EFFECTS OF ACSVL3 KNOCKOUT ON LIPID AND GLUCOSE METABOLISM IN MALIGNANT GLIOMA CELLS

By

Elizabeth Anne Kolar

A dissertation submitted to The Johns Hopkins University in conformity with the

requirements of the degree of Doctor of Philosophy

Baltimore, Maryland

March 2016

ABSTRACT

Gliomas are the largest category of primary central nervous system tumors.

Glioblastoma multiforme (GBM) is a World Health Organization Grade IV glioma that

comprises 70% of all gliomas. Prognosis is very poor once diagnosed, and current

treatments cannot prolong survival after relapse. Very long-chain acyl-CoA synthetase 3

(ACSVL3) is overexpressed in malignant glioma, and depleting ACSVL3 in GBM cells

(e.g. U87MG) diminishes their tumorigenic properties and affects signaling through receptor tyrosine kinases. An ACSVL3-deficient knockout (KO) U87MG cell line was generated to study how ACSVL3 contributes to the malignant properties of glioma cells.

Acyl-CoA synthetase enzyme activity was measured with long- and very long-chain fatty acids: palmitic acid (C16:0), stearic acid (C18:0), behenic acid (C22:0), and lignoceric acid (C24:0). There were significant decreases in the activation of stearic and behenic acids, while the activation of palmitic acid and lignoceric acid did not change. Ceramide synthesis assays and liquid chromatography/tandem mass spectrometry (LC/MS-MS) analysis revealed a decrease in C18:0 and C22:0 ceramides, reinforcing the enzyme activity assay results. LC/MS-MS analysis also revealed a decrease in sphingosine 1- phosphate, an important signaling molecule that affects growth and proliferation.

Proteomic analysis showed lower protein levels for enzymes involved in ceramide synthesis in the ACSVL3 KO line. Fluorescent microscopy and thin layer chromatography analyses show that ACSVL3 deficiency affects lipid rafts and ganglioside synthesis. Proteomic analysis also predicted changes in glycolysis and the tricarboxylic acid cycle (TCA) when ACSVL3 is depleted in U87MG cells. Glycolytic

ii enzymes were higher while TCA enzymes were lower in ACSVL3 KO cells.

Immunofluoresence using an antibody that detects Tom20, a mitochondrial outer membrane marker, revealed differences in mitochondrial morphology in the ACSVL3

KO cells when compared to the U87MG cells. From these studies, we conclude that

ACSVL3 is important for the synthesis of structural and signaling sphingolipids that contribute to the growth and proliferation of the GBM cells, and that this enzyme likely contributes to mitochondrial-involved carbohydrate metabolism.

Thesis Advisor: Paul A. Watkins, MD, PhD

Thesis Reader: Dan Raben, PhD

iii ACKNOWLEDGMENTS

There were a lot of people who helped me accomplish this work, whether it was helping with experiments in the lab or encouraging me from home, and I would like to acknowledge those who have made this possible.

I came to Hopkins with very specific ideas of what type of research I wanted to do, but as with many things in life, I was led in a very different direction. I never saw myself studying lipid biology, but I found my way to Paul’s lab, and I am very glad that I did. Paul, more than anyone else, knows of the struggles we have had in the lab.

Through his encouragement and expertise, I learned so much about science and about myself. I will always be grateful to Paul for all the opportunities and all that he has done.

Chapter 1 of this thesis would not have been possible without the collaborative spirit of our lab, and I will always be appreciative of the former and current lab members of the Watkins lab – Zhengtong Pei, Cicely Exeter, Xiaohai Shi, Haiyan Yang, Yanqiu

Liu, Xiaoli Ye, and Emily Clay. We got through the struggle with dead/dying/reverting cells together, solved the problem, and characterized the knockout cells as a lab. Above all, I don’t know if I would have made it through graduate school without everyone’s discussions, opinions, hard work, and above all, the laughter and fun they provided every day.

Thank you also to my thesis committee – Dan Raben, Will Wong, and Greg

Riggins. Their ideas and knowledge helped shape this thesis into what it is.

I will always cherish the amazing friends I found here at Hopkins. We came from all over the country – and sometimes from all over the world! – and graduate school

iv brought us together. I want to especially acknowledge Marcus Seldin, Michael

Multhaup, and Steven Wang for their support and friendship through the years. We have

been through a lot, whether it was changing dissertation topics or trying to survive the

city with as little damage as possible, we did it together.

I want to thank all of my aunts, uncles, and cousins for their support and love. I love you, and thank you for sticking with me through it all. You have all been my rock through this journey.

This is for my grandparents, Nicholas and Mary Kolar and Andrew and Patricia

Szoke, who mean everything to me. They were always quick with a prayer or novena, and I knew that I always, always had their support. I dedicate this to them, especially to my grandmother, Patricia, who will not be here to celebrate. I know she is always watching over me. I hope I have made her proud.

A huge thank you goes to Basil Hussain, without whom I don’t know if this would have been possible. We made it through graduate school together, and there is finally the light at the end of the tunnel. You were a pillar of support through the good and the bad, and I am excited to start our next journey. I love you.

Finally, I want to thank my parents and my brother Stephen, who always believed in me. They supported every crazy dream I ever had. Because of them, I realized I could achieve whatever I wanted, especially this. This degree was probably the hardest thing I ever had to do, and even if they didn’t always understand what I was doing and why I was so upset, they were always ones I could lean on. Thank you for everything.

v TABLE OF CONTENTS

Abstract ii

Acknowledgments iv

Table of Contents vi

List of Figures vii

List of Tables x

Introduction 1

Chapter 1

Introduction 24

Materials and Methods 26

Results 36

Discussion 52

Chapter 2

Introduction 57

Methods and Materials 61

Results 69

Discussion 92

Chapter 3

Introduction 100

Methods and Materials 104

Results 108

Discussion 130

References 133

Curriculum Vitae 144

vi LIST OF FIGURES

Figure 1. Lipid rafts are membrane microdomains enriched with cholesterol,

sphingolipids, and proteins………………………………………………………..5

Figure 2. A simplified receptor tyrosine kinase signaling cascade………………………9

Figure 3. The Warburg Effect in proliferating tissues increases lactate through aerobic

glycolysis………………………………………………………………………...12

Figure 4. Fatty acid activation reaction………………………………………………....16

Figure 5. Once activated, fatty acyl-CoA molecules can be used by cells in different

ways……………………………………………………………………………...17

Figure 6. ACS enzymes can be grouped by substrate specificity in a phylogenetic

study……………………………………………………………………………..18

Figure 7. Immunohistochemistry shows that ACSVL3 is overexpressed in glioma……21

Figure 8. ZFNs create a genomic ACSVL3 KO by deleting a 210 bp region…………..39

Figure 9. Proteomic analysis and qPCR show a decrease in ACSVL3 relative to the

U87MG cell line………………………………………………………………....40

Figure 10. ACSVL3 KO cells have an altered morphology and grow significantly

slower than the U87MG cells……………………………………………………42

Figure 11. ACSVL3 KO cells grow smaller subcutaneous tumors in nude mice………44

Figure 12. Total activation of long- and very long-chain fatty acids is lower in

ACSVL3 KO cells……………………………………………………………….49

Figure 13. The majority of ACSVL3 KO cells are in S-phase………………………….51

vii Figure 14. Total cholesterol is not different between U87MG cells and

ACSVL3 KO cells………………………………………………………………71

Figure 15. Lipid synthesis is not affected by depletion of ACSVL3 in U87MG cells…73

Figure 16. Ceramide synthesis decreases in ACSVL3 KO cells when the

substrate is C18:0……………………………………………………………….76

Figure 17. Ceramdies with acyl chains C18:0-C22:0 are decreased in ACSVL3

KO cells…………………………………………………………………………77

Figure 18. Sphingosine and S1P levels decrease when cells are depleted of

ACSVL3………………………………………………………………………..79

Figure 19. Fluorescent microscopy reveals an increase in lipid raft staining in

ACSVL3 KO cells………………………………………………………………85

Figure 20. Total gangliosides decrease in ACSVL3 KO cells, but GM1 ganglioside

increases compared to U87MG cells……………………………………………87

Figure 21. ACSVL3 KO cells do not increase lipid synthesis when incubated

with EGF………………………………………………………………………..90

Figure 22. Decreasing activation of fatty acids destined for sphingolipid synthesis

leads to aberrant signaling from receptor tyrosine kinases……………………..99

Figure 23. Glucose uptake in ACSVL3 KO cells relative to U87MG cells…………..110

Figure 24. Glycolytic pathway metabolites do not significantly change despite

a change in enzymes……………………………………………………………114

Figure 25. Pyruvate levels do not change with an ACSVL3 KO……………………...115

Figure 26. LDH enzyme levels increase in an ACSVL3 KO, but cellular lactate

levels are unchanged……………………………………………………………116

viii Figure 27. Oxidation of glucose is significantly downregulated in the

ACSVL3 KO……………………………………………………………………118

Figure 28. TCA Cycle intermediates are not changed overall in the ACSVL3 KO

cells……………………………………………………………………………..122

Figure 29. Mitochondrial morphology is different between the U87MG cell line and

the ACSVL3 KO cell line………………………………………………………128

ix LIST OF TABLES

Table 1. The relative abundance of the long- and very long-chain acyl-CoA

synthetases in U87MG cells and ACSVL3 KO cells…………………………….47

Table 2. Enyzmes involved in ceramide synthesis are decreased in the

ACSVL3 KO cells……………………………………………………………….82

Table 3. Glycolytic enzyme levels are increased in ACSVL3 KO cells………………113

Table 4. Levels of TCA cycle enzymes are decreased in ACSVL3 KO cells………....121

Table 5. The complexes of the Electron Transport Chain are lower in

the ACSVL3 KO cells………………………………………………………….124

Table 6. ATP synthase subunits levels are decreased in the ACSVL3 KO cells……...125

Table 7. Proteins involved with mitochondrial dynamics show differences in the

ACSVL3 KO cells……………………………………………………………..129

x INTRODUCTION

Glioblastoma Multiforme

Gliomas are the largest category of primary central nervous system (CNS) tumors, as they account for 78% of all primary intrinsic malignant CNS tumors (CBTRUS, 2006).

These tumors, which mainly occur in adults, are characterized based on histologic similarity to mature glial cells. The World Health Organization (WHO) grades gliomas by pathologic evaluation of the tumor. Low grade gliomas (WHO grade II) are well- differentiated and tend to exhibit benign tendencies and the patient usually has a better prognosis. High grade gliomas (WHO grades III and IV) are undifferentiated, are malignant, and carry a worse prognosis for patients. Diffuse tumors, such as astrocytomas (WHO grades II-IV), oligodendrogliomas (WHO grades II and III), and oligoastrocytomas (WHO grades II-IV), are characterized by their infiltrative properties.

Glioblastoma multiforme (GBM), the highest grade of primary brain tumor

(WHO grade IV), is the most common and fatal type. GBM is usually diagnosed without previous lower-grade tumors, and this is known as a primary or de novo GBM. It comprises 70% of all gliomas. GBM tumors grow quickly and are difficult to treat due to the cell type heterogeneity (Mineo et al., 2007). Prognosis is very poor once diagnosed.

Radiation and chemotherapy with the alkylating agent temozolomide increases survival slightly, however, most of these patients experience tumor recurrence (Sathornsumetee et al., 2007), and none of the current treatments can effectively prolong survival after

1 relapse (Weller et al., 2014). Therefore, new treatment strategies and new therapeutic targets are needed.

The U87MG cell line is a long established cell culture line in GBM research. The cells were isolated from a 44 year old Caucasian male with grade IV GBM. There have been over 1,700 publications using the U87MG cell line. It is hypodiploid with 44 chromosomes occurring in 48% of the cells with higher ploidy occurring at a rate of

5.9%. Even with the large number of chromosomal aberrations, the U87MG line has been relatively stable for years, and has not significantly changed based on genotyping by microarray (Clark et al., 2010). This cell line lacks the PTEN protein, a tumor suppressor that negatively regulates the Akt/Protein kinase B (PKB) signaling pathway. U87MG cells can successfully be used to grow subcutaneous and intracranial tumors in mice in order to study GBM in an in vivo environment.

Lipid Metabolism in Cancer

The mechanisms that integrate cell signaling and metabolism are, for the most part, conserved between normal cells and cancer cells. However, tumor cells differ through uncontrolled cell division and have a greater requirement for energy for rapid proliferation (Cantor and Sabatini, 2012). These cells often exhibit mutations so that these pathways are constitutive and allow the cells to maintain a high biosynthetic capacity (DeBerardinis et al., 2008). Over 50 years ago, it was noted that neoplastic tissues are able to synthesize lipids in a manner similar to embryonic tissue (Medes et al.,

1953). Cancer cells need increased lipid metabolism in order to meet the requirements for rapid proliferation. These lipids serve a variety of functions including a source of

2 building blocks of cellular membranes, and are required for cell signaling cascades that

encourage cellular growth and proliferation. Lipids also provide cells with a pool of acyl

groups that can be used for post-transcriptional modifications of proteins.

Cells, both normal and cancerous, require lipids from either an exogenous source, or via de novo biosynthetic pathways. The de novo synthesis of lipids is regulated by the sterol regulatory element-binding proteins (SREBPs) (Horton, 2002; Eberle, et al., 1997).

SREBPs are helix-loop-helix leucine zipper transcription factors that are translated as 125 kDa precursors that reside in the endoplasmic reticulum membrane and are bound by

SREBP cleavage-activating protein (SCAP). Once the proteins are processed through two rounds of proteolysis, the transcription factors can enter the nucleus and turn on lipid metabolism genes, such as acetyl-CoA carboxylase (ACC) and fatty acid synthase

(FASN). ACC catalyzes the rate-limiting step of de novo fatty acid (FA) synthesis, by converting acetyl-CoA to malonyl-CoA. Acetyl and malonyl groups can then be condensed by FASN to form a 4-carbon β-ketoacid, with release of CO2. Sequential

reduction, dehydration, and reduction steps, also catalyzed by FASN, convert the β-

ketoacid into a 4-carbon FA. Repeated rounds of condensation, reduction, dehydration, and reduction ultimately produce the 16-carbon long saturated FA, palmitic acid.

Kuhajda and colleagues (1996) demonstrated that a prognostic marker they had identified in breast cancer was, in fact, FASN. Since then, multiple studies have shown that tumor cells reactivate de novo lipid synthesis. Inhibition of ACC has been shown to induce growth arrest and apoptosis in prostate cancer cells (Gray-Bablin, et al., 1997).

Cholesterol is an essential component of cellular membranes. It regulates the fluidity of the lipid bilayer and also forms microdomains known as lipid rafts that

3 coordinate the activation of signaling pathways (Lingwood and Simons, 2010).

Cholesterol is also the precursor of bile acids and steroid hormones (Simons and Ikonen,

2000). Because of its importance, cholesterol’s synthesis and distribution are highly

regulated, with complex mechanisms overseeing intracellular synthesis, absorption, and

removal. Lipid rafts (Figure 1) serve as platforms for cell surface receptors, including

receptor tyrosine kinases (RTK) and G-protein coupled receptors (GPCR). These receptors can signal through a number of different intracellular pathways. One well known pathway is RTK signaling through Akt, a serine-threonine protein kinase that mediates cell survival and growth. It was recently shown in a prostate tumor model that a

reduction of membrane cholesterol levels caused the rearrangement of lipid rafts with

strong effects on Akt (Pommier et al., 2010).

4

Glycoprotein Integral protein

Glycosphingolipid

Phospholipid Cholesterol Peripheral protein

Figure 1. Lipid rafts are membrane microdomains enriched with cholesterol,

sphingolipids, and proteins. Lipid rafts are considered distinct microdomains in lipid bilayers that function as signaling platforms. These regions are distinct from other regions of bilayers due to their higher cholesterol and sphingolipid content, and are thought to be more “detergent-resistant”. Receptor tyrosine kinases are believed to mainly signal from these regions, and signaling can be influenced by different lipid content.

5 Regulation of Lipid Metabolism by Receptor Tyrosine Kinases

Receptor tyrosine kinases (RTKs, Figure 2) are important to cells for receiving

information from their environment and translating that into signaling cascades to

regulate metabolism, gene expression, cell growth, and cell cycle control (Blume-Jensen

and Hunter, 2001; Ullrich and Schlessinger, 1990). Humans are known to have 58

different RTKs. All RTKs consist of a single transmembrane domain that separates the

intracellular tyrosine kinase region from the extracellular portion (Ullrich and

Schlessinger, 1990). Ligand binding to the extracellular domain leads to conformational

changes that induce and stabilize receptor dimerization leading to kinase activity and

autophosphorylation of tyrosine residues (Greenfield et al., 1989; Ullrich and

Schlessinger, 1990; Heldin 1995). The mechanism of activation and key components of

the intracellular signaling pathways that are triggered through ligand binding are highly

conserved in evolution from C. elegans to humans, consistent with the roles they play.

Cancer cells have a wide range of mutations and deregulation of genes that lead to changes in cellular structure and function that contribute to the malignancy. Six hallmark traits of cancer have been described: self-sufficiency in growth signals, insensitivity to growth inhibitory signals, evasion of apoptosis, limitless replicative potential, induction of sustained angiogenesis, and invasion and metastasis (Hanahan and Weinberg, 2000).

Many of these traits involve RTKs and their signaling pathways. In fact, overactivation of tumor RTKs and their downstream signaling pathways is closely associated with malignant progression and poor patient survival (Birchmeier et al., 2003; Wong et al.,

1987; Simmons et al., 2001; Abounader and Laterra, 2005).

6 Two RTKs that have been implicated in the pathology of glioblastoma, as well as

other cancers, are the epidermal growth factor receptor (EGFR) and the hepatocyte

growth factor (HGF) receptor known as c-MET. EGFR overexpression is a significant

trait of GBMs, but it is rare in low-grade gliomas, suggesting a role for aberrant EGFR

signaling in the pathogenesis of GBM. RTK signal transduction continues mainly

through the protein kinase Akt/Protein Kinase B pathway or the MAPK pathway to

ultimately increase proliferation, angiogenesis, metastasis, and decreased apoptosis

(Mosesson et al., 2004). The tyrosine kinase activity may be dysregulated by gene

mutations, an increase in gene copy number, and/or EGFR protein overexpression

(Ciardiello and Tortora, 2008). Because of its role as a central regulator of biological

processes in glioma, as well as possibly contributing to resistance to apoptotic stimuli and

certain types of chemotherapy, it has attracted attention as a therapeutic target. It has

been shown that EGFR signaling through Akt promotes SREBP-1 cleavage and translocation to the nucleus to increase fatty acid concentration in GBM cells such as the

U87MG cell line (Guo et al., 2009). The same study analyzed tissue from 140 patients with primary GBMs, and demonstrated that this phenomenon found in U87MG cells was also seen in tissue, demonstrating that EGFR signaling is important to the pathology of glioblastoma.

HGF and c-MET are expressed in human gliomas with expression levels

correlating with tumor grade (Koochekpour et al., 1997; Moriyama et al., 1998; Rosen et

al., 1996). When HGF or c-MET is inhibited, in vivo tumor formation and growth is

inhibited Abounader et al., 1999, 2002). Upon binding of HGF to c-MET, the receptor

undergoes autophosphorylation and activates kinase activity, with signal transduction

7 occurring through the PI3K-Akt-mTORC pathway and the ERK/MAPK pathway. This can induce proliferative and anti-apoptotic responses in various cell types, and signaling through ERK/MAPK regulates cell proliferation, junctional competence, and motility. c-

MET mutations and overexpression have been described in a number of cancers (Ma et al., 2003; Danilkovitch-Miagkova and Zbar, 2002). Most of these mutations occur at the cytoplasmic activation loop domain.

8

Lipid Raft RTK GF

Cell membrane

Akt/PKB

Angiogenesis Protein Synthesis

Proliferation Cell Survival Lipid Synthesis

Figure 2. A simplified receptor tyrosine kinase signaling cascade. Receptor tyrosine kinases (RTKs) are proteins within the cell membrane that receive signals, usually in the form of growth factors (GF), from the extracellular environment. A number of different cascades exist, but the one most commonly upregulated in cancer is the Akt/Protein

Kinase B (PKB) signaling cascade. This is a signal for a number of different processes to occur, such as proliferation, cell survival, and lipid synthesis, all important processes for cancer cells.

9 Glucose Metabolism and Cancer

Otto Warburg (1927) made the initial observation that cancer cells were highly fermentative, and he hypothesized that this was due to some metabolic injury (Warburg,

1930). The Warburg effect describes a tumor cell’s ability to completely oxidize glucose, even in the presence of oxygen. Generally, under these conditions, cells prefer the more energetically favorable process of oxidative phosphorylation to produce ATP. Cancer cells generally have increased glucose consumption and lactate production (Figure 3).

Glycolytic enzymes are usually found to be overexpressed in cancer cells (Kim and

Dang, 2005). Even though ATP generation through aerobic glycolysis is less efficient, it facilitates uptake and incorporation of glycolytic intermediates into nucleotides, amino

acids, and lipids. This allows the cell to meet the biosynthetic demands required by

highly proliferative cancer cells (DeBerardinis et al., 2008; Heiden et al., 2009; Kroemer

and Pouyssegur, 2008; Menendez and Lupu, 2008). With more recent research into the

Warburg effect, it has been shown that this can occur, even without the defects in

oxidative metabolism (Moreno-Sanchez et al., 2007). However, the pathogenic role of

increased glycolysis in cancer cells remains controversial (Vander Heiden et al., 2009),

and discovering the true metabolism of these cells would be a significant step in

identifying more effective drugs and therapeutic targets.

Because the Warburg effect was so widely accepted, the status of mitochondria in

cancer cells was generally disregarded until recently. What has become increasingly

clear that aerobic glycolysis in cancer is a result of a more complex metabolic

rearrangement in which the mitochondria play an important role. All of these different

pathways – glycolysis, the tricarboxylic acid cycle, beta-oxidation, and anabolic

10 metabolism – adapt to respond to the uncontrolled proliferation characteristic of cancer cells by providing the cell with the energy and molecules necessary for synthesis of macromolecules required for survival (Moreno-Sanchez et al., 2009).

11

Figure 3. The Warburg Effect in proliferating tissues increases lactate through aerobic glycolysis. Cells from normal tissue (green), use glucose as a source of energy.

Under aerobic conditions, the cells produce pyruvate through glycolysis. Pyruvate can then enter the mitochondria to power the tricarboxylic acid (TCA) cycle to produce ATP efficiently through oxidative phosphorylation. Cancer cells undergo glycolysis, but produce lactate, even under aerobic conditions, with very little oxidative phosphorylation.

Figure from Goncalves et al., 2015.

12 Lipid Metabolism and Acyl-CoA Synthetases

Lipids are important macromolecules that play a variety of functions within and

outside the cell. FAs are characterized as a carboxylic acid with a long aliphatic chain,

and can be either saturated or unsaturated. They are incorporated into phospholipids that

are used to create the cell’s membrane and the membranes of the various organelles.

Phospholipids can be used as signaling molecules either intracellular or between

neighboring cells. FAs are also constituents of sphingolipids and glycolipids found in

cell membranes, and of lipid storage molecules such as triacylglycerol and cholesterol

esters. Free FAs are important to a cell because these can be oxidized by mitochondria

for energy production through beta-oxidation. Very long-chain FAs, which can be toxic to cells if present in excess, can be chain-shortened via beta-oxidation in peroxisomes; products of this process can then be further degraded by mitochondrial beta-oxidation.

Acyl-CoA synthetases (ACSs) are a family of enzymes that catalyze the thioesterification of fatty acids to Coenzyme A. This is a fundamental metabolic process that is conserved from Archaea to man (Watkins, 1997) that occurs in a two-step reaction.

First, the enzyme catalyzes the ATP-dependent formation an acyl-AMP conjugate with

the release of inorganic pyrophosphate. In the second step, the enzyme catalyzes the

formation of a thioester bond between Coenzyme A and the acyl-AMP to form the

activated fatty acyl-CoA with the release of AMP (Figure 4). Formation of acyl-CoA allows relatively unreactive fatty acids to participate in a number of metabolic pathways, such as signaling, lipid protein acylation, as well as for utilization in structural and storage lipid biosynthesis (Watkins, 2013) (Figure 5). More than 50 years ago, it was recognized that activation of short-, medium-, and long-chain fatty acids required

13 different enzymes. It is now known that there are 26 ACSs found in the human genome.

Phylogenetic analysis of their amino acid sequences has allowed classification by their

FA substrate chain-length specificity (Figure 6). Their specificity ranges from short-

(ACSS) to medium- (ACSM) to long- (ACSL) to very-long- (ACSVL) chain fatty acids.

An additional subfamily of ACSs homologous to the defective enzyme in the Drosophila melanogaster “bubblegum” mutant (ACSBG) and four “orphan” ACSs (ASCF1-4) complete the family.

The ACSVL family, also known as Fatty Acid Transport Proteins (FATPs), is conserved in many species. There are six proteins found in humans and rodents (Hirsch, et al., 1998; Watkins, et al., 1999; Steinberg, et al., 2000), eight in Zebrafish (Danio rerio), six in fruit fly (Drosophila melanogaster), and two in the roundworm

(Caenorhabditis elegans) genomes (Watkins, et al., 2007). The six human ACSVL proteins share 37-59% identity, but are only 17-25% identical to the other human ACSs.

All enzymatically active ACSs have two conserved domains in the amino acid sequence.

One is a 10-residue AMP-binding domain, known as Motif I, which is conserved in many enzymes whose reaction mechanism involves adenylation with release of inorganic pyrophosphate. The other is a 35-residue domain (Motif II) containing what was originally proposed as the fatty acid-binding “signature motif” (Watkins et al., 2007).

Both of these domains are highly conserved from archaea to humans. Sequence homology within Motif II has been used to assign the ACSs to subfamilies. Both the

ACSL enzymes and the ACSVL family are capable of activating fatty acids containing

16-18 carbons, but only the ACSVL family has the ability to activate fatty acyl substrates

14 that are 22 carbons or longer. Each ACSVL has a unique role in lipid metabolism based on tissue expression patterns, subcellular location, and substrate preferences.

15

Figure 4. Fatty acid activation reaction. The ACSs catalyze the thioesterification of Coenzyme A to a fatty acyl chain. The reaction is a two-step process. The first step requires the enzyme to bind the fatty acid and an ATP to form an acyl-AMP molecule and releases inorganic pyrophosphate. The second step forms a thioester bond between the Coenzyme A and the acyl chain to form the activated fatty acyl-CA, with the AMP being released.

16

Figure 5. Once activated, fatty acyl-CoA molecules can be used by cells in different ways. After activation, a fatty acyl-CoA can have one of many different fates. These lipids can be used to provide energy for the cell through oxidation, they can be used in the synthesis of more complex lipids, or for the modification of proteins.

17

Figure 6. ACS enzymes can be grouped by substrate specificity in a phylogenetic study. Phylogenetic analysis was performed using sequences from Motif II, the fatty acid binding motif. When grouped, the enzymes formed subfamilies based on substrate chain length. ACSS – short chain; ACSM – medium chain; ACSL – long chain; ACSVL – very long chain; ACSBG – “bubblegum” family. The ACSF enzymes are “orphan” enzymes that do not group with the other ACS subfamilies.

18 Very-Long Chain Acyl-CoA Synthetase 3 (ACSVL3) and Cancer

ACSVL3 (a.k.a SLC27A3 or FATP3) is one of the most recently characterized members of the ACS family (Pei et al., 2004). Although ACSVL family members are also known as FATPs, ACSVL3 is one of three in this family that does not transport fatty acids (Pei et al., 2004), the other two being ACSVL2 and ACSVL6 (Watkins, 2008).

Mouse ACSVL3 mRNA was found primarily in steroidogenic tissues – the adrenal, testis, and ovary – and to a lesser extent the brain, lung, and kidney (Pei, et al., 2004).

High levels of ACSVL3 mRNA can be detected in embryonic mouse brain (E12); however, levels rapidly decreased and by one month of age, the mRNA was barely detectable. Adult mouse brain sections show low levels of ACSVL3 protein by immunohistochemistry in cortical neurons, hippocampal neurons, and cerebellar Pukinje cells, but was not detected in glial cells (Pei, et al., 2004). ACSVL3 can be found in punctate vesicles via immunofluorescence in U87MG cells and mouse MA-10 Leydig cells and do not co-stain with markers for mitochondria or peroxisomes.

ACSVL3 has been found to be important in many solid malignancies (Pei et al.,

2009). Immunohistochemistry experiments using antibodies towards ACSVL3 have shown robust overexpression in different types of lung cancer (Pei, et al., 2013) and glioblastoma (Pei et al., 2009). In a tissue array of 79 gliomas of varying degrees,

ACSVL3 was overexpressed in all (Figure 7). In contrast to the adult immunohistochemistry, this protein is primarily expressed in neurons in normal human brain. The acyl-CoA synthetase ACSBG1, which is also primarily found in neurons, was used as a negative control to show that the overexpression of ACSVL3 in gliomas was specific. RNA interference (RNAi) targeting ACSVL3 in both lung cancer cell lines and

19 the U87 glioma cell line has been shown to slow cell proliferation and decrease the

number of colonies formed in soft agar (Pei et al., 2013).

In addition to our results, it has been shown that there is a higher frequency of genomic alteration at 1q21.3, which contains the SLC27A3 (ACSVL3) gene, in undifferentiated pleomorphic sarcomas (UPS) and leiomyosarcomas (LMS) (Silveira et al., 2013.). ACSVL3 mRNA was shown to be increased by qPCR, and they show that gains in 1q21.3 were an independent prognostic marker of shorter survival in LMS.

Mouse studies with A549 lung cancer cell xenografts showed decreased tumor volume when treated with fenretinide, a synthetic retinoid (Durante et al., 2014). ACSVL3 was

not shown to be a target of the compound, but by qPCR they show a reduction in

ACSVL3 levels in the treated tumors. Studies by our lab have also demonstrated that

ACSVL3 expression is enhanced with increased signaling through EGFR and c-MET

(Pei et al., 2009), and reducing ACSVL3 expression by RNAi was associated with aberrant signaling through the RTK-Akt axis. These data suggest that ACSVL3 plays an important role in the tumorigenicity of cancer cells.

20

Figure 7. Immunohistochemistry shows that ACSVL3 is overexpressed in glioma.

Pei et al. (2009) performed immunohistochemistry against ACSVL3 on an array of 79 tissues from patients with varying grades of glioma. Every grade exhibited an overexpression of ACSVL3 when compared to normal brain tissue. Another ACS,

ACSBG1, was used as a control on the same tissues, and was not found to be overexpressed in glioma.

21 Gaps in Knowledge

While we have shown that ACSVL3 is upregulated in various types of cancer, we

do not understand the consequences of this upregulation. The long chain acyl-CoA synthetases have been studied at great length in relation to disease states. Many papers investigating ACSL1 and ACSL4 have shown these enzymes are upregulated in a number of different cancers, suggesting that ACS activity plays an important role in cancer cell survival (Cao et al., 2000; Cao et al., 2001; Gassler et al., 2005). The ACS inhibitor

triacsin c was identified as an agent that shows selective cytotoxicity to malignant cancer

cells (Mashima et al., 2005), suggesting the importance of ACSs to tumor cell survival.

Very little research has been done to try to resolve the importance of ACSVL3 in cancer

cells. Knockdown of ACSVL3 using shRNA shows that while depleting the cells of the

enzyme slows down their growth, it is not required by the cells to grow.

The specific role of ACSVL3 in cellular lipid metabolism has not yet been

established is the current focus of our lab and the main subject of this Thesis. The

enzyme has a broad range of specificity between long- and very-long-chain fatty acyl-

CoAs (Pei et al., 2004) which can be used in a variety of different pathways. In addition to ACSVL3 knock-down via RNAi, I will also demonstrate that ACSVL3 is important by knocking out (KO) the gene using zinc-finger nucleases. The data presented in this

Thesis show that ACSVL3 KO U87 glioma cells exhibit the same phenotype as the

knock-down cells. The ACSVL3 KO cells exhibit slow growth, and when used to grow

subcutaneous xenografts, the injection sites either grow very small tumors compared to

the U87MG cells or they do not grow at all. Importantly, this study demonstrates for the

first time that ACSVL3 may play an important role in regulating sphingolipid

22 metabolism. We also observe differences in mitochondrial metabolism and morphology when cells are depleted of ACSVL3 that could also influence metabolic processes within the cells.

23 CHAPTER 1

Introduction

Glioblastoma multiforme (GBM) has a very poor prognosis with median survival

time of less than fifteen months after diagnosis. Recent studies indicate improved

survival with radiation and Temozolomide chemotherapy, but even then, survival is just

over one year. Numerous GBM cell lines have been established and studied over the

years. One of the most prevalent lines, the U87MG cell line, is a long established line

isolated from a GBM tumor in a 44-year old patient. It has been used in over 1,700

publications.

ACSVL3, a very-long chain acyl-CoA synthetase and our target gene, has been

shown to be overexpressed in U87MG cells, by Western blotting, and in glioma tissue

arrays, by immunohistochemistry. Our lab has done previous work using RNA

interference (RNAi) to knockdown (KD) ACSVL3 in the U87MG cells. We used two

different stable KD constructs, known as “KD3” and “KD4”, which were shRNA

sequences that targeted different regions of the mRNA (KD3:

5’CACGGCTCGCGGCGCTTTA-3’ targeted bp 394-412; KD4:

5’CGTCTATGGAGTCACTGTG- 3’ targeted bp 1861-1879). The RNAi experiments

showed that a decrease in ACSVL3 in U87MG cells results in slower cell growth,

decreases colony number in soft agar, and leads to significantly smaller xenografts in

nude mice (Pei et al., 2009). However, these stable KD cell lines proved to be sub-

optimal for investigation of the role of ACSVL3 in cancer: 1) The use of hygromycin to

keep selective pressure on the stable lines began to have adverse effects on cell

24 metabolism, and 2) the cells were found to revert after a several passages. To try to overcome these issues, we then turned to newer technology available at that time, and made knockout (KO) ACSVL3 U87MG cell lines using zinc finger nuclease (ZFN) technology.

ZFNs are fusions of the FokI restriction endonuclease with custom-designed

Cys2-His2 zinc-finger proteins (Kim and Chandrasegaran, 1994). These nucleases induce sequence-specific DNA double-strand breaks (DSBs) that can be repaired by the error-prone nonhomologous end joining (NHEJ) to yield small mutations within the targeted genomic sequence. This technology has been shown to be robust and specific within different cell types and model organisms.

After producing genomic ACSVL3 KOs, I sought to characterize them to determine whether they mimicked the properties initially observed in the RNAi KD cell lines. Here, we show that the KOs behave as predicted, in the same way as the KDs: the

ACSVL3 KO cells grew significantly slower than the wild type U87MG cells, produce smaller subcutaneous tumors, and have lower total ACS activity. We have also begun looking as changes in cell cycle as a possible mechanism underlying the slower growth of the KO cells, and preliminary results suggest that a very large percentage of the population is stalling in S phase, while the majority of the U87MG cells are found to be in G0/G1.

25 Methods and Materials

Materials and Media

The U87MG parental cell line was obtained from American Type Culture

Collection (HTB-14). For culturing and maintenance of U87MG cells and the ACSVL3

KO cell line, the cells were grown in MEM +10% FBS + 1% of the following – Sodium

Bicarbonate, Sodium Pyruvate, Non-Essential Amino Acids, and HEPES – all from

Corning Cellgro. Cells were maintained at 37C in a 5% CO2 atmosphere. Cells were

harvested for experiments (unless stated otherwise) using trypsin, then washed twice with

phosphate-buffered saline. The resulting cell pellets were resuspended in a buffer of 0.25

M sucrose, 1 mM Tris-HCl, pH 7.5, and 1 mM EDTA (STE). Protein concentrations

were measured using the assay as outlined by Lowry et al, (1951) or using the Pierce 660

nm Protein Assay (Thermo Fisher Scientific). All oligonucleotide primers used for

analysis were from IDT. [1-14C]Palmitic acid (C16:0), [1-14C]lignoceric acid (C24:0), [1-

14C]stearic acid (C18:0), and [1-14C]docosanoic acid (C22:0) were purchased from

Moravek.

Western blotting

TBS-T for Western blotting consisted of 0.15M NaCl, 0.05% Tween-20, and

0.01M Tris, pH 7.4. For sodium dodecyl sulfate-polyacrylamide gel electrophoresis

(SDS-PAGE), 5x sample loading buffer was prepared to yield a final 1x concentration of

2% SDS, 50 mM Tris, 0.2 mg/mL bromophenol blue, 5% 2-mercaptoethanol, 12.5 mM

EDTA, and 10% glycerol. Blocking and antibody dilution buffer for Western blotting

26 was 10% (w/v) dry milk in TBS-T. Protein samples were made by diluting to 2 ug/uL in

STE plus loading buffer, and boiled for 5 min. Bis-Tris acrylamide gels were prepared

by the method of Laemmli (1970) and contained 8% acrylamide/bis-acrylamide (Sigma

A3699) and 0.375M Tris-HCl; polymerization was facilitated by the addition of 0.067%

ammonium persulfate and 0.05% TEMED. 30 ug of protein per lane was loaded, and

proteins were separated at 95V. Proteins were transferred to PVDF for 3 hours in 1x

Tris-Glycine buffer with 20% MeOH. PVDF membranes were blocked with 10% milk in

TBS-T for one hour, washed with TBS-T and then incubated in anti-ACSVL3 antibody overnight (1:400 dilution). ACSVL3 antibody was raised in rabbits against the C- terminal 175 amino acids and affinity purified as previously described (Pei et al., 2006).

After incubation with primary antibody, the membrane was washed for 5 min with TBS-

T x3, after which it was incubated for one hour with goat anti-rabbit secondary antibody conjugated to horseradish peroxidase (Santa Cruz Biotechnology). The membrane was again washed TBS-T as above. Proteins were detected by chemiluminescence using the

SuperSignal West Pico reagent (Thermo).

Generation of the ACSVL3 KO in U87MG cells

The U87MG ACSVL3 KO cell line was produced using the zinc finger nuclease

(ZFN) method, using reagents designed and supplied by Sigma-Aldrich (CompoZr

Knockout Zinc Finger Nucleases). Two plasmids were obtained; pZFN1 (5’-

TGTGCTTTCCCACCCTTCTA-3’) targets the forward genomic DNA strand just upstream of Exon 2, and pZFN2 (5’-AGGTGAGGAGACTGGGAGT-3’) targets the reverse strand just downstream of Exon 2. Plasmids were co-transfected into U87MG

27 cells using FuGENE (Promega). After 48 hours, cells were harveste and counted using a

hemocytometer. Cells were plated into 96-well plates at an average density of 0.9 cells/well to produce clones generated from single cells. Clones were selected, expanded, and tested for ACSVL3 knockout by Western blot using affinity-purified ACSVL3 antibody as described above. Both genomic DNA and cDNA were prepared from clones and used for polymerase chain reaction- (PCR-) mediated amplification of the ZFN- targeted region.

Growth Curves

Cells were counted using a hemocytometer. U87MG and ACSVL3 KO cells were plated onto 6-well plates at 5,000 cells per well in U87MG media. Cells from triplicate wells were harvested and counted every other day from day 3 through day 11.

Counts were then averaged and the mean and standard deviation were calculated for each time point. Statistics were performed using a two-tailed Student’s t-test.

Acyl-CoA Synthetase Assay

Activation of fatty acids to their Coenzyme A derivatives was measured by utilizing radiolabeled palmitic acid (C16:0), stearic acid (C18:0), behenic acid

(docosanoic acid, C22:0), and lignoceric acid (C24:0). To yield a final assay concentration of 20 µM, working solutions of radiolabeled fatty acids were made in benzene such that 50 µL contains 1 nmol of [1-14C]fatty acid and 4 nmol unlabeled fatty

acid. For each sample, duplicate 50 uL aliquots of working solution were dried under

nitrogen in 13x100 mm glass tubes and fatty acids were solubilized by adding 50 µl of α-

28 cyclodextrin (10 mg/ml in 10 mM Tris-HCl, pH 8.0) and sonicating in a water-bath sonicator (Branson) for 5 min at 37C. After an additional incubation for 30 minutes in a

37C water bath with gentle shaking, respective amounts of protein (depending on the fatty acid being assayed) in 50 µL STE buffer were added to the tubes. For palmitic acid,

15 ug protein was used; for stearic acid, 30 ug protein was used; and for behenic acid and lignoceric acid, 60 ug protein was assayed. To initiate the reaction, 150 uL of a mixture containing (final concentrations) 10 mM ATP, 1 mM MgCl2, 0.2 mM CoA, and 0.2 mM dithiothreitol was added to the tubes, and the tubes were briefly vortexed. Blanks contained STE buffer alone. The samples were then incubated for 20 min in a 37C water bath with shaking. Reactions were stopped by addition of 1.25 mL modified Dole’s solution (Isopropanol: Heptane: 2N H2SO4 – 40: 10: 1).

The tubes were allowed to cool for at least 20 min at room temperature before separation of fatty acid substrate and acyl-CoA product by the method of Dole (1956).

Samples were centrifuged at room temperature for 10 min at 2,000 rpm. The supernatants were transferred to new 13x100 mm glass tubes. 0.75 mL heptane and 0.5 mL deionized water were added to each tube. The tubes were vortexed and once the two phases settled, the upper phase was discarded by aspiration. Another 0.75 mL heptane was added, tubes were vortexed, and the upper phase was aspirated; this process was repeated one additional time. After a final wash with 0.75 mL heptane and a 1 min centrifugation to fully separate the phases, the upper phase was aspirated and the lower phase was transferred to small scintillation vials. After addition of 5 mL Budget Solve

(RPI), radioactivity (disintegrations per minute (dpm)) in each sample was determined by liquid scintillation counting.

29 Results from duplicate samples were averaged, and appropriate blanks subtracted.

An aliquot of working solution was counted to calculate the specific activity (dpm/nmol)

for each substrate. Using the known protein concentrations for each sample and the

calculated specific activity, results were ultimately expressed as nmol/20 min/mg protein.

Standard deviation was determined and p-values were calculated using a two-tailed t-test.

Xenograft Studies

All animal protocols were approved by the Johns Hopkins Animal Care and Use

Committee. In vivo tumorigenesis of U87MG and ACSVL3 KO cells was assessed in 4-

to 6-week old female mice as previously described (Laterra et al., 1997; Kim et al.,

2006). NIH III Xid/Beige/Nude mice (National Cancer Institute, Frederick, MD) were injected with 4 x 106 cells in 0.1 mL of PBS in the dorsal areas. Tumor size was

measured using calipers, and volume was estimated by the following formula: volume =

(length x width2) / 2. Mice that were injected with U87MG cells were sacrificed 15 days

after injection, and those that were injected with ACSVL3 KO cells were sacrificed on

day 19. The xenografts were harvested and then weighed.

Proteomic Profiling of U87MG and the ACSVL3 KO cells

Sample preparation. Cells for proteomic profiling were cultured as biological

replicates, harvested by gentle trypsinization, and transported to the laboratory of Dr.

Akhilesh Pandey (Johns Hopkins University School of Medicine). Further preparation

and sample analysis was performed by Pandey lab personnel as follows. 4% SDS lysis

buffer (4% SDS, 100mM Tris pH 8.0) was added to the cell pellet and was heated at 95C

30 for five minutes to destroy protease activity. After heating, tubes were kept at room temperature. Samples were sonicated using a probe sonicator operating in a continuous mode at 20 Hz output for three 15 sec cycles. Samples were heated at 95̊C for another 10 minutes to ensure complete solubility, followed by centrifugation at 17,000 g for 15 minutes. The cleared lysate was collected and protein was measured using the

Bicinchoninic acid (BCA) assay (Pierce, Waltham, MA). Samples were stored at -80C until further analysis.

Protein digestion and tandem mass tag (TMT) labeling. 200 ug of protein lysate was reduced with 10mM DTT and incubated at 60C for 20 minutes. A 30 kDa molecular weight cut-off filter (Millipore, USA) was used to remove SDS and to exchange the buffer with 8M Urea in 50mM triethylammonium bicarbonate (TEAB) buffer by centrifugation at 14,000 x g for 15 minutes at room temperature. Reduced proteins were alkylated by adding 20mM iodoacetic acid and incubated in the dark at room temperature for another 30 minutes. Buffer exchange with urea was continued for another 4 cycles, after which the urea was depleted using 2 cycles of 50mM TEAB buffer alone. The final retentate was reconstituted in 200 ul of 50mM TEAB buffer and protein was measured using the BCA assay. Equal amounts of protein from each sample were digested with trypsin (Promega) in 50mM TEAB for 16h at 37C at an enzyme to substrate ratio of 1:50.

The digested peptides were purified using Sep-Pak® C18 cartridges (Waters, USA), lyophilized, and subjected to tandem mass tag (TMT) labeling according to the manufacturer’s instructions (Thermo Fisher, Pierce Scientific). After TMT labeling, samples were pooled, vacuum dried, and fractionated by high pH reversed-phase liquid chromatography (bRPLC) on an Agilent 1100 LC system. A total of 96 fractions were

31 collected and concatenated to 24 fractions. These fractions were then vacuum dried and

were subjected to LC-MS/MS analysis

LC-MS/MS analysis of enriched peptides. A total of 12 bRPLC fractions were

analyzed on an Orbitrap Elite mass spectrometer (Thermo Electron, Bremen, Germany)

interfaced with Easy-nLC II nanoflow liquid chromatography system (Thermo

Scientific, Odense, Denmark). The peptide digests were reconstituted in 0.1% formic acid

and loaded onto a trap column (75 µm x 2 cm) packed with Magic C18 AQ (Michrom

Bioresources, Inc., Auburn, CA, USA). Peptides were resolved on an analytical column

(75 µm x 30 cm) at a flow rate of 300 nL/min using a linear gradient of 10-35% solvent B

(0.1% formic acid in 95% acetonitrile) over 90 min. The total run time including sample loading and column reconditioning was 120 min. The Orbitrap Elite mass spectrometer was operated in a data dependent mode at High-High Orbitrap mode. The full scans in the range of m/z 350-1800 was used with 1.6 m/z isolation width and were measured using an Orbitrap mass analyzer at a mass resolution of 120,000 at m/z 400. The top 15 precursor ions were selected and were fragmented using normalized higher energy collisional dissociation (HCD) at 37% and measured using Orbitrap mass analyzer at a resolution of 30,000 at m/z 400. The ion filling times and AGC targets were set at 100 ms and 1X106 for full scans and 5X104 and 200ms for MS2 and MS3 scans respectively.

Dynamic exclusion was enabled and repeat duration was set for 45 seconds. Isobaric mass tag m/z 230.14 (TMT) was excluded for MS3 mode. Internal calibration was carried out using lock mass option (m/z 445.1200025) from ambient air.

Mass spectrometry data analysis. A total of 24 LC-MS/MS raw files that were acquired as technical runs were used for mass spectrometry data analysis for the peptide

32 identification and quantification. The raw data was processed through the Proteome

Discoverer 2.1.0.81 software suite to generate peak list files for the database searches.

Data was searched against the human Refseq 73 protein database. Combined Sequest and

Mascot search algorithms were used for the peptide identification and reporter ion quantifier node was enabled for peptide quantification. A dual processing workflow and consensus workflows were created with the following parameters. a) minimum and maximum precursor were selected as 350 Da and 8000 Da respectively; b) trypsin is selected as protease and a maximum of 2 missed cleavages were allowed; c) precursor and fragment mass tolerance were set as 20 ppm and 0.1 Da respectively; d) oxidation of methionine residue as static modification and carbamidomethylation of cysteine, peptide

N-terminus and lysine side chain as TMT reported tag were selected as variable modifications. Percolator node was used for calculating p values of identified PSMs and peptides for statistical significance. 1% protein level and peptide level FDR was used in the consensus workflow. Peptide quantification was carried out using reporter ion quantifier and isolation interference cut-off was set as 30% in order to account for the interference from co-eluting peptides. Only peptides that fell below this criterion were considered for peptide quantification.

Real-time PCR and Conventional PCR of ACSVL3 cDNA

RNA was extracted from U87MG and ACSVL3 KO cells using TRIzol (Thermo

Fisher Scientific). RNA concentrations were measured using a NanoDrop spectrophotometer, and a total of 3 ug of RNA per sample was used to synthesize cDNA using SuperScript III Reverse Transcriptase (Thermo Fisher Scientific) as described in

33 the manual. Reactions included 7.5 uL of SYBR Green Master Mix (Thermo Fisher

Scientific), 1 uL each of Forward and Reverse primers, 5 uL cDNA, and 0.5 uL dH2O.

The primers used for qPCR are as follows – Fwd: 5’-CAATGCCAGGGCTTCTATC-3’;

Rev: 5’-GGGCGAGGTAGATCACAT-3’. Primers were designed for RPS5 cDNA as

the normalizer – Fwd: 5’-AAAGCTCAGTGTCCCATTG-3’; Rev: 5’-

CAGGTGTATGATCTCGAAGG-3’. The reactions ran for 35 cycles in a Bio-Rad

CFX96 Real Time PCR Detection System with a melting temperature of 95̊C for 30

seconds, an annealing temperature of 55̊C for 15 seconds, and extension at 72̊C time of

15 seconds for each cycle.

Conventional PCR of ACSVL3 cDNA from U87MG and ACSVL3 KO cells was

performed in a T100 Thermal Cycler (Bio-Rad). Samples amplified over 35 cycles using

Phusion High Fidelity Polymerase (New England Biosciences). For each cycle the

following temperatures and times were used: initial melting occurred at 98̊C for 30 sec;

melting 98̊C for 8 sec; primers annealed at 58̊C for 20 sec; extension at 72̊C for 18 sec.

Final extension was at 72̊C for 8 min. ACSVL3 ZFN deletion forward primer sequence;

5’-CCTGCTGGAATTAGCGATT-3’. ACSVL3 ZFN deletion reverse primer sequence;

5’ –TGCCAGAGGTGAAGATGTA-3’

Cell Cycle Assays

Cells were harvested from 10 cm dishes using trypsin. Cells were counted using a

hemocytometer. A total of ~1 x 106 cells were used for each sample. Samples were labeled and processed as described by the Muse Cell Cycle Assay kit (Millipore). The cells were transferred to a 15 mL conical tube and were centrifuged at 300 x g for 5 min.

The supernatant was removed without disturbing the pellet. 1 mL of PBS per 1 x 106

34 cells was added and the cells were mixed well by pipetting several times. Samples were

centrifuged at 300 x g for 5 min. The supernatant was discarded, leaving ~50 uL per 1 x

106 cells. The pellet was resuspended in the PBS by pipetting several times. The cells

were resuspended drop-wise into a tube containing 1 mL of ice cold 70% ethanol while

vortexting at medium speed. The tubes were capped and kept at -20̊C for 72 hours before staining.

To stain with the Muse Cell Cycle Reagent (with propidium iodide), 200 uL of the ethanol-fixed cells were transferred to a 1.5 mL microcentrifuge tube. The samples were centrifuged at 300 x g for 5 min at room temperature. The supernatant was then discarded. The cell pellet was resuspended in 250 uL PBS, and this was centrifuged again at 300 x g for 5 min at room tempertature. The supernatant was removed. The cells were resuspended in 200 uL of the Muse Cell Cycle Reagent and incubated for 30 min, protected from light. Gating was adjusted once the first sample was run. The Muse was set to acquire 10,000 events per sample.

35 Results

Genomic Knockout (KO) of ACSVL3 in U87MG Cells Using Zinc Finger Nucleases

(ZFNs)

ACSVL3 is overexpressed in malignant gliomas, as well as lung and prostate

tumors (Pei et al., 2009, 2013) (Z Pei and PA Watkins, unpublished). Using the U87MG

glioma cell line as a model system, our lab previously showed that depleting ACSVL3 by

RNA interference decreased the malignant properties of these cells, both in culture and

when used to produce xenografts in mice. To extend these observations, and to

investigate the mechanisms underlying ACSVL3’s role in cancer, zinc-finger nuclease

(ZFN) reagents were obtained from Sigma-Aldrich and used to create a genomic KO of

ACSVL3 in U87MG cells. Our lab also sent the parental U87MG line to the Genetic

Resources Core Facility (Johns Hopkins School of Medicine, Institute of Genetic

Medicine) to authenticate our cell line by short tandem repeats, and found that the cells were indeed U87MG cells.

To characterize ACSVL3 KO cells, we wanted to 1) identify the mutation site within the gene and 2) make sure that it was a KO at both the genetic and protein level.

Genomic DNA was extracted from both the U87MG cells and the newly made KO cells, and was sequenced using primers upstream and downstream of the predicted KO site.

Sequencing showed that in the KO cells, there was an in-frame 210 bp deletion of Exon

2. More importantly, more than half of the nucleotides (19 out of 30) which encode

Motif I, the AMP binding domain of ACSVL3, were deleted (Figure 8A). Previous studies of Motif I of bacterial (Escherichia coli) and simple eukaryotic (Sacchromyces

36 cerevisiae) ACSs showed that mutation of any of the residues within this conserved

sequence abolishes or severely reduces catalytic activity (Weimer et al., 2002; Zou et al.,

2002).

In addition to sequencing, we also performed PCR of the deletion region using primers that were within the deletion region, with a predicted product size of 103 bp.

RNA was extracted from wild-type and KO cells and used to synthesize cDNA that was used as template for the PCR. The product was run on a 1% agarose 1x TBE gel and visualized using ethidium bromide. The results show that the region was indeed deleted in the proposed ACSVL3 KO, and that a specific band was amplified in the U87MG wild-type of the correct predicted size (Figure 8B).

To see if there was less ACSVL3 protein as a result of the ZFN deletion, we performed Western Blotting with a custom antibody that recognizes an epitope within the

C-terminal 175 amino acids of wild-type ACSVL3. 30 ug of protein was loaded into each well of an 8% polyacrylamide gel. The protein was transferred to a PVDF membrane and was probed with rabbit ACSVL3 antibody overnight (1:400 in 10% milk

+ TBS-T). After incubation with anti-rabbit secondary antibody and exposure to film, we find a very strong band in the U87MG cells of the correct molecular weight (~78 kDa)

(Figure 8C). Surprisingly, we found a weaker band around the same size in the ACSVL3

KO cell line. Another potential KO candidate, clone 27, was also included on the membrane to see if it was also an ACSVL3 KO cell line. This potential KO line had a 9 bp deletion that also abolished part of Motif I. While we find a weaker putative ACSVL3 band in this candidate cell line, we later discovered through sequencing that this was a heterozygous cell line, and was excluded from further investigation.

37 A proteomics study of the ACSVL3 KO and the U87MG cells was performed in

collaboration with Akhilesh Pandey, Ph.D. at Johns Hopkins University. First, we

wanted to see if the proteomics data agreed with our Western Blotting data showing that

there was lower ACSVL3 protein. Only two peptides, both N-terminal to the ZFN deletion site, were detected, and the data does show that there is a decrease in ACSVL3 protein levels in the KO compared to the U87MG cells (Figure 9A). However, like the

Western blotting result, we still do see peptides derived from the ACSVL3 protein. We believe that we may be seeing read-through of the transcript due to the in-frame deletion, and the lower levels of protein could be because the deletion makes the protein unstable.

Real-time PCR was also performed using SYBR green and primers specific for ACSVL3 cDNA to see if there was also a lower level of transcripts. A total of 5 samples per cell line were assayed, and there is a much lower level of ACSVL3 transcripts in the

ACSVL3 KO cell line (Figure 9B), which can also contribute to the lower levels of protein. Taken together, these data indicate that the ACSVL3 KO cell line can be used to investigate the metabolic role of this enzyme in cancer.

38

Figure 8. ZFNs create a genomic ACSVL3 KO by deleting a 210 bp region. (A)

Sequencing of both the genomic DNA and the mRNA (by synthesizing cDNA) of the

putative ACSVL3 KO cell line revealed an in-frame 210 bp region that was deleted in both the DNA and the mRNA correlating with most of Exon 2, including most of Motif I.

(B PCR amplification using primers specific for the deletion region show that DNA is

amplified in the U87MG cells, and not the ACSVL3 KO line). (C) Western blotting

shows a significant decrease in protein levels of ACSVL3 in the KO line and another

potential KO line, “#27”. While we detect a small amount of protein, it is believed to be

catalytically dead.

39

Figure 9. Proteomic analysis and qPCR show a decrease in ACSVL3 relative to the

U87MG cell line. (A) Proteomic analysis shows a 50% decrease in ACSVL3 peptide

levels in the ACSVL3 KO line. We believe that these peptides are indicative of read- through of transcript that is being produced, and that the product is catalytically dead. A total of two peptides were found during the analysis that were both N-terminal of the

ZFN deletion site. (B) qPCR revealed a marked decrease in ACSVL3 transcripts compared to the U87MG line.

40 ACSVL3 KO in U87MG Cells Causes a Change in Morphology and a Slower

Growth Rate

During the characterization of the ACSVL3 KO cells, I observed that the cell

morphology was different when compared to the U87MG cell line (Figure 10A). When

ACSVL3 is absent from U87MG cells, the cells take on a flatter morphology, and appear

take up much more surface area.

To determine whether the ACSVL3 KO cells exhibit the same growth defect that

was found in the stable KD cell lines, I performed a growth curve. The ACSVL3 KO cell

line and the U87MG cell line were both seeded at 5,000 cells per well in a 6-well cell culture dish in regular U87 culture media. Starting three days after seeding, triplicate wells of cells were harvested and counted every other day for 11 days (Figure 10B). The growth rate of ACSVL3 KO cells was significantly slower than U87MG cells. On day

11, the rate for KO cells was 12% of U87MG cells, a statistically significant difference

(p<0.005). This result was in agreement with that previously seen in ACSVL3 KD cells when compared to the U87MG cells (Pei, et al., 2009).

41

Figure 10. ACSVL3 KO cells have an altered morphology and grow significantly slower than the U87MG cells. (A) Light microscopy reveals differences in morphology between the U87MG cells (left) and the ACSVL3 KO cells (right). The

ACSVL3 KO cells appear larger, flatter, and take up more surface area. (B) 5,000 cells were seeded in each well on Day 0. Cells were counted every other day starting from

Day 3. When the assay ended on Day 11, the ACSVL3 KO cells showed significantly slower growth (p = 0.0003) and grew at rate that was 12% of the U87MG growth rate.

42 ACSVL3 KO Xenografts are Significantly Smaller than U87MG Xenografts

Previous studies demonstrated that the ACSVL3 KD cell lines had a gross effect

on glioma cell tumorigenicity in vivo (Pei et al, 2009). The KD cell lines exhibited

slower tumor growth rates over time and fewer tumors formed at injection sites when

compare to the U87MG cells. To test if the newly derived ACSVL3 KO cells grow in the

same manner as the ACSVL3 KD cells in vivo, nude mice were subcutaneously injected with 4 x 106 U87MG or ACSVL3 KO cells. For each cell type, 5 mice were injected in

both flanks. After one week of growth, the tumors were measured with calipers every

other day for width and length (Figure 11C). In mice bearing U87MG xenografts, tumors

became quite large (Figure 11A, B), necessitating sacrifice on day 15 for humane

reasons; mice injected with KO cells were sacrificed on day 19. Xenografts formed at all

10 sites in mice injected with U87MG cells. In contrast, tumors failed to form at 3 out of

10 sites injected with KO cells. After xenograft harvesting, the tumors were weighed.

The U87MG xenografts weighed significantly more than the ACSVL3 KO xenografts

(Figure 11D). These results corroborate the results that were obtained with the stable

ACSVL3 KD cell lines, and demonstrate that ACSVL3 is important for in vivo tumor

growth.

43

Figure 11. ACSVL3 KO cells grow smaller subcutaneous tumors in nude mice.

Cells of both U87MG and ACSVL3 were injected into nude mice (4 x 106 cells/injection site). (A) Subcutaneous tumors in the nude mice on Day 15 after injection. The

ACSVL3 tumors (top) are much smaller than the U87MG tumors (bottom). (B) Tumors of U87MG cells were harvested 15 days after injection (left) and the ACSVL3 KO tumors (right) were harvested on Day 19. Representative tumors are shown. (C) Tumor size was measured using calipers throughout the study, with the U87MG tumors growing significantly larger than the KO. (D) After harvesting, the tumors were weighed. The

U87MG tumors weighed about 6x more than the ACSVL3 KO tumors.

44 The Acyl-CoA Synthetase Profile of the ACSVL3 KO line

We also analyzed the proteomics data generated by the Pandey lab to see if there

was an overall change to the acyl-CoA synthetase profile of the ACSVL3 KO line. In

total, we were able to detect 7 long- and very-long chain ACSs – ACSL3, ACSVL4

(SLC27A4), ACSL1, ACSVL5 (SLC27A1), ACSL4, ACSVL3 (SLC27A3), and ACSL5

(Table 1). In both of these cell lines, we find that ACSL3 was the most abundant ACS,

and the value found in the U87MG cells was set at 1.00 for comparison of the other

ACSs, and between the U87MG cells and the ACSVL3 KO cells. ACSL3 is slightly

increased in the ACSVL3 KO line (Table 1). This has been observed in other cancers;

microarray analysis of melanoma cells shows that there is an upregulation of ACSL3

(Sumantran et al., 2015), however since the upregulation is occurring in the KO cells

with the growth defect, we do not think that this particular enzyme is important to

glioma. We do see slight decreases in the other long- and very long-chain ACSs, except

for ACSL5. ACSL5 has been shown to be a pro-apoptotic gene and is elevated with

DHX32, a gene implicated in proliferation and cell growth. It was depleted in colorectal cancer cells (Lin et al., 2015). Because it did not change with the depletion of ACSVL3 in U87MG cells, it suggests that changes we see in growth and tumorigenicity are because of changes in ACSVL3, and not because of other ACSs that have been implicated in cancer.

We also analyzed proteomic data from primary astrocytes, obtained in a separate experiment, from the Pandey lab. While we were not able to directly compare these data to data obtained with U87MG and KO cells, we used them here as a reference.

Interestingly, normal astrocytes expressed the same long- and very long-chain ACSs

45 found in U87MG and KO cells. Again, the major ACS was ACSL3, and this was set to

1.00 and we compared the long- and very long-chain ACSs to that. We found that

ACSVL3 was expressed at an extremely low level (0.04 relative to ACSL3) in normal astrocytes, compared to 0.38 relative to ACSL3 in U87MG cells. The low level in normal astrocytes also correlates with the IHC data for normal brain from the glioma tissue array shown in Figure 7 (Pei et al., 2009). ACSL5 was found to be below the level of detection in the primary astrocytes.

46

Table 1. The relative abundance of the long- and very long-chain acyl-CoA synthetases in U87MG cells and ACSVL3 KO cells. Proteomic analysis was performed on both cell lines. Proteomic data from primary astrocytes from a separate experiment was used as a reference. ACSL3 was the most abundant ACS found in

U87MG cells, and was set at 1.00. All other ACS values are relative to ACSL3. We see slight decreases in most of the ACSs in the ACSVL3 KO cells, except for ACSL3, which is increased.

47 ACSVL3 KO Cells Have Lower Activation of Long and Very-Long Chain Fatty

Acids

To investigate the effects lower ACSVL3 levels have on the activation of fatty

acids, we looked at the acyl-CoA synthetase enzyme activity using several long and very-

long chain fatty acid substrates. The activation of palmitate (C16:0), stearic acid (C18:0),

behenic acid (C22:0), and lignoceric acid (C24:0) was measured by incubating cell

suspensions with solubilized [1-14C]-labeled fatty acid and cofactors, including

Coenzyme A. The fatty acid substrates were separated from the acyl-CoA products using

Dole’s method, and radioactivity (dpm) in the latter was measured per sample using a

liquid scintillation counter; results were expressed as nmol/20 min/mg protein for final

analysis. When measuring enzyme activity using radiolabeled C16:0 and C24:0,

substrates that the lab had used before as representative long- and very long-chain fatty acids, there is a slight decrease in the KO cells, however this was not statistically significant (Figure 12A, D). The enzyme activity assay was then repeated with C18:0 and C22:0, and with these substrates we see a very significant decrease when ACSVL3 is depleted from cells (Figure 12B, C). The relevance of the significant decreases in activation of C18:0 and C22:0 vs. C16:0 and C24:0 will be discussed further in Chapter

2.

48

Figure 12. Total Activation of long- and very long-chain fatty acids is lower in

ACSVL3 KO cells. A total of 4 samples were assayed for each [1-14C]-labeled fatty

acid. C16:0 palmitic acid (A) and C18:0 stearic acid (B) are considered long-chain fatty acids, with C22:0 behenic acid (C) and C24:0 lignoceric acid (D) are very long-chain fatty acids. There was a slight decrease in the activation of C16:0 and C24:0, but the difference was not statistically significant. Significant decreases (p<0.001) were observed when C18:0 and C22:0 was used as substrates, with lower activation in the

ACSVL3 KO cells.

49 U87MG Cells and ACSVL3 KO Cells Proceed Through the Cell Cycle Differently

We have been exploring the factors responsible for the growth phenotype of the

ACSVL3 KO cells. There could be several reasons for the differences in growth we have observed, including changes in apoptosis, autophagy, cell cycle, or metabolism. Several indicies of apoptosis or autophagy were measured. Those studies concluded that the

ACSVL3 KO cell line did not have increased rates of either apoptosis or autophagy when compared to the U87MG cells (Watkins et al., unpublished). To assess if there were differences in cell cycle between our two cell lines that can explain the growth phenotype, I used the Muse Cell Cycle Assay (Millipore) This assay relies on the difference in binding and increasing fluorescence of propidium iodide to the DNA and can differentiate between the different phases of the cell cycle. The majority of U87MG cells appear to be in the G0/G1 phase, with an average of 71.1±3.8% (mean ± SD) of the population in that phase. Only 7.3±0.5% of the U87MG cells appeared to be in S phase, and 9.3±2.0% were in G2/M. The ACSVL3 KO cells exhibited a very different profile.

A very small percentage of the cells – 0.3% – were in G0/G1. The majority of the KO cells were found to be in S-phase, at 66.2±0.9%, and 9.3±0.2% were in G2/M (Figure

13). Further studies will be necessary to understand this result. We cannot conclude if the ACSVL3 KO cells are proceeding through S-phase slowly, or if there is a block at a checkpoint that is preventing a large population of the cells to enter into G2.

50

Figure 13. The majority of ACSVL3 KO cells are in S-phase. The Muse Cell Cycle

Assay was used, which relies on propidium iodide, to determine cell cycle status of the population of both U87MG and ACSVL3 KO cell lines. A total of 10,000 events were recorded. We found that the majority of the U87MG cells are in G0/G1 (71%), with a small percentage (7.3%) being in S phase. Surprisingly, the vast majority of the

ACSVL3 KO cells were in S phase (66%), with hardly any being in G0/G1 (0.3%).

51 Discussion

Acyl-CoA synthetases play a central role in fatty acid metabolism by “activating”

the fatty acids with the addition of a Coenzyme A. These activated fatty acyl-CoAs can be utilized by the cell in a number of metabolic pathways. They can be used as an energy source via β-oxidation in the mitochondria, provide substrates for synthesis of phospholipids and sphingolipids, or can be used to acylate proteins. Because of the varying lengths of fatty acids and the diverse nature of their metabolic fates, the human genome contains 26 different acyl-CoA synthetases, specific for varying substrate chain lengths.

Our lab has found that one of the very long-chain acyl-CoA synthetases,

ACSVL3, is overexpressed in a number of different cancers, including WHO grade IV glioblastoma multiforme, through a tissue array of 79 patient tissues of varying grades of glioma. To investigate the importance of ACSVL3 to tumorigenesis in glioma, the lab made a stable knockdown (KD) construct in the U87MG cell line. This cell line demonstrated that acyl-CoA synthetase activity was lower, cell growth was slower, and xenografts in nude mice were smaller when compared to the parental U87MG line. We wanted to further investigate the effects of glioma cells lacking ACSVL3, and created a genomic knockout (KO) cell line using zinc-finger nucleases (ZFNs).

The deletion region created by the ZFNs was characterized by genomic DNA sequencing. We determined that the deletion was 210 bp of genomic DNA that deleted most of Exon 2, which included most of Motif I, the AMP-binding site. It was also determined that the deletion was also in-frame. This site is highly conserved and is

52 critical for enzyme activity, as mutagenesis of any part of the motif abolishes enzymatic

activity. We were able to confirm the sequencing results through PCR using primers

specific for the deletion region. We were able to amplify product in the U87MG cell line

while we were not able to detect a band in the ACSVL3 KO line. We wanted to see if we

could detect any protein via Western Blotting using a custom antibody raised against the

C-terminal region of ACSVL3. We found that ACSVL3 is present in U87MG cells, but

that the protein levels are nearly zero in the ACSVL3 KO band. While some ACSVL3

protein is present, we believe that it is enzymatically dead.

Characterization of the ACSVL3 KO cell line shows that it shares similar

characteristics as the ACSVL3 KD line, making the KO line a viable model to further

study the mechanistic importance of ACSVL3 in glioma. When glioma cells are depleted

of ACSVL3, as proven by DNA and protein analysis, we find that cell growth is

significantly slower over an 11 day period. To show that it was an ACSVL3-specific

growth defect, Pei, et al. also used shRNA to deplete cells two other acyl-CoA synthetases, which are both expressed in U87MG cells. FATP4, another very long-chain acyl-CoA synthetase (Watkins, 2008), and ACSF2, which activates medium-chain fatty acids (Watkins, et al., 2007) were depleted in U87MG cells, and growth rate was measured in the same manner. They showed that knockdown of either FATP4 or ACSF2 did not affect growth over the same time period as ACSVL3 affected growth of U87MG cells.

We wanted to explore the growth defect further to determine the cause of the slower growth observed in the ACSVL3 KO. Previous unpublished work from our lab looked at potential differences in apoptosis or autophagy as possible explanations for this

53 difference we see between our two cell lines. The study concluded that neither pathway

could explain the growth differences. The other possibility was a difference in cell cycle

progression when ACSVL3 is absent in U87MG cells. We used the Muse Cell Cycle

Assay kit from Millipore to assess if there were any differences. This approach uses

propidium iodide, a DNA intercalating molecule, to detect DNA content differences. We

found that while most of the U87MG population was in G0/G1, the vast majority of the

ACSVL3 KO cells were in S phase. A typical rapidly proliferating human cell stays in S

phase for about 8 hours, G2 for about 4 hours, M/cytokinesis for about 1 hour, and the new cells enter G1 for about 11 hours (Cooper, 2009). We do not have enough information to know if the ACSVL3 KO cells are arresting in S phase, or if they are proceeding through S phase slower than the U87MG cells. This will be investigated

further to understand the effects that ACSVL3 has on the cell cycle.

We also show that the ACSVL3 KO cell line either forms very small

subcutaneous xenografts, or do not form tumors at all at the injection site. The

xenografts that do form are significantly smaller in size and lower in weight compared to those formed using U87MG cells. This characterization, along with the similar effects of the ACSVL3 siRNA KD lines, also demonstrates that ACSVL3 is not necessary for growth of wild type cells, but it is essential for the malignant properties exhibited by the

U87MG cells.

After we had determined that the ACSVL3 KO cell line affected the growth properties and tumorigenic properties of the parental U87MG cells, we wanted to look at the ACS profile of the two cell lines. Proteomic analysis of the U87MG line and our

ACSVL3 KO line show that there were 7 out of 11 long- and very-long chain ACSs

54 identified. We also obtained data from primary astrocytes from another experiment to

use as a reference, but not a direct comparison. These data were useful in determining

whether deleting functional ACSVL3 protein would affect the expression of the other

ACSs found in U87MG cells. We found that ACSL3 actually increased in the ACSVL3

KO cells, but another ACS known to be important in cancer, ASCL5, was found to be in

the same abundance across the two different cell lines.

At this point, we do not know if there are off target-effects and if this is the cause of any decreases we do see in the KO line in the other ACSs found. It could be due to the decrease in products of ACSVL3 or of the protein itself that may be affecting the expression of the other enzymes. Not much is known about the transcriptional and translational regulation of the acyl-CoA synthetases. Some data has been published suggesting that the SREBPs are involved in transcription, in particular for ACSL1 (Singh et al., 2016). The literature also shows PPARs are involved in regulating transcription of

ACSL4 (Kan et al., 2015).

We also tested the overall activation of long- and very long-chain fatty acids in

the U87MG cells and the ACSVL3 KO cells. We found an expected decrease in KO cell

enzyme activity with each of the [1-14C]labeled fatty acids we used. There was a slight

decrease in activation when we used C16:0 and C24:0 fatty acids, which are commonly

used by our lab as representative long- and very long-chain fatty acids. We also used

C18:0 and C22:0, and surprisingly, we found greater, statistically significant decreases in the ACSVL3 KO cells with both fatty acids. The long- and very long-chain ACSs have great substrate overlap in vitro, and so we expected to see decreases in KO cells with all of these fatty acids. However, we believe the significant decreases in C18:0 and C22:0

55 in the ACSVL3 KO cells indicate a greater specificity for these fatty acids over C16:0

and C24:0. This proved to be an important consideration when choosing substrates for

experiments that will be described in Chapter 2.

Now that we have established a viable way to study the effects of ACSVL3 in a

glioma cell model, we can ask why the cells behave the way they do when the cells are

depleted of ACSVL3. The physiological purpose of ACSVL3 overexpression has not

been resolved. The products of ACSVL3 are long- and very long-chain fatty acyl-CoAs, which can be used by the cell in a variety of different reactions, including β-oxidation for energy production, protein acylation, and incorporation into complex lipids. Research into the importance of the ACSs in regards to cancer, particularly the long- and very long-chain acyl-CoA synthetases is relatively new, and even then, most of the publications focus on the ACSL family of enzymes. Our lab was the first to show that

ACSVL3 is overexpressed in a number of different cancers, and to describe its role in glioma stem cell maintenance and tumorigenicity (Sun et al., 2014). It is also interesting to note that there is a correlation between ACSVL3 and Akt signaling in U87MG cells.

When ACSVL3 is depleted by siRNA in U87MG cells, Akt signaling also decreases, and that it in part is due to aberrant receptor tyrosine kinase (RTK) signaling. Using the new

ACSVL3 KO cells, we hope to identify the precise biochemistry by which ACSVL3 supports the malignant phenotype, including how it contributes to RTK signaling through

Akt.

56 Chapter 2

Introduction

Sphingolipids represent the second largest class of membrane lipids, and thousands of species have been identified. This class of lipids regulates a wide range of functions within a cell and is responsible for, or at least play a part in, pathways related to proliferation, differentiation, migration, and apoptosis (Hannun and Obeid, 2008). The basic structure of a sphingolipid contains a sphingoid base, a fatty amino alcohol, typically 18 carbons long. De novo synthesis of the base begins in the endoplasmic reticulum with the condensation of a palmitoyl-CoA and serine, a reaction that is catalyzed by the serine palmitoyltransferase enzymes (SPTs), to create dihydrosphingosine. This is then amino-acylated with a long- to very-long chain acyl-

CoA to form different species of dihydroceramide. This reaction is catalyzed by one of six different ceramide synthase enzymes. Dihydroceramide is desaturated to form ceramide, a biologically active molecule that can also be used as a precursor to more complex sphingolipids. Ceramide can also be deacylated by ceramidases to yield sphingosine. Sphingosine is another bioactive molecule, and this can be phosphorylated by sphingosine kinases to produce sphingosine 1-phosphate (S1P), another signaling molecule. This can also be dephosphorylated back to sphingosine, and sphingosine can be re-acylated back to ceramide. It is this interconversion of these three metabolites that form the basis of a regulatory “sphingolipid rheostat” hypothesis described by Spiegel and colleagues (Cuvillier et al., 1996).

57 Many studies performed over the last few decades have increased our understanding of bioactive lipids, and ceramide in particular. Ceramide, the most fundamental sphingolipid, has been found to be a tumor suppressor, promoting apoptotic and autophagic pathways, and inhibiting cell growth. Many enzymes responsible for the synthesis of ceramide are often found to be altered in cancer, resulting in a decrease of ceramide levels (Morad and Cabot, 2013). Six ceramide synthases (CerS1-6) have been discovered, and each enzyme has specificity for the synthesis of different ceramide species for different biological functions (Saddoughi and Ogretmen, 2013).

In contrast to ceramide, S1P is a potent proliferative, prosurvival, and promigratory factor (Maceyka et al., 2012; Rosen et al., 2009). Many growth factors, such as epidermal growth factor (EGF), as well as certain cytokines activate sphingosine kinase (SK1) acutely, resulting in higher levels of S1P (Hait et al., 2006). Once S1P has been generated, it can be transported from the inner leaflet of the plasma membrane to the exterior, where it can bind to specific receptors, S1P receptors1-5 (S1PRs). These receptors initiate signaling for motility, proliferation, migration, and survival, through typical G-protein coupled receptor signaling, including through Akt (Taha et al., 2004).

Gangliosides are another type of lipid important in cancer biology and signaling.

Gangliosides are glycosylated sphingolipids found on the outer leaflet of the plasma membrane, with their ceramide backbone inside the membrane and their carbohydrate head groups facing the extracellular environment. Gangliosides are important to many normal physiological processes, including cell adhesion and cell signaling (Hakomori,

2002), as well as many pathological ones, such as those related to cancer (Hakomori,

58 1996). Tumor-associated gangliosides play key roles in cancer cell invasion and metastasis, and this has been an active field of cancer research in the past few decades.

Cell membranes are structurally heterogeneous and composed of different domains with unique properties. These domains make it possible for disordered and ordered phases to coexist in the same membrane (Mesquite et al., 2000; Wang, et al.,

2000; and Wang and Silvius, 2000). Lipid rafts are one type of domain found in the cell membrane, and the hypothesis that these existed was proposed by Kai Simons and Elina

Ikonen in 1997 (Simons and Ikonen, 1997). Biochemical techniques have been developed to try to isolate lipid rafts by exploiting their detergent-resistant property in order to study their composition. Studies have shown that these tightly packed regions have high concentrations of sphingolipids, which include gangliosides, saturated fatty acids, and cholesterol.

Results presented here show that a decrease in ACSVL3 in U87MG cells causes a decrease in sphingolipids, but not cholesterol. We believe that the ceramides found in the parental U87MG cells provides a pool for the synthesis of other sphingolipids, including gangliosides and sphingosine 1-phosphate, therefore increasing signaling from lipid rafts, and perhaps signaling directly through the lipids internally, without increasing cholesterol levels in the cell. Depleting cells of ACSVL3 decreases ceramide levels affecting downstream lipids important in signaling and lipid raft structure. We observe a decrease in signaling through Akt in the ACSVL3 KO cells when incubated with EGF. U87MG cells have more C18:0 and C22:0 ceramide content than the ACSVL3 KO cells, as these species are decreased when ACSVL3 is absent, while C16:0 and C24:0 ceramides do not change. This , in addition to the acyl-CoA synthetase activity assays presented in

59 Chapter 1, supports the notion that the acyl chain-length preference of ACSVL3 is physiologically relevant.

60 Methods and Materials

General materials and media

U87MG and ACSVL3 KO cells were grown in standard U87 media. Ceramide

standards for thin layer chromatography were purchased from Matreya (Pleasant Gap,

PA). [1-14C]fatty acids were purchased from Moravek (Brea, CA) and unlabeled fatty

acids were purchased from Matreya. The internal standards for sphingosine and S1P

analysis, heptadecasphing-4-enine-1-phosphate and heptadecasphinganine-1-phosphate, were a gift from Ann Moser (Kennedy Krieger Institute). Ganglioside standards solution and equipment for ganglioside visualization via thin layer chromatography were kind gifts from Dr. Ronald Schnaar. Thin layer chromatography (TLC) plates used for ganglioside analysis were purchased from EMD Millipore by the Schnaar lab (Cat #

105635). Epidermal growth factor (EGF) was obtained from Sigma-Aldrich. [1-

14C]acetate was purchased from Moravek. TLC plates for the phospholipid and neutral

lipid synthesis analysis was purchased from Analtech, Inc (Cat # 01011).

Neutral and Phospholipid Synthesis Assay and Visualization

Cells were allowed to grow to confluence in 10 cm dishes. A total of 2 uCi of [1-

14 o C]acetate was added to each plate and allowed to incubate at 37 C in a 5% CO2

environment for 30 min. After incubation, the cells were harvested using trypsin and

were washed twice with PBS. The cell pellets were resuspended in STE buffer. Protein

concentrations were measured using the Lowry protein assay, using bovine serum

albumin (BSA) as the standard. A portion of cell suspension containing a total of 400 ug

61 protein was extracted with chloroform and methanol using the method of Folch et al.

(1957). Briefly, cell pellets in 1x PBS in a volume of 250 uL were transferred to a

16x125 glass tube with Teflon-lined caps. 5 mL of 2:1 chloroform:MeOH + 5mM HCl

and 1 mL of water was added to the cell suspension. The samples were mixed by

vortexing and then centrifuged for 2 min at 2,000 rpm in a table top centrifuge

(Beckman). After centrifugation, the aqueous upper phase was discarded. Folch’s

theoretical upper phase (3:48:47 chloroform:MeOH:H2O) was added to each tube. The

tubes were mixed by vortexing and centrifuged for 7 min at 2,000 rpm. The upper phase

was discarded and the wash was repeated until the white interphase was gone. After

removal of the upper (aqueous) phase, the lower organic phase containing extracted lipids

was evaporated to dryness under a stream of N2. Dried lipid samples were dissolved in

100 uL chloroform and a volume (20 uL) equal to 80 ug protein was spotted per lane on

the TLC plate in duplicate. Neutral lipids were separated via TLC using the solvent

system Hexane: Ethyl Ether: Glacial Acetic Acid (80:20:1). For separation of

phospholipids, the solvent system was Chloroform: Ethanol: dH2O: Triethylamine

(30:35:7:35). The following standards were used for analysis of neutral lipids and

phospholipids: cholesteryl ester was purchased from Sigma-Aldrich (Cat. #C6072); cholesterol was purchased from Matreya (#1006); tripalmitin, 1,3-dipalmitin, 1,2- dipalmitin, and monopalmitin were purchased from Nu-Chek Prep (Elysian, MN);

phospholipid standards (phosphatidic acid, phosphatidylinositol,

phosphatidylethanolamine, phosphatidylserine, phosphatidylcholine) were purchased

from Doosan Serdary Research Laboratories (Toronto, ON, Canada).

62 Ceramide Synthesis Assay

For assay of fatty acid incorporation into ceramide, “working solutions” of [1-

14C]fatty acids were prepared in benzene such that 50 uL contained ~1 nmol of radio- labeled fatty acid plus 4 nmol unlabeled fatty acid, for a total of 5 nmol. Working solutions of C16:0, C18:0, C22:0, and C24:0 were prepared. For assays, duplicate 50 uL aliquots of each fatty acid were dried down with nitrogen gas in a 13x100 mm glass tube.

The fatty acid was then solubilized by adding 50 uL of alpha-cyclodextrin (10 mg/ml in

10 mM Tris, pH 8.0) and sonicating in a water bath sonicator (Branson) for 2 minutes.

The fatty acid in alpha-cyclodextrin was further incubated in a 37C water bath for 30 minutes with gentle shaking. A reaction mix was made so that, when combined with solubilized fatty acid and cell suspension, it contained (final concentrations) : 40 mM

Tris, pH 8.0; 10 mM ATP, 10 mM MgCl2; 0.2 mM Coenzyme A, 0.2 mM dithiothreitol;

1 mM Serine; 0.2 mM NADPH. The pH was adjusted to 7.5 with 1N KOH. A cell suspension volume that was equivalent to 250 ug protein was added to the appropriate glass tubes and STE was added to adjust the total volume to 50 uL. Tubes that served as the blank received 50 uL STE only. 150 uL of mix solution was added to each tube, and the samples were then incubated in a 37C water bath for 2 hours with gentle shaking.

The reaction was stopped with 3.75 mL of 1:1 chloroform:methanol. Samples were extracted by the method of Folch et al. as described above for neutral and phoshpholipid synthesis. The final upper phase was discarded and the lower phase was dried under nitrogen gas. The resulting lipid pellet was resuspended in 50 uL 1:1 hexane:ethanol. 20 uL was spotted onto a TLC plate that was washed with 1:1 chloroform:methanol and dried before use. To resolve lipids on the plate, a solvent system of 94:1:5

63 chloroform:MeOH:glacial acetic acid was used, and the solvent front was allowed to run resolve until the front reached ~1.5cm from the top.

Ceramide extraction for LC-MS/MS Analysis

Cells were pelleted in a 1.5 microcentrifuge tube after harvesting and resuspended in 200 uL of dH2O. The cell suspensions were sonicated using a probe sonicator

(Missonix) three times, 5 seconds each time while on ice and a minute in between pulses.

600 uL of methanol, containing the internal standards (C12:0 ceramide, Avanti Polar

Lipids), was added. The samples were then vortexed. 800 uL of chloroform was then added. Samples were vortexed for 5 seconds three times. Tubes were centrifuged at

14,000 rpm for 5 minutes to separate organic and aqueous phases cleanly. The lower organic phase was collected and transferred to a separate glass vial and analyzed via LC-

MS/MS.

Sphingosine 1-phosphate and Sphingosine extraction for LC-MS/MS Analysis

The extraction method for sphingosine and S1P was adapted from Shaner, et al.,

(2009). The cells were washed twice with 1x PBS, aspirating as much of the liquid as possible after the last wash. Cells were scraped from the cell culture dishes in the residual PBS (around 0.2 mL). Protein concentrations were measured using the Lowry assay (Lowry et al., 1951). 400 ug protein was transferred to a 13x100mm borosilicate tube with a Teflon-lined cap for each sample. To each of the samples the following was added: 0.5 mL MeOH, 0.25 mL chloroform, and the internal standard cocktail for a total of 1 ng of each standard per sample (C17:0 sphingosine 1-phosphate, C17:0 sphinganine

64 1-phosphate, and C17:0 sphingosine – Avanti Polar Lipids). The samples were dispersed using a water bath sonicator at room temperature for 30 seconds. The mixture was incubated at 48C overnight in a heating block. This affords optimal extraction of sphingolipids due to their high phase transition temperatures. After cooling back to room temperature, 75 uL of 1M KOH in MeOH was added to each tube and after brief sonication, was incubated in a shaking water bath for 2 hr at 37C to cleave potentially interfering glycerolipids. The samples were again cooled to room temperature. 3-6 uL of

glacial acetic acid were added to bring the extract to a neutral pH. This was tested using

pH paper. The tubes were centrifuged to remove the insoluble residue and the

supernatant was collected. The samples were purified by centrifugation through a Spin-X

filter (Corning) and were analyzed by LC-MS/MS by Ann Moser in the Peroxisomal

Diseases Laboratory (Kennedy Krieger Institute).

Lipid Raft visualization

Plasma membrane lipid rafts between the U87MG cells and the ACSVL3 KO cells were compared using the Vybrant Alex Fluor 555 Lipid Raft Labeling Kit

(ThermoFisher). Cells were grown on 10-12 mm diameter circular glass coverslips in 6- well plates until confluent. Cells were labeled as described in the manual provided in the kit. The cells were labeled with 1 ug/mL Alexa 555-conjugated cholera toxin-B in

U87MG media for 10 min at 4C. After this, the cells were washed 5 times with ice-cold

1x PBS. To crosslink the CT-B-labeled lipid rafts, the cells were then incubated in a

1:200 dilution of rabbit anti-CT-B antibody in U87MG media for 15 min at 4C. Cells were again washed 5 times with ice-cold 1x PBS. Cells were fixed with 3.7%

65 paraformaldehyde in 1x PBS with magnesium and calcium, and then coverslips were

mounted on glass slides using mount solution (1.0 mg/ml phenylene diamine in 0.1M

Tris, pH 8.7 and 90% anhydrous glycerol) and sealed with clear fingernail polish to

prevent fading of the fluorescent signal. Raft-associated fluorescence was visualized

using a Zeiss Axioplan microscope and Axiovision software; digital images were

captured using identical exposure times.

Ganglioside extraction and TLC analysis

Once the U87MG and the ACSVL3 KO cells were confluent, media was aspirated

and the cells were washed with PBS twice. Cells were harvested in 500 uL deionized

H2O using a cell scraper. Another 500 uL of H2O was added to the plates and scraped to

retrieve remaining cells. The cells were then pelleted and weighed in pre-weighed 1.5 mL microcentrifuge tubes, and 4 volumes of deionized water was added (4 mL water/g cells).

The volume to acquire equal cell pellet weight for each sample was calculated and then appropriate volumes were transferred to a 16 x 125 mm glass tube. The total aqueous volume was calculated (volume of dH2O + 80% weight of tissue). To the samples, 2.67 volumes of room temperature methanol was added and the tubes were vortexed. 1.33 volumes of chloroform were added, and then the samples were vortexed again. The

samples were centrifuged for 15 min at room temperature and 2,000 rpm. The resulting

supernatant was then transferred to a new tube with a graduated pipet in order to note

how much of the volume was recovered. 0.173 volumes of dH2O were added and the

samples were vortexed. The samples were centrifuged for another 15 minutes at 2000

rpm. The upper phase was transferred to a new tube using a Pasteur pipet. During the

66 centrifugation, a tC18 Sep-Pak on a glass syringe was pre-washed with 3 mL of the

following in order – CHCl3:MeOH:H2O (2:43:55), MeOH:H2O (1:1), MeOH,

MeOH:H2O (1:1), and CHCl3:MeOH:H2O (2:43:55). The upper phase after

centrifugation was loaded onto the pre-washed Sep-Pak. The Sep-Pak was then washed with 3 mL of the following in order - CHCl3:MeOH:H2O (2:43:55) and MeOH:H2O

(1:1). Gangliosides were eluted with 3 mL of MeOH and collected in a new glass tube with a pointed bottom. The samples were dried down under nitrogen gas, and the sides of the tube were washed down with MeOH to collect any gangliosides that were on the walls on the tube, and then subsequently dried with nitrogen gas.

TLC plates were prepared by allowing the plate to dry in a 125C oven for 10 min.

Samples were dissolved in 10 uL of MeOH and 5 uL were spotted on to the TLC per lane using a glass syringe. Gangliosides were resolved using a solvent system consisting of

CHCl3:MeOH:0.25% aqueous KCl (60:35:8). Samples were allowed to resolve until the solvent front reached 2 cm from the top of the plate. The plate was allowed to dry for 10 min before spraying with resorcinol (0.3% resorcinol, .0031% CuSO4*5H2O, 30% HCl).

The plate was covered with a glass plate and clipped together in order to retain the resorcinol on the plate, and was then placed in an oven at 125C for 20 min. Gangliosides appear as light purple bands, which were scanned using a Microtek ScanMaker 8700.

Densitrometric analysis was performed using ImageJ (National Institutes of Health, http://imagej.nih.gov/ij/download.html ).

67 Incubation with EGF and Lipid Synthesis with [1-14C]acetate

Cells were grown and processed in the same way as previously described when analyzing neutral and phospholipid synthesis in U87MG and ACSVL3 KO cells. Before incubation for 30 min with [1-14C]acetate, EGF at a final concentration of 0.2ug/mL was added to the media and the cells were allowed to incubate for a total of two hours. For the last 30 minutes of EGF incubation, a total of 2 uCi of [1-14C]acetate was added to each plate.

68 Results

ACSVL3 Depletion Does Not Affect Cholesterol Levels or Synthesis

Initial efforts to characterize cholesterol homeostasis in the ACSVL3 stable

knockdown cell lines suggested that depleting cells of ACSVL3 decreased both synthesis

and total levels of cholesterol (Z. Pei and PA Watkins, unpublished). Therefore, I wanted

to verify and extend this observation in the ACSVL3 KO cells. Also, since cholesterol is

enriched in lipid rafts, I hypothesized that a decrease in cholesterol was mechanistically

involved in the decrease in RTK signaling observed in the ACSVL3 knockdown cells

when compared to the wild type U87MG cells.

The Amplex Red Cholesterol assay kit by Molecular Probes was used to quantify

total cholesterol levels per mg of cellular protein. Both wild type and KO cell lines were allowed to grow in 10cm dishes until confluent and then harvested using trypsin. As shown in Figure 14, total cholesterol levels were not changed when the ACSVL3 KO cells were compared to the U87MG cells. The method used allows measurement of both total and unesterified cholesterol, and the esterified cholesterol fraction can be calculated

by subtraction. However, in both U87MG and ACSVL3 KO cells, cholesterol esters

accounted for <1% of total cholesterol (data not shown). Thus, the majority of the cellular

cholesterol in both cell types was unesterified sterol, and there were no differences

between wild type and KO.

To investigate whether extracellular cholesterol present in the culture medium

affected cellular cholesterol levels, both cell lines were grown in U87 growth media

containing delipidated fetal bovine serum for 72 hours and then harvested with trypsin.

If any differences were observed, this could mean that there is a difference in cholesterol

69 uptake when ACSVL3 is depleted. The total cholesterol was measured using the Amplex

Red Cholesterol assay kit, and resulting cholesterol amount was normalized to protein

used in the assay, as above. Incubation with delipidated serum resulted in a decrease in overall cellular cholesterol when compared to the cells grown in regular media, but again, no difference was observed between the ACSVL3 KO cells when compared to the

U87MG cells (Figure 14).

70

Figure 14. Total cholesterol is not different between U87MG cells and ACSVL3 KO cells. The Amplex Red Cholesterol Assay was used to determine if cholesterol levels were different between the U87MG cells and the ACSVL3 KO cells. We did not observe a difference between the two cell lines when grown in regular (“reg”) U87MG growth media. Cells were also grown in media made with delipidated FBS (“DL”) to see if differences could be seen without an exogenous source of lipids. While the cholesterol levels decreased slightly, there still were no differences between the U87MG cells and the KO cells.

71 ACSVL3 Depletion Does Not Affect de novo Synthesis of Neutral Lipids or

Phospholipids

ACSVL3 depletion in glioma cells or lung cancer cells by siRNA (Pei et al. 2009;

2013) or in the ACSVL3 KO cells (Figure 10B) resulted in a significant decrease in

growth rate. One hypothesis to explain this phenomenon is that ACSVL3 is necessary to

supply bulk lipids for the high growth rate in cancer cells by de novo synthesis. This was

investigated by [1-14C]acetate incorporation studies. The TLC system used to resolve

cholesterol and cholesterol esters also separates triglycerides, diglycerides, and free FA.

There was no significant difference in synthesis of these neutral lipids when ACSVL3

was absent (Figure 15). To investigate de novo synthesis of phospholipids, cells were incubated with [1-14C]acetate and extracted lipids were separated by TLC using a

different solvent system. There were also no significant differences in de novo synthesis of phosphatidic acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, or phoshphatidylinositol when U87MG cells lacked ACSVL3. These observations suggest that ACSVL3 in U87MG cells does not affect growth rates by upregulating de novo lipid synthesisStudies to assess whether ACSVL3 KO affected incorporation of [1-14C]FA into neutral lipids and phospholipids were also performed in

the lab; in agreement with my findings with [1-14C]acetate, incorporation of C16:0 or

C24:0 into lipids was not significantly different in U87MG and KO cells (X Shi and PA

Watkins, unpublished). In view of these data, I explored other hypotheses that could

explain the importance of ACSVL3 in malignancy.

72

Figure 15. Lipid synthesis is not affected by depletion of ACSVL3 in U87MG cells.

Lipids from cells incubated with [1-14C]acetate were separated using thin layer chromatography. Left, neutral lipids. Chol, cholesterol; FFA, free fatty acids; TAG, triacylglycerol; ChE, cholesterol esters. Diacylglycerols were observed as faint bands running between Chol and FFA. Right, phospholipids. PA, phosphatidic acid; PE, phosphatidylethanolamine; PI, phosphatidylinositol; PC, phosphatidylcholine; PS, phosphatidyl serine. There were no significant differences in de novo lipid synthesis in the ACSVL3 KO cells when compared to the U87MG cells.

73 Ceramide Synthesis and Concentrations are Decreased in ACSVL3 KO Cells

Ceramides provide the basic structural precursors for biosynthesis of

sphingolipids that are important in signaling, as well as being important in supporting

signaling via receptor tyrosine kinases and G-protein coupled receptors found in lipid rafts. In addition, ceramides themselves have been shown to be a key player in intracellular signaling and are involved in apoptosis, proliferation, cell growth, and differentiation (Pettus et al., 2002). It has also been shown that long-chain and very-long chain ceramides have differing effects on cellular pathways. Because we observed a decrease in RTK signaling when ACSVL3 was depleted in ACSVL3 KD cells (Pei et al.,

2009) and in preliminary studies with the ACSVL3 KO cells when compared to the

U87MG cells, I wanted to determine whether the differences were due to ceramide and sphingolipid content and synthesis.

Ceramide synthesis was tested in both the U87MG cells and the ACSVL3 KO cells. I initially assayed synthesis using radiolabeled palmitic acid (C16:0) and lignoceric acid (C24:0), representative long and very-long chain fatty acids. The activation of these lipids was shown to be slightly lower in ACSVL3 KO cells in acyl-CoA synthetase activity assays, suggesting that incorporation of C16:0 and C24:0 into ceramides would also be lower. Cells were incubated with [1-14C]palmitate or [1-14C]lignocerate for 2 hrs;

lipids were extracted and labeled lipids were separated on a TLC plate and visualized

(Figure 16). No differences were observed when we compared the U87MG cells to the

ACSVL3 KO cells. As noted in Chapter 1, KO of ACSVL3 had a greater effect on

activation of 18- and 22-carbon FAs than on 16- and 24-carbon FAs (Figure 12).

Therefore, I investigated ceramide synthesis using 14C-labeled stearic acid (C18:0) and

74 behenic acid (C22:0) to see if perhaps there was a similar chain length preference.

When stearic acid and behenic acid were used as substrates, ACSVL3 KO cells

synthesized less ceramide when using C18:0 than the U87MG cells (Figure 16). No

change was seen in ceramide synthesis when C22:0 was the substrate.

To determine whether the decreased ceramide synthesis reflected decreased levels

of ceramides containing stearic or behenic acids, we extracted cellular lipids and looked

at ceramide levels by acyl chain length using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results of this analysis reinforce the ceramide synthesis data. I saw a significant decrease in ceramides that contain C18:0, C20:0, and C22:0 acyl chains in the ACSVL3 KO cells, while ceramides that contain C16:0 and C24:0 were not affected. The data suggests that there is a preference for ceramides that contain stearic acid, arachidic acid, and behenic acid in U87MG cells, and that the levels of these ceramide species decrease when cells are depleted of ACSVL3 (Figure 17). It also suggests that ACSVL3 has a fatty acyl-chain preference. ACSVL3, like many of the

ACSs, shows a broad range of activity, being able to activate long- to very long-chain fatty acids, however this is the first time we see any type of ACSVL3 preference for particular fatty acids reflected in their incorporation into downstream lipid species.

75

Figure 16. Ceramide synthesis decreases in ACSVL3 KO cells when the substrate is

C18:0. Ceramide synthesis was tested in the U87MG and ACSVL3 KO cells. Cells were incubated with either C16:0, C18:0, C22:0, or C24:0. Ceramides were extracted, and duplicate samples (a, b) were resolved by TLC. Changes in synthesis were not observed when C16:0, C22:0, or C24:0 were used as substrates. A significant decrease was seen when C18:0 was used.

76

Figure 17. Ceramides with acyl chains C18:0-C22:0 are decreased in ACSVL3 KO

cells. Ceramides were extracted from U87MG and ACSVL3 KO cells and quantitated by

LC-MS/MS as described in Methods. Analyte levels were normalized by the amount of internal standard (IS) recovered. The levels of C16:0 and C24:0 ceramides were the same in the U87MG cells and the ACSVL3 KO cells. Differences were found in the ceramides with C18:0-C22:0 acyl chains, with the KO cell line showing a decrease compared to the U87MG cells.

77 Sphingosine and Sphingosine 1-Phosphate Levels are Also Decreased in the

ACSVL3 KO Glioma cells

Ceramidase, or N-acylsphingosine deacylase, releases a fatty acyl chain from

ceramide to produce sphingosine. I therefore measured the sphingosine and S1P levels in

both the U87MG and ACSVL3 KO cells to see if reduced ceramide levels led to a

decrease in these bioactive molecules as well. Sphingosine and S1P were extracted using

the method published by Shaner, et al (2009) and then measured by LC-MS/MS. Our results show that the overall levels of both sphingosine and S1P are decreased in the

ACSVL3 KO cells when compared to the U87MG cells, with S1P showing a statistically significant decrease (Figure 18).

78

Figure 18. Sphingosine and S1P levels decrease when cells are depleted of ACSVL3.

Sphingosine and S1P levels were quantified using LC-MS/MS to see if there was also a decrease in sphingosine levels. (A) A decrease in sphingosine was observed in the

ACSVL3 KO cells, but was not statistically significant (p = 0.06). (B) S1P levels were also measured and quantified. Here, there was a significant decrease in the ACSVL3 KO cells (p = 0.03).

79 Proteomic Analysis Shows an Overall Decrease in Proteins Important in Ceramide

Synthesis

To determine whether decreased ceramide levels could be due to lower expression

of enzymes involved in its synthesis, U87MG and ACSVL3 cells were collected for

proteomic analysis. Proteins important in ceramide synthesis were identified within the

dataset (Table 2). The three different serine palmitoyltransferase enzymes (SPTLC1-3), which catalyze the first, and rate-limiting, step in synthesis, were identified, and all showed a decrease in the ACSVL3 KO cells relative to the U87MG cells. The product of this reaction is the sphingoid base, which is then used to make ceramide and other sphingolipids. The next set of enzymes that shows a decrease is the ceramide synthase family. Three of the six ceramide synthase (CerS) proteins were identified in the analysis

– CerS2, CerS5, and CerS6. These showed an overall decrease as well. Because of the decrease found in the first step, it suggests that there is less starting material in the

ACSVL3 KO cells to produce subsequent products, such as ceramide and sphingosine.

Even though this would indicate an overall decrease in ceramides, we only find the decrease in ceramides containing C18:0-C22:0, suggesting an important role for

ACSVL3 in ceramide synthesis.

More importantly for ceramides, because the CerS enzymes identified are lower in the KO cells, there is less ceramide formation, in agreement with the ceramide synthesis assay result, showing that there is less ceramide synthesis. The main CerS known to be responsible for the synthesis of C18:0 to C22:0 ceramides in pancreatic β- cells is CerS4 (Veret et al., 2011). Half of the CerS enzymes were not detected in the proteomic analysis, but they cannot be ruled out as not present and not contributing to the

80 overall ceramide synthesis of the cells. The overall results suggest that there is a decrease in ceramide synthesis machinery when ACSVL3 is depleted in U87MG cells.

81

Table 2. Enyzmes involved in ceramide synthesis are decreased in ACSVL3 KO

cells. The proteomic data was analyzed for the presence of enzymes involved in

ceramide synthesis. Three serine palmitoyltransferases (SPTLC1-3) were detected and the levels of all three were all decreased in the ACSVL3 KO cells. Three of six ceramide synthases could be found in the data set (Ceramide synthases 2,5, and 6), and all were decreased in ACSVL3 KO cells.

82 Lipid Rafts Are Increased in ACSVL3 KO Cells Compared to the U87MG Cells.

Our lab had previously shown (Pei et al., 2009) that when ACSVL3 is depleted

using shRNA, signaling through c-Met, the hepatocyte growth factor (HGF) receptor, is

disrupted. In ACSVL3 KD cells, phospho-Akt (Ser473) was shown to be slightly

elevated after a short time after incubation with HGF, but then total and phospho-Akt

levels decreased to nearly undetectable levels between 1 and 2 hours after treatment. In

contrast, both total and phospho-Akt remained high for at least 6 hours of HGF

incubation with wild type U87MG cells. Similar results were obtained when the KD

cells and U87MG cells were incubated with epidermal growth factor (EGF). Lipid rafts

are thought to be important signaling platforms in the plasma membrane, and these

microdomains are enriched in sphingolipids, such as sphingomyelin and

glycosphingolipids like gangliosides. Even though we found that cholesterol is

unchanged in the ACSVL3 KO cells, we decided to visualize lipid rafts because of the

changes seen in ceramide synthesis.

To assess lipid raft differences between the ACSVL3 KO cell line and the wild-

type U87MG cell line, the Vybrant Lipid Raft Labeling Kit from Molecular Probes was

used. This method employs cholera toxin subunit B (CT-B) conjugated to an Alexa Fluor

555 fluorescent dye. CT-B is known to bind to ganglioside GM1, a commonly used marker for lipid rafts (Simons and Ikonen, 1997), and when viewed with a fluorescent microscope, can be used to indicate differences in lipid rafts between different cell types.

We had hypothesized that there would be more lipid rafts in the U87MG cells than in the

ACSVL3 KO cells, due to the aberrations we saw in signaling with the KD cells.

83 However, we found that GM1 staining was actually increased in the ACSVL3 KO when compared to the U87MG cells (Figure 19).

84

Figure 19. Fluorescent microscopy reveals an increase in lipid raft staining in

ACSVL3 KO cells. The Vybrant Lipid Raft kit was used to detect differences in lipid rafts between the U87MG cell line and the ACSVL3 KO cell line. Lipid raft staining was increased in ACSVL3 KO cells, contrary to the hypothesis. CT-B binds to ganglioside

GM1 in the lipid rafts, and this may be more indicative of ganglioside composition than overall lipid raft prevalence.

85 Overall Ganglioside Levels Decrease in the Absence of ACSVL3

Because of the unexpected finding of increased ganglioside GM1 in ACSVL3 KO cells, we wanted to see if ganglioside levels extracted from U87MG cells and ACSVL3

KO cells reflected the Vybrant Lipid Raft staining. Ceramides provide the base lipid for gangliosides, and results presented above showed that there was a decrease in ceramide synthesis and overall concentration in the ACSVL3 KO cells. Gangliosides were extracted and analyzed by TLC as described by Ronald Schnaar and colleague (1994).

Ganglioside standards were run on the same TLC, and were a gift from Dr. Schnaar. The

TLC shows that overall ganglioside levels are decreased in ACSVL3 KO cells (Figure

20). The major gangliosides that were found on the TLC were GM1 and GM3. GM1, as was demonstrated in the Vybrant lipid raft images, shows a decrease in the ACSVL3 KO cells. In contrast, GM3 was found to be decreased in ACSVL3 KO cells. Both gangliosides are implicated in signaling, either enhancing (GM1) or inhibiting (GM3)

RTKs. The overall ganglioside result is consistent with previous results showing that

C18:0 to C22:0 ceramides were lower in the ACSVL3 KO cells. We believe that the decrease in ceramide precursors results in a decrease in gangliosides. This aberration could contribute to the differences in signaling through Akt that we observed in the

ACSVL3 KD cells (Pei et al., 2009), and what we are seeing with the KO line

(unpublished).

86

Figure 20. Total gangliosides decrease in ACSVL3 KO cells, but GM1 ganglioside increases compared to U87MG cells. Gangliosides were extracted from U87MG cells and ACSVL3 KO cells, and were separated by TLC. The major gangliosides that were found were GM3 and GM1. GM3 amounts were decreased in the KO cells compared to the parental U87MG cells while GM1 was increased. This finding was in agreement with the Vybrant Lipid Raft staining, where KO cells had increased GM1 in the cell membrane.

87 EGF Signaling Upregulates Lipid Synthesis in the U87MG Cells, While Not

Affecting Synthesis in the ACSVL3 KO Cells

Because of the effects we see in the ACSVL3 KO cells pertaining to cell sphingolipid composition and the differences we see in signaling between the two cell lines (unpublished data), we wanted to see if incubation with a growth factor would affect lipid synthesis. Growth factors, such as EGF, signal through RTKs that are found in lipid rafts, and a perturbation in raft composition may affect signaling. Both ACSVL3 KD

(Pei et al. 2009) and ACSVL3 KO cells (unpublished data) showed aberrant signaling through Akt. As previously mentioned, U87MG cells and ACSVL3 KO cells incubated with radiolabeled acetate do not exhibit any differences in lipid synthesis. To explore if signaling has an effect on lipid synthesis, we incubated cells with EGF for 1 hour. [1-

14C]acetate was added to the media and allowed to incubate for the last 30 min. Cells were also incubated with [1-14C]acetate for 30 min without EGF. Lipids were extracted and then separated on TLC plates (Figure 21). First, despite prior findings in Figure 15 where there were no differences in acetate incorporation into cholesterol between the

ACSVL3 KO cells and the U87MG cells, here we do find a difference in synthesis without EGF. U87MG cells exhibited higher cholesterol synthesis. When the cells are incubated for 1 hour with EGF, we find that overall lipid synthesis increases in both cell lines, but the only difference we see is in cholesterol synthesis, where synthesis is greatly upregulated in the U87MG cells. We also looked at phospholipid synthesis, and find that there is an overall increase in synthesis in response to EGF in both cell lines, but the synthesis at both steady-state (no EGF) and with growth factor are equal in the ACSVL3

KO cell line and the U87MG cell line. One potential explanation for the difference

88 between results shown in Figure 15 vs. those shown here for unstimulated cholesterol synthesis is that different lots of FBS were used to maintain the cell lines, and these lots potentially have varying profiles of growth factors that could affect cellular metabolism.

Given that both cell types were grown in the same serum, this would suggest that there are differences in the lipid synthesis, especially in the synthesis of cholesterol, that we didn’t see previously.

89

Figure 21. ACSVL3 KO cells do not increase lipid synthesis when incubated with

EGF. Both U87MG and ACSVL3 KO cell lines were incubated with EGF + [1-

14C]acetate to observe how lipid synthesis responds to incubation with growth factor.

Cells that were not exposed to EGF but incubated with labeled acetate were included to look at unstimulated levels of lipid synthesis. (A) Neutral lipids. Cells that were not incubated with EGF do not show differences in synthesis of free fatty acids (FFA), triacylglycerol (TAG), or cholesterol esters (ChE). Cholesterol (Chol) synthesis was lower in ACSVL3 KO cells. There was an overall increase in lipid synthesis when both cell lines were incubated with EGF. Again, FFA, TAG and ChE synthesis were unaffected; however, the differences in cholesterol synthesis were more pronounced than in cells incubated without EGF. (B) Phospholipids. The synthesis of phospholipids including phosphatidic acid (PA), phosphatidylethanolamine (PE), phosphatidylinositol

90 (PI), and phosphatidylcholine (PC) not affected by ACSVL3 KO, either in the presence or absence of EGF. Like neutral lipid synthesis, there was an overall increase in phospholipid synthesis when cells were treated with EGF.

91 Discussion

The goal of this study was to understand whether ACSVL3, a very long-chain

acyl-CoA synthetase, is important in regulating the lipid components of lipid rafts in

U87MG cells. In previous studies with U87MG cells where ACSVL3 was depleted via

shRNA, it was shown that in the absence of ACSVL3, decreased signaling through Akt occurred when the cells were incubated in the presence of either hepatocyte growth factor

(HGF) or epidermal growth factor (EGF) (Pei et al., 2009). We hypothesized that signaling defects may be caused by a difference in lipid profiles of rafts in which the receptor tyrosine kinases can be found, as well as differences in important bioactive sphingolipid molecules, such as sphingosine 1-phosphate (S1P) when ACSVL3 is absent.

The first thing examined was the cholesterol levels of the U87MG cells versus the

ACSVL3 KO cells. Early unpublished experiments with ACSVL3 KD cells suggested that total cholesterol levels decreased when ACSVL3 levels were lowered, and could be a cause of the aberrant signaling through the receptor tyrosine kinases c-MET, the receptor for HGF, and the EGF receptor. Lipid rafts are transient plasma membrane domains enriched in cholesterol that form stable platforms for receptors and signaling molecules.

However, in this study, I show using KO cells that ACSVL3 levels do not impact total cholesterol levels. Cholesterol levels were affected by amount of sterol in the surrounding media (regular FBS vs. delipidated FBS), but this change was equal in the

U87MG cells and the ACSVL3 KO cells. I conclude that any differences in signaling seen in the KO cells is not due to the cholesterol levels, as these are not different when compared to the U87MG cells.

92 Interestingly, while we did not find a difference in cholesterol content, we did

find differences between the two cell lines when assaying for cholesterol synthesis,

especially in the presence of EGF. The U87MG and ACSVL3 KO cell lines were

incubated with [1-14C]acetate, with and without EGF. While EGF did increase the

overall synthesis of both neutral and phospholipids, there was a clear difference in

cholesterol synthesis between U87MG cells and ACSVL3 KO cells. We hypothesize that

we did not see this difference in previous experiments when looking at the steady-state

synthesis of lipids is because of differences in lots of FBS. FBS is rich in lipids and

growth factors, and this could have affected previous studies. More work will have to

been done in the area of cholesterol synthesis to elucidate any role ACSVL3 may have in the pathway.

To see if there were any differences in lipid rafts between the U87MG cells and the ACSVL3 KO cells, I visualized lipid raft domains of the plasma membranes. Using the Vybrant Lipid Raft kit, which labels ganglioside GM1 commonly found to be enriched in lipid rafts, I found an increase in labeling in the ACSVL3 KO cells, contrary to what we hypothesized. To explore this further, I extracted gangliosides from both cell lines, separate them by TLC, and visualized them. Gangliosides GM3 and GM1 appear to be the most abundant. Although there was an overall decrease in gangliosides in the

ACSVL3 KO cells, GM3 was decreased in the ACSVL3 KO cells, while GM1 was increased, which agreed with and explained the Vybrant Lipid Raft labeling. While it has been documented in the literature that GM3 inhibits EGFR signaling (Hanai et al., 1988), and consequently inhibits cell growth (Bremer et al., 2986), we find that even though

GM3 is found in higher quantities in the U87MG cells, they still grow at a much faster

93 rate than the ACSVL3 KO cells. Similarly, GM1 levels are reverse of what would be

expected. Further study will be needed to fully understand the correlation between

ganglioside levels and RTK signaling in U87MG cells.

Because the difference is not cholesterol-dependent, as demonstrated by the total cholesterol levels in the U87MG and the ACSVL3 KO cells, we wondered if this was due to differences in sphingolipid synthesis and content, something not previously described in the ACSVL3 KD cells. Sphingolipids are present in all eukaryotic cells and contribute to membrane biology and signaling events that influence both cell behavior and function

(Holthuis et al., 2001; Merrill and Sandhoff, 2002). Biosynthesis of the sphingosine backbone begins in the endoplasmic reticulum with the condensation of serine and palmitoyl-CoA, followed by a reduction to dihydrosphingosine. Dihydrosphingosine is oxidized by FAD to produce sphingosine. Sphingosine can also be made from ceramide via ceramidase, which cleaves the fatty acyl chain from ceramide, leaving the sphingosine backbone.. Once created, the backbone can be phosphorylated to produce sphingosine 1-phosphate, a biologically active molecule or acylated by CerS enzymes to create ceramide, which is in itself an important biological molecule, or go on to create more complex sphingolipids, like gangliosides.

Proteomics data shows that there is a decrease in all three SPTLC enzymes in

ACSVL3 KO cells. These enzymes are the first step in sphingosine synthesis, catalyzing the condensation of serine and palmitoyl-CoA. In published RNAi studies targeting

SPTLC1, lack of this enzyme was found to affect cell growth in U87MG cells, with slower cell growth found over six days (Bernhart et al., 2015). The same study also

94 shows a decrease in ceramide levels when SPTLC1 is knocked down, which is similar to

what is observed in the ACSVL3 KO cells.

The study described here demonstrates that when ACSVL3 is absent in U87MG

cells, the levels of S1P decrease significantly. Recent studies indicate that S1P is a potent

mitogenic factor for several glioblastoma cell lines, stimulating proliferation in U373MG

cells through a G-coupled receptor and activating several different signaling pathways

(Brocklyn et al., 2003). Evidence suggests that S1P and its receptors are central players

that regulate glioblastoma growth, migration, and invasion (Kim et al., 2009), and

exogenously added S1P promotes glioma growth and enhances invasiveness (Brocklyn et al., 2002; Brocklyn et al., 2003; Annabi et al., 2009; Young et al., 2009). Sphingosine kinase (SphK), the enzyme that phosphorylates sphingosine to produce S1P, has been shown to be regulated by a number of extracellular ligands, including EGF, and this has been shown to activate both isoforms of SphK – SphK1 and SphK2 (Paugh et al., 2008;

Hait et al., 2005). Stimulation by EGF has also been shown to increase cellular invasion, and this occurs through SphK/S1P dependent activation of the ezrin, radixin, and moesin

(ERM) family of proteins, which are involved in cytoskeletal reorganization, cell division, migration, and invasion (Gandy et al., 2013). While this study does not demonstrate that SphK1 is higher in U87MG cells when compared to the ACSVL3 KO cells, the higher levels of S1P suggest that the regulation of one or both of these enzymes is altered in U87MG cells, and when ACSVL3 is depleted, the activity of SphK1/2 is also decreased, therefore suggesting an important role in the growth and proliferation of the cells.

95 Our data also suggests that ACSVL3 has a very important role in activating fatty

acids that go on to synthesize ceramides, specifically those that contain C18:0. This data is in agreement with our acyl-CoA synthetase activity assay data, showing that while

ACSVL3 has a very broad affect – C16:0 through at least C24:0 – there is significantly less activation of C18:0 and C22:0. It is interesting that in published data (Koybasi et al.,

2004), C18:0 ceramide was found to be increased with an overexpression of a gene known as LASS1 (Longevity Assurance), and lead to an inhibition of cell proliferation in human head and neck squamous cell carcinomas. There is evidence that counters this in breast cancer – ceramide levels were measured in both “normal” breast tissue and malignant breast tissue, and it was found that C18:0 ceramide was significantly higher in the malignant tissue (Schiffmann et al., 2009).

The ceramide synthase enzymes, CerS1-6, catalyze the N-acylation of the dihydrosphingosine backbone to produce ceramide (Stiban et al., 2010). Each CerS has been recognized to have specificity towards certain fatty acyl chain lengths. CerS1 has been shown to use C18-acyl-CoA (Venkataraman et al., 2002), CerS2 uses C22- or C24-

acyl-CoAs (Lavlad et al., 2008), CerS4 has specificity towards using C20-acyl-CoA, and

CerS5 and CerS uses C14- and C16-acyl-CoA (Riebeling et al., 2008; Mizutani et al.,

2003). While we do not find CerS1 in our proteomic analysis, we do find a decrease in

CerS2, as well as a decrease in CerS5 and CerS6. This suggests that there could be a

general decrease in the levels of CerS enzymes, affecting overall synthesis of ceramides.

While it is interesting to note that C16:0 or C24:0 ceramides are not decreased when the

CerS enzymes responsible for their synthesis are decreased, our data could suggest that it

96 is due to the significant decrease in activation of C18:0 and C22:0 by ACSVL3 that leads to the decrease of the corresponding ceramides.

ACSVL3 is important to U87MG cell proliferation, signaling, and the ability for the cells to form subcutaneous and orthotopic xenografts in nude mice. We asked why this particular acyl-CoA synthetase – whose only known function is to synthesize acyl-

CoAs – is important to the malignant properties of the cells. Results presented here suggest that this may be due to a decrease in sphingolipid synthesis. We find a significant decrease in S1P levels in the ACSVL3 KO, which is a biologically active molecule. Sphingosine, the backbone of sphingolipids, is also decreased, but to a lesser extent. Along with the lower levels of sphingosine, an ACSVL3 KO cell also sees decreased C18:0 and C22:0 ceramide content and synthesis. Lower levels of C18:0 ceramide are interesting because it is noted in the literature as to having a negative effect on head and neck squamous cell carcinoma tissue. Higher C18:0 ceramide levels were

50% lower in tumor tissue when compared to noncancerous tissue (Koybasi et al., 2004).

We believe that the lowered levels of sphingolipids and S1P in the ACSVL3 KO are due to a lack of starting materials (Figure 22). There is less sphingosine present in the

ACSVL3 KO cells, meaning that there is less material for signaling through S1P receptors and less starting material for ceramide synthesis. Because we see evidence of

ACSVL3 having greater specificity towards C18:0 and C22:0 activation, there is less acyl-CoA to be incorporated into ceramide. If there is less ceramide available, there is less incorporated into higher sphingolipids that are involved in signaling. With less sphingolipids at the plasma membrane supporting growth factor receptors, it could

97 explain the decrease in signaling through Akt, therefore making the ACSVL3 KO

U87MG cells less tumorigenic.

98

Figure 22. Decreasing activation of fatty acids destined for sphingolipid synthesis leads to aberrant signaling from receptor tyrosine kinases. Results presented in this chapter show that a decrease in the activation of fatty acids in the ACSVL3 KO cells leads to a decrease in synthesis of ceramides, S1P, and gangliosides, leading to a decrease in signaling from RTKs in the cell membrane localized to lipid rafts, or through S1P signaling. This may account for the decrease in cell proliferation, growth, and lipid synthesis in the ACSVL3 KO cells when compared to the U87MG cell line.

99 CHAPTER 3

Introduction

When a cell has made the switch from being a normal cell to becoming a cancer

cell, the cell is obligated to switch from a normal metabolic state to a state that favors

survival and proliferation (Ramanujan, 2015). One of the first identified and common

biochemical characteristics of cancer cells is aberrant glucose metabolism. Glucose

serves as a main source of energy in the form of ATP, and it can supply the precursors

and cofactors required for anabolic pathways f (Vander Heiden et al., 2009).

Under normal oxygen conditions, non-cancerous cells rely on mitochondrial

oxidative phosphorylation to generate ATP and switch to anaerobic glycolysis under

hypoxic conditions. Otto Warburg’s observation, that tumor cells took up very large

amounts of glucose and rapidly used it to produce lactate under aerobic conditions, is still

the most fundamental observation in tumor metabolism (Warburg, 1925; Warburg, 1956).

This was termed the Warburg Effect in the 1970s, and studies demonstrated that a

number of oncogenes are associated with the switch from oxidative phosphorylation to

glycolysis, such as myc, NF-kB, EGF, and Akt. With this increase in aerobic glycolysis,

higher levels of lactate are produced. High levels of lactate have been correlated with the

likelihood of metastases, tumor recurrence, and poor patient survival in a number of solid

tumors (Walenta, et al., 2016). Local acidosis and elevated lactate with or without

hypoxia characterizes many different tumors, with higher levels of acidosis associated

with increased invasive properties (Gillies, et al., 2008).

100 Warburg initially hypothesized that cancer cells develop a defect in mitochondria

that leads to impaired aerobic respiration, and thus rely on aerobic glycolysis (Warburg,

1956). However, it was found that the presence of aerobic glycolysis was not indicative

of impaired oxidative phosphorylation, and recent studies found that defects of

mitochondrial oxidative phosphorylation are not common in spontaneous tumors,

(Kroemer and Pouyssegur, 2008; Koppenol et al., 2011; Griguer et al., 2005). Still, the

role of mitochondria in tumor cells is often reduced to a provider of biosynthetic

intermediates for cellular proliferation (DeBerardinis, et al., 2008) which are now being

recognized as essential mediators of tumorigenesis. Consistent with this, for example,

breast and melanoma models indicate that metastasizing cancer cells have increased

levels of oxidative phosphorylation (LeBleu, et al., 2014).

The tricarboxylic acid (TCA) cycle plays a central role in the metabolism of

sugars, lipids, and amino acids (Scheffler, 2008). Pyruvate enters the mitochondria

through a heterodimeric complex composed of mitochondrial pyruvate carrier 1 and 2

(MPC1/2). From there, pyruvate can enter the TCA cycle (also known as the citric acid

cycle) to produce ATP, CO2, and the electron transport chain (ETC) cofactors, NADH

and FADH2. Specific cancer-associated mutations have been reported in nuclear-

encoded mitochondrial enzymes of the TCA cycle, including fumarate hydratase (FH)

(Xiao et al., 2012), succinate dehydrogenase (SDH) (Xiao et al., 2012), and isocitrate

dehydrogenase (IDH) (Dang et al., 2009).

Mitochondria also find themselves at a crucial intersection with lipid metabolism.

It is becoming clear that fatty acid oxidation by itself can promote metastasis of cancer cells. Inhibition of β-oxidation has been suggested as a potential therapy to slow tumor

101 growth (Samudio et al., 2010; Tirado-Velez et al., 2012), and several studies show that mitochondrial β-oxidation of free fatty acids is functional in cancer cells. This fatty acid metabolism may drive oxidative phosphorylation-dependent ATP production for cell

proliferation (Rodriguez-Enriquez et al., 2015). However, the data is somewhat

inconsistent with other studies showing some of the mRNA coding for components of the

β-oxidation machinery was significantly lower in colorectal carcinoma when compared to

normal colon tissue (Birkenkamp-Demtroder et al., 2002). Another study proposed that

mitochondrial β-oxidation is non-functional in several carcinoma cell lines but this

conclusion was based upon the high level of malonyl-CoA detected in the samples

(DeBerardinis et al., 2006).

Mitochondria are dynamic networks that are regulated and maintained by fusion

and fission (Westermann, 2010). Generally, it is thought that quiescent cells tend to have

mitochondria that exist as a meshwork of interconnected tubes while energy-producing

mitochondria are distributed through fission to regions of the cell with high energy

demands (Sanchez-Madrid and Serrador, 2009). Alterations to these dynamics are

associated with abnormal cell function which can leads to many human diseases (Liesa et

al., 2009), including cancer. Recent studies showed that a lung cancer cell line exhibited

excess mitochondrial fission and a defect in fusion that was important in cell cycle

progression (Rehman et al., 2012). Breast cancer cells that have impaired mitochondrial

fusion have inhibited migration and invasion while fission, which is regulated by the

protein Drp1 (Zhao et al, 2013), facilitates these processes..

In the study presented here, we show that a knockout of ACSVL3 results in

changes in glucose metabolism and the TCA cycle. ACSVL3 KO cell lines display an

102 increase in glycolytic enzymes and a decrease in TCA cycle enzymes protein levels.

Even with these large changes in enzyme levels, however, we do not see significant changes to metabolic intermediates of either pathway based on metabolomic analyses.

We also find that despite this decrease in TCA enzymes, in vivo glucose oxidation does decrease in the ACSVL3 KO cells as measured by the conversion of glucose to CO2.

While not an exhaustive study, we observe differences in mitochondrial morphology and proteins that suggests that ACSVL3 is important to mitochondrial function and dynamics.

103 Methods and Materials

Glucose Uptake Assay using 3H-2-Deoxyglucose

Both U87MG and ACSVL3 KO cells were cultured in duplicate 12-well culture plates until confluent. KRH buffer (0.5% BSA, 25mM HEPES, 120mM NaCl, 5mM

KCl, 1.2mM MgSO4, 1.3mM CaCl2, 1.3mM KH2PO4), serum-free U87 culture medium,

0.8% Triton, and 1x Dulbecco’s phosphate buffer saline solution (DPBS, with calcium and magnesium) were kept at 37C. The labeling buffer was made by adding 1 uL of 1 uCi/uL 3H-2-Deoxyglucose (a gift from Dr. William Wong) per 1 mL KRH buffer and mixed. Half of the labeling medium was kept at 37C (experimental plate) and the other half placed on ice (control plate). On the day of assay, cells were washed twice with warm 1x DPBS. 1 mL of warm serum-free U87 culture medium was added to each well, and the cells were placed in a CO2 incubator. After a 1 hour incubation, the cells were washed again twice with warm 1x DPBS. To each well, 1 mL of warm KRH buffer was added, and the cells were incubated for 20 min at 37C. After the 20 min incubation with

KRH buffer, the control plate was placed on ice. The KRH buffer was aspirated and 0.5 mL of warm labeling solution were added to each well of the experimental plate, and ice- cold labeling buffer added to the control plate on ice. The experimental wells were incubated at 37C for 10 min. The labeling buffer was aspirated, and the plates were put on a bed of ice to stop the reaction. Both experimental and control wells were washed twice with cold 1x DPBS. 240 uL of warm 0.8% Triton was added to the wells and were placed in a water bath sonicator for 10 min at 37C. Cell lysates were counted (150 uL) in a scintillation counter. All counts were normalized by protein.

104

Immunofluorescence

Immunofluorescence (IF) and Western blotting analysis was done using rabbit

anti-Tom20 antibody, a gift from Dr. Hiromi Sesaki. IF was performed by culturing

U87G and ACSVL3 KO cells on glass coverslips until nearly confluent. The coverslips were then washed twice with 1x PBS and fixed with 4% formaldehyde in 1x PBS for 20 min at room temperature. The fixation buffer was aspirated, and the coverslips were washed with 1x PBS 3x for 5 min each wash. Cells were permeabilized with 0.1% Triton

X-100 in 1x PBS for 8 min at room temperature. After removal of the Triton X-100, the coverslips were again washed with 1x PBS as above. Anti-Tom20 antibody was diluted to a final concentration of 1:400 in 0.5% BSA in 1x PBS. 20 uL of antibody was pipetted onto parafilm and the coverslips were gently placed upside down on the antibody dilution. Coverslips were incubated overnight at 4̊C in a humidified chamber.

Coverslips were washed the next day and then incubated in anti-rabbit secondary antibody conjugated to Cy3 (1:250) for 1 hour at room temperature. The coverslips were washed 3x with 1x PBS, and then mounted onto slides. Fluorescent images were captured using a Zeiss AxioImager fluorescent microscope with ApoTome attachment, and analyzed using Adobe PhotoShop CS5.

Metabolomic analysis of the U87MG cells and ACSVL3 KO cells

Both the U87MG cells and the ACSVL3 KO cells were seeded onto 150 mm dishes in U87 growth media. Plates were given to Dr. Anne Le (Dept. of Pathology) for

105 extraction and metabolomics analysis; this was done on a fee-for-service basis. Once the dishes were at least 85% confluent, the dishes were placed on ice. The cells were washed with ice-cold 1x PBS by adding 4 mL PBS to the dish and tilting the dish back and forth.

The 1x PBS was aspirated, and the cells were washed a second time the same way. After the PBS was aspirated for the last time, the cells were frozen by placing the dishes on dry ice. A 2.5:1 MeOH:H2O mix was made and was kept on ice until needed. 525 uL of the

MeOH:H2O mix was added to the 150 mm dish and tilted back and forth to cover the whole surface. The dish was placed on ice. Cells were scraped off of the 150 mm dish and cells+MeOH:H2O were collected into a 2 mL Eppendorf tube on ice. Another 525

uL of the MeOH:H2O mix was added to the dishes and any sample remaining on dish was

collected the same way and added to the 2 mL Eppendorf tube. The samples were

sonicated 3-5 times for 1 second each time while keeping the tube on ice. 375 uL

chloroform was added to the tubes while on ice for a ratio of 1:2:0.8

chloroform:MeOH:H2O. Tubes were mixed by vortexing, and then 375 uL of water was

added to the tubes. Tubes were mixed again, and another 175 uL chloroform was added

while the samples were kept on ice. The samples were mixed a final time and were

centrifuged for 30 min at 3,000 x g. After centrifugation, the samples separate into 3

layers – top (polar compounds), middle (protein), and bottom (lipids). The top layer of

each sample was transferred to appropriate tubes, volume was reduced using a SpeedVac,

and finally samples were lyophilized. The middle layer was used for protein

quantification, and was dried down using a SpeedVac. The bottom layer was saved and

dried for future lipidomic studies. Samples were analyzed using Q-TOF LC/MS with

data analysis performed with Qual and MPP software.

106

Oxidation of Glucose to Carbon Dioxide

U87MG and ACSVL3 KO cells were cultured in T-25 flasks until confluent. On

the day of the assay, the media was aspirated and the cells were washed 2x with pre-

warmed (37C) 1x PBS. One set of flasks was harvested with trypsin for protein. The

cells that were used in the assay, as well as a set of flasks used as a “blank” (flasks

without cells), were incubated with pre-warmed (37C) serum-free U87 media for 1 hour in a CO2 incubator. The media was aspirated, and then washed with 1x PBS twice. The

flasks were incubated with 5 mL of pre-warmed KRH buffer for 20 min in the 37C warm

room. During the incubation, uniformly 14C-labeled D-glucose (Moravek Biochemicals)

was added to pre-warmed KRH buffer for a final concentration of 5mM. The KRH

buffer was aspirated from the flasks, and 5 mL of labeled KRH buffer was added. The

flasks were capped with rubber stoppers fitted with hanging wells containing Whatman

glass microfiber filter paper that had been wetted with 20 uL of 1.0M KOH to trap the

14 CO2 produced. The flasks were incubated for 1 hour in the 37C warm room with gentle

shaking. The reactions were terminated by injection of 250uL of 60% perchloric acid

through the rubber stopper, and the flasks were kept at 4C overnight with gentle shaking

14 to trap the CO2. The filter paper was transferred to scintillation vials and 10 mL of

BudgetSolve counting solution was added. 14C in the vials was assayed by scintillation

counting. Dpms and protein concentrations were used to express results as nmol/20

min/mg protein.

107 Results

Glucose Transporters Glut1 and Glut3 Are Higher in U87MG cells, But Glucose

Uptake Remains the Same

Because U87MG cells lacking ACSVL3 have more normal growth properties compared to wild-type U87MG cells, we were interested to see if glucose metabolism was different in the two cell types. Glucose and lipid metabolism are interconnected through a number of different pathways, particularly in how the cell produces energy for growth and proliferation. We asked if glucose uptake would be affected by an ACSVL3

KO. We first looked at our proteomic data to see if we detected any glucose transporters.

Our analysis did detect two – Glut1 and Glut 3. These facilitative glucose transporters are overexpressed in different types of solid tumors consistent with their potential role to supply the cells with glucose needed for ATP generation through the Warburg effect

(Macheda et al., 2005; Amann and Hellerbrand, 2009; Shim et al., 2013; Ramani et al,

2013). Glut1 and Glut3 were both lower in our ACSVL3 KO cells, half of what was detected in the U87MG cells (Figure 22A).

To determine whether the decrease in the glucose transporters caused a decrease in glucose uptake in the KO cells, we performed a glucose uptake assay by incubating both cell lines with [3H]2-deoxyglucose. This deoxy sugar is taken up by glucose transporters but is not metabolized, thus providing an estimate of transport alone.

Following uptake, cells were lysed in 0.8% Triton and counted in a scintillation counter.

Final calculations were performed to reflect nmol/20min/mg protein. We found that even though the glucose transporter levels are decreased in our ACSVL3 KO cells, glucose

108 uptake was not affected (Figure 22B). One possible reason for this is because of the low

KM of the transporters (KM= ~1mM) which is well below the serum glucose concentration ~3-5mM) indicating these levels are not likely limiting.

109

Figure 23. Glucose uptake in ACSVL3 KO cells relative to U87MG cells. (A)

Proteomic analysis of the cell lines detected two of the glucose transporters: Glut1 and

Glut3. Both of these facilitative transporters were lower (0.5) in the ACSVL3 cells

compared to the U87MG cells. (B) Because the two detected glucose transporters were

lower, we wanted to see if glucose uptake was affected. Cells were incubated in a

labeling buffer that included 3H-2-deoxyglucose and samples were counted for radioactivity. There were no significant differences between the two cell lines (n = 5).

110 Glycolytic Enzymes Are Upregulated in ACSVL3-Depleted Cells Without

Significantly Affecting Metabolic Intermediates

Proteomic analysis of U87MG cells and ACSVL3 KO cells revealed a general increase in enzymes involved in glycolysis in the KO cells compared to the U87MG cells. Other than the two different glucose transporters, Glut1 and Glut3, which were both decreased by half in the KO cells, every other glycolytic enzyme was upregulated by at least 1.4-fold in the KO cells (Table 3). This came as a surprise, considering the KO cells’ less tumorigenic characteristics we didn’t expect an increase in glycolytic enzymes.

Importantly, however, although the glycolytic enzymes are more abundant in the KO cells, we cannot definitively conclude that there is an increase in glycolytic activity. To gain further insight, we used a metabolomics approach and investigated the levels of metabolic intermediates of glycolysis to establish whether or not glucose metabolism might actually be altered, and perhaps upregulated in the ACSVL3 KO cells.

Untargeted metabolomic analysis was performed on our U87MG cells and the

ACSVL3 KO cells in collaboration with the laboratory of Ann Le, Ph.D. (Johns Hopkins

University School of Medicine). Most intermediates of the glycolytic pathway were

detected, and levels in the U87MG cells and the ACSVL3 KO cells were compared

(Figure 23). Levels of glucose-6-phosphate, the product of the hexokinase enzymes, did not show an appreciable difference between the two cell lines (Figure 23A). There was also no significant change found in glyceraldehyde 3-phosphate levels (Figure 23B), but there was a significant decrease in glycerate 3-phosphate in the ACSVL3 KO cells

(Figure 23C). This would suggest that there is possibly less ATP being made even with an increase in expression of phosphoglycerate kinase. In the final ATP-generating step

111 of glycolysis, where phosphoenolpyruvate is converted to pyruvate, we do not detect any significant changes in the metabolites (Figure 23Dand E), even with an increase in enzyme levels.

The final product of glycolysis, pyruvate, was detected in the metabolomic analysis and was found at levels were not significantly different in the ACSVL3 KO cells

(Figure 24). Although both lactate dehydrogenase enzymes (LDH-A and LDH-B) were higher in KO cells, cellular lactate levels were not significantly higher (Figure 25).

However, other investigators in the lab measured lactate secreted into the culture medium after a one hour incubation and found that KO cells secreted ~1.3-fold more of this metabolite than U87MG cells (Y Liu and PA Watkins, unpublished). This may partly explain the observed upregulation of glycolytic enzymes without significant intracellular elevations in levels of pathway intermediates. Lactate levels are generally thought to promote a more tumorigenic phenotype. In contrast, cellular plus secreted lactate was higher in the less tumorigenic ACSVL3 KO cells. We conclude that the higher growth and proliferation levels seen in U87MG cells are not due to increased lactate production.

112

Table 3. Glycolytic enzyme levels are increased in ACSVL3 KO cells. Proteomic analysis reveals an increase in the expression of glycolytic enzymes in the ACSVL3 KO cells when compared to the U87MG cells. Some of these increases do not reach 2-fold that of what is found in U87MG (Hexokinase 1/2), however there are several large changes that are more than 4-fold higher than the parental cell line.

113

Figure 24. Glycolytic pathway metabolites do not significantly change despite a

change in enzymes. Glycolytic metabolites were extracted from U87MG cells and

ACSVL3 cells and were measured using Q-TOF LC-MS (n = 6). Data was normalized to protein in each sample. (A) Glucose 6-phosphate, (B) glyceraldehyde 3-phosphate, (C)

fructose 1,6-bisphosphate, (D) glycerate 3-phosphate, and (E) phosphoenol pyruvate

were all detected in the metabolomics study. The only metabolite that exhibited a

significant change was glycerate 3-phosphate (p = 0.01).

114

Figure 25. Pyruvate levels do not change with an ACSVL3 KO. Despite the increase in pyruvate kinase from the proteomic data, we do not see a change in pyruvate levels between the U87MG cells and the ACSVL3 KO cells.

115

Figure 26. LDH enzyme levels increase in an ACSVL3 KO, but cellular lactate levels are unchanged. (A) Proteomic analysis revealed that both LDH-A and LDH-B were higher in the ACSVL3 KO cells relative to the U87MG cells. (B) Metabolomic analysis showed that cellular lactate levels were not significantly different between

U87MG and ACSVL3 KO cells.

116 Glucose Oxidation to CO2 is Downregulated in ACSVL3 KO Cells

Glycolysis is a cytosolic process that intersects with processes that occur within

the mitochondria. Pyruvate, the end product of glycolysis, enters TCA cycle in the

mitochondria to produce CO2 and electron donors for the electron transport chain. A

glucose oxidation assay, which measures glucose conversion to CO2, was conducted to

determine whether this pathway was affected by lack of ACSVL3. We incubated both

U87MG and KO cell lines with uniformly labeled 14C- D-glucose. The reaction was stopped with 60% perchloric acid to release the CO2 from the media to be captured on filter paper with 1M KOH. We find that the U87MG cells converted significantly more glucose into CO2 than did the ACSVL3 KO cells do (Figure #26). This observation

suggests that depletion of ACSVL3 affects TCA cycle activity, flux through the electron

transport chain, or both.

117

Figure 27. Oxidation of glucose is significantly downregulated in the ACSVL3 KO.

Cells of both lines were treated with uniformly labeled 14C-D-glucose to look at how much glucose is converted to CO2. The U87MG cells converted significantly more glucose to CO2 (2.65 nmol/20 min/mg protein) than the ACSVL3 KO cells (0.39 nmol/20 min/mg protein). N = 4; p = 0.006.

118 Levels of the Citric Acid Cycle Enzymes are Lower in ACSVL3 KO Cells Without

Changing the Metabolite Profile

We next wanted to see was if there were any differences between the U87MG

cells and the ACSVL3 KO cells in regards to the tricarboxylic acid cycle (TCA) proteins

and metabolites. While we saw large changes in the glycolytic enzymes in the ACSVL3

KO cells, we wondered if the TCA enzymes would follow the same trend. We were able

to identify all of the enzymes involved, and we find that there is an overall decrease in

levels in the ACSVL3 KO cells (Table 4), in contrast to the glycolytic enzymes which

were elevated. Pyruvate dehydrogenase E1 is the first component enzyme of the

pyruvate dehydrogenase complex (PDC) and catalyzes the conversion of pyruvate to

lipoic acid. This is considered the rate-limiting step of the complex. We find that this enzyme is reduced by half in the ACSVL3 KO cells, with the other enzyme components of the PDC also reduced to some degree. The only enzyme involved in the TCA cycle that does not seem to decrease is citrate synthase, which catalyzes the synthesis of citrate from oxaloacetate and acetyl-CoA which is needed for lipid synthesis.

The metabolomic data was then analyzed for TCA cycle intermediate levels.

Seven of the eight metabolic intermediates were identified in the analysis (Figure 27).

Isocitrate was not individually detected due to the similarities between it and its precursor, citrate. Like the data for glycolysis, even with a decrease in TCA enzymes, we do not see significant changes for most of the TCA intermediates. While we may be seeing trends towards higher levels of certain intermediates in the ACSVL3 KO cells, like citrate and isocitrate, we cannot conclude that these changes are significant.

Metabolomic analysis detected a significant increase (p = 0.017) in α-ketoglutarate in the

119 ACSVL3 KO cells. This is the product of the isocitrate dehydrogenases (IDH). We find that the mitochondrial isoforms of this enzyme are lower, however the cytosolic isoform is increased in the ACSVL3 KO cells. This potentially confounds interpretation of the metabolomics because we cannot say with certainty that these levels accurately reflect the

TCA cycle of the cells. The other increase in the ACSVL3 KO cells we detect is with succinate (p = 0.002), but we do not see a difference in the next intermediate of the TCA cycle, fumarate, between the two cell lines. This could be due to a decrease in succinate dehydrogenase, but this will have to be explored in further detail. Even though there were not large changes in TCA cycle intermediates in the ACSVL3 KO cells, decreased

TCA enzyme levels may help explain the decreased glucose oxidation to CO2 seen in these cells.

120

Table 4. Levels of TCA cycle enzymes are decreased in ACSVL3 KO cells.

Proteomic analysis identified the enzymes of the TCA cycle in the U87MG cells and the

ACSVL3 KO cells. The TCA cycle enzymes, except for citrate synthase, were found to be decreased. Citrate synthase was found to be equal between the two cell lines.

121

Figure 28. TCA Cycle intermediates are not changed overall in the ACSVL3 KO cells. Metabolomic analysis detected six TCA cycle intermediates in both the KO cells and the U87MG cells – (A) Citrate, (B) α-Ketoglutarate, (C) Succinate, (D) Fumarate, (E)

Malate, and (F) Oxaloacetate. Significant increases are found in α-ketoglutarate (p =

0.017) and succinate levels (p =0.002). These measurements are total cellular levels, and may not reflect only mitochondrial metabolism. Overall, we do not see increases in TCA cycle intermediates.

122 Electron Transport Chain Complexes and ATP Synthase Subunits are Lower in the

ACSVL3 KO Cells

When we observed the decrease in the enzymes involved in the TCA cycle, we asked if the enzymes of processes downstream, e.g. the electron transport chain (ETC) and oxidative phosphorylation, would be affected as well. Levels of ETC complexes I,

II, III, and IV were all, in fact, decreased in the ACSVL3 KO cells (Table 5). Most of the subunits of ATP synthase were also decreased (Table 6). These observations, along with decreased levels of TCA cycle enzymes in ACSVL3 KO cells, are in agreement with the lower rate of glucose oxidation to CO2. Further studies will be needed to clarify the mechanism(s) that underlie changes in mitochondrial function caused by overexpression of ACSVL3 in U87MG cells.

123

Table 5. The complexes of the Electron Transport Chain are lower in the ACSVL3

KO cells. Proteomics identified most subunits of each of the four complexes of the ETC and analysis shows that expression of most, with the exception of a subunit of Complex I and one in Complex IV, is downregulated in the ACSVL3 KO cells.

124

Table 6. ATP synthase subunits levels are decreased in the ACSVL3 KO cells.

Proteomic analysis also reveals that there is a decrease in ATP synthase subunits which may lead to energetic differences between the ACSVL3 KO cells and the U87MG cells.

125 Changes in Mitochondrial Morphology Occur When U87MG Cells Are ACSVL3-

Deficient

Studies of glucose oxidation, along with proteomic and metabolomics analysis of

TCA cycle and the ETC, suggested that depletion of ACSVL3 affects mitochondrial

function. We therefore asked if this was accompanied by differences in mitochondrial

morphology. Mitochondrial morphology varies across different cell types, and the

regulation of fusion and fission responds rapidly to metabolic cues (Benard et al., 2007).

We performed immunoflurorescence (IF) using a rabbit antibody against Tom20, a mitochondrial outer membrane transporter, and found that there were striking differences in mitochondrial morphology in the U87MG and ACSVL3 KO cell lines. The mitochondria in the U87MG cell line appear more fragmented, while the mitochondria in the ACSVL3 KO cells are more fused and form reticular structures (Figure 28).

We referred to the proteomic data to see if there were any differences in proteins that are involved in mitochondrial fission and fusion that would explain these morphological differences (Table 7). These two functions have been shown to play important roles in cancer. Rehman et al. (2012) showed in human lung cancer cell lines that the cells exhibited excess mitochondrial fission. While we do see decreases in proteins that are involved in fusion in the ACSVL3 KO cells, it is the decrease that we see with the protein Mtfp1 that more likely accounts for the differences in morphology we are seeing in the mitochondria. Mtfp1 is a protein important in mitochondrial fission and when cells are depleted of only this protein, fission cannot occur (Tondera et al.,

2005).

126 Overall, results presented in this chapter suggest that ACSVL3 indirectly affects both glucose homeostasis and mitochondrial function and morphology, along with its more direct effects on sphingolipid metabolism. One possible explanation under consideration is an effect of ACSVL3 on mitochondrial membrane lipid composition.

Future experimentation will address this hypothesis.

127

Figure 29. Mitochondrial morphology is different between the U87MG cell line and the ACSVL3 KO line. Fluorescent microscopy using an antibody against Tom20, an outer mitochondrial membrane translocase, found morphological differences between the

U87MG cells and the ACSVL3 KO cells. The U87MG cell mitochondria appear more punctate while the mitochondria of the ACSVL3 KO cells are appear to be more filamentous.

128

Table 7. Proteins involved with mitochondrial dynamics show differences in the

ACSVL3 KO cells. Proteins involved in mitochondrial fusion and fission were identified in the proteomics study. Fusion proteins are decreased while most fission proteins are increased. Mtfp1, an important fission protein, is the only one decreased, and may indicate a failure for the ACSVL3 KO mitochondria to undergo fission.

129 Discussion

Upregulated expression of ACSVL3 in U87MG cells alters lipid metabolism by

increasing sphingolipid synthesis as well as increasing cholesterol levels when incubated with

growth factor relative to cells that are deficient in ACSVL3 enzyme, as shown in the previous

chapter, as we expected. Results presented in this chapter show that ACSVL3 also affects

glucose metabolism. While this was somewhat unexpected, regulatory links between glucose and

lipid metabolism are important control mechanisms for overall cellular energy homeostasis. For

example, the TCA cycle is an important crossroad between glucose and lipid metabolism.

Pyruvate, the end product of glycolysis, is metabolized by the pyruvate dehydrogenase complex

and then enters the TCA cycle as acetyl-CoA. Acetyl-CoA can be completely oxidized to CO2 for energy production, or can be used as building blocks for fatty acid and cholesterol synthesis.

More complex regulatory mechanisms linking glucose and lipid metabolism are also being discovered. A recent study showed that glucose can regulate lipid metabolism through N- glycosylation of the protein SREBP-cleavage activating protein (SCAP) to activate the SREBP transcription factors that induce lipid metabolism genes such as FASN and the LDL receptor

(Cheng et al, 2015). Aberrant glucose metabolism in cancer has been an extensive subject of study since Otto Warburg made his observation that cancer cells have increased glycolysis, even in the presence of oxygen. Findings presented in this chapter show that ACSVL3 KO in the

U87MG cell line affects glucose metabolism and mitochondrial function.

It is interesting that we found marked differences in two pathways that are linked through pyruvate – we found an increase in glycolytic enzymes and a decrease in enzymes of the TCA cycle in the ACSVL3 KO cells. However, even with these changes in enzyme levels, we found that the levels of the metabolic intermediates did not reflect these changes. Even with the decrease in the TCA cycle enzymes in ACSVL3 KO cells when compared to the U87MG cells,

130 we found some of the intermediates – such as succinate, α-ketoglutarate, and citrate – were higher in the KO cells. We looked at all of the different isozymes of the proteins important in the TCA cycle, and proteomic analysis detected both cytoplasmic and mitochondrial forms. For example, all three IDH isoforms were found, with the cytoplasmic isoforms more abundant in the ACSVL3

KO cells compared to the parental U87MG cells. The same trend was found for the malate dehydrogenase isoforms. This is important when considering the metabolomics data of the two different cell lines. While the levels of all of the mitochondrial enzymes are lower in the

ACSVL3 KO cells, the cytoplasmic isoforms could be contributing to 1) the overall level of the particular metabolite since analysis was a whole cell analysis, and 2) the metabolites could be shuttled into the mitochondria and fuel the production of the subsequent metabolites in the pathway.

The results of proteomics and metabolomics studies, in conjunction with follow-up experiments, indicated that there might be changes in mitochondrial structure when cells were depleted of ACSVL3. When we compared the cytoplasmic enzymatic isoforms to the mitochondrial isoforms of some proteins, we saw that there was an increase in the cytoplasmic isoforms in the ACSVL3 KO cells. Since there weren’t significant changes in metabolomics, we speculated that these differences originated from the mitochondria themselves. Mitochondrial morphology, particularly the dynamics of the mitochondria, has been shown to play an important role in cancer metastasis. A recent study showed that human lung cancer cell lines exhibited excess mitochondrial fission and impaired mitochondrial fusion (Rehman et al., 2012). In our study with the ACSVL3 KO cell line we find that the KO cells have network-like mitochondria, whereas the U87MG cells have more punctate mitochondria. We examined our proteomic data to see if we could find changes in expression of proteins that were important in fission and fusion, as our KO cells might have a defect in fission. We found that surprisingly, fusion proteins are low in the ACSVL3 KO cells, but fission proteins are higher, except for Mtfp1, also known as Mtp18.

This protein was found to be essential for mitochondrial fission, as loss of function (by RNAi)

131 resulted in highly fused mitochondria, even with an overexpression of another fission protein,

Fis1 (Tondera et al., 2005). This decrease in Mtp18 may be sufficient to prevent fission and keep

mitochondria in a highly fused form, despite the overexpression of other fission proteins.

Of course, since ACSVL3 is an enzyme responsible for the activation of fatty acids, we cannot ignore the possibility that what we see with mitochondrial morphology and the differences in mitochondrial enzymes is due to differences in mitochondrial membrane lipid components.

Cardiolipin is an important phospholipid of the mitochondrial inner membrane. It is unusual in that it is a diphosphatidylglycerol consisting of three glycerol backbones and four acyl chains, resulting in a very specific role in mitochondrial function. It has been implicated in the formation of enzyme complexes of the electron transport chain and in the mitochondrial apoptotic pathway.

However, when phospholipid synthesis from [1-14C]acetate was assessed in U87MG and

ACSVL3 KO cells, cardiolipin synthesis was below the level of detection on thin layer

chromatography plates. Further studies will be needed to resolve this issue.

This is the first time our lab has associated ACSVL3 with changes in mitochondria.

Mitochondria have been at the center of cancer metabolism for nearly a century. We have found

interesting data that raises only more questions as to the function of ACSVL3 in cancer cells.

This is not an exhaustive study as to why ACSVL3 is important in mitochondrial dynamics and

metabolism, but it opens up our lab to new questions relating ACSVL3 to the overall importance

of cancer metabolism, and more specifically, the importance of our enzyme to mitochondria. To

try to further answer the question of the importance of ACSVL3, studies with isolated

mitochondria will need to be performed to reduce any background from similar biological

processes occurring in other cellular compartments. However, we do believe that this has laid the

foundation to show that ACSVL3 is important in gliomas and other cancers.

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143 CURRICULUM VITAE FOR Ph.D. CANDIDATES

THE JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE

ELIZABETH ANNE KOLAR MARCH 18, 2016

15 Charles Plaza Apt 1105 Baltimore, MD 21201 [email protected] 410-207-8320

EDUCATIONAL EXPERIENCE

Ph.D. expected 2016 BCMB Program Johns Hopkins School of Medicine Mentor: Paul A. Watkins

B.S. 2007 Cellular and Molecular Biology Salisbury University Minor: Chemistry

OTHER PROFESSIONAL EXPERIENCE Thesis Research 2010-2016 Lab of Paul Watkins Johns Hopkins SOM

Identified novel role for one of the very long chain acyl-CoA synthetases (ACSVL3) that is upregulated in malignant glioma in U87 cells. An ACSVL3 knockout line using zinc finger nuclease technology in the parental U87 cells results in a decrease in cell growth, smaller subcutaneous tumors, decreased fatty acid activation and sphingolipid synthesis. We also find that this enzyme affects mitochondrial morphology and metabolism.

Post-Baccalaureate research 2007-2008 Lab of Michael Lichten National Cancer Institute

Examined the role of enzymes that are important in the resolution of joint molecules during meiotic DNA recombination in Sacchromyces cerevisiae.

Undergraduate Research 2004-2007 Lab of Kimberly Hunter Salisbury University

Investigated the effects of ploidy level on nordihydroguaiaretic acid (NDGA) in the leaves of the creosote bush, Larrea tridentata. Also examined microsatellite regions of the Larrea genome as a new way to examine the phylogenetic history of the genus.

FELLOWSHIPS

F31 Pre-Doctoral Fellowship 2011-2014 National Institutes of Health, NINDS

144 AWARDS AND HONORS

Graduate Student Travel Award 2012 ASBMB

Was awarded a travel award in the amount of $1,000 from the American Society of Biochemistry and Molecular Biology to travel to the annual conference, Experimental Biology, in San Diego, CA.

Young Botanist of the Year 2007 Botanical Society of America

Recognized nationally for contributions made to the field of Botany through undergraduate research.

PUBLICATIONS, PEER REVIEWED

DeMuyt A, Jessop L, Kolar E, Sourirajan A, Chen J, Dayani Y, Lichten M. (2012) BLM helicase ortholog Sgs1 is a central regulator of meiotic recombination intermediate metabolism. Molecular Cell 46(1):43-53. PMCID: PMC3328772

Jordan P, Copsey A, Newnham L, Kolar E, Lichten M, Hoffmann E. (2009) Ipl1/Aurora B kinase coordinates synaptonemal complex disassembly with cell cycle progression and crossover formation in budding yeast meiosis. Genes and Development 23(18):2237-51. PMCID: PMC2751982

Gradolatto A, Smart SK, Byrum S, Blair LP, Rogers RS, Kolar EA, Lavender H, Larson SK, Aitchison JD, Taverna SD, Tackett AJ. (2009) A noncanonical bromodomain in the AAA ATPase protein Yta7 directs chromosomal positioning and barrier chromatin activity. Molecular and Cellular Biology 29(17):4604-11. PMCID: PMC2725702

PRESENTATIONS

Kolar EA, Richard JP, Pei Z, Laterra J, and Watkins PA. (2012) Importance of very long chain acyl-CoA synthetase 3 (ACSVL3) in cholesterol homeostasis and lipid raft signaling in U87 glioma cells. Experimental Biology 2012, San Diego, CA, April 21-25, 2012 (presenter).

Watkins PA, Pei Z, Kolar EA, Clay EM, Shi X, Laterra J. (2012) Lipid metabolism alterations in U87 glioma cells deficient in very long-chain acyl-CoA synthetase 3 are associated with a less malignant phenotype. Experimental Biology 2012, San Diego, CA, April 21-25, 2012.

Kolar EA, Burnett EN, Miller KR, Hunter R, Hunter K. (2007) Quantification of nordihydroguaiaretic acid (NDGA) in the three ploidy levels of Larrea tridentata. Annual Meeting of the Botanical Society of America, Botany and Plant Biology 2007, Chicago, IL, July 7-12, 2007 (Speaker).

145 Kolar EA, Wiley M, Burnett AL, Parke K, Hunter R, Hunter K. (2005) Development of microsatellite markers in Larrea (Zygophyllaceae): A new way to investigate the evolutionary history of Larrea. Annual Meeting of the Botanical Society of America, Botany 2005, Austin, TX, August 12-15, 2005 (presenter).

SERVICE AND LEADERSHIP

Editor-In-Chief, Hopkins Biotech Network, Johns Hopkins University 2015-present

Recruited and coordinated volunteer writers for the bimonthly newsletter, The Transcript (~2,000 subscribers). Also responsible for reviewing, editing, and the creation of content on the HBN website.

Program Director, Connect-A-Kid (national) 2015-present

Organizes programming for Connect-A-Kid, a national 501(c)(3) organization that mentors young international adoptees and their families. Coordinates 10 teams across the country. Facilitates mentor training and family support. Advises the National Leadership team and Executive Board on upcoming programming for organization. Actively recruits mentors and families for current and new teams.

Team Lead and Mentor, Baltimore Team, Connect-A-Kid 2015-present

Organized the launch of the new Baltimore Connect-A-Kid team. Actively recruited mentors and families. Facilitated communication between the team and families about monthly outings with the adoptees.

Executive Board Member, Adoption Links, DC 2015-present

Worked with three other board members to apply for 501(c)(3) status and incorporation of organization. Communicates with over 400 members via social media. Organize monthly outings for adult adoptees to socialize and share experiences with adoption.

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