blood from tissue samples prior to processing. The chest cavity was surgically opened to allow access to the heart. Up to 600μl blood was sampled via cardiac puncture of the right ventricle using a needle and syringe pre-coated with 3.2% sodium citrate(Sigma Aldrich, Dorset, UK) to prevent coagulation. A 21G butterfly needle was inserted then secured in the left ventricle. The right atrium was punctured to create an outflow from the circulation. Animals were perfused transcardially with 30ml ice-cold 0.9% saline over 3 min. The required organs were then taken and snap-frozen in dry ice. Whole cardiac blood samples were centrifuged soon after removal for 15 minutes, 10,000 RPM at 4°C before and the resultant plasma fraction was aliquoted and snap frozen in dry ice and stored at -80°C until subsequent analysis. Brains were divided hemi-spherically, one half being snap frozen, the other being post- fixed for 2 days at 4°C in 3ml of 4% PFA (Sigma Aldrich, Dorset, UK).

Tissue homogenisation: A small 100mg section of either lung or frontal brain tissue was excised using a razor and added to 1ml of RIPA buffer containing total inhibitors (Roche, West Sussex, UK) and PMSF (Sigma Aldrich, Dorset, UK). Tissue was then homogenised using a VDI12 hand-held tissue homogeniser (VWR international, Leicestershire, UK), before being snap frozen on dry ice and centrifuged from frozen (free-thawing sample) at 14,000 RPM, 4°C for 30 minutes. The pellet was then resuspended using a handheld, 100 watt Sonicator (Misonix, New York, US) and the sample again snap frozen on dry ice. The sample was then centrifuged for 14,000 RPM, 4°C for 30 minutes and the supernatant removed and aliquoted for protein quantification, normalisation and western blotting.

Protein normalisation: One aliquot of frozen tissue homogenate was thawed and diluted 8, 16 or 32 fold in RIPA buffer then 5µl of each dilution loaded in triplicate into a 96 well plate (Millipore, Feltham, UK). Albumin standards provided with the BCA kit (Thermo scientific, Hemel Hempstead, UK) were diluted to: 125ng/ml, 250ng/ml, 500ng/ml 1000ng/ml, 1500ng/ml and 2000ng/ml in RIPA buffer; in addition to a negative control (RIPA buffer only), 5µl of each standard was then loaded onto the 96 well plate in triplicate. 5µl of compatibility reagent was then added to each sample/standard before the plate was incubated for 15 minutes at 37°C. After making up the BCA colour reagent, 190 µl was added to each well using a multichannel pipette and the plate incubated for a further 30 minutes at 37°C. The plate was then read using a spectrophotometric plate reader for absorbance at 562nm. A standard curve was created from averaged albumin standard values using a linear equation; the corresponding equation was then used to determine protein content of each sample. The P a g e | 42 three dilution factors of each sample were corrected to their non-diluted values then averaged together; except where individual values exceeded the linear 125-2000ng/ml range. All samples were normalised to 3000ng/ml in RIPA buffer containing total inhibitors and PMSF(Sigma Aldrich, Dorset, UK), an aliquot again taken and diluted to 2 and 4 fold concentrations. The BCA process was then repeated on the preliminarily normalised/diluted aliquots, protein content determined and the preliminarily normalised stock being further normalised to 2000ng/ml and a number of 200 µl aliquots snap-frozen in dry ice and stored at -80°C until use.

Western blotting: SDS-PAGE gels were poured using a Bio-Rad gel pouring system (Bio-Rad Ltc. Hertfordshire, UK), using either a 17% or 10% polyacrylamide resolving gel and a 4% polyacrylamide stacking gel. Gels were loaded into a Bio-Rad 1 dimensional electrophoresis tank and covered with Tris- Glycine SDS-buffer running buffer. Tissue aliquots were thawed, 5xSDS buffer added and samples heated to 70°C for 10 minutes. Samples were briefly centrifuged before 40 µl was added to the required well, left-most lane being loaded with 10 µl of kaleidoscope coloured standard (Bio-Rad Ltc. Hertfordshire, UK). Gels were run at 120 volts for 90 minutes. Where conditioned media was used, a large SDS-PAGE system (Bio-Rad Ltc. Hertfordshire, UK) was used to avoid the need for concentration of samples, 180µl of media was loaded per well and run at 200 volts for 200 minutes. Progranulin blots from tissue samples were transferred using a wet transfer system (Bio-Rad Ltc. Hertfordshire, UK) with gels being placed on top of a nitrocellulose membrane (Amersham, GE Ltd., Buckinghamshire, UK), inside a sandwich made of 2 pieces of blotting paper and 2 pieces of sponge. The transfer tank was filled with transfer buffer and transferred with 90 volts for 70 minutes. All other gels were transferred using a semi-dry system(Bio-Rad Ltc. Hertfordshire, UK), gels were laid on top of nitrocellulose membranes (Amersham, GE Ltd., Buckinghamshire, UK), and encased in a sandwich of 4 pieces of blotting paper, soaked in transfer buffer and transferred for 90 minutes at 15 volts. Nitrocellulose membranes were washed in TBST-Tween before being soaked in Ponceau solution (Sigma Aldrich, Dorset, UK), for 5 minutes and briefly washed again in TBST-Tween. If protein loading appeared normalised, a photo was taken before membranes were washed 3 times in TBST-Tween, 5 minutes per wash. Membranes were then blocked for 30 minutes using 5% BSA(Sigma Aldrich, Dorset, UK), TBDT-Tween before primary antibody was added to the specified concentration and the membrane incubated overnight at 4°C. For antibody suppliers and concentrations used, see supplementary section. The following day, membranes were again washed 3 times in TBST-Tween, 5 minutes per wash, before being incubated for 1 hour at room temperature in TBST-Tween containing 5% milk and secondary antibody (all secondary P a g e | 43 antibodies were HRP linked, provided by Abcam, and used 1:4000). Membranes were again washed 3 times in TBST-Tween for 5 minutes per wash, before being briefly air dried and covered in ECL prime (Amersham, UK) and incubated for 5 minutes at room temperature. Membranes were developed using an imageQuant system (GE Ltd., Buckinghamshire, UK). 2.5: Cell culture, siRNA treatment and enzyme treatments.

Immortalised cell lines used were either T98G or H4 neuroblastoma cells; Hela-M cells or HEK293 kidney cells. Cells were passaged every 4-5 days and maintained in seed media. Both over-expression and siRNA knock-down was achieved using Jet-Prime reagent (Polypus transfection, Illkerch, France). SLPI, GRN and All-star siRNA’s were provided by Qiagen (Qiagen Ltd., Manchester, UK) and the neutrophil elastase plasmid was obtained from source bioscience (Nottingham, UK). Cells were seeded at 90,000 cells per ml, 2 mls being seeded per well of a 6 well plate (Thermo scientific, Hemel Hempstead, UK)and 24 hours post seeding the media was replaced with fresh seed media (1.5mls per well). Transfection reagent was pre-incubated for 10 minutes in a 24 well plate (Thermo scientific, Hemel Hempstead, UK)6µL of Jet-Prime reagent and 200 µL of Jet prime buffer along with either 22pmols of siRNA or 2.5µg of plasmid DNA. Media was replaced 4 hours post-transfection. Active neutrophil elastase (R&D systems ltd. Abingdon, UK) was diluted to 50ng/ml to digest conditioned serum free media and incubated at 37°C for the stated time(s). For activation of pro-neutrophil elastase, 200ng/ml of DPPI (R&D systems ltd. Abingdon, UK) was incubated with either 50ng/ml of pro-neutrophil elastase (R&D systems ltd. Abingdon, UK) or over-expressed neutrophil elastase at 37°C for the stated time(s).

2.6: Antibody characterisation for western blot Murine Progranulin antibody characterisation To assess progranulin concentration in tissue, validation of progranulin antibodies was required. Recombinant murine progranulin (Enzo Life science, Exeter, UK) or murine lung tissue was used in conjunction with two deglycosylating enzymes: Endoglycosidase-H (partial deglycosylation) and PNGase (full deglycosylation) (both provided by New England Biolabs, Hertfordshire, UK). Fully glycosylated progranulin is reported as being observed around 80kDa (Kessenbrok et al., 2008), smaller or absent banding should be observed in deglycosylated samples. 1.25µg of recombinant murine progranulin (Enzo Life Sciences, Exeter, UK) or 10µl of lung homogenate was used and the sample denatured for 10 minutes. Samples contained:  20µl of denatured sample  3µl of 10x deglycosylation buffer(New England Biolabs, Hertfordshire, UK)  1µl of PNGase F or EndoH enzyme (New England Biolabs, Hertfordshire, UK)  6µl of NP-40 sample buffer P a g e | 44

Samples were incubated at 37°C for 1 hour prior to the addition of 10µl of 5x SDS-loading buffer and the resulting sample run on a 10% acrylamide gel as described previously. Figure 2.6.1 shows the failure of the rabbit antibody (panel A) to bind to full length progranulin from tissue, whereas; panel B and C illustrate that the sheep antibody is capable of detecting both recombinant and tissue containing Progranulin and a partially glycosylated form (seen in the EndoH lane). Surprisingly, this antibody was less able to detect the recombinant progranulin protein (Panel B). This may reflect artificial differences in the glycosylation state of the recombinant protein used or sample degradation. See section 2.12 for antibody concentrations.

Figure 2.6.1: Comparative deglycosylation of recombinant murine progranulin or murine lung tissue using either EndoH or PNGase. Panel A: Xymed, rabbit, anti-progranulin antibody; Panel B & C: R&D systems, sheep, anti-progranulin antibody. Imaged from the same membrane, panel B & C represent different exposure settings due to an inability to detect recombinant protein. Markers indicate predicted sizes for mature protein.

Human SLPI and Progranulin antibody characterisation: To ensure antibody specificity for western blot analysis of (human) cell culture experiments, siRNA treatment was employed. T98G cells were treated with SLPI, progranulin and All-Star siRNA as described previously, cell lysates were harvested 24 hours post transfection in RIPA buffer and run on a western blot as previously described. Membranes were probed with SLPI (R&D systems, Exeter, UK), progranulin (Invitrogen, Paisley, UK) or actin (Santa Cruz, US). Figure 2.6.2 shows successful siRNA knock-down of SLPI and progranulin and assures the specificity of the antibodies used.

Figure 2.6.2: T98G cell lysate probed with SLPI (panel A), progranulin (panel B) and actin (panel C). Markers indicate predicted sizes for each mature protein. P a g e | 45

2.7: Progranulin ELISA validation.

The progranulin ELISA used was obtained from R&D systems, its validation and use was based on the protocol provided. Each well of a 96 well plate (Thermoscientific, Hemel Hempstead, UK) was pre-coated overnight at 4°C in 100µL of capture antibody, diluted to 1µg/ml in PBS. Wells were then aspirated and washed 3 times with 400µL of wash buffer before 300 µL of blocking solution was added to each well and incubated at room temperature for 1 hour. Wells were again washed 3 times with 400µL of wash buffer, before 100 µL of sample or standard was added to each well and incubated for 2 hours at room temperature. Progranulin standards were made up at: 0.125, 0.25, 0.5, 1, 2, 4, 8 and 10: ng/ml in blocking solution. Following another 3 washes, 100 µL of detection antibody was added, also diluted to 1µg/ml and again incubated at room temperature for 2 hours. The plate was again washed 3 times and 100µL of streptavadin solution was added to each well and the plate incubated again for 20 minutes at 37°C. The plate was given 3 final washes before 100 µL of substrate solution (R&D Systems, Exeter, UK) was added to each well and the plate incubated for 20 minutes at 37°C. Finally, 50 µL of stop solution was added to each well, incubated for 5 minutes at room temperature and the optical density assessed at 450nm using a plate reader.

Figure 2.7.1: Standard curve generated from progranulin standard (ng/ml) versus Optical Density at 405nm.

To ascertain if there were interfering substances within murine blood plasma that might confound accurate progranulin quantification, a spike assay was performed. Blood plasma was diluted in a range of serial dilutions: 30, 60, 100 and 200 fold dilution in block solution. An aliquot of each of these samples was taken and “spiked” with an additional 2ng/ml of progranulin standard to ensure the elicited response corresponded to the expected increase in OD. Spiked and non-spiked dilutions were loaded in triplicate (in addition to standards), Figure 2.7.1 shows the standard curve generated from progranulin standards, Figure 2.7.2 shows the resulting concentrations from the spike assays with value interpolated from the standard curve. P a g e | 46

Serum ranging from 60-200 fold dilutions elicited a linear response and the expected spikes in concentration.

Figure 2.7.2: Spike assay showing a serial dilution of blood plasma, a serial dilution of blood plasma spiked with 2ng of progranulin standard and a “corrected” trace of the spiked sample, subtracting 2ngs.

2.8: Immunoglobulin clearance of blood plasma.

Serum progranulin analysis by western blot was achieved using Millipore immunoglobulin depletion columns (Millipore, Feltham, UK). Columns were pre-cleared with 1ml of sample buffer then 60µL of plasma diluted in 540µL of sample buffer and added to the column and the flow through collected. 600µL of sample buffer was then added to the column and collected for the first elution, a second 600µL of sample buffer was then added to the column and the second elution fraction collected. Samples were then analysed by western blot as described previously. Figure 2.8.1 shows western blot analysis of each fraction, for progranulin quantification the flow through fraction was used.

Figure 2.8.1: Immunoglobulin depletion calibration for progranulin. Western blot probed with murine progranulin antibody (R&D systems). Markers indicate mature progranulin.

2.9: Neutrophil elastase activity assay.

The neutrophil elastase activity assay was provided by Cayman chemicals (Cambridge, UK). Each assay was performed in a 96 well plate, 5 µL of luminescent elastase substrate: (Z-Ala-Ala- P a g e | 47

Ala-Ala)2Rh110 and each reaction made up to 100µL total volume. For neutrophil elastase standard 2.5ngs of active neutrophil elastase was added in triplicate. Lung or brain tissue (50mg) was homogenised in 1ml of activity buffer, as described previously but omitting any freeze thawing. Protein was normalised to 2mg/ml then diluted 1 in 5 and loaded in triplicate; blood serum was diluted 1 in 10. A plate reader heated to 37°C was then used to assess optical density at 405nm, every 15 minutes for 240 minutes.

2.10: Primary neuronal culture:

Timed matings between genotyped, homozygous, SLPI null or Wild-type mice were carried out and subsequent embryos harvested at day 16. Pregnant mice were euthanized in accordance with the schedule 1 procedures of the Home Office animals in research act (1986) via physical dislocation of the neck. Post-mortem the abdominal cavity was then opened and the embryo sack excised. Brains were excised from the embryos, washed in wash media then transferred to dissociation media and placed into a shaking incubator for 30 minutes, 50rpm at 37°C. Excess media was aspirated before trypsin activity was quenched by adding 2ml of ice cold FCS for 2 minutes. Brain samples were then washed 3 times in 20ml of wash media, transferred to 20ml of seeding media (with anti-oxidants) before being dissociated by pipetting up and down using a 12ml stripette around 30 times. Cells were then filtered through sterile 80µM gauze and cell density measured using a haemocytometer. Cells were then diluted to 600,000 cells per ml and 1ml seeded per well of a 12 well plate or 500µL of a 24 well plate (both provided by Thermo Scientific, Hemel Hempstead, UK). All cell culture plates used were pre-coated with Poly-D Lysine (Sigma Aldrich, Dorset, UK), washed and pre-warmed. Cells were then placed into an incubator at 37°C and 5% CO2. After 4 days in culture, media was aspirated and replaced with pre-warmed seed media (without anti-oxidants) and placed back into the incubator. At day 7 a half media change was performed using seed media (without anti-oxidants), removing 45% of the total media and replacing it with 55% of the desired total to account for transpiration. All experiments were started at the 14th day in culture.

LPS treatment of primary neurones: Primary neurones were treated with either: 25ng, 100ng or 500ng of LPS (Sigma Aldrich, Dorset, UK) per ml of media. To assess secretion of progranulin, two 24 well plates were used and each treatment performed in triplicate. Media was diluted 1 in 10 in PBS for ELISA, using the same ELISA methodology as described in blood serum ELISA section. For intracellular progranulin response to LPS 12 well plates were used. Media was aspirated, cells washed with ice cold PBS then 150 µL of RIPA buffer added to each well. The plate was then frozen at -80°C, P a g e | 48 thawed, scrapped with a cell scraper and pipetted up and down several times before being added to 5xSDS and heated for 10 minutes at 80°C. Western blotting methodology used was as described in western blot section. Both experimental methodologies were replicated 4 times.

2.11: Wax sectioning and Immunohistochemistry.

Each brain was fixed for 2 days in PFA, then the following dehydration programme used:

 70% Ethanol for 2 hours  80% Ethanol for 1 hour  96% Ethanol for 2 hours  100% Ethanol for 4 hours  100% Xylene for 3 hours  Paraffin wax (57°C) for 2 hours Samples were then placed into molten paraffin wax (Poth Hille, Rainham, UK) and embedded onto a sectioning cassette, orientated horizontally with the sagittal plane perpendicular to the plane of the cassette. Was sections were cut at 3.5µm, floated on warm water and then mounted and dried on glass slides (Thermo scientific, Hemel Hempstead, UK). Sections were then re- hydrated using:  100% Xylene for 5 minutes (x 2)  100% Ethanol for 5 minutes (x2)  90% Ethanol for 5 minutes  70% Ethanol for 5 minutes  Distilled water for 2 minutes (x 3) Antigen unmasking was achieved by placing the sections into near boiling citric acid for 10 minutes, heated using a microwave. Slides were then washed 3 times in distilled water, 5 minutes per wash before endogenous peroxidise activity quenched via incubation in (room temperature) methanol for 30 minutes. Slides were again washed in distilled water, 5 minutes per wash for 3 washes. Slides were then blocked overnight at 4C using vector laboratories blocking buffer. Primary antibody was then added (See 2.12) and incubated for 1 hour at room temperature. Slides were then washed 3 times in PBS (5 minutes per wash) before being incubated in secondary antibody (vector laboratories) for 30 minutes at room temperature. Slides were again washed 3 times in PBS (5 minutes per wash) before being incubated with ABC reagent (Vector laboratories, Peterborough, UK) for 30 minutes at room temperature. Slides were then incubated in DAB solution (Sigma Aldrich, Dorset, UK) for 5 minutes before being washed in tap water. Slides were then counter-stained with haematoxylin for a few seconds P a g e | 49 before being washed again in tap water. Samples were then dehydrated with the following incubations:  70% Ethanol for 5 minutes  90% Ethanol for 5 minutes  100% Ethanol for 5 minutes ( x2)  100% Xylene for 5 minutes (x2) Slides were then mounted with DPX (Sigma Aldrich, Dorset, UK) and a cover-slip.

2.12: Antibodies used

Protein raised Species of Species Concentration against epitope raised in Supplier Purpose used Actin Human & mouse Goat Santa Cruz WB 1 in 2000 N. Elastase Human & mouse Goat Santa Cruz WB 1 in 1000 SLPI Human Goat R & D systems WB 1 in 500 SLPI Mouse Goat R & D systems WB 1 in 250/500 Progranulin Human Rabbit R & D systems WB 1 in 1000 Progranulin Human Goat R & D systems WB 1 in 1000 Progranulin Mouse Sheep R & D systems WB 1 in 1000 Tau Human & mouse Mouse Pierce IHC 1 in 1000 TDP-43 Human & mouse Rabbit ProteinTech IHC 1 in 1000 Ubiquitin Human & mouse Rabbit Abcam IHC 1 in 1000 GFAP Human & mouse Chicken Millipore IHC 1 in 1000 FUS Human & mouse Rabbit ProteinTech IHC 1 in 1000 Goat IgG Goat Donkey Santa Cruz WB 1 in 4000 Rabbit IgG Rabbit Goat Santa Cruz WB 1 in 4000 Sheep IgG Sheep Donkey Santa Cruz WB 1 in 4000 Chicken IgG Chicken Goat Abcam IHC 1 in 2000

2.13: Statistical analysis

All data analysis and graphs shown throughout were created using Prism, Graphpad 6. Where statistical tests were used to identify significant difference between means (the majority of tests used), unpaired, student t-test were perform and where indicated, a bonferoni correction to account for multiple comparisons. All age dependent effects were assessed using a linear regression analysis. For the Pavlovian fear conditioning test, which required multiple comparisons to be made between age and genotype, a 2- way ANOVA was utilised in conjunction with a Tukey correction. P a g e | 50

Chapter 3: Behavioural evaluation of SLPI null mice.

P a g e | 51

3.1:Introduction.

Progranulin haploinsufficiency which is observed in FTLD patients with GRN mutations, manifests as a consistent series of behavioural and/or linguistic deficits (Baker et al., 2006, Cruts et al., 2006 and Mackenzie et al., 2006). In keeping with this precedent, transgenic, GRN knockout mice have been shown to exhibit a behavioural phenotype that is reminiscent of bvFTD, a syndrome that can be caused by a number of different GRN mutations (Yin et al., 2010; Goshal et al. 2012). GRN haploinsufficiency leads to a characteristic histopathology with “Type A” TDP-43 positive inclusion bodies: short dystrophic neurites and crescent/oval NCI’s that are focused in neocortical layer 2 (Mackenzie et al., 2011) in addition to ubiquitinated lentiform NII’s within the neocortex and striatum (Mackenzie et al., 2006). This neurodegenerative damage manifests as wide-spread bilateral frontotemporal and parietal atrophy (Witwell et al., 2010). Owing to this large affected area, GRN mutation patients show a heterogeneity of symptoms and can go on to develop bvFTD, PNFA or corticobasal syndrome (Spina et al., 2007; Snowden et al., 2007; Baker et al., 2006 and Cruts et al., 2006). Studies in GRN null mice have also shown that decreased progranulin expression leads to a measurable behavioural profile that is in keeping with FTLD: deficits within social awareness, apathetic or depressive like affect and reduced overall anxiety (disinhibited). This is contrasted with a lack of memory dysfunction up until mice are in their very oldest years. Apathetic, depressive like behaviour is shown to be elevated in both tail-suspension and forced swim tests. Sociability as assessed by interest in a stranger mouse over a familiar one also implies neurological deficits, in addition to reduced anxiety as assessed by elevated plus maize. Though not common to FTLD patients, GRN knockout mice also show reduced olfactory function as assessed by an olfactory discrimination task. Finally, these mice also show the onset of spatial learning and memory deficits at 18 months, in keeping with FTLD whereby memory is generally unaffected in the early and intermediate stages of the disease (Yin et al., 2010). If SLPI exhibits a potent role in progranulin regulation, SLPI null mice should exhibit increased progranulin cleavage thereby reducing functional progranulin signalling. This would manifest as a profile that is similar to GRN null mice, whereby an age dependent lack of progranulin signalling leads to the observed behavioural phenotype. Heterozygous GRN null mice (effectively haploinsufficient) are indistinguishable from age-matched control animals with respect to a number of immunohistochemical markers for neurodegeneration (Ahmed et al., 2010). This implies that any relevant behavioural affects observed in SLPI null mice would indicate a highly attenuated progranulin signal and implicate a potent role for SLPI within progranulin regulation. P a g e | 52

3.2: Methods

Mice and cohorts. SLPI null and control mice were split into 3 age matched cohorts with behaviour being assessed at 6, 12 and 20 months of age. These ages allow a comparison to be drawn between SLPI null mice and GRN null mice that have been used in existing studies. For each cohort a total of 14 animals per genotype were assessed, however; owing to progranulins sex dependent role it was decided that equal numbers of male and female animals (7+7) would be used for each time point. Behavioural tests can induce a stress response in test animals that might alter the elicited behaviour from later tests. To account for this a minimum of 5 days was given between each behavioural test and testing ordered so that the least (potentially) stressful tests were carried out first, with the most stressful (Fear conditioning) performed last (See figure 3.2.1).

Figure 3.2.1: Sequence of behavioural tests from least stressful (left) to most stressful (right).

Open-field arena Anxiolytic or disinhibited behaviour was assessed using the open-field paradigm whereby mice are placed into a randomised corner of a high-sided square arena (28cm x 28cm shown in figure 3.2.1). Over the course of a 5 minute trial, an overall measure of anxiety can be obtained by assessing the ratio of time spent in the open against time spent near the arena walls. Open field tests were assed using HVS video tracking software and lighting conditions of 150 lux.

Y-maze spontaneous alternation Spatial working memory was tested using the Y-maze spontaneous alternation paradigm. Mice are placed into one of three randomly determined arms of a Y shaped arena (figure 3.2.2), facing the arm terminus. The test mouse is then given 5 minutes to freely explore each of the 3 arms, wherein, a mouse with a functional working spatial memory is less likely to explore an arm that it has just explored. The arms are designated as A, B and C; the order in which the test mouse visits each arm is recorded and used to calculate a periodicity score. Periodicity scores of 50% P a g e | 53 indicate random walking with no spatial recollection; higher scores imply increased spatial recollection.

Social interaction and social preference Deficits in sociability were assessed using the social interaction and social preference paradigms. The test mouse is placed into a 3 chambered sociability arena and allowed to acclimatize for 10 minutes. A stranger mouse (of the same age and sex) is then placed into a cage within one of the two possible interaction chambers (see figure 3.2.5); while an empty cage is placed into the other social interaction chamber. Social interaction is assessed by the ratio of time the test mouse spends interacting with (sniffing and closely inspecting) the stranger mouse, compared to the empty control cage over a 10 minute period. A second paradigm is then run whereby the now familiar mouse remains in that test cage, however, a new stranger mouse is placed into the previously empty cage. Cognitively normal mice will tend to interact with the novel, stranger mouse more than the now familiar one. As in the previous paradigm, a 10 minute test period is given.

Olfactory discrimination Assessing olfaction of rodents is a good overall marker for neurodegeneration as their olfactory bulbs comprise such a large proportion neurological matter. Assessing olfaction is also important as it is the primary method by which mice identify other mice (Cheng et al., 2011), and so any observed deficits within the sociability paradigms may just be an olfactory deficit (rather than a social cognition deficit). The test mouse is placed into the olfactory discrimination arena along with a piece of filter paper that has been dabbed with distilled water, the time spent sniffing it is assessed over a 3 minute period. This is then compared to the time spent sniffing an identical piece of filter paper that has been dabbed with sesame seed extract, over a second 3 minute period.

Tail suspension Increased apathy and motivational deficits are observed in GRN null mice (Yin et al., 2010). To assess this characteristic, mice are suspended by their tails for a 6 minute trail period and their motivational state deduced by the total amount of time they remain immobile, not trying to reach up to free themselves from restraint (depicted in figure 3.2.4). Mice that are suffering motivational deficits spend an increased amount of time immobile as compared to cognitively normal mice (Cryan, J.F. et al., 2005).

P a g e | 54

Fear conditioning As GRN null mice have shown impaired memory function within late age cohorts (Yin et al., 2010; Ahmed et al., 2010), a second metric of memory and recall was also assessed. This was assessed by exploiting the “startle response”; whereby mice freeze in response to a loud noise or short averse stimuli such as a (mild) electric shock. This response is then paired to the animals’ ability to recall of a specific stimulus such as a light turning on. Mice are placed into a freeze response chamber (Figure 3.2.6) where the movement of the mouse is assessed by the time taken (latency) to break an infrared beam. Mice are first acclimatised in the test chamber for 300 seconds before a conditioned stimulus (a light) is given, followed by an unconditioned stimulus (a small electric shock to the feet). Three conditioning sequences are given over a 12 minute period with freeze responses being assessed within individual 30 second time bins. The following day, recall of the testing arena is assessed over 480 seconds, with latency again being tested in 30 second time bins. Recall of the stimulus is then assessed on the third day, with the arena being disguised so that environmental recall is diminished. After a 2 minute acclimatisation period, the light stimulus is activated and increased latency (freezing) is assessed in 30 second time bins for a further 6 minutes (see figure 2.3.1).

Figure 3.2.2: Open-field arena, test mouse in peripheral area, the central area has been labelled for diagrammatic purposes. Figure 3.2.3: Y-maze arena with test mouse depicted as being within arm “A”, visual cues are also shown at each arm terminus. Figure 3.2.4: Tail suspension test depicting a test mouse being secured by its tail 30 cm from the floor. Figure 3.2.5: Social interaction arena depicted in social preference paradigm with a test mouse in the central chamber and a stranger and familiar mouse in cages 1 and 2. Figure 3.2.6: Freeze response chamber, non-disguised paradigm. P a g e | 55

3.3: Results: SLPI null mice show no deficit in motility, anxiety or spatial working memory Within the open field paradigm, SLPI null mice showed no significant decrease in motility as compared to wild-type controls using an unpaired student t-test (Figure 3.3.1). Overall walking distances ranged between 1.8 to 3 metres within the 3 minute trial period, no significant age dependent reduction in distance travelled could be observed for either genotype. To assess anxiolytic or disinhibited behaviour of mice within the open field paradigm, time spent in the central section of the arena is expressed as a percentile of the total time. SLPI null mice showed no significant difference (using an unpaired, student t-test) to wild-type control animals, at all assessed ages (Figure 3.3.2). Additionally, no age dependent trend could be observed for times spent in the central area for either genotype.

Figure 3.3.1: Open-field arena, mean scores of total distance moved by the test mouse (in metres) over a 5 minute period with standard deviation indicated by error bars. Wild-type depicted in black, SLPI null in white at the ages of 6, 12 and 20 months (n=14).

Figure 3.3.2: Open-field arena, mean scores of the percentage of time spent in the centre of the arena, over a 5 minute period, indicating standard deviation with error bars. Wild-type depicted in black, SLPI null in white at the ages of 6, 12 and 20 months (n=14). P a g e | 56

To ensure a spatial working memory deficit could be identified using a y-maze paradigm, 10 month old Alzheimer’s triple transgenic mice (3xTgAD) were compared to age matched wild-type animals (NonTg). These mice were comprised of a mixture of sexes: 10 male and 9 female 3xTgAD mice; 9 male and 9 female NonTg mice (Oddo et al., 2003). A significant, 23% reduction in successful triad frequency (spontaneous alternation) was observed within the 3xTgAD mice, when compared to the NonTg group (Figure 3.3.3).

No significant change between wild-type or SLPI null animals at any age in the alternation task could be observed. Median periodicity scores ranged from 61-66, indicating successful visuospatial recall. No age dependent change in periodicity could be observed for either genotype, using a linear regression analysis (Figure 3.4.4).

Figure 3.3.3: Y-maze, spontaneous alternation paradigm. The y-axis showing the percentage of correct triads as a fraction of total arm entries where 50% indicates random walk. Wild-Type mice depicted in black (n=19) and 3xTgAD mice in white (n=18), both genotypes aged 9-10 months. p<0.001 using a student t-test, error bars indicate standard deviation.

Figure 3.3.4: Y-maze, spontaneous alternation paradigm. The y-axis shows the percentage of correct sequential periods as a fraction of all arm entries, 50% indicating random walk. Wild-type animals are shown in black, SLPI null in white at ages 6, 12 and 20 months (n=14). Error bars indicate standard deviation. P a g e | 57

3.4: SLPI null mice display no deficit within social interaction paradigms or olfactory discrimination.

The social interaction paradigm assesses the time in which the test mouse spends interacting with a test mouse over an empty cage. At all assessed ages, no genotype dependent effect could be observed which might indicate a different preference for the test mouse or the empty cage (Figure 3.4.1). Both genotypes did however, display a significant preference for stranger mice over empty cages at 6 and 12 months of age; however, at 20 months of age, no significant difference could be observed for a preference for stranger mice over empty cages. Figure 3.4.2 shows a linear regression analysis of the social preference paradigm of both genotypes over the 3 assessed ages. Amount of time spent with stranger mice shows a significant, age dependent reduction for both genotypes from mean interaction times of 78/71 seconds (wild- type/SLPI null) at 6 months of age, to 21/24 seconds at 20 months of age. Assessment of interaction time with empty cages showed only an age dependent reduction within wild-type mice.

Figure 3.4.1: Social interaction paradigm, Y-axis indicates mean time (in seconds) the test mouse spends interacting with either an empty cage or a stranger mouse over a 10 minute period. Wild-type depicted in black, SLPI null in white; at 6 (A), 12 (B) and 20 (C) months of age (n=14). p values > 0.001 using an unpaired student t-test, error bars indicate standard deviation. P a g e | 58

Figure 3.4.2: Linear regression analysis of stranger interaction time and empty cage interaction time. Both genotypes show an age dependent decrease in interaction time with stranger mice: wild-type R- Squared of 0.6632 and p<0.0001; SLPI null, R-Squared of 0.5801 and p<0.0001. Interaction times with empty cages also showed a significant age dependent decrease for wild-type mice (R-Squared of 0.2608, p=0.0005); SLPI null mice failed to show a significance decrease (R-Squared of 0.0847, p=0.0614).

The social preference paradigm assesses a test mouse’s preference for a novel (stranger) mouse, over a familiar mouse. At all assessed ages, no genotype dependent effects could be observed whereby SLPI null mice showed an altered preference for either novel mice or familiar mice (Figures 3.4.3). Both genotypes displayed a significant preference for stranger mice over familiar mice at 6 and 12 months of age; however, at 20 months of age, no significant difference could be observed for a preference for stranger mice over familiar mice.

Figure 3.4.4 shows a linear regression analysis of the social preference paradigms over each of the 3 ages. Both genotypes show an age dependent decrease in stranger interaction times from 74/69 seconds (Wild-type/SLPI null) at 6 months of age to 24/21 seconds at 20 months of age. Similarly, both genotypes displayed an age dependent decrease of familiar mouse interaction time, from 38/33 seconds at 6 months of age, to 16/19 seconds at 20 months of age.

P a g e | 59

Figure 3.4.3: Social preference paradigm, Y-axis indicates mean time (in seconds) the test mouse spends interacting with either a familiar mouse or a stranger mouse over a 10 minute period. Wild-type depicted in black, SLPI null in white at 6 (A), 12 (B) and 20 (C) months of age (n=14). p values > 0.001 using an unpaired student t-test, error bars indicate standard deviation.

Figure 3.4.4: Social preference, linear regression analysis of stranger mice interaction times and familiar mice interaction times. Both genotypes show an age dependent decrease in stranger interaction time (wild-type R-squared of 0.4824, p<0.0001; SLPI null R-Squared of 0.2619, p=0.0005). Both genotypes also displayed an age dependent decrease of familiar mouse interaction time (wild-type mice R-squared of 0.7655, p<0.0001; SLPI null mice R-Squared of 0.6969, p<0.0001). P a g e | 60

Olfactory discrimination was used to determine the amount of time a test mouse sniffs a piece of blotting paper dabbed with sesame seed extract, compared to a control dabbed with water. No genotype related difference could be observed at any cohort age, with both wild-type and SLPI null animals spending statically equivalent times sniffing water or sesame seed extract as each other (Figure 3.4.5). Both wild-type and SLPI null animals, did however, spend significantly more time sniffing sesame seed extract than water at all assessed ages (all p values < 0.001 using an unpaired, two tailed student t-test using a Bonferroni correction). Figure 3.4.6 displays a linear regression analysis of time spent sniffing sesame seed extract as a proportion of time spent sniffing water, against age in months, for both genotypes. Both genotypes show an age dependent decrease in olfactory ability as assessed by this ratio, reducing from 0.60/0.64 at 6 months of age to 0.38/0.39 at 20 months of age.

Figure 3.4.5: Olfactory discrimination task, whereby a test mouse sniffs either a scented (sesame) or non-scented (water) piece of blotting paper over two sequential 3 minute periods. Times are record for 6 (A), 12 (B) and 20 (C) month old cohorts, n=14. p<0.001 using an unpaired student t-test , error bars indicate standard deviation. P a g e | 61

Figure 3.4.6: Regression analysis of olfactory discrimination within the ratio of time spent sniffing sesame divided by time spent sniffing water. Both genotypes displayed an age dependent reduction, with a wild-type R-squared of 0.1961, p=0.0033 and SLPI null R-squared of 0.3036, p=0.0002.

3.5: SLPI null mice show no increase in depressive behaviour or deficit in Pavlovian freeze response.

The tail suspension test assesses the total time the test mice spend immobile, in seconds. Two mice (both male animals from the 6 month cohort) which climbed their tails for more than 25 seconds (and so no longer suspended by their own tails) were eliminated from the analysis. No genotype specific differences could be observed at any of the assessed ages, with SLPI null mice being statistically indistinguishable from wild-type mice (figure 3.5.1).

Figure 3.5.2 shows a linear regression analysis of tail suspension immobility times for both genotypes as a function of age in months. Both genotypes show an age dependent increase in immobility scores as assessed by this ratio

Figure 3.5.1: Tail suspension test, mice are suspended by their tails and the total amount of time spent immobile (in seconds) assessed. n=12 for the 6 month cohort (due to elimination), n=14 for 12 and 20 month cohorts, , error bars indicate standard deviation. P a g e | 62

Figure 3.5.2: Tail suspension, linear regression analysis of the time spent immobile. Wild-type R- squared of 0.1961, p=0.0033; SLPI null R-squared of 0.3036, p=0.0002.

Pavlovian fear conditioning assesses the recollection of a mild electrical shock to the feet (an unconditioned stimulus) paired to a light pulse (a conditioned stimulus) and then measures the animals freeze response (an unconditioned response) to the light pulse or to the testing arena (environmental recall). The freeze response is assessed by the latency it takes (in seconds) until the test mice moves, which is detected by an infrared motion detector.

Figure 3.5.3 shows the freeze response latency times for aged cohorts over the day 1, entrainment regiment. No genotype specific differences could be observed for any aged cohort, with SLPI null animals being statistically indistinguishable from wild-type animals. To assess age related effects, a 2-way ANOVA comparing each age and genotype was performed in conjunction with a Tukey correction for multiple comparisons. Some age related differences could be observed, with both wild-type and SLPI null animals of the 20 month old cohorts showing a significantly increased latency time at the base line period, when compared to younger cohorts of their corresponding genotype. 20 month old wild-type and SLPI null animals also elicited a significantly reduced latency time at the third entrainment event, compared to their 6 and 12 month corresponding genotypes (Supplementary Data tables 1 and 2); however, no genotype specific effects could be observed at any age/time point. Similarly, within the second day of the programme (environmental recall), no significant genotype specific differences could be observed at any age (Figure 3.5.4). Despite this, significant age depended differences could however be observed within the 2-4 minute time bin, whereby both wild-type and SLPI null 20 month old animals elicited significantly reduced latency times when compared to younger animals of the same genotype. Both p values were <0.001, using a 2-way ANOVA with a Tukey correction (Supplementary data table 3). P a g e | 63

Figure 3.5.3: Fear conditioning, entrainment, showing the aggregate latency times for each time bin, defined as the time taken (in seconds) between a time bin commencing and the test mouse moving. n=14, significant differences between groups was assessed at each aggregate time point by 2-way ANOVA, p<0.001.

Figure 3.5.4: Fear conditioning, environmental recall, showing the aggregate latency times for each time bin, defined as the time taken (in seconds) between a time bin commencing and the test mouse moving. significant differences between groups was assessed at each aggregate time point by 2-way ANOVA, p<0.001.

Figure 3.5.5 shows the latency scores from the third day, which assesses recall of the conditioned response (freezing in response to the light pulse). No significant genotype specific differences could be observed at any ages (figure 3.5.5). Significant age related differences could however be observed within the base-line period, whereby both wild-type and SLPI null 20 month old animals elicited significantly increased latency times when compared to younger animals of the same genotype. P a g e | 64

Additionally, a significantly reduced latency time could also be observed in 20 month old wild-type and SLPI null animals over the 6-8 minute period. All p values were <0.001, using a 2-way ANOVA, using a Tukey correction for multiple comparisons.

Figure 3.5.5: Fear conditioning, conditioned response recall, showing the aggregate latency times for each time bin, defined as the time taken (in seconds) between a time bin commencing and the test mouse moving. n=14, significant differences between groups was assessed at each aggregate time point by 2-way ANOVA, p<0.001.

3.5: Discussion of behavioural evaluation

Open field analysis did not show any evidence of a disinhibited phenotype within SLPI null mice as would have been indicated by an increase in the proportion of time spent in the centre of the arena. Kayasuga and colleagues evaluated GRN null mice within an open field paradigm and found that GRN null mice spent a reduced amount of time in the central arena compared to the peripheral area, implying an anxiolytic phenotype (Kayasuga et al., 2007). This is perhaps in contradiction to work done by Yin and co-workers who found a disinhibited phenotype within GRN null mice using the elevated plus maze (Yin et al., 2010). There are several confounding features that may account for this effect such as laboratory specific selection/analysis criteria for the assessment of anxiolytic behaviour. Indeed, there is precedent for strains of mice showing (seemingly) contradictory effects between elevated plus maze and open-field even within the same study. Rogers and colleagues ranked 6 inbred mice strains by anxiolytic behaviour using open-field and elevated plus maze and found no strong correlation between the two paradigms (Rogers et al., 1999). More recent work which assessed various aspects of the two paradigms, found a correlation between 4 of a possible 5 criteria, leaving some room for divergence (Carola et al., 2001). Despite these differing views, there appears to be no motivational affect within SLPI null mice utilising this paradigm. P a g e | 65

Within Y-maze assessment of periodicity scores by a cognitively normal mouse have been reported within the range of 70-60% (Moran et al., 1995, Wietrzych et al., 2005), concurring with the values obtained within this behavioural battery. As a control to ensure diminished visuospatial memory could be observed within this paradigm, triple transgenic Alzhiemer’s disease mice (Oddo et al., 2003) aged 10 months were also tested using the same protocol. These mice displayed a profound deficit within the spontaneous alternation paradigm, with transgenic mice periodicity scores falling to the “random chance threshold” of 50%. Granted the assurance that this paradigm can identify severely inhibited visuospatial cognition, it is clear that SLPI null mice are cognitively normal within the sensitivity range of this test. This behavioural battery also failed to show any age dependent reduction in spontaneous alternation within wild-type animals which might be expected from normal cognitive decline. Other studies (using Ts65Dn null mice) have found age dependent reductions in periodicity scores between 4 to 16 months of age, within C57Bl/6J control animals (Chang and Gould 2008), however using a longer trial time of 8 minutes. Olfactory ability was assessed both as a control for sociability testing (which has a strong scent component) and as an overall measure of degeneration of the olfactory bulb. Both wild-type and SLPI null mice displayed an age dependent increase in time spent sniffing (sesame seed extract) ensuring this testing paradigm does have sensitivity to identify a phenotype imparted by normal aging. Unlike GRN mice which display an increased amount of time spent sniffing sesame seed extract at 18 months of age (although not before that time)(Yin et al., 2010); SLPI null mice showed no olfactory phenotype at any age. The social interaction tests employed a methodology whereby contact time (time facing interacting cages) was assessed; over differing protocols whereby time spent in each individual chamber is assessed. This metric allows direct comparison to work done by Yin and co-workers (Yin et al., 2010) and eliminates confounding elements such as mice spending time in a corner of the interaction chamber but not interacting with the stranger/familiar mouse. Pearson and co- workers employ a different experimental strategy whereby familiar and stranger mice have their cage positions randomised between the social interaction and social preference paradigms arguing that the stranger mouse should be novel only in its appearance and not only in a positional sense to the test mouse (Pearson et al., 2010). This paradigm was purposely avoided in these tests as switching interaction mice positions assumes that social recognition must occur independently of spatial or contextual recognition: when and where type memory. Within this dataset a strong preference for a novel mouse over an empty cage was observed for both genotypes at all ages. Interestingly, increased interaction time for stranger mice over familiar mice was observed at ages 6 and 12 months of age but not at 20 months of age, implying that significant cognitive decline may have occurred at this age. To corroborate this P a g e | 66 observation, both SLPI null and wild-type mice displayed an age dependent decrease in interaction times with stranger mice over empty cages and over familiar mice, while both social preference and social interaction paradigms showed similar interaction times to that displayed by wild-type mice evaluated by yin and co-workers (between 75-35 seconds). As with other behavioural tests, SLPI null mice failed to show any behavioural phenotype contrary to the profound deficit within social recognition that can be observed within GRN null mice at all ages (yin et al,. 2010). As this is the most profound behavioural deficit observed within GRN null mice, it could be assumed that sociability tests should be the most sensitive to any progranulin dysregulation. As such, it seems unlikely there is any progranulin signalling deficits within SLPI null mice to the extent that it could manifest behaviourally. As with sociability assays, Tail suspension tests failed to show any preferential deficits within SLPI null mice, however, both SLPI null and wild-type mice did display an age dependent increase in the time spent immobile. This illustrates that although this test has the required sensitivity to detect an increase in apathetic/depressive behaviour resulting from aging; the SLPI genotype failed to produce any further increase in immobility scoring. GRN null mice have been reported to show increased immobility scores which lessened relative to wild-type mice as immobility scores for wild-type mice increased (Yin et al., 2010). As a second measure of memory function, Pavlovian fear conditioning was employed which unlike Y-maze spontaneous alternation (which is visuospatial dependent); relies upon limbic and thalamic association between fear and a freeze response. To date, no fear conditioning response has be assessed within GRN null mice, however, a number of groups have assessed freeze responses within transgenic AD mice where time spent immobile is increased compared to wild-type controls, indicating a decline in fear-associated memory (Espana et al., 2010). Some age dependent differences were observed within the oldest (20 months) mice, both genotypes showing a deficit within 3rd entrainment event compared to their 12 month old counterparts: potentially implicating reduced hippocampus mediated learning. Similarly on day 2, environmental recall of the fear conditioning arena appears diminished compared to 6 and 12 month old animals during the period of highest freeze recall in the other age cohorts. In keeping with the observed deficits within 20 month old mice, inhibited freeze recall to the conditioned response can be observed within both SLPI null and wild-type mice at the 6-8 minute period and for wild-type mice within the 4-6 minute period (SLPI null mice showing a reduction within this period, however, slightly below the significance threshold). As with other behavioural tests, no convincing preferential differences between SLPI null and wild-type mice could be observed at any age. This further supports the other behavioural tests that no significant behavioural phenotype is apparent and the null hypothesis appears true with respect to SLPI null mice showing no signs of progranulin dysregulation. P a g e | 67

Chapter 4: Evaluation of SLPI dependent progranulin regulation

P a g e | 68

4.1: Introduction

SLPI has been shown to have a key modulatory role over progranulin by protecting progranulin from cleavage by neutrophil elastase (Doumas et al., 2005). Supportingly, SLPI null mice have been shown to have wound healing deficits (Ashcroft et al., 2000) that can be rescued by cutaneous application of progranulin to the wound site (Zhu et al., 2002). This has lead to the hypothesis that SLPI knockout mice have reduced levels of progranulin and that SLPI modulates tonic progranulin concentration. To test this hypothesis, relative expression of progranulin protein was assessed within frontal brain tissue, lung and blood serum. Brain tissue was chosen owing to its importance to FTLD pathology, whereas lung tissue and blood plasma were selected for their relatively high expression levels of both SLPI and progranulin (Van Seruningen et al., 1995 and Daniel et al., 2000). Owing to the differing glycosylation states of progranulin (Zhou et al., 1993): brain and lung homogenate was assayed using western blotting (which can differentiate glycoforms by mass), whereas; blood serum was first pre-cleared of immunoglobulins before being run as a western blot. Blood plasma progranulin levels were also assessed by ELISA within all of the animals used in the study, recapitulating progranulin blood serum measurements taken from FTLD patients, a technique that can be used to identify GRN mutation carriers (Finch et al., 2009). Neutrophil elastase activity is also a key component within the current hypothesis of progranulin regulation. To asses this, neutrophil elastase abundance was measured by western blot and a colorimetric assay was used to gauge elastase specific activity via its ability to cleave a fluorescently tagged substrate. As a proof of concept, SLPI’s protective effect on neutrophil elastase cleavage of progranulin was also determined within the conditioned media of immortalized cell lines. These cell lines were treated with either a control or SLPI specific siRNA, the media removed and then treated with active, recombinant neutrophil elastase. Following digestion, progranulin cleavage was assessed by western blot. The biosynthesis of neutrophil elastase involves multiple steps which may be pertinent to SLPI relevant progranulin regulation. As with most secreted serine proteases, neutrophil elastase is first secreted as a pro-enzyme that is then cleaved and activated by other proteases. This activation of neutrophil elastase is reported to be achieved by activated by cathepsin C (DPPI) (Korkmaz et al., 2010) to corroborate this effect, recombinant pro-elastase and over-expressed pro-elastase were used within immortalized cell lines, before DPPI was added to the media and progranulin cleavage assessed by western blot. Finally, to assess the role of SLPI within a neurological inflammatory context, neuronal primary cells were taken from E15 embryos of SLPI null and wild-type mice and cultured for 16 days, P a g e | 69 whereupon they were treated with lipopolysaccharide (LPS), triggering an immune response. Following treatment, progranulin secretion was assessed by western blot and ELISA.

4.2: Methods Western blots For tissue (frontal cortex and lung) and lysate blots, 40µl of sample (normalised and containing SDS buffer) was loaded per well onto a 10% acrylamide gels; or 17% acrylamide gels when probing for SLPI. Gels were run at 120 volts for 90 minutes and transferred as described previously. The resulting membrane was probed overnight with 1 in 1000 dilution of the relevant primary antibody (See section 1.12); with the exception of SLPI probed blots where a 1 in 250 dilution was used for brain tissue and 1 in 500 for all other purposes. Secondary antibodies were used at 1 in 4000 dilution. For conditioned media blots, media was boiled in 5xSDS buffer for 10 minutes, 180µL was loaded per well and gels run at 200 volts for 200 minutes.

Progranulin ELISA Progranulin ELISA was performed as described previously (See section 2.7), blood plasma was diluted 1 in 100 using ELISA diluents, whereas cultured media was used directly, without dilution. Standards were diluted as described previously (in a range from 0.125ng/ml to 12ng/ml). All standards, blanks and samples were loaded in triplicate. Standard curves were generated for each plate used (as described in section 2.7) and used to infer progranulin concentration, then subsequently multiplied by to give the original values.

Colorimetric assay Colorimetric assays were performed as previously stated, with 2mg/ml of lung or brain homogenate being diluted 1 in 5, using a standard of 2.5ng/ml of active neutrophil elastase. Three different animals were used per genotype and tissue type and all samples and standards were run in triplicate. Optical density was assessed at 405nm every 15 minutes for 4 hours.

Cell culture Immortalized human cell lines used were human: Hela, HEK, T98G, H4 or SH-SH5Y cells. All cell lines were seeded at 200,000 cells per six well plate and the medium changed to serum free media following the relevant transfection (for full description, see section 2.5). Primary neurones were obtained from E15 embryos of SLPI null or wild-type mice. Following processing and seeding (see section 2.10) the neurones were cultured for 14 days prior to treatment with 25, 100 or 500ngs of LPS. P a g e | 70

4.3: Results: Brain homogenate of SLPI null mice shows no evidence of excessive progranulin cleavage.

Figure 4.3.1 shows no observable reduction in mature (~80kDa) progranulin within SLPI null brain homogenate (frontal cortical tissue) as compared to wild-type controls, for 20 month old animals. Similarly, no additional granulin cleavage products can be observed within the SLPI null brain homogenate as compared to wild-type brain homogenate. Actin loading controls appeared relatively normalised, indicating that accurate comparisons between samples can be assured. In accordance with 20 month old animals, brain homogenate taken from 12 month old animals also show no reduction in mature progranulin within SLPI null brains, or additional cleavage products (figure 4.3.2). Actin loading controls also appearing normalised, allowing accurate sample comparison.

Figure 4.3.1, A: Western blot of normalised frontal brain homogenate, 20 month old male mice, probed with progranulin. C: Western blot of normalised frontal brain homogenate, 20 month old female mice, probed with progranulin. B and D: Loading control of the above blots, probed with actin.

Figure 4.3.2, A: Western blot of normalised frontal brain homogenate, 12 month old male mice, probed with progranulin. C: Western blot of normalised frontal brain homogenate, 12 month old female mice, probed with progranulin. B and D: Loading control of the above blots, probed with actin.

Figure 4.3.3 reveals the presence of neutrophil elastase within brain homogenate, indicated by the banding at 29kDa. No total differences within total neutrophil elastase protein could be observed between SLPI null and wild-type animals. In accordance with this finding, colorimetric P a g e | 71 assay for neutrophil Elastase activity within brain homogenate revealed no significant difference between SLPI null and wild-type samples (figure 4.3.3).

Figure 4.3.3 also shows the presence of SLPI within wild-type brain homogenate, compared to its absence in SLPI null brain homogenate. A faint contaminating band is also within SLPI null brain homogenate, however, this appears slightly smaller than the ~12 kDa SLPI band. Exposure settings and primary antibody concentration were heavily increased to visualise SLPI within brain homogenate, indicating a low level of protein expression.

Figure 4.3.3, A: Western blot of normalised frontal brain homogenate, 20 month old male mice, probed with neutrophil elastase. B: Replicate of the above blot, probed with SLPI. C: Actin loading control of the above two blots. D: Neutrophil elastase activity assay of frontal brain homogenate, n=3 per genotype.

4.4: Lung homogenate analysis reveals no evidence of excessive progranulin cleavage in SLPI null animals.

Figure 4.4.1 shows progranulin probed lung homogenate from 20 month old animals. Progranulin appears as a diffuse smear from ~85-65 kDa within all samples. Large amounts of variability can also be observed between samples, despite normalised loading as assessed by actin loading controls. Despite this large amount of variability between samples, no convincing differences of band intensity or appearance could be observed between SLPI null and Wild-type samples. Correspondingly, no increase in potential granulin cleavage products could be observed in SLPI null samples. Figures 3.4.2 shows progranulin probed lung homogenate taken from 12 month old animals. As with the older animals, a large degree of variability can be observed between individual animals, however, no convincing reduction in mature progranulin or additional cleavage products could be observed within SLPI null animals. P a g e | 72

Figure 4.4.1, Panel A: Western blot of normalised lung homogenate, 20 month old male mice, probed with progranulin. C: Western blot of normalised lung homogenate, 20 month old female mice, probed with progranulin. B and C: Loading control of the above blots, probed with actin.

Figure 4.4.2, Panel A: Western blot of normalised lung homogenate, 12 month old male mice, probed with progranulin. C: Western blot of normalised lung homogenate, 12 month old female mice, probed with progranulin. B and C: Loading control of the above blots, probed with actin.

Figure 4.3.3 shows neutrophil elastase expression from (20 month old male) lung homogenate. No convincing differences could be observed within total neutrophil elastase protein expression, or amounts of active neutrophil elastase as judged by colorimetric assay. Unlike brain tissue, there appears to be strong expression of SLPI within wild-type lung homogenate, and a faint contaminating band within SLPI null animals.

Figure 4.4.3 A: Western blot of normalised frontal brain homogenate, 20 month old male mice, probed with neutrophil elastase. B: Replicate of the above blot, probed with SLPI. C: Actin Loading control of the two above blots. D: Neutrophil elastase activity assay of frontal brain homogenate. P a g e | 73

4.5: Blood serum analysis reveals no evidence of excessive progranulin cleave in SLPI null mice.

Figure 4.5.1 shows progranulin ELISA data obtained from blood serum of male mice, at the 3 assessed time points (6, 12 and 20 months), N=7 per age per genotype. No significant differences between genotypes were observed at any age using multiple, two-tailed T-test with Bonferroni correction for multiple comparisons. Data appeared to indicate an age dependent increase in progranulin, figure 4.5.2 shows a linear regression analysis of male, progranulin blood serum concentration as a function of age, increasing from 134/128 ng/ml (wild-type/SLPI null) at 6 months of age to 218/110 at 20 months of age, an average increase of ~60%.

Figure 4.5.1: Progranulin concentration of blood plasma of male mice, adjusted to ng/ml. Wild-type and SLPI null at 6, 12 and 20 months of age; n=7, error bars indicate standard deviation.

Figure 4.5.2: Regression analysis of progranulin ELISA from male mice, blood plasma adjusted to ng/ml. Both wild-type and SLPI null mice showed a significant age dependent increase; wild-type: R-squared of 0.232, P=0.027; SLPI null R-Squared of 0.272 and P= 0.0153. P a g e | 74

Figure 4.5.3 shows the progranulin ELISA data obtained from the blood serum of female mice, at the 3 assessed time points (6, 12 and 20 months), N=7 per age per genotype. No significant differences between genotypes were observed at any age using multiple, two-tailed T-test with Bonferroni correction for multiple comparisons. While the data appeared to indicate an age dependent increase in progranulin; linear regression of female progranulin blood serum concentration versus age failed to show a linear correlation (See figure 4.5.4). However, when both genotypes are aggregated together (see figure 3.5.5), both sexes show a significant age dependent increase in progranulin concentration, males: R-squared of 0.140, P=0.015; females: R-Squared of 0.125 and P= 0.022, elevation and intercept values were also found to be significantly different from one another (indicating significantly increased progranulin concentration in female mice), p<0.001; however, the elevation of the slopes was found to be statistically indistinguishable between male and female mice, indicating no heightening of the age dependent progranulin increase effect in either sex.

Figure 4.5.3:progranulin concentration of blood plasma of female mice. Wild-type and SLPI null at 6, 12 and 20 months of age; N=7, error bars indicate standard deviation.

Figure 4.5.4: Regression analysis of progranulin ELISA from female mice, blood plasma. Wild-type: R- squared of 0.114, P=0.135; SLPI null R-Squared of 0.152 and P= 0.081 P a g e | 75

Figure 4.5.5: Regression analysis of progranulin ELISA from grouped (wild-type and SLPI null) male and female mice, blood plasma. Both sexes show a significant age dependent increase in progranulin concentration, males: R-squared of 0.140, P=0.015; females: R-Squared of 0.125 and P= 0.022.

Figure 4.5.6 shows the resulting western blots of progranulin probed, immunoglobulin depleted blood plasma. As with brain and lung homogenate, no reduction of the mature (~80 kDa) progranulin form can be observed within SLPI null blood plasma, nor can any evidence of excessive granulin cleavage products. In keeping with progranulin ELISA data, there is a large amount of variability between samples, and some small variability in banding intensities. Figure 4.5.7 shows the presence of SLPI within the blood serum of a wild-type animal, in comparison to its absence in SLPI null blood plasma. Panel B displays the presence of neutrophil elastase within blood plasma (indicated by the banding at ~29kDa); however, panel C indicates a total lack of any neutrophil elastase activity within either SLPI null or wild-type blood plasma.

Figures 4.5.6, A: Western blot of immunoglobulin depleted blood serum from male mice, aged 20 months. Elution 1 fraction, probed with progranulin. B: Western blot of immunoglobulin depleted blood serum from female mice, aged 20 months. Elution 1 fraction, probed with progranulin. Arrows indicate mature progranulin. P a g e | 76

Figure 4.5.7, A: Western blot of murine blood plasma, probed with SLPI B: Western blot of murine blood plasma probed with neutrophil elastase antibody. C: Neutrophil elastase activity assay of blood plasma showing no activity for wild-type or SLPI null mice after 240 minutes. Arrows indicate mature SLPI and Elastase.

4.6: SLPI protects progranulin from cleavage and SLPI null primary neurones show altered LPS response.

Figure 4.6.1 displays the protective effect SLPI exerts over progranulin. Conditioned media from T98G immortalized cells transfected with either SLPI targeting siRNA or non-specific control siRNA, was taken and treated with active neutrophil elastase. Progranulin appears far more susceptible to elastase activity in the absence of SLPI (SLPI siRNA treated samples), after 10 minutes of elastase digestion SLPI protects the majority of progranulin (Compared to the T=0 time point); whereas progranulin is nearly completely depleted in the SLPI absent sample. By 20 minutes progranulin appears depleted by roughly 50% in the presence of SLPI, whereas it is almost completely depleted in the absence of SLPI.

Figure 4.6.1 A: Western blot of conditioned T98G cell line media probed with progranulin antibody. Cells were treated with All-star control siRNA or SLPI siRNA for 48 hours before media extracted and digested with recombinant neutrophil elastase for 0, 10, 20 or 30 minutes at 37°C. B: Replicate of the above blot, probed with SLPI. Arrows indicate mature progranulin and mature SLPI. P a g e | 77

Figure 4.6.2 shows the successful activation of (recombinant) pro-neutrophil elastase by (recombinant) DPPI. After 5 minutes, enough neutrophil elastase is activated to completely digest the full length (~80kDa) progranulin and increase the intensity of smaller bands (~40 kDa, ~27kDa and ~24 kDa) in keeping with progranulin cleavage products. Neither DPPI nor Pro-Neutrophil elastase appears capable of digesting progranulin alone. Figure 4.6.3, panel A shows the effect on secreted progranulin of DPPI treatment of various cell types which have been transfected with a neutrophil elastase expression plasmid. Hela, H4, SH- SH5Y and T98G cells appear incapable of expressing functional elastase, however, HEK cells appear to secrete functional neutrophil elastase. Panel B shows DPPI treatment of control cell lines, which were transfected with a control plasmid. These cell lines show no evidence of elastase activation from endogenously expressed neutrophil elastase.

Figure 4.6.2 Western blot of conditioned T98G cell line media probed with progranulin antibody. Media was extracted from cells and digested with recombinant, pro-neutrophil elastase (alone), recombinant DPPI (alone) or pro-neutrophil elastase and DPPI. Media was digested for 0, 5 or 10 minutes at 37°C. Arrows indicate mature progranulin.

Figures 4.6.3, A: Western blot of conditioned media from various cell types, probed with progranulin. Cells were transfected with a neutrophil elastase expression plasmid, the media removed after 48 hours and DPPI added for 0, 1.5 or 3 hours at 37°C. B Control treatments: Cells were transfected with a control plasmid, the media removed after 48 hours and DPPI added for 0, or 3 hours at 37°C. Arrows indicate mature progranulin. P a g e | 78

Figures 4.6.3 displays the progranulin response to LPS treatment within murine primary neurones at 12 and 24 hours post treatment. The titration of increasing LPS appears to mediate a roughly dose dependent response, the 500ng treatment inducing the strongest responses for both genotypes. The SLPI null primary cultures instigate largely increased progranulin expression in response to LPS as compared to wild-type derived neurones at both time points and all LPS titrations. Figures 4.6.4 and 4.6.5 shows ELISA data obtained from the conditioned media of the same LPS treatment. At both assessed time points and at all LPS titrations, progranulin secretion is significantly higher in SLPI null neurones, baring the 25ng treatment at 12 hours, which fell below the significance threshold. On average, progranulin response was found to be 1.56 fold higher within the 12 hour post-treatment group and 1.65 fold higher in the 24 hours post treatment group.

Figures 4.4.3: Western blot of extracted lysate, Wild-type and SLPI knockout murine neuronal primary cells at D14; probed with progranulin. Primary neurones were incubated with LPS at 25, 100 or 500ng’s for 12 hours (A), and 24 hours (B) post treatment. C and D: Actin loading controls of the above blots. Arrows indicate mature progranulin.

Figure 4.6.4: Progranulin ELISA of media, wild-type and SLPI knockout murine neuronal primary cells at D14. Primary neurones were incubated with LPS at 25, 100 or 500ng’s for 12 hours before media was extracted. P<0.001 using an unpaired, student t-test, error bars indicate standard deviation. P a g e | 79

Figure 4.6.5: Progranulin ELISA of media, Wild-type and SLPI knockout murine neuronal primary cells at D14. Primary neurones were incubated with LPS at 25, 100 or 500ng’s for 24 hours before media was extracted. P<0.001 using an unpaired, student t-test, error bars indicate standard deviation.

Figure 4.6.6 shows the assessment of neutrophil elastase activity within the conditioned media of SLPI null and wild-type primary neurones treated with LPS (500 ng/ml), 24 hours post transfection. Both genotypes display no observable neutrophil elastase activity. This lack of active neutrophil elastase was observed in 12 hours post-transfection, 500ng LPS.

Figure 4.6.6: Colorimetric assay for neutrophil elastase activity within media of wild-type and SLPI knockout murine neuronal primary cells at D14. Shown is data from 24 hours post transfection treated with 500ng LPS.

4.7: Discussion:

No reduction in mature progranulin or excessive cleavage products could be observed within SLPI null brains. This occurs even when SLPI and active neutrophil elastase are both present, as can be observed by western blot and colorimetric assay. This illustrates that SLPI’s role within tonic neurological progranulin regulation appears negligible, even within 20 month old aged brains where some overall naturally accrued age related damage may have occurred. P a g e | 80

This lack of SLPI’s protective effect over progranulin in the brain may be due to up regulation of other protease inhibitors to compensate for SLPI’s absence or spatial separation of active neutrophil elastase from available progranulin/SLPI under tonic situations. It should also be noted that the SLPI primary antibody concentration needed to label SLPI within the brain was extremely high (1:250) coupled with long exposure times, implying that SLPI content was extremely low within the brain. Unfortunately, no currently available antibodies preferentially recognise active neutrophil elastase over its inactive proenzyme form which contains an additional two N-terminal residues: serine and glutamine (Okano et al., 1990), which are cleaved and removed by DPPI (Adkison et al., 2001) making assessment of active neutrophil elastase localisation difficult to determine.

Within lung homogenate (as with brain homogenate) no preferential progranulin reduction could be observed within SLPI null derived samples. Unlike brain homogenate which displayed a distinct banding pattern within progranulin probed western blot; lung homogenate displayed a diffuse, smeared band that makes accurate determination of differences within progranulin glycoforms or cleavage products impossible. Despite this lack of a defined single band, it is clear that there is a large amount of variation between different lung samples, in addition to no obvious reduction in overall progranulin within SLPI null samples. This blurring and large variability within band intensity between samples may be an artefact of the perfusion technique employed in which saline was administered into the left ventricle and drained via the right atrium, although some perfusion of the lungs does occur with this methodology; it is at lower pressure and not as controlled as tissue from the rest of the peripheral vasculature.

Unlike in brain tissue where SLPI expression was incredibly low, strong SLPI and progranulin expression was observed within lung tissue. Despite this strong expression of both of these interacting components, the absence of SLPI appears to have a negligible impact upon progranulin cleavage. As with brain samples, neutrophil elastase activity was also confirmed via colorimetric assay, implying that SLPI modulation of progranulin cleavage is minimal within a non-inflammatory setting, even in a tissue where excessive quantities of both SLPI and progranulin can be found.

Progranulin content within blood serum appears to follow the same trend as brain and lung homogenate in that no reduction in progranulin content could be observed within SLPI null derived samples (as assessed by both ELISA and western blot) and no evidence of excessive cleavage products could be observed within IgG depleted blood plasma samples that might indicate excessive progranulin cleavage. Unlike lung and brain derived samples, an obvious explanation for the lack of a SLPI protective effect can be attributed to a total lack of active neutrophil elastase as determined by colorimetric assay, despite the presence of some of the P a g e | 81 proform as assessed by western blot. This implies that any modulatory role that SLPI might play over progranulin, there is a prerequisite that neutrophil elastase is first activated by cathepsin C (DPPI).

Progranulin blood serum ELISA’s revealed a large difference between males and females with males displaying mean progranulin blood serum content of 134ng/ml-216 ng/ml compared to females 412-571 ng/ml. This compares well to values of progranulin concentration within blood serum taken from humans, which are reported as a range between 100-500 ng/ml, with an average around 250ng/ml. No age or sex related colorations are generally observed within datasets of human progranulin blood plasma concentration (Carecchio et al., 2009); however, there is some precedent for this effect as female Alzheimer’s disease patients appear to present an age dependent increase in progranulin blood plasma concentration (Piscopo et al., 2013). Though it is possible female specific factors may have inflated the apparent progranulin levels observed in female mice, comparative western blots of male and female IgG depletes samples show a large increase in band intensity around 80 kDa within female samples, consistent with full length progranulin (see supplementary materials). Male mice also displayed an age dependent increase in progranulin blood serum concentration, which was not found within female mice unless both SLPI and Wild-type females were aggregated, indicating insufficient n numbers when divided by genotype.

Though it was difficult to find evidence of SLPI’s role within tonic progranulin regulation, a strong protective effect could be observed within an in vitro environment where active neutrophil elastase was exogenously administered. Treatment with 50ng/ml active neutrophil elastase, tonic SLPI secretion levels of T98G cells appear to protect progranulin at 10, 20 and 30 minutes. To confirm the role of cathespsin C within progranulin regulation, pro-neutrophil elastase was activated by 200ng/ml of cathepsin C, the resulting progranulin cleavage could be observed almost immediately (5 minutes following transfection). Interestingly, in a mirroring set of experiments where over-expression of neutrophil elastase (the entire human mRNA construct) was followed by activation using the same quantity of cathepsin C, only one cell line used (HEK cells) appeared capable of expressing neutrophil elastase that was functional: capable of both cathepsin C activation and progranulin cleavage.

The perception of progranulin regulation within the FTLD field has been strongly influenced by the work of Zhu, Ashcroft and others. By utilising a wound healing paradigm within SLPI null mice these studies identified an area in which SLPI has a large impact upon progranulin regulation: counteracting elastase activity and protecting progranulin from degradation (Zhu et al., 2002 and Ashcroft et al., 2000). While neuroinflammation is a component of FTLD, it is a mistake to confuse persistent, chronic neurological inflammation with that of acute wound P a g e | 82 healing. As such SLPI’s role within tonic progranulin regulation is largely overlooked area and is needed to give a more nuanced view of progranulin modulation.

The lack of any reduction in mature progranulin within the brain, lung or blood serum of SLPI null mice implies that SLPI’s role in FTLD relevant progranulin regulation may be less important than previously thought. It is conceivable that protease inhibitors such as SLPI may be important regulators of progranulin concentration within the later stages of neurodegeneration where neuroinflammation is widespread and proteases are activated, but in the course of patients’ lives leading up to disease onset and in early disease progression it appears unlikely that SLPI plays a critical role.

The major convergence point between neurodegeneration and neuroinflammation are microglia. These are the key mediators of both acute and chronic long term inflammation, where the latter has been shown to lead to neuronal cell death (Frank-cannon et al., 2009). Activation of microglia appears an integral step in neurodegeneration within the FTLD/ALS spectrum, with widespread glial activation being observed in FTLD (Schofeld et al., 2002) while glial activation can be observed prior to symptom onset within mSOD1 ALS mice (Henkel et al., 2006). This chronic glial activation (which can lead to down-stream neuronal cell death) is an area where SLPI may potentially play a critical role, via its involvement with TNF regulation and its ability to inhibit macrophage activation by LPS in a non-protease inhibitory manner (Yang et al., 2005).

Within neuronal primary cultures, both wild-type and SLPI null genotypes displayed elevated progranulin secretion upon LPS challenge at both 12 and 24 hours post transfection. This was observed in both the media and within progranulin probed lysate. This effect is unusual as existing studies point to progranulin secretion being inhibited upon LPS challenge. Suh and co- workers report a ~50% reduction in progranulin secretion from microglia upon LPS challenge (Suh et al., 2012), implying differences within brain derived cells. Outside of the CNS, progranulin stimulation upon LPS challenge has been reported within lung endothelium, with a large increase in progranulin secretion into the bronchoalveolar lavage fluid being reported 24h post LPS challenge (Guo et al., 2012).

One potential explanation for this difference between neuronal cell types lies in the relative abundance of progranulin expression. Martens and colleagues show that microglial expression of progranulin mRNA is around 10 times higher than that displayed in neurones (Martens et al., 2012). Given the relative abundances of progranulin expression, the up-regulation of progranulin expression upon LPS challenge within neurones (increasing from 1-2ng’s/ml to anywhere up to 6ng/ml) would be cancelled out by a relative drop in microglial expression P a g e | 83 which is reported as a drop from 30ng/ml to around 10ng/ml. This altered response within neurones indicates different progranulin signalling responses to TLR ligands within neurones as opposed to microglia.

Within this primary neuronal model, SLPI null primary neurones appear to display an increased progranulin response to LPS, compared to wild-type controls. This outcome is surprising given the deficit in wound healing that has been reported in SLPI null mice which can be restored by exogenously applied progranulin (Zhu et al., 2002), implying a reduction in progranulin at the inflammatory wound site in the absence of SLPI. This finding can be partially explained by the lack of any observable neutrophil elastase within LPS treated media (from both wild-type and SLPI null neurones), implying that SLPI’s protective role is redundant within this paradigm and so the two finding may not be contradictory. This finding does however illustrate that progranulin inflammatory signalling is modified by SLPI in a non-enzymatic manner. This effect is somewhat in agreement with findings by Vroling and co-workers, who found that SLPI is able to diminish LPS activity by interfering with the transfer of LPS to CD14 in addition to SLPI’s inhibition of the NF- κB signalling pathway (Vroling et al., 2011). This would imply that in the absence of SLPI the LPS response would be elevated and show an increased inflammatory response with respect to progranulin production. Alternatively, it is possible that SLPI binding to progranulin modifies progranulin/receptor interactions (TNFR, sortillin or a currently unknown progranulin binding receptor) interfering with progranulin feed-back mechanisms within an inflammatory setting.

P a g e | 84

Chapter 5: Pathological examination of

SLPI null brains for hallmarks of FTLD.

P a g e | 85

5.1: Introduction

For assessment of FTLD relevant pathology, or pathology associated with progranulin dysfunction, brain sections from SLPI null and wild-type mice were compared for any apparent histological differences within: glial fibrillary acidic protein (GFAP), TDP-43, ubiquitin, FUS and tau staining. FTLD patients with progranulin haploinsufficiency display a characteristic “Type A” pathological profile showing TDP-43 positive inclusion bodies: short dystrophic neurites and crescentic or oval neuronal cytoplasmic inclusions within neocortical layer 2 (Mackenzie et al., 2011) in addition to ubiquitinated lentiform NII’s within the neocortex and striatum (Mackenzie et al., 2006). Supportingly, GRN null mice also show mild TDP-43 dysfunction with increased cytoplasmic accumulation of TDP-43 in the hippocampus and thalamus (Yin et al., 2010). Type A inclusion bodies within FTLD are also immuno-positive for ubiquitin, a cellular tagging protein that has a variety of signalling roles but can target a cellular body for degradation (Kimura and Tanaka 2010). As such, assessment of ubiquitin staining within immunohistochemistry is widely used as a marker for aberrant protein aggregation that is relevant to FTLD (Mackenzie et al., 2011). Astrocytes are a useful, general marker for assessing any potential neurological damage. In response to CNS damage, astrocytes change from a quiescent state into a reactive state. In a process that is known as reactive gliosis, astrocytes undergo a morphological change and increase expression of GFAP (Middeldorp and Hol 2011). In addition to general CNS damage, GFAP also appears to increase in response to TDP-43 dysfunction (Herman et al., 2012) and increased GFAP staining is observed within GRN null mice from 12 months of age (Yin et al., 2010). Any increase in GFAP staining or astrocyte morphology within SLPI null mice would be a strong indication of progranulin dysfunction and neurodegeneration. While not primarily associated with GRN mutations, aggregation of FUS protein is associated with FTLD and ALS (Uurwin H et al., 2010). FUS pathology is dependent on a number of mutations within the FUS gene (Uurwin et al., 2010), however, FUS and TDP-43 do appear to have similar roles within mRNA binding and regulation (Colombrita C et al., 2012). While FUS dysfunction would be an unlikely marker for progranulin dysfunction, it localisation and potential inclusion within aggregate bodies was assessed in the event of any non-direct interaction that might have occurred. Mutations within the tau encoding, MAPT gene account for a large proportion of FTLD cases (Hutton, M et al., 1998). Although tau dysfunction is considered distinct from TDP-43 proteinopathies or as a response to altered progranulin signalling (Warren et al., 2010), its relative abundance and localisational state was also assessed in the event of any non-direct pathology. P a g e | 86

5.2: Methods

Sample processing and microscopy. Brains from 20 month old wild-type or SLPI null brains were post fixed for 2 days in PFA and then set in wax as according to the protocol outlined in section 2.11. Histological sections were cut using a wax microtome (Leica, German) to 3.5µm and floated onto microscope slides (Thermo scientific, Hemel Hempstead, UK). Epitope unmasking was achieved using a 10 minute, near boiling citric acid treatment and sections were blocked at 4°C overnight. Primary antibodies were incubated for 1 hour at room temperature using the antibodies and concentrations outlined in section 2.12, secondary antibody incubation were achieved at room temperature for 30 minutes.

5.3: Results Within both genotypes, GFAP staining of hippocampal sections reveals cellular bodies that appear to have the correct morphology for astrocytes: a distinctive cell body and a number of jagged cellular process that extend outwards (indicated by a white arrows, figure 5.3.1). The number of astrocytes, their localisation and overall morphology appears to be the same in both SLPI null and wild-type brain samples, indicating no increase in astrocyte activation within the hippocampus of SLPI null animals. Similarly, GFAP staining of frontal cortical sections reveals cell types conforming to astrocytes morphology; however these are less numerous than those observed in the hippocampal sections (marked with white arrows in figure 5.3.2). No overt differences in density, localisation or morphology of astrocytes can be observed between wild-type and SLPI null genotypes.

Figure 5.3.1: Hippocampal sections stained with glial fibrillary acid Protein (GFAP). Cell types corresponding to astrocyte morphology can be observed (marked with arrow). Top rows show wild- type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification. P a g e | 87

Figure 5.3.2: Cerebral cortical area sections stained with glial fibrillary acid protein (GFAP). Cell types corresponding to astrocyte morphology can be observed (marked with arrow). Top rows show wild- type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification.

Staining of hippocampal sections with TDP-43 appears to show predominantly nuclear localisation for both genotypes, as would be expected from normal TDP-43 function (Figure 5.3.4). Critically, no inclusion bodies or aggregate depositions can be observed in either SLPI null or wild-type animals implying no acute FTLD-TDP pathology as a result of SLPI’s absence. More generally, localisation of TDP-43, its general staining pattern and intensity appears equal in SLPI null and wild-type animals.

Frontal cortical sections stained with TDP-43 also show a predominantly nuclear localisation with both genotypes being indistinguishable from one another in staining pattern and intensity (Figure 5.3.5). As with hippocampal sections, no inclusion bodies or large aggregate depositions can be observed in either genotype.

Figure 5.3.3: Hippocampal sections stained with TDP-43. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification. P a g e | 88

Figure 5.3.4: Cerebral cortical area sections stained with TDP-43. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification.

Staining of hippocampal sections with ubiquitin appears typical, showing a dark staining pattern localised to the nucleus and diffusely within the cytoplasm (Figure 5.4.5). As with TDP-43 staining, no apparent aggregate species or inclusion bodies can be observed in either genotype. More generally, the overall pattern of staining and intensity appears broadly similar in SLPI null and Wild- type sections, implying no abnormal ubiquitination within the SLPI null genotype. Fontal cortical sections stained with ubiquitin also appeared typical, in that staining was nuclear in addition to diffuse cytoplasmic localisation (Figure 5.4.6). As with the hippocampal sections, no obvious aggregate bodies can be observed in either of the genotypes and their staining patterns appear indistinguishable.

Figure 5.3.5: Hippocampal sections stained with ubiquitin. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification. P a g e | 89

Figure 5.3.6: Cerebral cortical area sections stained with ubiquitin. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification.

When probing hippocampal sections with FUS, staining appears predominantly nuclear, with some cytoplasmic deposition (figure 5.3.7). No overt differences can be observed for the presence of aggregates bodies, FUS miss-localisation or increased FUS staining between SLPI null and age matched wild type mice. Similarly, cortical sections stained with FUS appeared to show predominantly nuclear localisation, with both genotypes being broadly the same in staining intensity and pattern (figure 5.3.8).

When staining with Tau, diffuse cytoplasmic staining was observed within both hippocampal (figure 5.3.9) and cortical regions (figure 5.3.10). No aggregate bodies or unusual deposition of Tau can be observed in either genotype, and overall staining appears indistinguishable between genotypes.

Figure 5.3.7: Hippocampal sections stained with FUS. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification. P a g e | 90

Figure 5.3.8: Cerebral cortical area sections stained with FUS. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification.

Figure 5.3.9: Hippocampal sections stained with microtubule binding protein, tau. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification. P a g e | 91

Figure 5.3.10: Cerebral cortical area sections stained with microtubule binding protein, tau. Top rows show wild-type, bottom showing SLPI null. Panels arranged left to right: 10x, 20x and 40x magnification.

5.4: Discussion

The lack of any increased GFAP staining within SLPI null cortical and hippocampal regions differs from the phenotype observed in GRN null mice; which display increased GFAP staining, owing to widespread astrocyte activation (Yin et al., 2010 and Ahmed et al., 2010). In addition to the lack of a progranulin dysfunction phenotype, the SLPI null mice also do not appear to have accrued any excessive neurological damage over and above wild-type control animals, even at 20 months of age. This is surprising given the inhibited wound healing phenotype displayed by SLPI null animals (Ashcroft et al., 2000) and SLPI’s hypothesised neuroprotective role following neurological damage such as stroke (Wang et al., 2003). This potentially indicates that although SLPI’s role is important within acute wound healing scenarios, it is more redundant in persistent, low damage situations like normal age related neurological damage.

The absence of any TDP-43 miss-localization in SLPI null brain sections (compared to wild-type animals) supports a normal progranulin signalling phenotype. Reports of TDP-43 dysfunction within GRN null mice differ. Ahmed and co-workers found no difference within TDP-43 abundance or cytoplasmic distribution by 22 months of age; whereas Yin and colleagues reported cytoplasmic phospho-TDP accumulation in both the thalamus and hippocampus by 18 months of age (Yin et al., 2010; Ahmed et al., 2010). Despite this difference in opinion, even where TDP-43 dysfunction can be observed, it is relatively mild (no inclusion bodies are observed) and required a total absence of progranulin. P a g e | 92

As a more sensitive measure of FTLD like pathology indicative of progranulin dysfunction, ubiquitin staining can evaluate the overall cellular burden of accrued proteins intended for degradation. Both groups working with GRN null mice (Yin et al., 2010 and Ahbed 2010) agree that a progranulin deficit results in an overall increase in ubiquitin staining within the hippocampus, potentially resulting from an increase in lipofuscin vacuoles. SLPI null mice also failed to display any increase in ubiquitination over wild-type animals, again pointing towards a lack of progranulin dysfunction.

While not thought to be associated with progranulin, FUS and tau staining was performed to evaluate any potential increase in overall protein clearance burden. FUS staining was confined to the nucleus as expected, and showed no cytoplasmic deposition within SLPI null animals that might implicate FTLD like pathology. Similarly, tau staining appeared as expected but revealed no overall difference between genotypes.

While not definitive, the immunohistochemical profile shown in SLPI null mice does indicate a lack of severe progranulin dysfunction; however, mild progranulin signalling deficits cannot be ruled out, nor can a potentially important role for SLPI within acute injury be evaluated in this paradigm. This data does however show that the normal neurological damage that occurs as brains age, appears to illicit the same response in SLPI null mice as within wild-type mice, and that the animals do not develop any overt FTLD like pathology.

P a g e | 93

Chapter 6: Conclusions

P a g e | 94

Chapter 6: Discussion

Given the lack of an observable reduction in progranulin protein, the absence of any of the hallmarks of FTLD pathology (TDP-43, tau and FUS miss-localisation) within SLPI null mice is unsurprising, given that these effects are thought to be a result of diminished progranulin signalling. Findings differ upon the exact severity of TDP-43 effects within GRN null mice, however, even taking the most extreme reported pathology,TDP-43 phosphorylation, GFAP activation and increased lipofuscin deposition; illustrates that mice are incredibly resilient to the loss of progranulin (Yin et al,. 2010, Ahmed et al., 2010). These species differences may arise from a lack of progranulin dependency within murine neuronal populations or an artefact caused the much shorter life spans of mice thus giving less time for a progranulin deficit to affect TDP-43 aggregation. With this resilience in mind, the total absence of any FTLD hallmarks within a SLPI deficit model is entirely consistent with GRN null mice findings. By assessing mature progranulin levels in conjunction with elastase activity assays, using various tissues types of SLPI null mice, it is clear that SLPI does not profoundly affect progranulin regulation under tonic physiological conditions. This suggests that SLPI’s role in progranulin regulation is dependent upon active neutrophil elastase that is co-localised with progranulin and SLPI, however, under tonic physiological conditions, either elastase inactivity or its compartmentalisation negates SLPI’s involvement. Conversely, within acute inflammatory response such as wound healing, SLPI does appear to play a vital role in progranulin regulation by protecting it from abundant, bio-available and enzymatically active proteinases like neutrophil elastase.

In spite of a lack of a reduction in progranulin protein levels in SLPI null mice; behavioural evaluation still proved underwhelming with respect to an overt neurologically relevant and measurable phenotype. This is surprising given SLPI’s role within NF-kB and its ability to inhibit a wide array of extracellular proteinases. Work by Ashcroft and colleges illustrates that within a wound healing assay, SLPI null mice display wounding recovery rates (by area) of roughly 20% that which can be observed in wild-type control animals, from Day 3 – Day 14 post wounding (Ashcroft et al., 2000). Not surprisingly, SLPI null mice within this study also appeared more susceptible ill health and far more SLPI null mice had to be euthanized due to animal welfare considerations than heterozygous breeding stock or wild-type animals. Given these affects which stem from attenuated inflammatory control, the lack of measurable neurological damage that was accrued through age related damage to the brain has a number of potential implications.

P a g e | 95

Many biological systems incorporate redundancy within their architecture, the inflammatory response’s utilisation of multiple cytokines with overlapping function is often denoted as the archetypal example of parallel biological pathways which build redundancy into a system. Given the overlap of function with other proteinase inhibitors: elafin, alpha-1 protease inhibitor and alpha-macroglobin (Korkmaz et al., 2010), it is possible that elevated tonic enzymatic activity was kept in check via these other inhibitory proteins. However, within an inflammatory situation (such as the wounding assays employed by Ashcorft and Zhu) enzymatic activity exceeds the extent of this anti-protease overlap, and the absence of SLPI manifests as a severe phenotype. In a similar manner, SLPI’s role within NF-kB signalling which may contribute the wound healing deficit within SLPI null animals is also potentially a redundant aspect of the NF-kB pathway under a non-stressed state. As with inflammatory signalling the NF-kB pathway is a highly interconnected and tightly controlled network and it is feasible that the loss of SLPIs function can be substituted for by that of other proteins. Further evidence of this redundancy within SLPI’s function at tonic levels is evidenced by the lack of any additional glial activation, which would have been indicated by an increase in GFAP staining within SLPI null brains. Repression of NF-kB protein activity leads to a marked reduction in GFAP activation (Bae et al., 2006), however, the absence of SLPI’s NF-kB repressing ability appears not to manifest as increased GFAP staining within this paradigm. In an additional level of regulation, elastase localisation and activation represents a key process whereby progranulin processing is controlled; irrespective of SLPI. Evaluation of blood serum within this study illustrates that tonic activity of elastase in blood serum is negligible; despite measurable quantities of elastase being present. This implies that activation of elastase is a critical event within progranulin signalling and as a result, activity of DPPI (cathepsin C) may be an overlooked facet of FTLD pathology. Furthermore, proteomic analysis of the CNS reveals DPPI protein expression in cortical endothelial and neuronal cells; however not within glial cell types (Uhlen et al., 2005).This localisation within FTLD relevant areas and cell types implies that inflammation instigated by neurodegeneration could very likely further exacerbate progranulin haploinsufficiency by activation of elastase and DPPI.

Localisation also appears to be incredibly important aspect of elastase control. Both lung and brain homogenates reveal the presence of active elastase as assessed by colorimetric assay; however, showed no excessive progranulin processing in SLPI null animals. These regulatory elements of neutrophil elastase function (activation by DPPI and localisation/secretion) represent an under-appreciated facet of progranulin regulation within FTLD and a pre-requisite of SLPI involvement. P a g e | 96

Treatment of SLPI null cultured primary neurones with LPS elicited interesting findings which may be pertinent to the FTLD field. Diverging from observations made within microglial and astrocyte cultures (Suh et al,. 2012), neuronal cultures appear to increase progranulin production in response to LPS and not diminish it. This illustrates that neuronal LPS triggered progranulin response is more akin to findings made within lung epithelium than to other CNS cell populations (Guo et al., 2012). Owing to these differences within TLR ligand response with respect to progranulin, it is possible that neuronal signalling illicit other differences (compared to macroglial/astrocyte cultures) within a granulin haploinsufficent individual. This study also illustrates that SLPIs regulatory role over progranulin is more complex than its anti-proteinase effect alone, with the observation that LPS challenged neurones elicited a heightened progranulin up-regulation. There is president for this effect within both monocytes (taggart 2002) and bone marrow derived macrophages (Vroling et al., 2012) which show a heightened response to LPS challenge. However, these studies did not investigate progranulin response, instead focusing on NF-kB pathway intermediates. Given these findings (and those made within lung epithelium), it raises the possibility that progranulin expression may be up- regulated at a wound site of SLPI null animals, however, this increase would be completely abolished by excessive elastase activity, explaining the recovered deficit upon exogenous progranulin treatment. To test this hypothesis, analysis of progranulin transcription would have to be assessed at the wound site of a SLPI null animal or epithelial culture.

One as yet unanswered question pertaining to SLPI regulation of progranulin signalling is if its interaction to inter-granulin regions (Zhu et al., 2002) interferes with progranulin/receptor interactions. Finding by Zang et al. suggest that progranulin binds sortilin receptor via its c- terminal region making SLPIs interference unlikely (Zang et al., 2011). However, it is possible that SLPI binding to progranulin may inhibit its antagonistic effects on TNFR (tang et al., 2011) or alter progranulin’s ability to form homodimer (Ngyuyen et al., 2013), a property which also remains unstudied with respect to receptor binding.

Finally, findings by Gass and co-workers illustrate that individual granulins may account for a large proportion of progranulin signalling as a strong correlation can be observed between neuronal outgrowth and granulin treatment (Gass et al., 2012). This may represent a relatively unexplored signalling pathway whereby progranulin haploinsufficiency within FTLD may be instigating TDP-43 dysfunction via loss of granulin function and not the intact protein, or some combinatory effect of the two. Given the potential importance of granulins within FTLD, progranulin processing may represent central feature of pathology. This would suggest that elastase (Zhu et al., 2002), proteinase-3 (Kessenbrok et al., 2008) and MMP-12 (Suh et al., 2012) are important actors within FTLD. This study shows that inhibitors of these enzymes such as P a g e | 97

SLPI, play an important role within progranulin signalling, however; enzyme activation is an area that is often overlooked within experimental models. Studies within SLPI null mice show that activation of these progranulin processing enzymes is tightly regulated and is an area that requires further study.

Future experiments.

 SLPI’s interaction with progranulin raises the possibility that it may modulate the binding of progranulin to other proteins. SLPI could conceivably inhibit progranulin homodimerization or progranulins interaction with receptor proteins. Indeed, it is possible the progranulin homodimer may bind to different receptors types or exhibit altered pharmacokinetic properties than the monomeric form. To test this, Co- Immunoprecipitation studies could be carried out between progranulin and its likely integration partners, combined with a titration of SLPI.

 Tests on SLPI null primary neurones treated with LPS suggest that progranulin expression may be up regulated within wounding assays on SLPI null mice, compared to Wild-type animals. The increase in progranulin production would however, be cancelled out due to excessive elastase activity. To test this hypothesis, mRNA analysis of tissue taken from murine cutaneous wounding assays (SLPI null vs. Wild-type) could be used to evaluate relative progranulin expression. A similar scenario could also be explored using epidermal and neuronal primary cultures, which would then undergo a scratch assay.

 SLPI null mice appear to show an elevated response to acute inflammation such as cutaneous wounding or LPS response. Utilising the neuronal primary culture used in this study, in addition to mixed glial and astrocyte preparations, the role of SLPI in neuroinflammation could be further studied. Treatment with a variety of inflammatory mediators such as IL-1beta, TNF-alpha, IL-8 or INF-Υ upon wild type and SLPI null primary cultures would help further elucidate SLPI’s role. To assess the effects of different treatments, multiplex cytokine arrays could be utilised, in addition to progranulin ELISA’s and cell death assays such as MTT or LDH.

 Proteinase activity remains an understudied aspect of neurodegenerative disease. While some level of expression can be viewed within post-mortem brain samples (combined with ELISA, Western blot and Immunohistochemistry), using colorimetric assays for neutrophil Neutrophil elastase, Proteinase-3 and MMP-9 activity would reveal the factors which might affect progranulin stability in FTLD patients. Owing to protein P a g e | 98

instability, these measurements would have to be taken from blood plasma and/or cerebrospinal fluid of FTLD patients with GRN mutation.

 The protease inhibitors: elafin, alpha-1 protease inhibitor and alpha-macroglobin all have overlapping regulatory functions with SLPI with respect to protecting signalling proteins during inflammation. It is conceivable that there are feedback mechanisms between SLPI and these other protease inhibitors which could be investigated with knock-down and over-expression. Similarly, it may be useful to ascertain there relative expression levels within the above two experiments.

P a g e | 99

Chapter 7: References

P a g e | 100

Amador-Ortiz C, Lin WL, Ahmed Z, Personett D, Davies P, Duara R, Graff-Radford NR., Hutton ML and Dickson DW. TDP-43 immunoreactivity in hippocampal sclerosis and Alzheimer’s disease. Ann. Neurol. 2007. 61; 435–445.

Arai T, Hasegawa M, Akiyama H, Ikeda K, Nonaka T, Mori H, Mann D, Tsuchiya K, Yoshida M, Hashizume Y and Oda T. TDP-43 is a component of ubiquitin-positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Biochem Biophys Res Commun. 2006 Dec. 351(3):602-11.

Arai T, Mackenzie IR, Hasegawa M, Nonoka T, Niizato K, Tsuchiya K, Iritani S, Onaya M and Akiyama H. Phosphorylated TDP-43 in Alzheimer's disease and dementia with Lewy bodies. Acta Neuropathol. 2009 Feb. 117(2):125-36.

Ashcroft GS, Lei K, Jin W, Longenecker G, Kulkarni AB, Greenwell-Wild T, Hale-Donze H, McGrady G, Song XY and Wahl SM. Secretory leukocyte protease inhibitor mediates non- redundant functions necessary for normal wound healing. Nat Med. 2000 Oct. (10):1147-53.

(A) Ayala YM, Misteli T and Baralle FE. TDP-43 regulates retinoblastoma protein phosphorylation through the repression of cyclin-dependent kinase 6 expression. Proc Natl Acad Sci USA. 2008 Mar. 105(10):3785-9.

(B) Ayala YM, Zago P, D'Ambrogio A, Xu YF, Petrucelli L, Buratti E and Baralle FE. Structural determinants of the cellular localization and shuttling of TDP-43. J Cell Sci. 2008 Nov. 121 (Pt22):3778-85.

Bae MK, Kim SR, Lee HJ, Wee HJ, Yoo MA, Ock Oh S, Baek SY, Kim BS, Kim JB, Sik-Yoon and Bae SK. Aspirin-induced blockade of NF-kappa B activity restrains up-regulation of glial fibrillary acidic protein in human astroglial cells. Biochim Biophys Acta. 2006 Mar;1763(3):282-9.

Baker M, Mackenzie IR, Pickering-Brown SM, Gass J, Rademakers R, Lindholm C, Snowden J, Adamson J, Sadovnick AD, Rollinson S, Cannon A, Dwosh E, Neary D, Melquist S, Richardson A, Dickson D, Berger Z, Eriksen J, Robinson T, Zehr C, Dickey CA, Crook R, McGowan E, Mann D, Boeve B, Feldman H and Hutton M. Mutations in progranulin cause tau-negative frontotemporal dementia linked to chromosome 17. Nature. 2006 Aug. 442 (7105):916-9.

Bhandari V, Palfree RG and Bateman A. Isolation and sequence of the granulin precursor cDNA from human bone marrow reveals tandem cysteine-rich granulin domains. Proc Natl Acad Sci USA. 1992. 89: 1715-1719.

P a g e | 101

Brain WR and Walton JN: Brain's diseases of the nervous system. Oxford university press; 1969.

Buratti E and Baralle FE. Characterization and functional implications of the RNA binding properties of nuclear factor TDP-43, a novel splicing regulator of CFTR exon 9. J Biol Chem. 2001 Sep. 276(39):36337-43.

Buratti E and Baralle FE. Multiple roles of TDP-43 in gene expression, splicing regulation, and human disease. Front Biosci. 2008 Jan. 13:867-78. Review

Buratti E, and Baralle FE. The molecular links between TDP-43 dysfunction and neurodegeneration. Adv Genet. 2009. 66:1-34. Review.

Borroni B, Alberici A, Grassi M, Turla M, Zanetti O, Bianchetti A, Volta GD, Rozzini R, Gilberti N, Bellelli G and Padovani A. Is Frontotemporal Lobar Degeneration a Rare Disorder? Evidence from a Preliminary Study in Brescia County, Italy. J. of Alzheimer's Dis, 2009 Sep. (1):111-6.

Bose JK, Wang IF, Hung L, Tarn WY and Shen CK. TDP-43 overexpression enhances exon 7 inclusion during the survival of motor neuron pre-mRNA splicing. J. Biol. Chem. 2008 Oct. 283(43):28852-9.

Byrne S, Elamin M, Bede P, Shatunov A, Walsh C, Corr B, Heverin M, Jordan N, Kenna K, Lynch C, McLaughlin RL, Iyer PM, O'Brien C, Phukan J, Wynne B, Bokde AL, Bradley DG, Pender N, Al- Chalabi A and Hardiman O. Cognitive and clinical characteristics of patients with amyotrophic lateral sclerosis carrying a C9orf72 repeat expansion: a population based cohort study. Lancet Neurol. 2012; 11:232 – 40 .

Cairns NJ, Bigio EH, Mackenzie IR, Neumann M, Lee VM, Hatanpaa KJ, White CL, Schneider JA, Grinberg LT, Halliday G, Duyckaerts C, Lowe JS, Holm IE, Tolnay M, Okamoto K, Yokoo H, Murayama S, Woulfe J, Munoz DG, Dickson DW, Ince PG, Trojanowski JQ and Mann DM. Consortium for Frontotemporal Lobar Degeneration. Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: consensus of the Consortium for Frontotemporal Lobar Degeneration. Acta Neuropathol. 2007 Jul. 114(1):5-22.

Cannon A, Fujioka S, Rutherford NJ, Ferman TJ, Broderick DF, Boylan KB, Graff-Radford NR, Uitti RJ, Rademakers R, Wszolek ZK, Dickson DW. Clinicopathologic variability of the GRN A9D mutation, including amyotrophic lateral sclerosis. Neurology. 2013 May 7;80(19):1771-7.

P a g e | 102

Carola V, D’Olimpio F, Brunamonti E, Mangia F, Renzi P. Evaluation of the elevated plus-maze and open-field tests for the assessment of anxiety-related behaviour in inbred mice. Behavioural Brain Research 134 (2002) 49–57

Chang Q and Gold P. Age-related changes in memory and in acetylcholine functions in the hippocampus in the Ts65Dn mouse, a model of Down syndrome. Neurobiol Learn Mem. 2008 February; 89(2): 167–177

Chiang PM, Ling J, Jeong YH, Price DL, Aja SM, Wong PC. Deletion of TDP-43 down-regulates Tbc1d1, a gene linked to obesity, and alters body fat metabolism. Proc Natl Acad Sci USA 2010;107: 16320–16324.

Chen-Plotkin AS , Xiao J, Geser F, Martinez-Lage M, Grossman M, Unger T, Wood EM, Van Deerlin VM, Trojanowski JQ and Lee VM. Brain progranulin expression in GRN-associated frontotemporal lobar degeneration. Acta Neuropathol. 2010 Jan. 119(1):111-22.

Chow TW, Miller BL, Hayashi VN and Geschwind DH. Inheritance of frontotemporal dementia. Arch Neurol. 1999 Jul. 56(7):817-22.

Clauss A, Lilja H and Lundwall A. The evolution of a genetic locus encoding small serine proteinase inhibitors. Biochem Biophys Res Commun. 2005 Jul. 333(2):383-9.

Cleveland DW, Hwo SY and Kirschner MW. Purification of tau, a microtubule-associated protein that induces assembly of microtubules from purified tubulin. J. of Mol Bio. 1977. 16, 207-225.

Cruts M, Kumar-Singh S and Van Broeckhoven C. Progranulin mutations in ubiquitin-positive frontotemporal dementia linked to chromosome 17q21. Curr Alzheimer Res. 2006 Dec. 3(5):485-91.

Dahlgren C and Karlsson A. Respiratory burst in human neutrophils. J Immunol Methods. 1999 Dec. 232(1-2):3-14.

Daniel R, He Z, Carmichael KP, Halper J and Bateman A. Cellular localization of gene expression for progranulin. J Histochem Cytochem. 2000. 48: 999-1009.

Denison FC, Calder AA and Kelly RW. The action of prostaglandin E2 on the human cervix: stimulation of interleukin 8 and inhibition of secretory leukocyte protease inhibitor. Am. J. Obstet. Gynecol. 1999.180, 614–620.

P a g e | 103

Dormann D, Capell A, Carlson AM, Shankaran SS, Rodde R, Neumann M, Kremmer E, Matsuwaki T, Yamanouchi K, Nishihara M and Haass C. Proteolytic processing of TAR DNA binding protein- 43 by caspases produces C-terminal fragments with disease defining properties independent of progranulin. J Neurochem. 2009 Aug. 110(3):1082-94.

Doumas A, Kolokotronis P and Stefanopoulos. Anti-inflammatory and antimicrobial roles of secretory leukocyte protease inhibitor. Infect. Immun. 2005. 73:1271-1274.

Ebneth A, Godemann R, Stamer K, Illenberger S, Trinczek B, Mandelkow E. Overexpression of tau protein inhibits kinesin-dependent trafficking of vesicles, mitochondria, and endoplasmic reticulum: implications for Alzheimer's disease. J Cell Biol. 1998 Nov 2. 143(3):777-94. Eisenberg S P, Hale KK, Heimdal P and Thompson RC. Location of the protease inhibitory region of secretory leukocyte protease inhibitor. J. Biol. Chem. 1990. 265;7976-7981.

Faller B, Frommher K and Bieth JG. Heparin interferes with the inhibition of neutrophil elastase by its physiological inhibitors. Biol. Chem. 1992. 373;503-508.

Finch N, Baker M, Crook R, Swanson K, Kuntz K, Surtees R, Bisceglio G, Rovelet-Lecrux A, Boeve B, Petersen RC, Dickson DW, Younkin S, Deramecourt V, Julia Crook J, Graff-Radford N and Rademakers R. Plasma progranulin levels predict progranulin mutation status in frontotemporal dementia patients and asymptomatic family members . Brain 2009: 132; 583–591

Forman MS, Mackenzie IR, Cairns NJ, Swanson E, Boyer PJ, Drachman DA, Jhaveri BS, Karlawish JH, Pestronk A, Smith TW, Tu PH, Watts GD, Markesbery WR, Smith CD and Kimonis VE. Novel ubiquitin neuropathology in frontotemporal dementia with valosin-containing protein gene mutations. J Neuropathol Exp Neurol. 2006 Jun; 65(6):571-81.

Frank-Cannon TC, Alto LT, McAlpine FE, Tansey MG. Does neuroinflammation fan the flame in neurodegenerative diseases? Mol. Neurodegener. 2009 Nov 16;4:47. doi: 10.1186/1750-1326- 4-47

Fukui K, Sugita M, Kawamura J, Shiota and Nakano I. Primary progressive apraxia in Pick's disease A clinicopathologic study. Neurol. 1996. 47:467-473

Fuortes M, Melchior M, Han H, Lyon G and Nathan C. Role of the tyrosine kinase pyk2/RAFTK in the integrin-dependent activation of human neutrophils by TNF. J. Clin. Invest. 1999. 104:327-35.

Gass J, Cannon A, Mackenzie IR, Boeve B, Baker M, Adamson J, Crook R, Melquist S, Kuntz K, Petersen R, Josephs K, Pickering-Brown SM, Graff-Radford N, Uitti R, Dickson D, Wszolek Z, P a g e | 104

Gonzalez J, Beach TG, Bigio E, Johnson N, Weintraub S, Mesulam M, White CL 3rd, Woodruff B, Caselli R, Hsiung GY, Feldman H, Knopman D, Hutton M and Rademakers R. Mutations in progranulin are a major cause of ubiquitin-positive frontotemporal lobar degeneration. Hum Mol Genet. 2006 Oct. 15(20):2988-3001.

Gillissen A, Birrer P, McElvaney NG, Buhl R, Vogelmeier C, Hoyt RF Jr, Hubbard RC and Crystal RG. Recombinant secretory leukoprotease inhibitor augments glutathione levels in lung epithelial lining fluid. J Appl Physiol 1993. 75:825–832

Gorno-Tempini ML, Brambati SM, Ginex V, Ogar J, Dronkers NF, Marcone A, Perani D, Garibotto V, Cappa SF, Miller BL.The logopenic/phonological variant of primary progressive aphasia. Neurology 2008;71:1227–1234.

Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, Ogar JM, Rohrer JD, Black S, Boeve BF, Manes F, Dronkers NF, Vandenberghe R,Rascovsky K, Patterson K, Miller BL, Knopman DS, Hodges JR, Mesulam MM and Grossman M. Classification of primary progressive aphasia and its variants. Neurology. 2011 Mar; 76(11):1006-14.

Grütter MG, Fendrich G, Huber R and Bode W. The 2.5 A X-ray crystal structure of the acid-stable proteinase inhibitor from human mucous secretions analysed in its complex with bovine alpha- chymotrypsin. EMBO J. 1988 Feb. 7(2):345-51.

Harvey R J, Skelton-Robinson M and Rossor MN. The prevalence and causes of dementia in people under the age of 65 years. J Neurol Neurosurg Psych. 2003. 74:1206–1209

Hasegawa M, Arai T, Nonaka T, Kametani F, Yoshida M, Hashizume Y, Beach TG, Buratti E, Baralle F, Morita M, Nakano I, Oda T, Tsuchiya K and Akiyama H. Phosphorylated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Ann Neurol. 2008 Jul. 64(1):60-70.

He Z and Bateman A. Progranulin (granulin-epithelin precursor, PC-cell-derived growth factor, acrogranin) mediates tissue repair and tumorigenesis. J Mol Med. 2003 Oct. 81(10):600-12.

He Z, Ong CH, Halper J and Bateman A. Progranulin is a mediator of the wound response. Nat Med. 2003 Feb; 9(2):225-9.

Beers DR, Henkel JS, Xiao Q, Zhao W, Wang J, Yen AA, Siklos L, McKercher SR, Appel SH. Wild- type microglia extend survival in PU.1 knockout mice with familial amyotrophic lateral sclerosis. Proc Natl Acad Sci U S A. 2006 Oct 24;103(43):16021-6.

P a g e | 105

Hrabal R, Chen Z, James S, Bennett HP and Ni F. The hairpin stack fold, a novel protein architecture for a new family of protein growth factors. Nat Struct Biol 1996. 3:747-752 .

Hutton M, Lendon P, Rizzu M, Baker S, Froelich H, Houlden SP, Brown S, Chakraverty A, Isaacs A, Grover J, Hackett J, Adamson S, Lincoln D, Dickson P, Davies RC, Petersen M, Stevens E, de Graa E, Wauters, J, van Baren M, Hillebrand M, Joosse JM, Kwon P, Nowotny LK, Che J, Norton JC, Morris LA, Reed JQ, Trojanowski H, Basun L, Lannfelt M, Neystat S, Fahn F, Dark T, Tannenberg PR, Dodd N, Hayward J, Kwok PR, Scho¢eld A, Andreadis J, Snowden D, Craufurd D, Neary F, Owen BA, Oostra J, Hardy A, Goate J, van Swieten, Mann D, Lynch T and Heutink P. Association of missense and 5'-splice-site mutations in tau with the inherited dementia FTDP-17. Nature 1998. 393; 702-05.

Igaz LM, Kwong LK, Xu Y, Truax AC, Uryu K, Neumann M, Clark CM, Elman LB, Miller BL, Grossman M, McCluskey LF, Trojanowski JQ and Lee VM. Enrichment of C-terminal fragments in TAR DNA-binding protein-43 cytoplasmic inclusions in brain but not in spinal cord of frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Am J Pathol. 2008 Jul. 173(1):182-94.

Ikeda M, Ishikawa T and Tanabe H. Epidemiology of Frontotemporal Lobar Degeneration Dementia. Geriatr Cogn Disord. 2004; 17:265–268

Inukai Y, Nonaka T, Arai T, Yoshida M, Hashizume Y, Beach TG, Buratti E, Baralle FE, Akiyama H, Hisanaga S and Hasegawa M. Abnormal phosphorylation of Ser409/410 of TDP-43 in FTLD-U and ALS. FEBS Lett. 2008 Aug 20. 582(19):2899-904.

Irwin D, Lippa CF and Rosso A. Progranulin (PGRN) expression in ALS: an immunohistochemical study. J Neurol. Sci. 2009 Jan 15. 276(1-2):9-13.

Johnson BS, McCaffery JM, Lindquist S, Gitler AD. A yeast TDP-43 proteinopathy model: Exploring the molecular determinants of TDP-43 aggregation and cellular toxicity. Proc Natl Acad Sci USA. 2008 Apr 29.105(17):6439-44.

Johnson JK, Diehl J, Mendez MF, Neuhaus J, Shapira JS, Forman M, Chute DJ, Roberson ED, Pace- Savitsky C, Neumann M, Chow TW, Rosen HJ, Forstl H, Kurz A and Miller BL Frontotemporal lobar degeneration: demographic characteristics of 353 patients. Arch Neurol. 2005 Jun. 62(6):925-30

Kabashi E, Lin L, Tradewell ML, Dion PA, Bercier V, Bourgouin P, Rochefort D, Bel Hadj S, Durham HD, Velde CV, Rouleau GA and Drapeau P. Gain and loss of function of related mutations of TARDBP (TDP-43) cause motor deficits in vivo. Hum Mol Genet. 2010 Feb;19(4):671-83 P a g e | 106

Kikuchi T, Abe T, Hoshi S, Matsubara M, Tominaga Y, Satoh K. and Nukiwa T. Structure of the Murine Secretory Leukoprotease Inhibitor (SLPI) Gene and Chromosomal Localization of the Human and Murine SLPI Genes. Am. J. Respir. Cell Mol. Biol., Dec, 1998. 19(6);875-880

Kim SH, Shi Y, Hanson KA, Williams LM, Sakasai R, Bowler MJ, Tibbetts RS. Potentiation of amyotrophic lateral sclerosis (ALS)-associated TDP-43 aggregation by the proteasome-targeting factor, ubiquilin 1. J Biol Chem. 2009 Mar. 284(12):8083-92.

Kertesz A, McMonagle P, Blair M, Davidson W and Munoz DG. The evolution and pathology of frontotemporal dementia. Brain. 2005 Sep. 128(Pt 9):

Kessenbrock K, Fröhlich L, Sixt M, Lämmermann T, Pfister H, Bateman A, Belaaouaj A, Ring J, Ollert M, Fässler R and Jenne DE. Proteinase 3 and neutrophil elastase enhance inflammation in mice by inactivating antiinflammatory progranulin. J Clin Invest. 2008 Jul. 118(7):2438-47.

Kraemer BC, Schuck T, Wheeler JM, Robinson LC, Trojanowski JQ, Lee VM and Schellenberg GD. Loss of murine TDP- 43 disrupts motor function and plays an essential role in embryogenesis. Acta Neuropathol 2010; 119:409–419.

Krecic AM and Swanson MS. hnRNP complexes: composition, structure, and function. Curr Opin Cell Biol. 1999 Jun. 11(3):363-71. Review.

Kwiatkowski TJ, Bosco DA, Leclerc AL, Tamrazian E, Vanderburg CR, Russ C, Davis A, Gilchrist J, Kasarskis EJ, Munsat T, Valdmanis P, Rouleau GA, Hosler BA, Cortelli P, de Jong PJ, Yoshinaga Y, Haines JL, Pericak-Vance MA, Yan J, Ticozzi N, Siddique T, McKenna-Yasek D, Sapp PC, Horvitz HR, Landers JE and Brown RH. Mutations in the FUS/TLS Gene on Chromosome 16 Cause Familial Amyotrophic Lateral Sclerosis. Science. 2009. 323;1205–1208.

Lagier-Tourenne C and Cleveland DW. Rethinking ALS: the FUS about TDP-43. Cell. 2009 Mar 20. 136(6):1001-4.

Lee SC and Dickson DW. Microglia in HIV-related CNS neuropathology: an update. J Neuro. AIDS. 1996. 1(1):57-83. Review.

Lentsch AB, Jordan JA, Czermak BJ, Diehl KM, Younkin EM, Sarma V and Ward PA. Inhibition of NF-kappaB activation and augmentation of Ikapp-B-beta by secretory leukocyte protease inhibitor during lung inflammation. Am J Pathol. 1999 Jan. 154(1):239-47.

Lokesh C, Wijesekera and P Nigel Leigh. Amyotrophic lateral sclerosis. Orphanet J Rare Dis. 2009 Feb. 3;4:3 P a g e | 107

Mackenzie IR, Baker M, Pickering-Brown S, Hsiung GY, Lindholm C, Dwosh E, Gass J, Cannon A, Rademakers R, Hutton M and Feldman HH. The neuropathology of frontotemporal lobar degeneration caused by mutations in the progranulin gene. Brain. 2006 Nov.129(11):3081-90.

Mackenzie IR, Neumann M, Bigio EH, Cairns NJ, Alafuzoff I, Kril J, Kovacs GG, Ghetti B, Halliday G, Holm IE, Ince PG, Kamphorst W, Revesz T, Rozemuller AJ, Kumar-Singh S, Akiyama H, Baborie A, Spina S, Dickson DW, Trojanowski JQ and Mann DM. Nomenclature and nosology for neuropathologic subtypes of frontotemporal lobar degeneration: an update. Acta Neuropathol. 2010 Jan;119(1):1-4

Mackenzie IR, Neumann M, Baborie A, Sampathu DM, Du Plessis D, Jaros E, Perry RH, Trojanowski JQ, Mann DM and Lee VM. A harmonized classification system for FTLD-TDP pathology. Acta Neuropathol. 2011 Jul;122(1):111-3

Mandillo S, Tucci V, Hölter SM, Meziane H, Banchaabouchi M, Kallnik M, Lad H, Nolan P, Ouagazzal A, Coghill E, Gale K, Golini E, Jacquot S, Krezel W, Parker A, Riet F, Schneider I, Marazziti D, Auwerx J, Brown S, Chambon P, Rosenthal N, Tocchini-ValentiniG, Wurst WV. Reliability, robustness, and reproducibility in mouse behavioral phenotyping: a cross-laboratory study. Physiological genomics, 34(3), 243–55. 2008

Mesulam MM. Slowly progressive aphasia without generalized dementia. Ann Neurol. 1982 Jun.11(6):592-8.

Miller ZA, Rankin KP, Graff-Radford NR, Takada LT, Sturm VE, Cleveland CM, Criswell LA, Jaeger PA, Stan T, Heggeli KA, Hsu SC, Karydas A, Khan BK,Grinberg LT, Gorno-Tempini ML, Boxer AL, Rosen HJ, Kramer JH, Coppola G, Geschwind DH, Rademakers R, Seeley WW, Wyss-Coray T and Miller BL. TDP-43 frontotemporal lobar degeneration and autoimmune disease. J Neurol Neurosurg Psychiatry. 2013 Mar 30.

Mori H, Nishimura M, Namba Y and Oda M. Corticobasal degeneration: a disease with widespread appearance of abnormal tau and neurofibrillary tangles, and its relation to progressive supranuclear palsy. Acta Neuropathol. 1994. 88(2):113-21

Mukaida N and Matsushima K. Regulation of IL-8 production and the characteristics of the receptors for IL-8. Cytokines. 1992. 4:41-53

Mukherjee O, Pastor P, Cairns NJ, Chakraverty S, Kauwe JS, Shears S, Behrens MI, Budde J, Hinrichs AL, Norton J, Levitch D, Taylor-Reinwald L, Gitcho M, Tu PH, Tenenholz Grinberg L, Liscic RM, Armendariz J, Morris JC and Goate AM. HDDD2 is a familial frontotemporal lobar degeneration with ubiquitin-positive, tau-negative inclusions caused by a missense mutation in the signal peptide of Progranulin. Ann Neurol. 2006. 60:314–22 P a g e | 108

Müncha C, Prechterb F, Xub R, Linkec P, Prudlod J, Kuzmae M, Kwiecinskie H, Albert C. L and Meyerc T. Frequency of a tau genotype in amyotrophic lateral sclerosis. J. of the Neuro.Sci. 2005. 236,(1-2);13-16

Neary D, Snowden JS, Mann DM, Northen B, Goulding PJ and Macdermott N. Frontal lobe dementia and motor neuron disease.J Neurol. Neurosurg. Psych. 1990 Jan. 53(1):23-32.

Neary D, Snowden JS, Gustafson L, Passant U, Stuss D, Black S, Freedman M, Kertesz A, Robert PH, Albert M, Boone K, Miller BL, Cummings J and Benson DF. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology. 1998 Dec. 51(6):1546-54.

Neary D, Snowden JS and Mann DM. Classification and description of frontotemporal dementias. Ann N Y Acad Sci. 2000. 920:46-51.

(A) Neumann M, Igaz LM, Kwong LK, Nakashima-Yasuda H, Kolb SJ, Dreyfuss G, Kretzschmar HA, Trojanowski JQ and Lee VM. Absence of heterogeneous nuclear ribonucleoproteins and survival motor neuron protein in TDP-43 positive inclusions in frontotemporal lobar degeneration. Acta Neuropathol. 2007 May. 113(5):543-8.

(B) Neumann M, Mackenzie IR, Cairns NJ, Boyer PJ, Markesbery WR, Smith CD, Taylor JP, Kretzschmar HA, Kimonis VE and Forman MS. TDP-43 in the ubiquitin pathology of frontotemporal dementia with VCP gene mutations. J of Neuropath and Exp. Neurol. 2007. 66; 152-157

Neumann M, Kwong LK, Lee EB, Kremmer E, Flatley A and Xu Y. Forman MS, Troost D, Kretzschmar HA, Trojanowski JQ, Lee VM J. Phosphorylation of S409/410 of TDP-43 is a consistent feature in all sporadic and familial forms of TDP-43 proteinopathies. Acta Neuropathol. 2009. 117:137–149

Neumann M.,Rademakers R, Roeber S, Baker M, Kretzschmar HA and Mackenzie IRA.A new subtype of frontotemporal lobar degeneration with FUS pathology. Brain. 2009. 132;2922–2931

Neumann M, Sampathu DM, Kwong LK, Truax AC, Micsenyi MC, Chou TT, Bruce J, Schuck T, Grossman M, Clark CM, McCluskey LF, Miller BL, Masliah E, Mackenzie IR, Feldman H, Feiden W, Kretzschmar HA, Trojanowski JQ and Lee VM. Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science. 2006; 314(5796):130-3

Nishimoto Y, Ito D, Yagi T, Nihei Y, Tsunoda Y and Suzuki N. Characterization of alternative isoforms and inclusion body of the TAR DNA-binding protein-43. J Biol Chem. 2010 Jan 1. 285(1):608-19. P a g e | 109

Nonaka T, Kametani F, Arai T, Akiyama H and Hasegawa M. Truncation and pathogenic mutations facilitate the formation of intracellular aggregates of TDP-43. Hum Mol Genet. 2009 Sep. 18(18):3353-64.

Oddo S, Caccamo A, Shepherd JD, Murphy MP, Golde TE, Kayed R, Metherate R, Mattson MP, Akbari Y and LaFerla FM. Triple-transgenic model of Alzheimer's disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron. 2003 Jul; 39 (3):409-21.

Ohlsson K, Bjartell A and Lilja H. Secretory leukocyte protease inhibitor in the male genital tract: PSA-induced proteolytic processing in human semen and tissue localization. J. Androl. 1995. 16, 64–74.

Ou SH, Wu F, Harrich D, García-Martínez LF and Gaynor RB. Cloning and characterization of a novel cellular protein, TDP-43, that binds to human immunodeficiency virus type 1 TAR DNA sequence motifs. J Virol. 1995 Jun. 69(6):3584-96.

Poorkaj P, Bird TD, Wijsman E, Nemens E, Garruto RM, Anderson L, Andreadis A, Wiederholt WC, Raskind M, Schellenberg GC. Tau is a candidate gene for chromosome 17 frontotemporal dementia. Ann. Neurol. 1998. 43;815-825.

Terri L, Petkau, Neal SJ, Orban PC, MacDonald JL, Hill AM, Lu G, Feldman HH, Mackenzie I, Leavitt BR. Progranulin expression in the developing and adult murine brain. J of Comp. Neurol. 2010. 518(19);3931–3947 Phukan J, Pender NP and Hardiman O. Cognitive impairment in amyotrophic lateral sclerosis. Lancet Neurol. 2007 Nov; 6(11):994-1003.

Pittman AM, Myers AJ, Abou-Sleiman P, Fung HC, Kaleem M and Marlowe L. Linkage disequilibrium fine-mapping and haplotype association analysis of the tau gene in progressive supranuclear palsy and corticobasal degeneration. J Med Genet. 2005; 42: 837–46.

Pines J and Lindon C. Proteolysis: anytime, anyplace, anywhere? Nat Cell Biol. 2005 Aug;7(8):731-5.

Piscopo P, Rivabene R, Galimberti D, Crestini A, Talarico G, Vanacore N, Scarpini E, Bruno G and Confaloni A. Gender Effects on Plasma PGRN Levels in Patients with Alzheimer's Disease: A Preliminary Study. J Alzheimers Dis. 2013 Feb 8.

Py B, Basmaciogullari S, Bouchet J, Zarka M, Moura IC, Benhamou M, Monteiro RC, Hocini H, Madrid R and Benichou S. The phospholipid scramblases 1 and 4 are cellular receptors for the secretory leukocyte protease inhibitor and interact with CD4 at the plasma membrane. PLoS One. 2009.4(3):5006. P a g e | 110

Rademakers R, Neumann M and Mackenzie IR. Advances in understanding the molecular basis of frontotemporal dementia. Nature Reviews Neurology 8, 423-434, Aug 2012

Rademakers R, Van der zee J, Kumar-Singh S, Dermaut B, Cruts M and Van Broeckhoven C. Chromosome 17-linked Frontotemporal dementia with Ubiquitin-Positive, Tau-Negative Inclusions. Res. & Persp. in Alzheimer's Dis. 2005. 117-137

Roeber S, Mackenzie I, Kretzschmar HA and Neumann M. TDP-43-negative FTLD-U is a significant new clinico-pathological subtype of FTLD. Acta. Neuropathol. 2008 Aug;116(2):147-57

Rogers DC, Jones D, Nelson P, Jones CM, Quilter CA, Robinson and Hagan JJ. Use of SHIRPA and discriminant analysis to characterise marked differences in the behavioural phenotype of six inbred mouse strains. Behavioural Brain Research 105 (1999) 207–217.

Rosen DR, Siddique T, Patterson D, Figlewicz DA, Sapp P, Hentati A, Donaldson D, Goto J, O'Regan JP and Deng HX. Mutations in Cu/Zn superoxide dismutase gene are associated with familial amyotrophic lateral sclerosis. Nature. 1993 Jul. 364(6435):362.

Sallenave JM, Si Tahar M, Cox G, Chignard M and Gauldie J. Secretory leukocyte proteinase inhibitor is a major leukocyte elastase inhibitor in human neutrophils. J. Leukoc. Biol. 1997. 61(6):695-702.

Schulze H, Korpal M, Bergmeier W, Italiano JE Jr, Wahl SM and Shivdasani RA .Interactions between the megakaryocyte/platelet-specific beta1 tubulin and the secretory leukocyte protease inhibitor SLPI suggest a role for regulated proteolysis in platelet functions. Blood. 2004 Dec 15.104(13):3949-57.

Schymick JC, Yang Y, Andersen PM, Vonsattel JP, Greenway M, Momeni P, Elder J, Chiò A, Restagno G, Robberecht W, Dahlberg C, Mukherjee O, Goate A, Graff-Radford N, Caselli RJ, Hutton M, Gass J, Cannon A, Rademakers R, Singleton AB, Hardiman O, Rothstein J, Hardy J, Traynor BJ. Progranulin mutations and amyotrophic lateral sclerosis or amyotrophic lateral sclerosis–frontotemporal dementia phenotypes. J Neurol Neurosurg Psychiatry 2007;78:754-756

Seelaar H, Kamphorst W, Rosso SM, Azmani A, Masdjedi R, de Koning I, Maat-Kievit JA, Anar B, Kaat LD, Breedveld GJ, Dooijes D, Rozemuller JM, Bronner IF, Rizzu P and van Swieten JC. Distinct genetic forms of frontotemporal dementia. Neurology. 2008 Oct 14;71(16):1220-6. P a g e | 111

Sell C, Dumenil G, Deveaud C, Miura M, Coppola D,DeAngelis T, Rubin R, Efstratiadis A and Baserg R. Effect of a null mutation of the insulin-like growth factor I receptor gene on growth and transformation of mouse embryo fibroblasts. Mol Cell Biol. 1994 June; 14(6): 3604–3612.

Sephton CF, Good SK, Atkin S, Dewey CM, Mayer P 3rd, Herz J and Yu G. TDP-43 is a developmentally regulated protein essential for early embryonic development. J Biol Chem 2010; 285:6826–6834.

Shankaran SS, Capell A, Hruscha AT, Fellerer K, Neumann M, Schmid B and Haass C. Missense mutations in the progranulin gene linked to frontotemporal lobar degeneration with ubiquitin- immunoreactive inclusions reduce progranulin production and secretion. J Biol Chem. 2008 Jan 18. 283(3):1744-53.

Schofield E, Kersaitis C, Shepherd CE, Kril JJ and Halliday GM. Severity of gliosis in Pick’s disease and frontotemporal lobar degeneration: tau‐positive glia differentiate these disorders. Brain (2003) 126 (4): 827-840.

Simon-Sanchez J , Dopper EGP , Cohn-Hokke PE , Hukema RK , Nicolaou N , Seelaar H , de Graaf JR, de Koning I, van Schoor NM, Deeg DJ, Smits M, Raaphorst J, van den Berg LH, Schelhaas HJ, De Die-Smulders CE, Majoor-Krakauer D, Rozemuller AJ, Willemsen R, Pijnenburg YA, Heutink P and van Swieten JC. The clinical and pathological phenotype of C9orf72 hexanucleotide repeat expansions. Brain 2012; 135: 723–35.

Skibinski G, Parkinson NJ, Brown JM, Chakrabarti L, Lloyd SL, Hummerich H, Nielsen JE, Hodges JR, Spillantini MG, Thusgaard T, Brandner S, Brun A,Rossor MN, Gade A, Johannsen P, Sørensen SA, Gydesen S, Fisher EM and Collinge J. Mutations in the endosomal ESCRTIII-complex subunit CHMP2B in frontotemporal dementia. Nat Genet. 2005 Aug; 37(8):806-8.

Smith V, Chou KN and Lashkari D. Functional analysis of the genes of yeast chromosome 5 by genetic footprinting. Science.1996. 274:2069–74

Smith C E and Johnson DA. Human bronchial leucocyte proteinase inhibitor. rapid isolation and kinetic analysis with human leucocyte proteinases. Biochem. J. 225 (1985) 463-472.

Snowden JS, Bathgateb D, Varmaa A, Blackshawa A, Gibbonsa ZC, Neary D. Distinct behavioural profiles in frontotemporal dementia and semantic dementia. J Neurol Neurosurg Psych. 2001. 70:323-332

Snowden JS, Harris J, Richardson A, Rollinson S, Thompson JC, Neary D, Mann DM, Pickering- Brown S. Frontotemporal dementia with amyotrophic lateral sclerosis: a clinical comparison of patients with and without repeat expansions in C9orf72. P a g e | 112

Amyotroph Lateral Scler Frontotemporal Degener. 2013 Apr;14(3):172-6.

Snowden JS, Gouding PJ and Neary D. Semantic dementia: A form of circumscribed cerebral atrophy. 1989. Behav. Neurol. 2, 167–182.

Snowden J S., Nearly D, and Mann D. Frontotemporal dementia. Brit. J. of psych. 2002. 180;140-143

Snowden, J, Neary, D and Mann D. Frontotemporal lobar degeneration: clinical and pathological relationships. Acta Neuropathol. 2007.114:31–38

Snowden JS, Rollinson S, Thompson JC, Harris JM, Stopford CL, Richardson AM, Jones M, Gerhard A, Davidson YS, Robinson A, Gibbons L, Hu Q, DuPlessis D, Neary D, Mann DM, Pickering-Brown SM. Distinct clinical and pathological characteristics of frontotemporal dementia associated with C9ORF72 mutations. Brain. 2012 Mar;135(Pt 3):693-708

Dahl SW, Halkier T, Lauritzen C, Dolenc I, Pedersen J, Turk V, and Turk B. Human Recombinant Pro-dipeptidyl Peptidase I (Cathepsin C) Can Be Activated by Cathepsins L and S but not by autocatalytic processing. Biochemistry 2001 40 (6), 1671-1678

Spillantini MG, Crowther RA and Goedert M. Comparison of the neurofibrillary pathology in Alzheimer's disease and familial presenile dementia with tangles. Acta Neuropathol. 1996. 92(1):42-8.

Spillantini MG, Murrell JR, Goedert M, Farlow MR, Klug A and Ghett B. Mutation in the tau gene in familial multiple system tauopathy with presenile dementia. Proc. Natl. Acad. Sci. USA 1998. 98:7737-7741.

Stetler G, Brewer MT and Thompson RC. Isolation and sequence of a human gene encoding a potent inhibitor of leukocyte proteases. Nuc. Acids Res. 1986. 14:7883-7896.

Stevens M, van Duijn CM, Kamphorst W, de Knijff P, Heutink P, van Gool WA, Scheltens P, Ravid R, Oostra BA, Niermeijer MF and van Swieten JC. Familial aggregation in frontotemporal dementia. Neurol. 1998. 50(6):1541-5.

Su JH, Nichol KE, Sitch T, Sheu P, Chubb C, Miller BL,Tomaselli KJ, Kim RC and Cotman CW. DNA damage and activated caspase-3 expression in neurons and astrocytes: evidence for apoptosis in frontotemporal dementia. Exp Neurol. 2000 May;163(1):9-19.

Sullivan AL, Dafforn T, Hiemstra PS and Stockley RA. Neutrophil elastase reduces secretion of secretory leukoproteinase inhibitor (SLPI) by lung epithelial cells: role of charge of the proteinase-inhibitor complex. Respir Res. 2008. 9:60. P a g e | 113

Suzuki M, Lee HC, Kayasuga Y, Chiba S, Nedachi T, Matsuwaki T, Yamanouchi K and Nishihara M. Roles of progranulin in sexual differentiation of the developing brain and adult neurogenesis. J Reprod Dev. 2009. 55(4):351-5.

Taggart CC, Greene CM, McElvaney NG and O'Neill S. Secretory leukocyte protease inhibitor prevents lipopolysaccharide-induced I-kappa-B-alpha degradation without affecting phosphorylation or ubiquitination. J Biol Chem. 2002.13;277(37):33648-53.

Tatom JB, Wang DB, Dayton RD, Skalli O, Hutton ML, Dickson DW and Klein RL. Mimicking aspects of frontotemporal lobar degeneration and Lou Gehrig's disease in rats via TDP-43 overexpression. Mol Ther. 2009.(4):607-13.

Thompson, R.C. and Ohlsson, K. Isolation, properties, and complete amnio acid sequence of human secretory leukocyte protease inhibitor, a potent inhibitor of leukocyte elastase. Proc. Natl Acad. Sci. USA. 1986. 83;6692–6696.

Uhlen M, Bjorling E, Agaton C, Szigyarto CA, Amini B, Andersen E, Andersson AC, Angelidou P, Asplund A, Asplund C, Berglund L, Bergström K, Brumer H, Cerjan D, Ekström M, Elobeid A, Eriksson C, Fagerberg L, Falk R, Fall J, Forsberg M, Björklund MG, Gumbel K, Halimi A, Hallin I, Hamsten C, Hansson M, Hedhammar M, Hercules G. A human protein atlas for normal and cancer tissues based on antibody proteomics. Mol Cell Proteomics 2005, 4:1920-1932.

Van Damme P, Van Hoecke A, Lambrechts D, Vanacker P, Bogaert E, van Swieten J, Carmeliet P, Van Den Bosch L and Robberecht W. Progranulin functions as a neurotrophic factor to regulate neurite outgrowth and enhance neuronal survival. J Cell Biol. 2008 Apr. 181(1):37-41.

Van der Zee J, Rademakers R, Engelborghs S, Gijselinck I, Bogaerts V, Vandenberghe R, Santens P, Caekebeke J, De Pooter T, Peeters K, Lübke U, Van den Broeck M, Martin JJ, Cruts M, De Deyn PP, Van Broeckhoven C, Dermaut B. A Belgian ancestral haplotype harbours a highly prevalent mutation for 17q21-linked tau-negative FTLD. Brain. 2006 Apr;129(Pt 4):841-52.

Van Es MA, Veldink JH, Saris CG, Blauw HM, van Vught PW, Birve A, Lemmens R, Schelhaas HJ, Groen EJ, Huisman MH, van der Kooi AJ, de Visser M, Dahlberg C, Estrada K, Rivadeneira F, Hofman A, Zwarts MJ, van Doormaal PT, Rujescu D, Strengman E, Giegling I, Muglia P, Tomik B, Slowik A, Uitterlinden AG, Hendrich C, Waibel S, Meyer T, Ludolph AC, Glass JD, Purcell S, Cichon S, Nöthen MM, Wichmann HE, Schreiber S, Vermeulen SH, Kiemeney LA, Wokke JH, Cronin S, McLaughlin RL, Hardiman O, Fumoto K, Pasterkamp RJ, Meininger V, Melki J, Leigh PN, Shaw CE, Landers JE, Al-Chalabi A, Brown RH Jr, Robberecht W, Andersen PM, Ophoff RA and van den Berg LH. Genome-wide association study identifies 19p13.3 (UNC13A) and 9p21.2 as susceptibility loci for sporadic amyotrophic lateral sclerosis. P a g e | 114

Nat Genet. 2009 Oct. 41(10):1083-7.

Vance C, Rogelj B, Hortobagyi T, de Vos KJ, Nishimura AL, Sreedharan J, Hu X, Smith B, Ruddy D, Wright P, Ganesalingam J, Williams KL, Tripathi V, Al-Saraj S, Al-Chalabi A, Leigh PN, Blair IP, Nicholson G, de Belleroche J, Gallo JM, Miller CC, Shaw CE. Mutations in FUS, an RNA processing protein, cause familial amyotrophic lateral sclerosis type 6. Science 2009; 323: 1208–11.

Van Seuningen I, Audie JP, Gosselin B, Lafitte JJ and Davril M. Expression of human mucous proteinase inhibitor in respiratory tract: a study by in situ hybridization. J Histochem Cytochem 1995, 43:645–648

Verny M, Duyckaerts C, Agid Y and Hauw JJ. The significance of cortical pathology in progressive supranuclear palsy. Clinico-pathological data in 10 cases. Brain. 1996 Aug;119 ( Pt 4):1123-36.

Vroling AB, Konijn T, Samsom JN and Kraal G. The production of secretory leukocyte protease inhibitor by dendritic cells. Mol Immunol. 2011 Jan;48(4):630-6.

Wahl SM, McNeely TB, Janoff EN, Shugars D, Worley P. Secretory leukocyte protease inhibitor (SLPI) in mucosal fluids inhibits HIV-I. Oral Dis. Suppl. 1997. 1:64–69.

Wang X, Fan H, Ying Z, Li B, Wang H and Wang G. Degradation of TDP-43 and its pathogenic form by autophagy and the ubiquitin-proteasome system. Neurosci Lett. 2010 Jan. 469(1);1112-6

Wang X, Li X, Xu L, Zhan Y, Yaish-Ohad S, Erhardt JA, Barone FC and Feuerstein GZ. Up-Regulation of Secretory Leukocyte Protease Inhibitor (SLPI) in the Brain after Ischemic Stroke: Adenoviral Expression of SLPI Protects Brain from Ischemic Injury. Mol. Pharmacol., October 1, 2003; 64(4): 833 - 84

Wegorzewska I, Bell S, Cairns NJ, Miller TM and Baloh RH.TDP-43 mutant transgenic mice develop features of ALS and frontotemporal lobar degeneration. Proc Natl Acad Sci USA. 2009.106(44):18809-14.

Weihl CC, Pestronk A and Kimonis VE. Valosin-containing protein disease: inclusion body myopathy with Paget's disease of the bone and frontotemporal dementia. Neuromuscul Disord. 2009 May; 19(5): 308–315.

Wiedow OJ, Ludemann B, Utecht E, Christophers. Inhibition of proteinase-3 activity by peptides derived from human epidermis. Adv. Exp. Med. Biol.1993.61-64. P a g e | 115

Wilhelmsen T, Lynch E, Pavlov M, Higgins TG, Nygaard AM. J.Localization of disinhibition-dementia-parkinsonism-amyotrophy complex to 17q21-22. Hum. Genet. 1994. 55:1159-1165

Williams D.R Tauopathies: classification and clinical update on neurodegenerative diseases associated with microtubule-associated protein tau. Int. Med. J. 2006. 36: 652–660

Williams D and Lees A. Progressive supranuclear palsy: clinicopathological concepts and diagnostic challenges. Lancet Neurol. 2009.8(3);270-279

Winton MJ, Igaz LM, Wong MM, Kwong LK, Trojanowski JQ, Lee VM. Disturbance of nuclear and cytoplasmic TAR DNA-binding protein (TDP-43) induces disease-like redistribution, sequestration, and aggregate formation.J Biol Chem. 2008 9;283(19):13302-9.

Wilmer JL and Luster MI. Chemical induction of interleukin-8, a proinflammatory chemokine, in human epidermal keratinocyte cultures and its relation to cytogenetic toxicity. Cell Biol & Tox. 1995. 11:3-50.

Williams RL, Urbé S. The emerging shape of the ESCRT machinery. Nat Rev Mol Cell Biol. 2007. 8(5):355-68.

Wszolek ZK, Tsuboi Y, Ghetti B, Pickering-Brown S, Baba Y and Cheshire WP. Frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17). Orphanet J Rare Dis. 2006 Aug 9;1:30. Review.

Xu Y. Generation and characterization of human TDP-43 transgenic mice. Soc for Neurosci Abs, Annual Meeting Publications (2008)

Yang J, Zhu J, Sun D, Ding A. Suppression of macrophage responses to bacterial lipopolysaccharide (LPS) by secretory leukocyte protease inhibitor (SLPI) is independent of its anti-protease function. Biochim Biophys Acta. 2005 Sep 30;1745(3):310-7.

(A) Yin F, Banerjee R, Thomas B, Zhou P, Qian L, Jia T, Ma X, Ma Y, Iadecola C, Beal MF, Nathan C and Ding A. Exaggerated inflammation, impaired host defense, and neuropathology in progranulin-deficient mice. J Exp Med. 2010 Jan. 207(1):117-28.

(B) Yin F, Dumont M, Banerjee R and Ding A. Behavioral deficits and progressive neuropathology in progranulin-deficient mice: a mouse model of frontotemporal dementia. FASEB J. 2010. PMID 20667979 P a g e | 116

Zhang D, Simmen RC, Michel FJ, Zhao G, Vale-Cruz D and Simmen FA. Secretory leukocyte protease inhibitor mediates proliferation of human endometrial epithelial cells by positive and negative regulation of growth-associated genes. J Biol Chem. 2002. 277(33):29999-30009.

Zhang YJ, Xu YF, Dickey CA, Buratti E, Baralle F, Bailey R, Pickering-Brown S, Dickson D and Petrucelli L. Progranulin mediates caspase-dependent cleavage of TAR DNA binding protein-43. J Neurosci. 2007. 27(39):10530-4.

Zheng Y, Brady OA, Meng PS, Mao Y and Hu F. C-terminus of progranulin interacts with the beta- propeller region of sortilin to regulate progranulin trafficking. PLoS One 2011, 6:e21023.

Zhou J, Gao G, Crabb JW and Serrero G. Purification of an autocrine growth factor homologous with mouse epithelin precursor from a highly tumorigenic cell line. J Biol Chem 1993. 268:10863-10869.

Zhu J, Nathan C, Jin W, Sim D, Ashcroft GS, Wahl SM, Lacomis L, Erdjument-Bromage H, Tempst P, Wright CD and Ding A. Conversion of proepithelin to epithelins: roles of SLPI and elastase in host defense and wound repair. Cell. 2002 Dec. 111(6):867-78

P a g e | 117

Chapter 8: Supplementary information

P a g e | 118

Reagents

Proteinase K Digestion buffer: 50 mM Tris-HCL (pH 7.4) 100 mM EDTA 100 mM NaCl 1% SDS (pH 8.0)

T.E. Buffer: 10 mM Tris-HCL (pH 7.4) 1 mM EDTA (pH 8.0)

PBS: 137 mM NaCl, 2.7 mM KCl, 8.1 mM Na2HPO4, 1.5 mM KH2PO4, pH 7.2 - 7.4, 0.2 µm filtered.

4% PFA: 100mls PBS 4mgs of Paraformaldehyde Heated to 55°C and filtered with filter paper

Saline: 1000mls Distilled water 9mgs of sodium chloride

RIPA buffer: 50 mM Tris-HCl (pH 7.4) 150 mM NaCl 1% Triton x-100 1% Sodium deoxycholate 0.1% SDS (pH 8.0) 1 mM EDTA (pH 8.0) Protease Inhibitors

P a g e | 119

3.2% Sodium Citrate: 10mls distilled water 0.32mgs sodium citrate

Tris-Glycine SDS running buffer (2L): 28.8g Glycine 6.04g Tris Base 2g SDS 2L Distilled water

TBST-Tween: 1L of Distilled water 8.8 g of NaCl 0.2g of KCl 3g of Tris base 500ul ofTween-20

NP-40 buffer: 20 mM Tris HCl pH 8 137 mM NaCl 10% Glycerol 1% Nonidet P-40 2 mM EDTA

5% BSA-TBST-Tween, 400mls: 20g Bovine Serum Albumin (Sigma) 400msl TBST-Tween, 0.2µM filtered

10% SDS-NUPAGE resolving Gel, 40mls: 15.8mls Distilled water. 13.3mls 30% Bis/Acrylamide Mix (Amersham) 10.0mls 1.5 M Tris, pH 8.8 0.4mls 10% Sodium Dodecyl Sulfate (SDS) 0.4mls 10% Ammonium Persulfate (APS) 16µLs TEMED (N,N,N’,N’-tetramethylethylenediamine) P a g e | 120

17% SDS-NUPAGE resolving Gel, 40mls: 7.2mls Distilled water. 22.0 mls 30% Bis/Acrylamide Mix (Amersham) 10.0mls 1.5 M Tris, pH 8.8 0.4mls 10% Sodium Dodecyl Sulfate (SDS) 0.4mls 10% Ammonium Persulfate (APS) 16µls TEMED (N,N,N’,N’-tetramethylethylenediamine)

SDS-NUPAGE stacking gel, 5mls: 4.1mls Distilled water 1mls 30% Bis/Acrylamide Mix (Amersham) 0.75mls 1.0 M Tris, pH 6.8 60 µls 10% Sodium Dodecyl Sulfate (SDS) 60 µls 10% Ammonium Persulfate (APS) 6 µls TEMED (N,N,N’,N’-tetramethylethylenediamine)

Western Blot transfer buffer: 1.8L Distilled water 28.8g Glycine 6.04g Tris base 200ml Methanol

5x SDS Loading Buffer: 10% SDS 10mM Beta-mercato-ethanol 20% Glycerol 0.2M Tris-HCL pH6.8 0.05% Bromophenol Blue

(Immortalized cell lines) Seed media: DMEM (Gibco) 10% FCS (Sigma) 1% Penicillin/Streptomycin (Sigma)

P a g e | 121

(Immortalized cell lines) Serum free media: DMEM (Gibco) 1% Penicillin/Streptomycin (Sigma)

(Neuronal) Seed media: Neuro-Basal Media (Gibco) 5% Plasma-derived serum (Gibco) 1% Penicillin/Streptomycin (Sigma) 1% glutamine (Sigma) 2% B27 with antioxidants (Sigma)

Starve media: DMEM (Gibco) 1% glutamine (Sigma)

Dissociation media: 1.8ml of starve media (Gibco) 200uL 10x trypsin (Sigma) 750 units of DNAase (Sigma)

Wash media: DMEM (Gibco) 10% FCS (Sigma) 1% Penicillin/Streptomycin (Sigma)

Wash Buffer: 0.05% Tween PBS, pH 7.2 - 7.4

ELISA Blocking Solution: 1% BSA PBS, pH 7.2 - 7.4, 0.2 µm filtered

Substrate Solution: 1:1 mixture of Colour Reagent A (H2O2) and Colour Reagent B (Tetramethylbenzidine)

Stop Solution: 2 N H2SO4 P a g e | 122

Supplementary results

Supplementary figure 1: Immunoglobulin depleted blood plasma of 12 month old, alternating male and female samples.

Supplementary data, Table 1: Fear conditioning, base rate - Multiples comparisons

Tukey's multiple comparisons test Mean Diff. 95% CI of diff. Significant? Summary

6:Wild-type vs. 6:SLPI null -0.03234 -0.2251 to 0.1604 No ns 6:Wild-type vs. 12:Wild-type 0.01995 -0.1728 to 0.2127 No ns 6:Wild-type vs. 12:SLPI null -0.0001 -0.1929 to 0.1927 No ns 6:Wild-type vs. 20:Wild-type -0.3438 -0.5366 to -0.1510 Yes **** 6:Wild-type vs. 20:SLPI null -0.3791 -0.5718 to -0.1863 Yes **** 6:SLPI null vs. 12:Wild-type 0.05229 -0.1405 to 0.2450 No ns 6:SLPI null vs. 12:SLPI null 0.03224 -0.1605 to 0.2250 No ns 6:SLPI null vs. 20:Wild-type -0.3115 -0.5042 to -0.1187 Yes *** 6:SLPI null vs. 20:SLPI null -0.3467 -0.5395 to -0.1540 Yes **** 12:Wild-type vs. 12:SLPI null -0.02005 -0.2128 to 0.1727 No ns 12:Wild-type vs. 20:Wild-type -0.3638 -0.5565 to -0.1710 Yes **** 12:Wild-type vs. 20:SLPI null -0.399 -0.5918 to -0.2062 Yes **** 12:SLPI null vs. 20:Wild-type -0.3437 -0.5365 to -0.1509 Yes **** 12:SLPI null vs. 20:SLPI null -0.3789 -0.5717 to -0.1862 Yes **** 20:Wild-type vs. 20:SLPI null -0.03525 -0.2280 to 0.1575 No ns

P a g e | 123

Supplementary data, Table 2: Fear conditioning, 3rd light/shock - Multiples comparisons

Tukey's multiple comparisons test Mean Diff. 95% CI of diff. Significant? Summary

6:Wild-type vs. 6:SLPI null 0.07694 -0.4513 to 0.6052 No ns 6:Wild-type vs. 12:Wild-type -0.1128 -0.6411 to 0.4154 No ns 6:Wild-type vs. 12:SLPI null -0.03963 -0.5679 to 0.4886 No ns 6:Wild-type vs. 20:Wild-type 0.9567 0.4285 to 1.485 Yes **** 6:Wild-type vs. 20:SLPI null 0.7865 0.2583 to 1.315 Yes *** 6:SLPI null vs. 12:Wild-type -0.1898 -0.7180 to 0.3385 No ns 6:SLPI null vs. 12:SLPI null -0.1166 -0.6448 to 0.4117 No ns 6:SLPI null vs. 20:Wild-type 0.8798 0.3515 to 1.408 Yes **** 6:SLPI null vs. 20:SLPI null 0.7096 0.1813 to 1.238 Yes ** 12:Wild-type vs. 12:SLPI null 0.0732 -0.4551 to 0.6015 No ns 12:Wild-type vs. 20:Wild-type 1.07 0.5413 to 1.598 Yes **** 12:Wild-type vs. 20:SLPI null 0.8993 0.3711 to 1.428 Yes **** 12:SLPI null vs. 20:Wild-type 0.9964 0.4681 to 1.525 Yes **** 12:SLPI null vs. 20:SLPI null 0.8261 0.2979 to 1.354 Yes *** 20:Wild-type vs. 20:SLPI null -0.1702 -0.6985 to 0.3580 No ns

Supplementary data, Table 3: Environmental recall, base rate - Multiples comparisons

Tukey's multiple comparisons test Mean Diff. 95% CI of diff. Significant? Summary

6:Wild-type vs. 6:SLPI null 0.1223 -0.5561 to 0.8007 No ns 6:Wild-type vs. 12:Wild-type 0.2802 -0.3983 to 0.9586 No ns 6:Wild-type vs. 12:SLPI null 0.6092 -0.06922 to 1.288 No ns 6:Wild-type vs. 20:Wild-type 1.828 1.149 to 2.506 Yes **** 6:Wild-type vs. 20:SLPI null 1.729 1.050 to 2.407 Yes **** 6:SLPI null vs. 12:Wild-type 0.1579 -0.5206 to 0.8363 No ns 6:SLPI null vs. 12:SLPI null 0.4869 -0.1915 to 1.165 No ns 6:SLPI null vs. 20:Wild-type 1.706 1.027 to 2.384 Yes **** 6:SLPI null vs. 20:SLPI null 1.606 0.9280 to 2.285 Yes **** 12:Wild-type vs. 12:SLPI null 0.329 -0.3494 to 1.007 No ns 12:Wild-type vs. 20:Wild-type 1.548 0.8692 to 2.226 Yes **** 12:Wild-type vs. 20:SLPI null 1.449 0.7701 to 2.127 Yes **** 12:SLPI null vs. 20:Wild-type 1.219 0.5402 to 1.897 Yes **** 12:SLPI null vs. 20:SLPI null 1.12 0.4411 to 1.798 Yes **** 20:Wild-type vs. 20:SLPI null -0.0991 -0.7775 to 0.5793 No ns

P a g e | 124

Supplementary data, Table 4: Conditioned response, base rate - Multiple comparisons Tukey's multiple comparisons test Mean Diff. 95% CI of diff. Significant? Summary

6:Wild-type vs. 6:SLPI null -0.1442 -0.3871 to 0.09864 No ns 6:Wild-type vs. 12:Wild-type 0.1078 -0.1351 to 0.3507 No ns 6:Wild-type vs. 12:SLPI null -0.03789 -0.2808 to 0.2050 No ns 6:Wild-type vs. 20:Wild-type -0.4535 -0.6964 to -0.2106 Yes **** 6:Wild-type vs. 20:SLPI null -0.3768 -0.6196 to -0.1339 Yes *** 6:SLPI null vs. 12:Wild-type 0.252 0.009151 to 0.4949 Yes * 6:SLPI null vs. 12:SLPI null 0.1063 -0.1365 to 0.3492 No ns 6:SLPI null vs. 20:Wild-type -0.3093 -0.5521 to -0.06639 Yes ** 6:SLPI null vs. 20:SLPI null -0.2325 -0.4754 to 0.01032 No ns 12:Wild-type vs. 12:SLPI null -0.1457 -0.3886 to 0.09718 No ns 12:Wild-type vs. 20:Wild-type -0.5613 -0.8041 to -0.3184 Yes **** 12:Wild-type vs. 20:SLPI null -0.4846 -0.7274 to -0.2417 Yes **** 12:SLPI null vs. 20:Wild-type -0.4156 -0.6585 to -0.1727 Yes **** 12:SLPI null vs. 20:SLPI null -0.3389 -0.5818 to -0.09602 Yes ** 20:Wild-type vs. 20:SLPI null 0.07671 -0.1662 to 0.3196 No ns

Supplementary data, Table 5: Conditioned response, 3rd Light/shock - multiple comparisons Tukey's multiple comparisons test Mean Diff. 95% CI of diff. Significant? Summary

6:Wild-type vs. 6:SLPI null 0.07694 -0.4484 to 0.6023 No ns 6:Wild-type vs. 12:Wild-type -0.3128 -0.8382 to 0.2125 No ns 6:Wild-type vs. 12:SLPI null -0.03963 -0.5650 to 0.4857 No ns 6:Wild-type vs. 20:Wild-type 0.7567 0.2314 to 1.282 Yes *** 6:Wild-type vs. 20:SLPI null 0.5865 0.06116 to 1.112 Yes * 6:SLPI null vs. 12:Wild-type -0.3898 -0.9151 to 0.1356 No ns 6:SLPI null vs. 12:SLPI null -0.1166 -0.6419 to 0.4088 No ns 6:SLPI null vs. 20:Wild-type 0.6798 0.1544 to 1.205 Yes ** 6:SLPI null vs. 20:SLPI null 0.5096 -0.01578 to 1.035 No ns 12:Wild-type vs. 12:SLPI null 0.2732 -0.2522 to 0.7986 No ns 12:Wild-type vs. 20:Wild-type 1.07 0.5442 to 1.595 Yes **** 12:Wild-type vs. 20:SLPI null 0.8993 0.3740 to 1.425 Yes **** 12:SLPI null vs. 20:Wild-type 0.7964 0.2710 to 1.322 Yes *** 12:SLPI null vs. 20:SLPI null 0.6261 0.1008 to 1.152 Yes * 20:Wild-type vs. 20:SLPI null -0.1702 -0.6956 to 0.3551 No ns