The Impact of PLEKHM2 Mutation on Neuronal Differentiation and Impaired Autophagy

Ben-Gurion University of the Negev Faculty of Engineering Sciences The Avram and Stella Goldstein-Goren Department of Biotechnology Engineering

Thesis Submitter in Partial Fulfillment of the Requirements for the M.Sc. Degree

By Hadas Ben-Zvi

Supervised by Prof. Smadar Cohen, Dr. Rivka Ofir and Dr. Ginat Narkis

October 2020

Ben-Gurion University of the Negev Faculty of Engineering Sciences The Avram and Stella Goldstein-Goren Department of Biotechnology Engineering

The Impact of PLEKHM2 Mutation on Neuronal Differentiation and Impaired Autophagy

Thesis Submitter in Partial Fulfillment of the Requirements for the M.Sc. Degree

By Hadas Ben-Zvi

Supervised by Prof. Smadar Cohen, Dr. Rivka Ofir and Dr. Ginat Narkis

Author:………………………… Date:……………..24.9.2020 Supervisor:…………………….. Date:……………..24.9.2020 Supervisor:…………………….. Date:……………..29.9.2020 Supervisor:…………………….. Date:…29.9.2020………….. Chairman of Graduate Studies Committee:………… Date:…………….30.9.20 .

October 2020

Abstract

Mutated PLEKHM2 (mPLEKHM2) causes dilated cardiomyopathy with left ventricular noncompaction (DCM-LVNC) resulting in a premature death of mPLEKHM2 individuals due to heart failure. PLEKHM2 (also known as SKIP) is a factor in autophagy, a master regulator in cell homeostasis, decomposes pathogens, proteins and other cellular compartments. Autophagy is mainly carried out by the lysosome that contains enzymes for degradation, and by the autophagosome, which engulfs substances marked for decomposition. PLEKHM2 is a part of a protein complex which allows lysosomal movement toward the cell periphery, therefore as anticipated, mPLEKHM2 patient fibroblasts exhibited perinuclear localization of the lysosomes. This could be one of the reasons for the autophagic dysregulation discovered in patient fibroblasts cells, resulting with a severe disease DCM-LVNC.

Autophagic dysregulation was observed in the context of neurodegenerative diseases. Many factors could stimulate neuronal cell death in neurodegenerative disorders such as cellular stressors, bioenergy failure, misfolded protein accumulation and impaired autophagy. Thus, modulation of autophagy holds considerable potential as a therapeutic approach to these diseases.

Previously, induced pluripotent stem cells (iPSCs) were generated from mPLEKHM2 patient and healthy fibroblasts in our laboratory (BGU Regenerative Medicine and Stem Cell -RMSC). Our hypothesis is that neurons derived from iPSCs with mPLEKHM2 will present impaired functions as compared to normal iPSCs-derived neurons.

In our study, a protocol of directed neural differentiation has been employed and optimized upon two healthy and two patient (mutated) iPSC lines including characterizing neurons in the culture. Both control and patient lines showed similar pattern of differentiation into immature motor neuron cells; the cultures were composed of 64% Tuj1+ cells, 28% GFAP+ cells and 6% isl1+ cells. An assay designed to identify autophagosome accumulation at different stages of the differentiation showed that patient lines had a trend of reduced generation of autophagic bodies during D6 and D18. Neuron functionality was examined using microelectrode array (MEA). Patient cells presented maximal activity during D30 to D33 of differentiation, with irregular and

II more frequent firing rate as compare to healthy cells. Our results suggest that patient neuronal cell cultures were unable to maintain homeostasis properly as result of impaired autophagy flux.

Keywords: Neurons, Motor Neurons, Autophagy, PLEKHM2, DCM-LVNC, Cardiomyopathy, Neurodegeneration, Lysosomes, Autophagosomes, iPSCs, Disease Model.

III

Acknowledgments

This work was performed under the supervision of Prof. Smadar Cohen, Dr. Rivka Ofir and Dr. Ginat Narkis in the Department of Biotechnology, Ben-Gurion University of the Negev.

I would like to thank all three for many hours spent debating our study and future progress, excellent guidance, encouragement and support.

A very special thanks to Dr. Gad Vatine, whose door was always open, sharing his abundant knowledge of neuroscience whole heartedly.

Also, to Tatiana Rabinski for taking me under her wing, like any student, teaching and assisting me with great patience and respect.

Last but not least, my boyfriend Ran, who supported me through this study with endless love, by my side come what may.

Table of Contents

Abstract...... I

Keywords...... II

Acknowledgments...... III

Table of Contents ...... IV

List of abbreviations ...... VI

List of Figures ...... VIII

List of Tables ...... IX

1. Introduction ...... 1 1.1. PLEKHM2 Mutation Causes Dilated Cardiomyopathy (DCM) with Left Ventricular Noncompaction (LVNC)………………………………………………………………1 1.2. Induced Pluripotent Stem Cells (iPSCs) as a DCM-LVNC Disease Model………..….2 1.2.1. DCM-iPSCs………………………………………………………………………3 1.3. Autophagy…………………………………………………………………………….5 1.3.1. Autophagosome………………………………………………………………….5 1.3.2. Lysosome………………………………………………………………………...6 1.3.3. DCM Fibroblasts and Autophagy………………………………………………...7 1.4. Neurodegenerative Diseases…………………………………………………………..8 1.5. Neural Disease Models………………………………………………………………..9 1.5.1. Neural Subtypes in Scientific Research…………………………………………10 1.5.2. Motor Neuron Differentiation…………………………………………………...10 1.5.3. Autophagy and Neurodegeneration…………………………………………..…11 1.5.3.1. Stress Induction……………………………………………………….12 2. Research Hypothesis and Objectives...... 14 2.1. Research Hypothesis…………………………………………………………………14 2.2. Objectives……………………………………………………………………………15 3. Materials and Methods ...... 16

3.1. Materials ...... 16 3.2. Cell Culture...... 16 3.3. Monolayer Differentiation...... 16 3.4. Karyotype Analysis...... 17 3.5. Mycoplasma Contamination Examination...... 17 3.6. Flow Cytometry Quantification...... 18 3.7. Autophagy Flux Detection...... 18 3.8. Microelectrode Array (MEA) Assay...... 18 3.9. Western Blot...... 19 3.10. Immunocytochemistry...... 19 3.11. Metabolism Assay...... 20 3.12. Statistical Analysis...... 20 4. Results ...... 21 4.1. Characterization of DCM-iPSC ...... 21 4.2. MN Differentiation...... 22 4.3. Stress Induced Autophagy Flux...... 25 4.3.1. Flow Cytometry...... 26 4.3.2. Western Blot...... 28 4.4. Functional Tests...... 29 4.4.1. Cellular Metabolism...... 29 4.4.2. iPSCs-derived MN Activity...... 32 5. Discussion ...... 33 5.1. Mutation in PLEKHM2 Does Not Impact Neural Differentiation…………………33 5.2. Stress Induction of mPLEKHM2 Cells Results in a Modest Autophagosome Flux…34 5.3. Functional Tests Indicate mPLEKHM2 Neurons are Highly Active………………...36 6. Conclusions ...... 38 7. Appendix ...... 39 8. References ...... 44

List of Abbreviations

AA ascorbic acid AD Alzheimer’s disease AFU arbitrary fluorescent unit ALS amyotrophic lateral sclerosis BDNF brain-derived neurotrophic factor CHIR CHIR99021 Chr chromosome CM cardiomyopathy CNS central nervous system DAPT γ-secretase inhibitor db-cAMP dibutyryl cyclic AMP DCM dilated Cardiomyopathy DCM-LVNC dilated Cardiomyopathy with left ventricular noncompaction DIV days in vitro ESC embryonic stem cell FTD frontotemporal dementia GDNF glial-derived neurotrophic factor HD Huntington’s disease IMDM Iscove’s modified Dulbecco’s medium iMN immature motor neuron iPSC induced pluripotent stem cell

LC3B microtubule-associated protein light chain 3 β LDN LDN193189 MEF mouse embryonic fibroblasts MFI median fluorescence intensity MHC major histocompatibility complex NEAA MEM non-essential amino acids MN motor neuron MNPC motor neuron progenitor cell mPLEKHM2 mutated PLEKHM2 MTOC microtubule-organizing center mTORC1 mammalian target of rapamycin 1 NEP neuroepithelium

VII

NPC neural progenitor cell PLEKHM2 pleckstrin homology domain containing, family M member 2 PBS phosphate buffered saline PD Parkinson’s disease PEI polyethyleneimine PNS peripheral nervous system PSA Penicillin-Streptomycin-Amphotericin RA retinoic acid RMSC regenerative medicine and stem cell RT room temperature S1M stage 1 medium S2M stage 2 medium S3M stage 3 medium SB SB431542 sd standard deviation SEM standard error of the mean SKIP Sifa and kinesin interacting protein SAG smoothened agonist Y-27632 ROCK inhibitor WT wild type

VIII

List of Figures

Figure 1: PLEKHM2 protein variants………………………………………………………....2

Figure 2: Lysosome movement within the cell………………………………………………..7

Figure 3: Neural disease models………………………………………………………………9

Figure 4: Proposed model for neural induction using dual SMAD inhibition……………..…11

Figure 5: Proposed mechanism by which lysosomal positioning coordinates mTOR signaling and autophagy ……………………………………………………………………….……….13

Figure 6: iPSC lines are self-renewing and have not accumulated genetic mutations……….22

Figure 7: Monolayer MN differentiation. ………………………………………………...…24

Figure 8: Autophagy flux using CYTO-ID® assay…………………………………………..27

Figure 9: Western blot analysis of NEP……………………………………………………...29

Figure 10: iMNs D18 metabolism assay……………………………………………………...31

Figure 11: Spontaneous activity within neuronal cultures………...…………………………..32

Figure 12: Mycoplasma free cells.……………………………………………………………39

Figure 13: Representative neural culture images……………………………………………..39

Figure 14: Autophagy flux of grouped control and mPLEKHM2 cell lines under R+CQ stress unless stated otherwise gathered from flow cytometry analysis……………………………….40

Figure 15: Basal and starved autophagosome levels………………………………………….42

Figure 16: Autophagy flux of BGU-iPSC using CYTO-ID® assay…………………………..43

Figure 17: Neural activity raster plots of P.2 and mP.2 D18 iMNs…………………………….43

List of Tables

Table 1: iPSC reprogramming and cell source………………………………………..……….4

Table 2: Autophagy fold change R+CQ and NLM+CQ stress data gathered from flow cytometry analysis……………………………………………………………………………39

Table 3: Autophagy fold change data gathered from western blot analysis…………………41

1. Introduction

1.1. PLEKHM2 Mutation Causes Dilated Cardiomyopathy (DCM) with Left Ventricular Noncompaction (LVNC)

Cardiomyopathies (CM) represent a heterogeneous group of diseases that compromise ordinary heart function. Defined by uncharacteristic chamber size and wall thickness, or functional contractility —mainly systolic or diastolic dysfunction in the absence of coronary artery disease, hypertension, valvular disease, or congenital heart disease. This wide group of heart diseases is classified into primary and secondary CM. Primary CM pathology is confined to the heart, whereas secondary CM is a result of a systematic complication, which is accompanied by a damage to the myocardium. Dilated cardiomyopathy (DCM) is a primary CM which could either originate from a genetic abnormality or may be acquired. It is defined by enlarged ventricles, normal left ventricular wall thickness, and systolic dysfunction. About a third of the cases are genetic, asymptomatic and commonly arise at ages of 40 to 59. Hence, genetic testing of family members can accompany traditional screening performed regularly by physicians for early detection and treatment [1] [2].

In the year of 2015, a group from Ben-Gurion University published an article about a novel subclass of DCM attributed to a mutation in PLEKHM2 gene, which results in DCM-LVNC [3]. Left ventricular noncompaction is a rare and newly discovered condition, wherein the embryonic myocardium doesn’t mature properly. Distinguished by significant trabeculation and deep intertrabecular recesses in the left ventricle interfering with systematic compaction [1]. The genetic mutation prevailed since the family is highly inbred and so, a recessive phenotype arose. Because of the disease, patients pass away prematurely at their teen years as a result of a heart attack. First, a scarring of the heart appears due to noncompaction of the myocardium, followed by a cardiac arrest due to the arrythmia worsened by the scar tissue accumulating on the left ventricle.

In the article published, a sequencing of genomic DNA from the blood reviled a mutation in PLEKHM2 gene in the affected siblings. Nucleotide deletion was found in Chr1:16055171_16055172delAG (GRCh37/Hg 19) in exon 12 which consequently lead to a translation of a shorter protein. Regularly, PLEKHM2 has an N-terminal RUN domain, two WD domains and a carboxy-terminal PH domain (fig. 1). The frameshift deletion occurs in the middle of the protein which is encoded by exons 10 through 12, thus a deletion of AG results either an elimination of PH domain or the skipping of exon 11 entirely, shortening the segment connecting WD and PH domains.

Figure 1: PLEKHM2 protein variants. Top – normal translation of the protein containing 3 domains – RUN, WD and PH. The mutation generates two variants, left - all domains remain, but exon 11 is skipped and right - incomplete translation halting in the mutation site. Modified from [3].

This group’s research focused on patient isolated fibroblasts and the discovery of the biomolecular mechanism which is responsible for the pathology. Primary fibroblasts from the DCM-LVNC patients exhibited abnormal subcellular distribution of endosomes marked by RAB5, RAB7 and RAB9, abnormal lysosomes localization and impaired autophagic flux.

1.2 Induced Pluripotent Stem Cells (iPSCs) as a DCM-LVNC Disease Model

Over the past four years, a PhD student Nataly Korover supervised by Prof. Smadar Cohen and Dr. Rivka Ofir, has been striving to generate a disease-in-a-dish model for DCM-LVNC. The goal was to decipher whether and how the PLEKHM2 mutation affects cardiomyocytes (CMs) in these patients. As alive human primary adult cardiomyocytes are not available, Nataly created a disease-in –a dish model by reprogramming patient fibroblasts into induced pluripotent stem cell (iPSC), followed by their differentiation into cardiomyocytes. Those

cardiomyocytes were investigated to decipher whether the disease phenotype was apparent in vitro and additionally explain why mutant PLEKHM2 leads to DCM-LVNC.

The process of iPSCs generation involves culturing adult cells in vitro and inducing a over expression of pluripotency genes according to the protocol generated by Nobel prize laureate Kazutoshi Takahashi and Shinya Yamanaka [4]. They cultured adult fibroblasts with four factors, Oct3/4, Sox2, c-Myc, and Klf4, under embryonic stem cells (ESC) culture conditions and generated the first lines of iPSCs. iPSCs closely resembled ESCs’ gene expression; highly expressing Oct3/4 and Nanog for instance, and down regulating lineage specific genes. Those four factors are known today as Yamanaka factors and are widely used for reprogramming protocols. Moreover, nowadays other somatic cells, like blood cells, were successfully reprogrammed into iPSCs which facilitates sample collection. iPSCs post another advantage as they could be transplanted autologously without causing graft rejection, in addition to personalized drug screening, development of tailor-made regenerative medicine and contribution to disease cure and exploration [5].

Reprogramming can be induced in a variety of methods categorized by integrating and non- integrating vectors. The first, is based on retroviral vectors, which insert their DNA into the host’s genomic DNA. While successful, it integrates randomly, and therefore might obstruct important genes resulting in mutagenesis. Clinically, this is an unappealing method. Therefore, non-integrating vectors are more desirable, accomplished by episomal vectors, Sendai virus (SeV) or mRNA transfection. Episomal vectors use components of a virus to facilitate transcription factors delivery into somatic cells. SeV is non-pathogenic to humans and doesn’t integrate with cellular genome and is more efficient than episomal vectors. mRNA transfections depend on RNA rather than DNA delivery to the cell, therefore the process is more complex as RNA decomposes quicker and requires delicate treatment [6].

1.2.1 DCM-iPSCs

As mentioned, reprogramming iPSC lines requires a biopsy from a patient and usually a healthy relative to set as a control. Commonly, skin fibroblasts are used for this procedure, which begins with insertion of transduction vector carrying Yamanaka factors. Later, the fibroblasts are plated

on a surface of mouse embryonic fibroblasts (MEFs) which promote pluripotent gene expression in the culture. iPSCs are identified initially by the colony morphology followed by isolation of numerous colonies, eventually using several assays to verify culture pluripotency: spontaneous differentiation into three germ layers, ectoderm, mesoderm and endoderm in vivo and in vitro, by teratoma induction in NUDE mice (containing defect in their immune system) and by embryonic body (EB) formation, respectively; detecting the expression of the pluripotent proteins and mRNA of Oct3/4, SSEA-4 and Tra-1-60 for instance. Karyotype examination is performed to ensure that while the cells proliferate in culture, they did not chromosomal aberrations; the process involves visualizing 46 chromosomes human cells during mitosis [4] [7] [5]. Furthermore, DNA sequencing was made to ensure that the newly generated patient`s iPSC lines contain the PLEKHM2 mutation.

The iPSC cells that used in this study [produced recently in BGU Regenerative Medicine and Stem Cell (RMSC) research center] originated from one healthy heterozygote sibling and two homozygote patients with mutation in PLEKHM2. Three clones were generated from each individual. In this study we used two clones from the healthy sibling (termed here P.1, P.2) and two clones each from a patient with mutation in PLEKHM2 (termed mP.1, mP2).

The clones studied are presented in table 1 – P.1, P.2, mP.1 and mP.2.

Table 1: iPSC reprogramming and cell source. Patient age and Reprogramming Clone gender Symptoms Cell source method

P.1 12 Healthy heterozygote Skin punch

P.2 Healthy heterozygote Skin punch 12 SeV Feeder dependent mP.1 16 Ventricular tachycardia Skin punch (grown on MEF) Connective tissue from Asymptomatic familiar CM mP.2 pacemaker replacement 13 checkout procedure

Another human iPSC (hiPSC) line which served as a control was BGU-iPSC, it originated from a layer of peritoneum that surrounds the abdominal organs from a patient that underwent gallbladder surgery [8].

1.3. Autophagy Autophagy is a homeostatic process ensuring intracellular removal of damaged proteins, organelles and pathogens by lysosomal degradation. Several forms of autophagy have been described, including macroautophagy, microautophagy, chaperone-mediated autophagy, and piecemeal microautophagy of the nucleus. They differ in their mechanisms and functions. In macroautophagy (hereafter referred to as autophagy) another key component, in addition to the lysosome, is the autophagosome. A fusion of the two organelles allows for the enzymes encapsulated within the lysosome to flow into the autophagosome carrying labeled substances for decomposition, to generate a larger combined organelle – the autolysosome. Other forms of autophagy mainly rely on lysosomal rather than autophagosomal involvement [9] [10]. The basic understanding of the molecular mechanism of autophagosome formation mainly originated from the study of a set of autophagy-related genes (ATG) identified from yeast genetic screens. This process was first discovered in yeast and found to be a highly conserved evolutionary system in eukaryotes [11]. Autophagy occurs at a basal, constitutive level and functions as a quality control system that can be up-regulated in response to cellular stresses, such as starvation. Moreover, it plays an essential role in cellular differentiation, cell death, and aging. Defective autophagy may promote certain human diseases such as cancer, neurodegenerative diseases, muscular disorders and pathogen infections [12]. 1.3.1. Autophagosome

The autophagosome originates in the cytosol from an enclosed double membrane portion known as a phagosome. A complex process allows its formation incorporating the mitochondria, for lipids surrounding the organelle, the plasma membrane, contributing membrane for phagophore production and the endoplasmic reticulum (ER), essential for phagophore formation and elongation [13]. Both organelle and soluble cargoes are internalized into autophagosomes, including mitochondria and ubiquitin [14]. Specifically in neurons, autophagosome biogenesis initiates at the tip of a growing neurite. The machinery mediating autophagosome maturation is

under spatiotemporal control and provides regulatory nodes to integrate nutrient availability with autophagy activity. A disruption in autophagosome generation could have serious repercussions on cellular homeostasis. Therefore, autophagosome formation is investigated widely; it is identified by proteins assembling around the autophagosome such as microtubule- associated protein light chain 3 β -II (LC3BII), p62 and beclin-1. Usually the identification of at least two proteins is customary [13] [10].

1.3.2. Lysosome

Lysosome, is additional important organelle in the autophagic process, as the lysosome carries over 60 different soluble hydrolases, allowing it to decompose each macromolecule in a cell. This organelle is formed by a vesicle budding from the Golgi complex combined with enzyme generated in the ER, referred to as endosome in its early stages of development. It matures increasing its acidity to a pH of 4.5 to 5.5, preparing for fusion with the autophagosome [15].

Lysosomal movement is escorted by motor proteins which interact with microtubules. Retrograde movement of the lysosome is, in most cells, from a positive to a negative charge upon the microtubule therefore to the cell nucleus. Whereas anterograde movement is in the exact opposite direction. With lysosomes, dynein controls retrograde movement and kinesin – anterograde movement [16].

In mammalian non-polarized cells, lysosomes concentrate mainly in the microtubule- organizing center (MTOC), and some distribute peripherally, even as far as plasma membrane and cell protrusions. In polarized cells such as neurons, lysosomes are found in all cytoplasmic domains including the soma, axon and dendrites.

As PLEKHM2 (also known as SKIP) comprises of the protein complex attaching the lysosome to kinesin, it is well expected that anterograde movement will be affected. A study showed that lysosomes are highly dispersed within wild type (WT) HeLa cells. While, a knock-out of a peptide which assists with lysosomal-kinesin interaction (myrlysin) resulted in perinuclear distribution of lysosomes. SKIP overexpression, on the other hand, directs lysosomes mainly to the periphery [17].

PLEKHM2

Figure 2: Lysosome movement within the cell [18]. Anterograde movement assisted by a protein complex connecting kinesin, a motor protein, and the lysosome [16]

Lysosome motility is also rather important in other systems like antigen presentation, neurotransmitter excretion and liver function. Lysosomes degrade labelled macromolecules and during an immune response they assists with decomposition of pathogens to generate epitopes for loading upon major histocompatibility complex (MHCII), allowing other immune cells to identify and battle pathogens. Neurotransmitter secretion requires lysosomal movement to the synapses, providing hasty response passing information between neurons [19].

1.3.3. DCM Fibroblasts and Autophagy

In study performed before by Muhammad E. et al. (2015), fibroblasts from sick patients (termed here mPLEKHM2 fibroblasts) were isolated in order to explain why PLEKHM2 mutation leads to the severe disease DCM-LVNC. By western blot analysis, they showed that the cells containing the mutated gene don’t generate a significant autophagic flux, quantified by amount of autophagosomes accumulated under treatment of the cells with leupeptin (inhibitors of cysteine, serine and threonine peptidases), while control fibroblasts do attain significantly higher amounts of autophagosomes post treatment with leupeptin, suggesting that mPLEKHM2 invokes impaired autophagy. Impaired autophagy may interfere with the ability of certain cells (like cardiomyocytes) to maintain homeostasis.

Disturbance in the lysosomal – motor protein interaction could result in an irregular distribution of the lysosomes. Since PLEKHM2 engages in lysosome-kinesin1 interaction, Muhammad et

al. (2015) examined whether the lysosomal motility was also affected. Indeed, immunofluorescent staining proved that mPLEKHM2 fibroblasts exhibit perinuclear distribution of the lysosomes as compared to control fibroblasts with higher dispersity of the organelles in the cytoplasm. Interestingly, the abnormal distribution of lysosomes in mPLEKHM2 fibroblasts resembled the pattern of lysosome distribution in myrlysin knockout HeLa cells and may contribute to the mechanism which underlies the disease pathology [17].

1.4. Neurodegenerative Diseases Neural diseases are a wide variety of mild to very severe illnesses affecting neural networks which could involve the central or peripheral nervous system (CNS or PNS). Most of known cases arise at an old age, but there are also juvenile onset cases. Approved therapies provide primarily symptomatic relief and do not dramatically modify disease course. Moreover, many treatments become ineffective over time and can even produce disruptive symptoms of their own. Thus, the urgent need to develop more effective treatments for neurodegenerative disorders is widely recognized. Although in many of these ailments, very little is known about the pathogenesis or progression, diseases like Alzheimer’s disease (AD), Parkinson’s disease (PD) and Huntington’s disease (HD) share several common features. Abnormal accumulation of certain proteins was suggested as one of the mechanisms which leads to neurodegenerative process [20] [21] [22]. Moreover, misfolded protein may induce regular protein misfolding and therefore spread to unaffected areas through the body. In AD for instance, amyloid plaques externalized in the brain parenchyma and around the cerebral vessel walls [23]. In PD, aggregates of α-Synuclein form in neuron cytoplasm located in the substantia nigra [24]. In brains of HD patients, intracellular deposit of polyglutamine-rich of huntingtin are found [25]. Genetic mutations or environmental factors, such as oxidative or metabolic stress, have been suggested to promote protein misfolding and aggregation in these neurodegenerative diseases. The mechanisms of protein aggregation have yet to be fully comprehended [20]. Animal models, isolation of cells, iPSCs and clinical cases assist in data collection and acquiring of knowledge.

1.5. Neural Disease Models Today, even finding a drug to ease patients’ lives is essential, therefore many studies are focused on creating models that will imitate the pathology as closely as possible and then test multiple drugs simultaneously to assess whether the neural cells survive and heal. In the past, a more common approach was generation of in-expensive animal models [26]. But in addition to ethical issues raised, these models have occasionally proven to be inaccurate [27]. For example, candidate drugs for neuroprotection verified on mice, were failed in translation to human patients [28]. Valuable drugs may be discarded after negative response in animal models. In the last ten years it became evident that human iPSC-derived neuronal cultures may serve as an adequate physiologically relevant model to study human brain diseases including neurodegenerative diseases. Once establishing such models, they will enable to screen new substances to serve as drugs for these devastating diseases. To generate such models, patient specific cells are isolated and reprogrammed into iPSCs. Inducing disease relevant cellular subtype differentiation, followed by proof of disease specific phenotype will enable creating a disease-in-a-dish model. Such models will permit testing of substances for their trophic or toxic effect on the cells. Disease-in- a-dish models will also enable to study the basic mechanisms of brain pathogenesis [7]. The process is simplified and explained in figure 3.

Figure 3: Neural disease models [7].

1.5.1. Neural Subtypes in Scientific Research

Motor neurons (MNs) and dopaminergic neurons have been the prime targets for differentiation from ESCs/iPSCs given their potential application in studying and treating neurodegenerative diseases such as ALS and PD. Control of movement of tissues and organs is achieved by MNs, which are located throughout the CNS in the cerebral cortex, brainstem, and spinal cord. Dopaminergic neurons are involved in diverse functions from sense and motion to emotion and reside in the olfactory bulb, cerebral cortex, hypothalamus, midbrain, and retina. Classification of neurons depends on their location throughout the body and the neurotransmitter they exert or react to. Neurons which utilize the same neurotransmitter but are confined to different brain regions are specified through very different molecular pathways during embryonic development. Thus, differentiation to a specific neuron subtype in vitro requires a custom- tailored protocol [29].

1.5.2. Motor Neuron Differentiation

A well-known, recently established protocol for neural differentiation of ESCs and iPSCs is dual SMAD inhibition using small molecules. Suppressing pluripotency networks transforming growth factor beta (TGFβ)/activin and bone morphogenetic protein (BMP) via SB431542 (SB) and Noggin/LDN193189 (LDN) (fig. 4). Blocking of these pathways is also required to prevent trophectoderm formation, and impede the formation of mesendoderm and nonneural ectoderm. A modification of such a differentiation entails the activation of WNT pathway, through inhibition of glycogen synthase kinase 3 (GSK-3β) enzyme with the assistance of small molecule, CHIR99021 (CHIR). These three factors applied for only 6 days promote neurulation, guiding the iPSCs toward a neuroepithelium (NEP) multipotent culture in which every individual cell is a neural progenitor cell (NPC) [30]. NPCs can either form a neurosphere and cultured in suspension, later dissociated and matured or maintained in a monolayer followed by maturation of the cells towards a specific lineage.

In this stage, other small molecules aid in shepherding NPCs to differentiate into MNs through motor neuron progenitor cells (MNPCs). Generation of MNPCs requires retinoic acid (RA) which promotes hindbrain and anterior spinal cord patterning as implicated during CNS development [31], while addition of smoothened agonist (SAG) allows cell proliferation. Their combination generates midbrain/hindbrain dopaminergic neurons [32] [33] [34].

Later, maturation into spinal MNs is achieved by the combination of compound E, DAPT, SAG, dibutyryl cyclic AMP (db-cAMP), RA, ascorbic acid (AA),glial-derived neurotrophic factor (GDNF) and brain-derived neurotrophic factor (BDNF) [35] [36] [37] [26]. Mature MNs are electro-physiologically functional, exerting spontaneous firing potentials, express MN-specific markers such as isl1, HB9, ChAT as well as neuron specific markers like β-III tubulin (Tuj1) and

MAP2 [38] [26].

Figure 4: Proposed model for neural induction using dual SMAD inhibition [35].

1.5.3. Autophagy and Neurodegeneration

An estimated 30% of newly synthesized proteins are incorrectly folded and degraded under normal conditions [39]. Regularly, cells are able to efficiently utilize their protein quality control system to decompose misfolded proteins and maintain the protein homeostasis. This system includes chaperones, ubiquitin and autophagy. Chaperones recognize, assist in refolding, prevent aggregation, and help repair misfolded proteins [40]. Chaperones also interact with ubiquitin to degrade misfolded proteins via ubiquitin-proteasome system [41]. Autophagy collects proteins, pathogens and organelles for degradation constitutively; the process is amplified upon starvation.

Autophagy is an essential cellular degradation pathway in neurons. When defective, autophagy is sufficient to induce neurodegeneration, as aggregated proteins might overwhelm the protein

quality control system, further accumulate, induce cellular stress and eventually stimulate neurodegeneration. For that reason, abundancy of studies focus on the relation between neurodegenerative diseases and autophagy.

In AD, functional abnormalities of autophagosomes and lysosomes were found to precede pathological changes in AD brains. The most common gene affected in early onset familial AD is PS1, which is essential for autophagy. Therefore, it comes as no surprise that mutations in PS1 impair autophagic pathways [42] [43]. PD is the second most common neurodegenerative disease and mutations in LRRK2 are autosomal dominant and inhibit autolysosome fusion, resulting in accumulation of proteins intracellularly [44]. Also, mutation in TMEM230 triggers a reduction in autophagic cargo degradation and secretory autophagy [45]. C9orf72 mutation causes the most common cases of ALS and frontotemporal dementia (FTD; it regulates autophagy and lysosomal homeostasis through interactions with SMCR8, ULK1 and Rab-GTPases [46] [47] [48].

As mentioned, PLEKHM2 is also a protein involved in autophagy. A mutation in this gene resulted in impaired autophagy as DCM-LVNC fibroblasts were unable to generate as many autophagosomes under stress induction, compared to a control. It was also found that PLEKHM2 is highly expressed in the brain [3], therefore a mutation in this gene might have a great impact on the neuronal cell’s ability to execute autophagy properly.

1.5.3.1. Stress Induction

Widespread neurodegeneration in specific brain regions is induced by deficits in protein quality control systems and other factors, such as inflammation and oxidative or metabolic stress and pathogenic disease-associated mutations [21]. In order to simulate this environment within the original tissue, many times researchers choose to use stressors imitating cellular stress to elucidate mechanisms of pathogenesis and disease progression [49].

Autophagy is upregulated under stressing conditions, such as starvation (fig. 5), allowing the researcher to visualize cellular response in sick cells as compared to control cells. Generally, proper response constitutes an accumulation of autophagosomes and autolysosomes, lysosomal and cytosolic acidification, retrograde movement to permit fusion and down regulation of

protein synthesis (represented by mammalian target of rapamycin complex1 - mTORC1), as the cell recycles proteins in autophagy [50].

Common stressors include generation of reactive oxygen species (by H2O2 e.g.), starvation (rapamycin, nutrient deprived media e.g.) and agents inhibiting lysosomal acidification (by chloroquine e.g.).

Figure 5: Proposed mechanism by which lysosomal positioning coordinates mTOR signaling and autophagy [50]

2. Research Hypothesis and Objectives

2.1. Research Hypothesis

It has been recently shown that mutation in PLEKHM2 gene causes recessive dilated cardiomyopathy (DCM) with left ventricular noncompaction (LVNC) in a large Bedouin family in the Negev, Israel. The DCM-LVNC patients pass away as early as their 20’s due to heart failure, therefore indicating the importance of PLEKHM2’s to the well maintenance of heart tissue. Specifically, the PLEKHM2 protein (sometimes referred to as SKIP) is an autophagy regulator and has been found vital for endocytic trafficking.

Autophagy is a mechanism responsible for maintaining cellular homeostasis. The main two organelles orchestrating this complex process are the autophagosome and the lysosome. Their fusion allows enzymes within the lysosome to encounter the proteins marked for disintegration retained by the autophagosome, those are decomposed and recycled for amino acid reuse. PLEKHM2 integrates in a protein complex designed to join lysosomes to kinesin-1, allowing their movement to the cell periphery as a part of the autophagic process [16]. As a result of the mutation, DCM-LVNC patient fibroblasts, in contrast to control fibroblasts, exhibited perinuclear distribution of the lysosomes and impaired autophagy flux [3].

A connection between impaired autophagy and neurodegenerative diseases was described numerous times formerly. In ALS and frontotemporal dementia (FTD), the most common mutation causing these diseases occurs in C9orf72, which regulates autophagy and lysosomal homeostasis through interactions with SMCR8, ULK1 and Rab-GTPases. In certain Parkinson’s disease (PD) patients, a mutation in TMEM230 triggers a reduction in autophagic cargo degradation and secretory autophagy [48]. These phenomena are well-known due to a vast variety of researches.

Interestingly, a gene expression assay showed the brain tissue expressed the higher amount of PLEKHM2 relative to the heart, lungs and liver [3].

We hypothesize that mutated PLEKHM2 (mPLEKHM2) iPSCs-derived neurons, when compared to healthy iPSCs-derived neurons, will present changes in their phenotype due to impaired autophagy.

To test our hypothesis, healthy control and patient iPSCs were differentiated into neurons using a chemical induced monolayer differentiation protocol. Biochemical and phenotypic parameters assays were studied in both types of neurons to determine whether dissimilarity among the mPLEKHM2 and the healthy differentiated cell lines exists.

2.2. Objectives

• Optimizing the protocol for monolayer directed differentiation of iPSCs into motor neurons.

• Determine autophagic flux difference between neuronal culture of mPLEKHM2 and control cell types.

• Assess functionality the motor neurons using parameters relevant to neurodegenerative diseases like: survival following stress conditions, autophagy induction, media

deprivation and spontaneous neuronal activity.

3. Materials and Methods

3.1. Materials Matrigel®-coated plates were from BD Biosciences (San Jose, CA). ROCK inhibitor (Y-27632) from R&D Systems, Minneapolis, MN; CHIR99021, SB-431542, LDN-193189, DAPT and compound E were purchased from Tocris, United Kingdom; Cell culture reagents: NutriStem® hESC XF Culture Media, Penicillin-Streptomycin-Amphotericin B (PSA), Fetal Bovine Serum (FBS) were from Biological Industries (Kibbutz Beit-Haemek, Israel). B27 supplement, N-2 supplement, MEM Non-Essential Amino Acids Solution (NEAA), StemPro® Accutase® Cell Dissociation Reagent, Versene Solution, Iscove’s Modified Dulbecco’s Medium - IMDM (- thioglycerol, -2-mercaptoethanol) and F-12 (HAM) were from GIBCO (Gaithersburg, MD). SAG was purchased from Cayman Chemical Company (Michigan, USA). brain-derived neurotrophic factor (BDNF) and glial-derived neurotrophic factor (GDNF) were from PeproTech Asia (Rechovot, Israel). CYTO-ID® Autophagy Detection Kit was from ENZO Life Sciences (New York, USA). Presto Blue - Cell Viability Reagent, was from Invitrogen (Karlsruhe, Germany). Other reagents, unless specified otherwise, were from Sigma-Aldrich (Rechovot, Israel). All reagents were of analytical grade. 3.2. Cell Culture hiPSC lines were cultured in NutriStem® hESC XF medium (Biological Industries) in feeder- free conditions on Matrigel®-coated plates (BD Biosciences). The quality of hiPSC lines was routinely assessed by flow cytometry of pluripotent marker, Oct3/4. Additionally, a mycoplasma evaluation was performed regularly. All Cells were cultured under standard conditions at 370C and 5% CO2, in a humidified incubator. 3.3. Monolayer Differentiation iPSCs were maintained in NutriStem medium on Matrigel and passaged at 80% confluence at a ratio of 1:6 to 1:15 using Versene. For differentiation generating NEP stock, split iPSCs were seeded on 6 well Matrigel coated plates at a density of 104 cells/cm2 (105cells) or 1.5*104 cells/cm2 for mP.1 as its doubling rate is slower. After 2 days or arrival at 30-40% confluence, neural induction began with stage 1 medium (S1M), containing IMDM: F12 1:1, 2% B27, 1% N2,

NEAA and PSA, 10μM SB, 3μM CHIR and 0.2μM LDN. Medium was exchanged daily for 6

days. NEP cells were dissociated to single cells using Accutase 5min and seeded at 1.25*105 or

1.5*105 cells/cm2 when thawed with 5µM ROCK inhibitor (Y-27632) on 5μg/cm2 laminin coated wells. For imaging purposes, cells were seeded at 5*104 cells/cm2. Stage 2 medium (S2M) contained S1M constituents with an addition of 0.1µM all-trans retinoic acid (RA) and 1µM smoothened agonist (SAG). Half of S2M was exchanged every other day for 6 days. On day12 (D12) of the differentiation, the medium was changed completely to stage 3 medium (S3M) for maturation. The medium contained IMDM: F12 1:1, 2% B27, 1% N2, NEAA and PSA, 2.5µM

γ-secretase inhibitor (DAPT), 0.5µM RA, 0.1µM compound E, dibutyryl cyclic AMP (db-cAMP) and SAG, 200ng/ml ascorbic acid (AA) and 10ng/ml BDNF and GDNF. Half of S3M was exchanged every 2 days for the remainder of the differentiation.

3.4. Karyotype Analysis Cell were cultured in 6 well plates and reached a confluence of 50-70%, detached from the wells with 1ml versine for 4min at 37°C and 5% CO2, before treatment with 0.1μg/ml colcemid solution (Biological Industries) for 1hr at 37°C and 5% CO2. Metaphases were obtained adding hypotonic solution of 0.075M KCl in DDW 30min at 37°C and 5% CO2, and fixated washing with 5ml ice-cold 3:1 methanol:glacial acetic acid solution 3 times. Karyotype analysis with G- banding method was carried out by an outside professional facility - AMG Lab (Herzeliya Pituach, Israel). 3.5. Mycoplasma Contamination Examination The absence of mycoplasma contamination was confirmed by PCR, using Hy-Mycoplasma PCR (hylabs) according to manufacturer’s instructions. Briefly, spent iPSC medium was centrifuged at 16,000g, 10°C for 5min and the pellet resuspended and added to the PCR mix. PCR was performed with VeritiTM Thermal Cycler (Applied Biosystems, CA, USA) under the following conditions: 94 °C for 1 min followed by 35 cycles of 94 °C for 30s, 63°C for 1min and 70 °C for 45s, then 72 °C for 10min and 4 °C for holding. Samples were loaded and run on a DNA gel to visualized amplification of a negative or a positive strand of mycoplasma DNA.

3.6. Flow Cytometry Quantification

Cells were dissociated into a single-cell suspension using versene for iPSCs or Accutase for differentiated cells and fixed using the Foxp3 / Transcription Factor Staining Buffer Set (eBioscience, San Diego, CA) according to manufacturer's instructions. Cellular marker quantification was performed using NovoCyte NovoSampler Pro (Acea Biosciences, Santa Clara, CA), utilizing FlowJoTM software (BD Life Sciences) for flow cytometry analysis. Primary antibodies used were anti Oct3/4 (sc-2004, 1:100, Santa Cruz), Sox1 (ab87775,1:500, Abcam), Nestin (ABD69,1:500,Sigma-Aldrich), Tuj1 (T8660,1:1,000, Sigma-Aldrich), GFAP (ab7260,1:1,000,Abcam) isl1 (ab178400, 1:100, Abcam), MAP2 (M1406,1:500, Sigma-Aldrich). Secondary antibodies were: Goat anti-mouse Alexa Fluor 488 (A-11029, 1:500, Thermo Fisher), Goat anti-Rabbit Alexa Fluor 633 (A-21071, 1:500, Thermo Fisher). Median fluorescence intensity (MFI) was calculated for each representative MFI histograms, and fold change calculations consisted of dividing treated cell MFI in untreated control MFI.

3.7. Autophagy Flux Detection

For autophagy measurements, iPSCs and differentiated neural cultures were treated according to CYTO-ID® kit (Almog) manufacturers’ protocol. Briefly, iPSCs were seeded in 12 well plates at a density of 4*104 cells/cm2 or 4.5*104 cells/ cm2 for mP.1 and cultured regularly for two days and treated on the second day, differentiated cells were seeded according to the differentiation protocol described above and treated 1 day prior to the experiment. Stress treatments consisted of 500nM rapamycin and 20μM chloroquine for 20hr or F12 (HAM) nutrient media from now forward - nutrient limited media (NLM) and 20μM chloroquine for 4hr. iPSCs were detached using versene and differentiated cells – Accutase, washed with assay buffer X1 supplemented with 5% FBS and pelleted at 250g for 5min. Incubated for 30min at 37°C, 5% CO2 with CYTO- ID® Green Detection Reagent (1:2000), washed with assay bufferX1 supplemented with 5%FBS and analyzed using flow cytometry.

3.8. Microelectrode Array (MEA) Assay Cells were plated on 24-well MEA plates (Axion BioSystems) coated with 0.1% polyethyleneimine (PEI) and 5μg/cm2 laminin at day 6 of differentiation (NEP). At a plating

density of 1.25*105 cells/cm2 or 1.5*105 cells/cm2 when thawed and differentiated according to the protocol stated above (chapter 3.3). Spontaneous activity was measured every 2-3 days for 15min on the Maestro MEA platform (Axion BioSystems, Atlanta, GA). Waveform events were identified using adaptive spike threshold crossing with a standard deviation (sd) of electrode noise set at 6. A minimum of five spikes per minute was used to include events for analysis. 3.9. Western Blot Cells were cultured and collected for protein extraction in ice-cold radioimmunoprecipitation (RIPA) buffer (Cell Signaling) supplemented with 1mM phenylmethylsulfonyl fluoride (PMSF). Total protein quantification was performed using micro BCA protein assay (Pierce

Biotechnology). 20μg total protein samples were separated on a mini-PROTEAN TGX gel (Bio-

Rad, Hercules, CA) for 1hr and 15min under 100V current, and then transferred to nitrocellulose membranes (Bio-Rad) 45min, 100V. Blocked for 1hr in a 5% BSA (Millipore, Bedford, MA), then incubated overnight with a primary anti-LC3 (nb100-2220 ,1:500, Novus Biologicals), anti- p62 (P0067,1:500, Sigma-Aldrich) and anti-GAPDH (G9545 ,1:1,000, Sigma-Aldrich), followed by 1hr secondary goat anti-rabbit IgG-HRP (sc-2004, 1:5,000, Santa Cruz) and finally developed with EZ-ECL kit (20-500, Biological Industries). The signal was detected using Fusion Solo X (Vilber Lourmat, Collegien, France) and densitometric analysis was carried out using imageJ software (U. S. National Institutes of Health, Bethesda, MD, http://imagej.nih.gov/ij/). Band intensity was normalized to GAPDH. 3.10. Immunocytochemistry

Cells were fixed with 4% formaldehyde for 15 min, blocked for 1hr in 5% BSA (Millipore, Bedford, MA) with 0.1% Triton-X 100 in PBS. Then, incubated overnight with primary antibodies against Oct3/4 (sc-5279, 1:100, Santa Cruz), LC3B (nb100-2220, 1:500, Novus Biologicals), LAMP1 (D2D11, 1:500, Cell Signaling Technology), (T8660,1:1,000, Sigma- Aldrich), GFAP (ab7260,1:1,000,Abcam). Followed by 4hr incubation with secondary antibodies: donkey anti-rabbit Alexa Fluor 594 antibody (711-585-152, 1:500, Jackson ImmunoResearch) and donkey anti-mouse Alexa Fluor 488 antibody (715-545-150, 1:500, Jackson ImmunoResearch). After a brief wash, stained with NucBlueTM (R37605, Themo Fisher Scientific) for nuclei detection. Fluorescent images were acquired using Nikon C1si laser

scanning confocal microscope abb. LSCM (Nikon, Tokyo, Japan) and EVOS® FL (AMG, Bothell, WA).

3.11. Metabolism Assay Cell viability in iPSCs-derived neuronal culture was measured by PrestoBlue® Assay according to the manufacturer’s protocol. On DIV18, the cells were incubated for 3 hours at 37°C and 5% CO2. with half a fresh S3M supplemented with 10%v/v PrestoBlue® (Thermo Fisher Scientific). The PrestoBlue® metabolism was expressed as fluorescence intensity units and measured on a SpectraMax® iD3 Multi-Mode microplate reader (Molecular Devices, Sunnyvale, CA) with excitation/emission = 560 nm/590 nm. 3.12. Statistical Analysis Statistical analysis was performed with GraphPad Prism version 6.07 for Windows (GraphPad Software, San Diego, CA). Results were presented as mean ± SEM from at least two independent experiments. Two-tailed student's t-test and one-way ANOVA for repeated measures with Tukey’s post-hoc test were used appropriately. Values of p< 0.05 were considered significant.

4. Results

4.1. Characterization of mPLEKHM2 iPSC (DCM-iPSC)

Previously, biopsies and patient fibroblasts were brought into our lab. Those were reprogrammed into patient specific iPSCs. In the present research, 4 of these clones were used – two of a healthy heterozygote sibling who presented no DCM-LVNC phenotype, and two of the homozygote patients who suffered from the disease referred to from now on P.1, P.2 and mP.1, mP.2, respectively. The mutation results in a shorter PLEKHM2 protein, translated either with or without PH domain. iPSCs allow researchers to proliferate mutated cells to engineer disease models in vitro, and this work sought to differentiate them to neurons. But first, as reprogramming may cause alterations in the DNA, such as chromosomal aberrations and polyploidy, diploid genetic material consisting of a total of 46 chromosomes should be verified. All cell lines exhibited a normal karyotype during a standard G-banding test in relevant passages (fig. 6a), and highly expressed pluripotent marker Oct3/4 throughout the study (>90%, fig. 6b-c). Cells were mycoplasma free as checked routinely (Appendix fig. 12). Those allowed further research to be conducted.

Figure 6: iPSC lines are self-renewing and have not accumulated abnormal aberrations. a Karyotypes of 4 cell lines in this research. Top – control clones. Bottom – mPLEKHM2 patient clones. b Representative graph of pluripotency marker, Oct3/4, expression. C Immunofluorescent image of Oct3/4 expression in culture (left-DAPI, right – Oct3/4). Scale bar 150μm.

4.2. MN Differentiation Motor neuron differentiation was executed according to modified protocols described [51] [37] and schematically shown in fig. 7a. Neuralization is induced using stage 1 medium (S1M) containing the small molecules CHIR, LDN and SB. As described previously (chapter 1.4.2), all three factors assist in inhibition of pluripotency; CHIR activates WNT, LDN and SB inhibit the BMP and TGFβ pathways respectively. Therefore, avoiding differentiation into trophectoderm and mesoderm, and allowing generation of primitive neural stem cells in a layer called neuroepithelium (NEP). Morphologically, it is a very dense layer of round quickly multiplying cells (fig. 7b). Next, stage 2 medium (S2M) induces the differentiation into a motor neuron progenitor cell (MNPC) culture with the addition of SAG and RA (fig. 7a). Cells continue to proliferate and

elongate (fig. 7b). Proliferation halts at stage 3 medium (S3M) and maturation begins using 8 factors (detailed in section 1.5.2), guiding MNPCs towards mature MN fate (fig. 7a). Maturation may continue up to 56 days for experimentation if the cells don’t detach as they are very sensitive to culture condtions. An upregulation of neural proteins was witnessed by FACS analysis (fig. 7c). Pluripotency was down regulated as Oct3/4 expression decreased from 73.3% in iPSCs to 13.6%, 0.96% and finally 3.3% in NEP, MNPCs and iMNs, respectively. NEP is defined by Sox1 and nestin high expressing cells as observed (74.9% and 85.5%, correspondingly). Those markers are downregulated in later stages of differentiation, while a rise in Tuj1, GFAP and isl1 occurs. Tuj1 is β-III tubulin seen particularly in neurons, GFAP labels astrocytes, also in the neural culture, and isl1 is a motor neuron specific marker. iMNs were 64% Tuj1+, 28.3% GFAP+ and 5.8% isl1+ (fig. 7c). Expression of lineage specific proteins in mPLEKHM2 and control cell lines in both NEP (fig. 7d) and iMNs (fig. 7e) stages weren’t significantly different (p>0.05), except one marker of two lines during iMNs stage. BGU-iPSC iMN culture contained more astrocytes (labeled by GFAP) than P.1. BGU-iPSC [8] is another human iPSC cell line used as a control, beside the two- heterozygote healthy relative cell lines, P.1 and P.2. P.1 culture was less dense and therefore the differentiation hadn’t been as successful, resulting in reduced number of neural cells overall. Collectively, the comparison above implies that PLEKHM2 mutation does not interfere with iPSC differentiation towards MN.

Figure 7: Monolayer MN differentiation. a Differentiation outline; Four media changes occur. S1M causes neurulation, S2M generates MNPCs and S3M matures the culture into MN. b Representative images of four different stages of the differentiation. Scale bar: iPSCs 400μm, MNPCs, iMNs 200μm and NEP, MNs 100μm. c Protein expression during differentiation (n>3 except MNPCs Oct3/4 and isl1 n=2) d Expression of relevant proteins in NEP (n>3 except P.1 n=1) e and iMNs (n=2 or isl1, mP.1, mP.2 n=1). Mean±SEM presented. Multiple comparisons statistical analysis was performed by one-way ANOVA, comparisons between groups performed by Tukey test (* p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001).

4.3. Stress Induced Autophagy Flux Since PLEKHM2 influences autophagy [3] [16] [17], control and mPLEKHM2 cell lines were examined to determine whether this activity was compromised. A well-known stressor is rapamycin (R) that mimics starvation in the cells through inhibition of mTOR. Nutrient deprivation (termed here NLM) is also a popular method to generate stress, as the cell begins recycling nutrients. Therefore, a rise in autophagosome numbers is expected under those treatments. Chloroquine (CQ) alkalinizes lysosomal pH, interfering with its normal function in degradation. A combination of either R+CQ or NLM+CQ treatment is expected to exhibit an accumulation of autophagosome organelles in the cells.

4.3.1. Flow Cytometry

A simple method to detect autophagosomes is through fluorescent labeling of the organelles and analyzing the cells with a flow cytometer machine. CYTO-ID®, a commercial kit, was used for this experiment assessing either the amount or size of autophagosomes in each individual cell. All cell lines were differentiated and taken during four time points to document autophagosome accumulation under R+CQ stress induction (fig. 8); NLM+CQ was carried out only on iMNs (fig. 8).

Figure 8a presents fold change of autophagosome accumulation compared to untreated cells throughout the days of differentiation. Commonly, the trend shows a low fold change during iPSC stage, followed by a great impact on NEP cultures, MNPCs are the least affected differentiated cells and iMNs react to the stress induction more severely. When looking at each differentiation stage separately (fig. 8b), almost no difference is detected between the MNPC lines. P.2, mP.1 and mP.2 accumulate a similar amount of autophagosomes as iPSCs, but P.1 is significantly different from them as it accumulates about 2-fold more autophagosomes. Control lines retain more autophagosomes than mPLEKHM2 lines during NEP stage, P.1 closer to the mPLEKHM2 but still slightly higher. iMNs only shows that P.2 conserves more autophagosomes than P.1. Average fold change of each stage chronologically (iPSC, NEP, MNPC, iMN) is as follows 1.7, 2.3, 1.2 and 2.3 respectively. Therefore, NEP and iMN stages generated a great interest for further investigation.

NLM+CQ stress induction was performed on iMNs (fig. 8c) and a similar trend to R+CQ stress induction was apparent; mP.2 produces more organelles than mP.1, and P.2 creates more organelles than P.1 and mP.1, but the differences are non-significantly. It was clear that the treatment generates a response, but this kit didn’t allow to record a clear statistically significant difference between the control and the mPLEKHM2 cell lines, hence, another technique was employed.

Figure 8: Autophagy flux using CYTO-ID® assay. a Divided by cell line throughout the differentiation. b Divided by differentiation stage. c D18 iMNs reaction to rapamycin and NLM stress induction. Fold change is defined as treated median fluorescence intensity (MFI) divided by control (DMSO) MFI. Mean±SEM, multiple comparisons statistical analysis was performed by one-way ANOVA, comparisons between groups performed by Tukey test n>3 (except P.1 MNPCs n=0, and iMNs n=2).

4.3.2. Western Blot

As P.2 NEP cells presented the highest fold change difference in comparison to mPLEKHM2 NEP cells using CYTO-ID®, further inspection of this cellular homeostatic state was tested by quantifying LC3B and p62 employing western blot analysis. LC3B and p62 were chosen to indicate autophagosome accumulation within the cells, as both of which are attached to a mature autophagosome.

Western blot analysis of NEP culture supported the trend seen in flow cytometry analysis. The two stress treatments seem to provoke a similar response, with a lower production of autophagosomes by quantified expression of LC3B protein in mPLEKHM2 cells (fig. 9). R+CQ induced a more intense reaction as in healthy cell lines, the LC3B expression rose by 2.33 on average as compared to mPLEKHM2 lines with 0.57 average. This tendency was also seen in LC3B expression under NLM+CQ stress (control lines 2.35, mPLEKHM2 lines 1.17 average). p62 doesn’t provide a clear image, as mP.1’s production of the protein is as high as the control cells. However, when looking at the average fold change of the control and the mPLEKHM2 of p62 under R+CQ stress, control lines’ autophagosome flux remains more excessive (control lines 1.54, mPLEKHM2 lines 1.38).

Figure 9: Western blot analysis of NEP. a Autophagosome fold change represented by p62 and LC3B under stressors, R+CQ and NLM+CQ. b Raw western blot membranes. Mean±SEM presented. Multiple comparisons statistical analysis was performed by one-way ANOVA, comparisons between groups performed by Tukey test n=3 (except P.1 n=2).

4.4. Functional Tests Inspection of functional aspects of the neuronal cultures were desired. First, metabolism was examined and later, spontaneous activity recorded in a MEA plate. 4.4.1. Cellular Metabolism PrestoBlue is a solution containing resazurin compound which permeates cellular membrane without harming the cells and is reduced by mitochondrial enzymes of viable cells to a fluorescent molecule, resorufin. The shift from blue to red-pink fluorescence can be quantified using either fluorometric or spectrometric method, allowing to visualized and quantify viable cells performing metabolism regularly [52] [53].

iMNs were chosen for cellular metabolism examination because they present the closest stage of neural culture to MN inspected in this article. Additionally, their autophagic flux was affected by the PLEKHM2 mutation. Metabolism per DNA presented a metabolic rate for each cell line quantified by arbitrary fluorescent unit (AFU) of PrestoBlue divided by AFU of Hoechst. Fig. 10a displays cell specific metabolic rate in basal state and under R+CQ starvation treatment. When dividing the cell lines into skin punch origin cells and connective tissue and omental cells we may see a trend of very high metabolic rate in the latter and lower in the former. The first group ranges between 1.32 to 6.70, in a basal level, as the second group is around 20 (fig.10a). Starvation treatment harmed cellular viability, with loss of up to 94% of mP.2 viable cells in 20hr treatment. The least impacted cell line is mP.1 who only lost 1% of viable cells under treatment. P.1 was the only significantly influenced cell line with 39% viable cells post treatment. Metabolism in BGU-iPSC and mP.2 has decreased immensely, 74% and 94% respectively (fig. 10b-c). Because of those findings, BGU-iPSC has proven to be an inadequate control for mPLEKHM2 cells but sufficed when no other control was available, as mP.2 behaves similarly to this line at least metabolically (Appendix fig. 15). When comparing the fold change values of the two lines gathered by CYTO-ID® flow cytometry analysis, no significant difference between is found in stages NEP and iMN under both treatments (data not shown).

Figure 10: iMNs D18 metabolism assay. a Cellular metabolism divided by total DNA in the cell. b Loss of viable cells. R+CQ treated cells compared to untreated cells - 100% viability. c Dividing the graph above into cells from the skin punch (left) and cells from connective tissue and BGU-iPSC (right). Mean±SEM presented. Two-tailed student’s t-test n>3 (except mP.2+ n=2).

4.4.2. iPSCs-derived MN Activity To test electrophysiological function of the neural culture, microelectrode array (MEA) method was chosen. Cells exerting action potential spontaneously are recorded by the 16 electrodes in a 24well MEA plate and visualized. In this type of differentiation, D6 NEP are plated onto a PEI and laminin coated well (fig. 11a) and recorded every 2-3 days. In mPLEKHM2 cells, neuronal activity peaked at D30-D33 of differentiation (MN) with mP.1 being the most active cell line, average of 1787 spikes/recording amounting to 119 spikes/min. At D33 mP.2 exerted an average of 352 spikes/recording (23.5 spikes/min). BGU-iPSC cells presented a rise in firing potential during D20 (iMNs) with 136 spikes/recording (fig. 11c). mPLEKHM2 lines fired signals with irregular rate with a very high frequency. Only preliminary results exist for P.2 activity, with one biological repetition which recorded constant firing rate of every 200s during D18 (fig. S444). It is clear that the differentiation protocol has proven successful in generating active MNs and the these preliminary results imply that differences in electric functionality between the cells exists.

Figure 11: Spontaneous activity within neuronal cultures. a illustration presenting D6 cells plated on MEA plate for further differentiation. b Representative image of iMNs inside a MEA well, specifically D22 mP.1, morphologically like motor neurons. Scale bar 400μm. c Neuronal spiking d and bursts during the differentiation. Recording time was 15min, presenting mean ± SEM n=2.

5. Discussion

In this study, we strived to find a connection between PLEKHM2 mutation and impairment of autophagy in neural culture, derived following differentiation of iPSCs generated from diseased patients. In the process, we have successfully differentiated mPLEKHM2 and control iPSCs into MNs (64% tuj1+ and 6% isl1+), using a novel protocol that was brought to our laboratory and executed solely for this project. Our derived cultures were heterogeneous, as expected from many differentiation protocols, with the lion’s share of cells other than neurons being glial cells, specifically astrocytes, consisted of about 30% of the culture. Therefore, the results refer mostly to neuronal cells.

5.1. A Mutation in PLEKHM2 Does Not Impact Neural Differentiation First and foremost, identification of protein expression relating to specific lineage was required during the differentiation. A significant downregulation in pluripotency gene, Oct3/4 is apparent throughout the process (p<0.0001); a rise in neural culture genes, tubulin β-III and GFAP (used commonly to distinguish neural differentiation) and a significant increase in motor neuron specific protein islet-1 (p<0.01), were presented in figure 7c. Evidently, control lines (P.1, P.2 and BGU-iPSC) and mPLEKHM2 lines (mP.1 and mP.2) successfully differentiated into NPCs (NEP) and iMNs, with no significant difference between the lines. In NPCs, Sox1 and nestin were highly expressed as expected (fig. 7d), and the iMN culture contained both neurons and astrocytes with a subpopulation of motor neurons (fig. 7e). This finding emphasizes that the PLEKHM2 mutation doesn’t affect iPSC differentiation into MN lineage pathways, nonetheless biochemical and functional impairments could still arise. Furthermore, iMN culture was morphologically similar to rat E18.5 isolated spinal cord neural culture after 20 days in vitro (DIV20). Neurons appear with a small round soma and a long axon, when dense, the somas clump together (Appendix fig.13). BGU-iPSC and P.1 iMNs were significantly different in GFAP expression (34.5% and 21.5% respectively) but we think this was due to a low-density culture of P.1 which resulted in less differentiation, underlining the importance of high-density cultures for neural differentiation [35] [54].

5.2. Stress Induction of mPLEKHM2 Cells Results in a Modest Autophagosome Flux Previously, primary mPLEKHM2 fibroblasts subjected to leupeptin treatment presented reduced amounts of autophagosomes when compared to control fibroblasts [3]. Leupeptin inhibits enzyme activity therefore helps to visualized cellular production of various transient components, such as LC3B-II and p62. Both of which attach to a mature autophagosome labeled to preparing for fusion with the lysosome [10] [13]. Since the mutation in PLEKHM2 induces this deviation from homeostasis in fibroblasts, we hypothesized that a similar effect would be apparent in iPSCs-derived neurons from these diseased patients. Such an abnormality could be disastrous in neurons as those are highly sensitive cells, using autophagy for neurotransmission and assist in transporting components to the growing axon during neural maturation [12] [55]. Dysregulation of autophagy in a mature neuron could be disastrous as evading homeostasis might provoke amyloid formation, for example, and possibly lead to pathogenesis of a neurodegenerative disease. As seen during the differentiation process, no significant difference was detected on protein expression levels between the cell lines. Nevertheless, autophagic impairment might still be at hand. For that purpose, stress induction was applied to the cells examined. Reaction to stressors indicates the response of the cells of interest to the environment from which those cultures originate. Rapamycin encourages autophagosome production, as it simulates starvation, similarly to media deprivation. Chloroquine alkalizes the lysosome, therefore inhibits its function. While utilizing CYTO-ID® commercial kit for flow cytometry to investigate the four stages of differentiation, we found mPLEKHM2 cells gravitate towards a reduced accumulation of autophagosomes under R+CQ and NLM+CQ stress induction (fig. 8). The former induced a more acute reaction, as the differences amid control and mPLEKHM2 lines is the biggest. With iPSCs and MNPCs presenting the lowest fold change compared to NEP and iMNs (table 2). Therefore, autophagy might be more critical at those stages of differentiation and require further inspection. NEP is the first stage following iPSCs, they form a uniform layer of round cells, consisting mostly of their nucleus (fig. 7b), hence those cells still possess the ability to proliferate and do so rapidly. Also reinforced by Oct3/4 expression, which persists at this stage with about

13.62% expression [56]. The great impact on iMNs may be due to their more evolved stage of differentiation as they are closest to mature MN, and therefore are more sensitive to environmental changes than neural stem cells and progenitors, as their ability to proliferate has diminished [37]. As fold change values of autophagosome production and retention don’t always present the same trend, a different representation of the results may assist in clearing the image. Raw results of the MFI of the untreated and the starved cells show that basal levels of autophagosomes within mPLEKHM2 tend to be higher than control lines (Appendix fig. 15). Especially, when looking at the average of the control judged against mPLEKHM2. The largest difference is apparent in NEP culture, as P.1 and P.2 have a significantly lower basal amount of autophagosomes than mP.2 (p<0.05). Therefore, mPLEKHM2 cells may already be under a type of stress internally. Human fibroblasts (hF) presented the same results with a significant difference between basal level of P.2 and mP.2 (p<0.001). When dividing the MFI of treated line by its untreated control of each hF line (defined here as fold change), an insignificant difference between the fold changes is seen (data not shown). Another iPSC control, BGU-iPSC, was tested using the same kit. Fold change values were extremely high compared to all cell lines (fig. 16). iPSCs had the highest fold change of 2.72, NEP following after (p<0.05) and iMN with the lowest value (p<0.001), unlike the trend in mPLEKHM2 -derived cells (table 2, fig. 14). Thus, we have chosen to discard it as a control for autophagy flux purposes. A modest autophagy flux could indicate the cell is unable to maintain homeostasis as it fails to produce a sufficient amount of autophagosomes, or imply autophagosomes are decomposed rapidly; both possibilities affect homeostasis. An elevated autophagosome count might suggest a cell line is unable to remove autophagosomes or an over production occurs. It may be that mPLEKHM2 accrue autophagosomes basally and at certain differentiated states are unable to produce a sufficient amount of autophagosomes under stress. Many studies suggest more than one technique shall be exhausted when trying to detect autophagy flux. Since no significant difference was observed with the FACS method, Western blot analysis of NEP set to shed light on our results (fig. 9). Those results present a trend of decreased fold change in mPLEKHM2 cell lines in comparison to control lines using both p62

and LC3B, which label mature autophagosome. LC3B protein expression under both stressors in control lines was higher than in mPLEKHM2 lines. Moreover, the fold change values of R+CQ in the control lines were almost identical (tables 2 and 3). As P.2 presents a high SEM, comparing P.1 to mP.1 and mP.2, showed statistically difference (p<0.05). P.1 possesses more autophagosomes relative to mPLEKHM2 lines. p62 expression hasn’t assisted in obtaining a clear image, mainly because P.2 and mP.1 retain a high SEM. This is due to one control (ctrl1) in each line which scarcely expressed p62 (fig. 9b). When P.1 and mP.2 are separated and compared by two tailed t-test, P.1 p62 expression under R+CQ stress is significantly different from mP.2 expression (p<0.05). R+CQ stress is more severe, as mentioned before. Differentiation is affected by many factors, therefore many repetitions are required in order to minimize the variances inflicted during the experiments.

5.3. Functional Tests Indicate mPLEKHM2 Neurons are Highly Active In order to learn whether iPSCs-derived neurons are actually functional, additional tests were required. Studies were performed on iMNs as they are the closest stage to mature MN. A very common viability assay exercised is PrestoBlue usually to test toxicity of a compound using sequential rising concentrations. Here, we have used this assay to determine cell specific metabolism and viability compared to untreated cells. BGU-iPSC and mP.2 presented an extremely high metabolic rate of 18.74 and 20.7 AFUPrestoBlue/AFUDNA (fig. 10a). While P.1, P.2 and mP.1 values circled around a closer range (6.70, 1.73 and 3.12 AFUPrestoBlue/AFUDNA respectively).

This finding along with discrepancies of BGU-iPSC as a control prior to this assay, lead to the conclusion that BGU-iPSC may be more similar to mP.2 than the rest of the lines. BGU-iPSC was generated from the connective tissue located in the peritoneal infoldings and intra- abdominal structures [8] [57] [58]. mP.2, in contrast to P.1, P.2 and mP1 cell lines that were generated from skin biopsy, was reprogrammed from an extracted connective tissue after a surgery to place pacemaker in the heart of the sick patient (table 1). Hence, this may explain why BGU-iPSC and mP.2 lines behave differently in certain assays.

If the untreated state is considered as 100% viability, the stressed R+CQ culture presents reduced viability relative to the control (fig. 10b). Once the cell lines are separated into two different graphs (fig. 10c), a different picture appears. Applying stress to P.1 and P.2 cells, reduces their viability tremendously, as the former loses 65% viable cells (p<0.05) and the latter 39%. Interestingly, only 1% of mP.1 cells are exhausted. This could indicate mP.1 cells are already experiencing strain under regular conditions. This is supported by their elevated basal amount of autophagosomes. On the other hand, BGU-iPSC and mP.2 lines endure a grave loss in viable cells when treated with R+CQ, 74% and 94% respectively. Which implies that both lines are highly affected by starvation, even more than the other 3 lines, possibly due to their primary cell source. These data reinforces the need to separate them from the group in certain assays.

Eventually, differentiated lines were recorded for neural activity on a MEA plate, as the prevalence of a neural culture is characterized by spontaneous electrical activity. The software outputs a list of number of spikes, bursts and active electrodes for example. A spike is recorded when a change in membrane potential is detected by either one of the sixteen electrodes in the MEA well [59]. Bursts represent the general phenomenon of activation patterns of neurons in the CNS and spinal cord. Many rapid consecutive spikes were fired, followed by quiescent short interval between firing of additional action potentials. Only BGU-iPSC and the mPLEKHM2 cells were recorded on the MEA plate more than once. Activity of BGU-iPSC ascended at D20 and later faded, probably due to cellular detachment from the well. mP.1 and mP.2 showed more activity, setting motion from D25 to a maximum at D30-33, followed by a fast decline in activity by D35. The results indicated that both mPLEKHM2 cell cultures contained successfully differentiated active viable neurons (fig. 11c) but with irregular behaviour. The cell lines presented a high firing rate with infrequent spiking (Appendix fig. 17), presented by the number of bursts per recording in figure 11d. P.2 culture began to show activity but it quickly diminished owing to detachment of cells from the surface. Yet, on D18 of the culture frequent and consistent firing was observed, about each 200s. The results imply that mPLEKHM2 lines possess a dysregulation of firing potential similar to epilepsy [60] [61], but more experiments with control lines are needed to complete the comparison.

6. Conclusions

In this study, a disease-in- a dish model of mPLEKHM2 iPSC-derived neurons was established and studied. For this purpose, I implemented a new differentiation protocol that last 20 to 34 days. I could show that culture on day 18 is comprised of 64% neurons of which 6% were iMNs. I used this system to set protocols for comparing between sick and healthy cells in respect to autophagy functionality under stress, and in assay that measure spontaneous neural activity.

Regarding autophagy, my results exhibit a tendency of less autophagy activity in neuronal cells from mPLEKHM2 cells under stress conditions. Interestingly, autophagosome basal levels were higher in mPLEKHM2 cells as compared to control healthy cells in most of the differentiation stages examined. I suggest that it may be that the cells derived from sick patient are experiencing already strain and stress in basal conditions and are less influenced by stress in culture.

Measurements of spontaneous activity of mPLEKHM2 patient neurons showed high and infrequent firing rate. This behavior is very different from what is known for healthy neuronal cells in culture. I suggest that impaired autophagy might lead to non-canonical behavior that is critical for neurons.

Overall, the model presented here showed the impact of mutated autophagy related protein on the abnormal functionality of neuronal cells derived from sick patient. More experiments will strengthen my results and will contribute to the understanding of the relationship between impaired autophagy and brain diseases.

7. Appendix

Figure 12: Mycoplasma free cells. All cell lines were routinely checked for mycoplasma presence in the culture.

Figure 13: Representative neural culture images a E18.5 rat isolated spinal cord neural tissue DIV20 and b-c D18 iMNs. Scale bar a,c - 200μm, b - 100μm.

Table 2: Autophagy fold change R+CQ (top) and NLM+CQ (bottom) stress data gathered from flow cytometry analysis. iPSCs NEP MNPCs iMNs

Mean±SEM Average Mean±SEM Average Mean±SEM Average Mean±SEM Average P.1 2.34±0.18 1.997±0.22 - 1.64±0.01 1.88 2.48 1.18 1.98 P.2 1.41±0.22 2.97±0.80 1.18±0.62 2.21±0.17 mP.1 1.45±0.24 1.97±0.39 1.31±0.46 1.71±0.25 1.37 2.06 1.24 2.25 mP.2 1.30±0.12 2.18±0.28 1.18±0.64 2.79±0.71

BGU-iPSC 2.72±0.14 2.28±0.11 - 1.34±0.21

iMNs

Mean±SEM Average P.1 0.97±0.18 1.48 P.2 2.17±0.74 mP.1 1.03±0.17 1.2 mP.2 1.37±0.21

BGU-iPSC 1.23±0.15

iP S C s N E P D 6

4 4

3 3

a h

2 h 2

o F 1 F 1

0 0 C o n tro l m P L E K H M 2 C o n tro l m P L E K H M 2

M N P C s D 1 2

n a

h 2

l o

F 1

0 C o n tro l m P L E K H M 2

iM N s D 1 8 iM N s D 1 8 R + C Q N L M + C Q

4 4

3 3

e e

g g

n n

a a h

h 2 2

C C

d d

l l

o o F F 1 1

0 0 C o n tro l m P L E K H M 2 C o n tro l m P L E K H M 2

Figure 14: Autophagy flux of grouped control and mPLEKHM2 cell lines under R+CQ stress unless stated otherwise gathered from flow cytometry analysis. Mean ± SEM. Two-tailed student’s t-test, n>3.

Table 3: Autophagy fold change data gathered from western blot analysis.

LC3B p62

R+CQ NLM+CQ R+CQ NLM+CQ Mean±SEM Average Mean±SEM Average Mean±SEM Average Mean±SEM Average P.1 2.23±0.78 1.82±0.47 2.07±0.09 1.93±0.24 2.35 2.35 1.54 2.33 P.2 2.44±1.86 2.89±0.998 1.02±0.71 2.74±1.32 mP.1 0.50±0.16 0.79±0.16 1.8±1.5 2.68±2.07 1.17 1.17 1.38 2.09 mP.2 0.64±0.17 1.56±0.73 0.96±0.22 1.51±0.73

BGU-iPSC 0.56±0.23 0.77±0.33 0.57±0.26 0.72±0.19

Figure 15: Basal and starved autophagosome levels. Presenting median fluorescent intensity (MFI) of untreated cells versus R+CQ or NLM+CQ treated cells; iPSCs, NEP, MNPCs, iMNs and human fibroblasts (hF). Mean ± SEM. Multiple comparisons statistical analysis was performed by one-way ANOVA, comparisons between groups performed by Tukey test n=3 (except P.1 iMNs n=2, hF n=2).

B G U -iP S C s

4 .0 ** *

e 3 .0

a h

2 .0

l o

F 1 .0

0 .0 i P S C s N E P M N P C s i M N s

Figure 16: Autophagy flux of BGU-iPSC using CYTO-ID® assay. Mean ± SEM. Multiple comparisons statistical analysis was performed by one-way ANOVA, comparisons between groups performed by Tukey test, n=3 (except iMNs n=2).

Figure 17: Neural activity raster plots of P.2 and mP.2 D18 iMNs.

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תקציר

מוטציה בגן mPLEKHM2 ( PLEKHM2( היא הסיבה להתפתחות המחלה dilated cardiomyopathy DCM-LVNC( with left ventricular noncompaction(. מחלת הלב הזו היא הגורם למוות בטרם עת של החולים בה עקב דום לב. PLEKHM2 )או בשמו הנוסף SKIP( הוא פקטור באוטופגיה, מנגנון רגולטורי ראשי השולט בהומאוסטאזיס תאי, מאחר והוא אחראי על פירוק פתוגנים, חלבונים ומרכיבים תאיים אחרים. אוט ופגיה מנוהלת על ידי שתי אורגנלות עיקריות, הליזוזום שמכיל את האנזימים הדרושים לפירוק, והאוטופגוזום אשר עוטף את המרכיבים שסומנו לדגרדציה. PLEKHM2 מהווה חלק מקומפלקס החלבונים המאפשר את תזוזתו של הליזוזום לעבר פריפריית התא, לפיכך כמצופה, פיברובלסטים של חולים להם mPLEKHM2 הציגו פיזור של ליזוזומים בעיקר סביב הגרעין )perinuclear localization(. יתכן וזו אחת מהסיבות לכך שהאוטופגיה איננה מבוקרת כיאות ) autophagic dysregulation( בתאי הפיברובלסטים של החולים וכתוצאה מכך מתפתחת המחלה הקשה – DCM-LVNC.

בעיה בבקרה על אוטופגיה נצפתה גם בהקשרים של מחלות נוירודגנרטיביות. הרבה גורמים יכולים לגרום למוות תאי במחלות נוירודגנרטיביות, כגון סטרסורים תאיים, כשל ביצירת ביואנרגיה ואגרגציית חלבונים שאינם מקופלים כהלכה. לפיכך, קיים פוטנציאל רב בשליטה באוטופגיה ככלי טיפולי למחלות אלו.

בעבר, תאי גזע מושרים )iPSCs( נוצרו מדגימות ביופסיה של פיברובלסטים עם מוטציה ב PLEKHM2 ופיברובסלטים של קרובי משפחה הטרוזיגוטים, שאינם מבטאים את פנוטיפ המחלה, במעבדתינו )מרכז למחקר רפואה רגנרטיבית ותאי גזע - RMSC(. ההיפותיזה שלנו היא שתפקוד הנוירונים הממוינים מiPSCs עם mPLEKHM2 יפגע בהשוואה לנוירונים אשר התמיינו מתאי iPSCs ללא מוטציה.

במחקר הנוכחי, הפרוטוקול למיון מ -monolayer בוצע על שתי שורות תאים בריאים ושתי שורות תאים עם מוטציה. לא נצפו הבדלים משמעותיים בין המרקרים של שורות התאים השונות במהלך המיון, תרבית תאי עצב מוטוריים לא בוגרים הכילה בערך GFAP+28% ,Tuj1+ 64% ו isl1+ 6%-. בנוסף, בדיקה להצטברות אוטופגוזומים בוצעה בשלבי מי ון שונים. שו רות התאים המוטנטיות הראו נטייה להצטברות מועטה יות ר של אורגנלות אוטופגוזומים בימים 6 ו - 18. פעילות נוירונלית נבחנה עם שימוש במכשיר Microelectrode MEA( array( שמודד פולסים חשמליים. תאי mPLEKHM2 הראו פעילות מקסימלית בין ימים 30 ל33 בפלטה, עם פוטנצי אלי פעולה בתכיפות רבה ובקצב לא קבוע. אמנם לא נעשו מספיק חזרות בכדי להראות הבדלים סטטיסטיים בניסויינו, אך אנו סבורים כי הממצאים הללו מציגים מגמה ברורה.

לסיכום, התגליות מהעבודה מצביעות על כך שלנוירונים המכילים mPLEKHM2 יש התנהגות של תרבית תאים שאינה שומרת על הומאוסטאזיס נורמלי עקב תפקוד לקוי של מערכת האוטופגיה, מצב המשפיע ישירות על תפקוד נוירונלי לא תקין.

אוניבריסטת בן גוריון הפקולטה למדעי ההנדסה המחלקה להנדסת ביוטכנולוגיה על שם אברם וסטלה גולדשטיין גורן

השפעת מוטציה ב- PLEKHM2 על מיון נוירונלי ותהליך האוטופגיה

חיבור זה מהווה חלק מהדרישות לקבלת תואר מגיסטר בהנדסה

מאת הדס בן- צבי

בהנחיית פרופ' סמדר כהן, ד"ר רבקה אופיר וד"ר גינת נרקיס

אוקטובר 2020

אוניבריסטת בן גוריון הפקולטה למדעי ההנדסה המחלקה להנדסת ביוטכנולוגיה על שם אברם וסטלה גולדשטיין גורן

השפעת מוטציה ב- PLEKHM2 על מיון נוירונלי ותהליך האוטופגיה

חיבור זה מהווה חלק מהדרישות לקבלת תואר מגיסטר בהנדסה

מאת הדס בן- צבי

בהנחיית פרופ' סמדר כהן, ד"ר רבקה אופיר וד"ר גינת נרקיס

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