Identifying Critical Genes for Cholesterol Metabolism in Macrophages Using CRISPR-Cas9 Whole-Genome Screens

South Dakota State University Open PRAIRIE: Open Public Research Access Institutional Repository and Information Exchange

Electronic Theses and Dissertations

2019

Kevin Wanniarachchi South Dakota State University

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Recommended Citation Wanniarachchi, Kevin, "Identifying Critical Genes for Cholesterol Metabolism in Macrophages Using CRISPR-Cas9 Whole-Genome Screens" (2019). Electronic Theses and Dissertations. 3644. https://openprairie.sdstate.edu/etd/3644

This Thesis - Open Access is brought to you for free and open access by Open PRAIRIE: Open Public Research Access Institutional Repository and Information Exchange. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of Open PRAIRIE: Open Public Research Access Institutional Repository and Information Exchange. For more information, please contact [email protected]. IDENTIFYING CRITICAL GENES FOR CHOLESTEROL METABOLISM IN

MACROPHAGES USING CRISPR-CAS9 WHOLE-GENOME SCREENS

KEVIN WANNIARACHCHI

A thesis submitted in partial fulfillment of the requirement for the

Master of Science

Major in Biological Sciences

Specialization in Biology

South Dakota State University

2019

iii

ACKNOWLEDGEMENTS

I would like to thank my advisor Dr. Natalie Thiex for her guidance, advice and, encouragement throughout the process of my work. I would like to acknowledge Dr. Lu

Huang and current and former members of the Thiex lab for their advice, guidance and support in this work. And, I would like to thank Dr. Adam Hoppe and his lab for their guidance and support. Also, I extend my acknowledgment to Dr. Xijin Ge and his lab for their guidance and support in completing this work. I would also like to extend my acknowledgement and thanks to my committee members Dr. Adam Hoppe, Dr. Darci

Fink, Dr. Junwon Seo and Dr. Natalie Thiex for their advice and support. Finally, I would like to thank my funding sources from the Department of Biology and Microbiology at

South Dakota State University and the National Science Foundation/EPSCoR.

CONTENTS

ABSTRACT v Chapter I 1 Public health significance and overview of atherosclerosis pathophysiology 1 Significance of this work 2 Macrophage exposure to LDL leads to elevated cholesterol trafficking, lipid droplet formation and elevated neutral lipid metabolism. 4 References 9 Chapter II 16 Introduction 16 Methods 19 Results 27 CRISPR-Cas9 whole genome screens identified and ranked genes regulating the neutral lipid content of BMDMs 27 Genes leading to low neutral lipid content in BMDMs were validated by targeted sgRNA gene disruption 28 Genes leading to accumulation of neutral lipid in BMDMs post-LDL chase were identified and validated by targeted sgRNA gene disruption 31 References 44 Chapter III 58 Golgi apparatus conserved oligomeric complex and endoplasmic reticulum membrane protein complex are critical for LDL processing as revealed by CRISPR-Cas9 whole genome screens 58 Model for low-density lipoprotein uptake, lipid droplet formation and degradation, and cholesterol metabolism in BMDMs 61 References 62 Supplement 65

ABSTRACT

IDENTIFYING CRITICAL GENES FOR CHOLESTEROL METABOLISM IN

MACROPHAGES USING CRISPR-CAS9 WHOLE-GENOME SCREENS

KEVIN WANNIARACHCHI

2019

Macrophage foam cells contribute to atherosclerotic plaque formation, a pathology that underlies heart disease, peripheral arterial disease and stroke. Foam cells form when macrophages take up excessive amounts of low-density lipoprotein (LDL) leading to elevated cellular levels of neutral lipids, which are packaged into lipid droplet organelles. Despite the high public health priority motivating research of cardiovascular disease processes, current understanding of macrophage cholesterol metabolism including mechanisms of LDL uptake, cholesterol trafficking, lipid droplet biogenesis, lipid droplet degradation and cholesterol efflux is limited. Here, we implemented a

CRISPR-Cas9 whole genome screening strategy to identify critical genes regulating macrophage cholesterol metabolism. Murine bone marrow derived macrophages

(BMDM) were derived from transgenic mice expressing Cas9 protein and transduced with a pooled library of guide RNAs (sgRNA) that contained ~80,000 sgRNA targeting the majority of protein-coding genes in the mouse genome. BMDM were transduced with low viral multiplicity of infection to produce a single sgRNA insertion per cell. To identify gene disruptions conferring gain-of-function or loss-of-function effects on LDL uptake, cholesterol trafficking, or lipid droplet biogenesis, we exposed the mutant populations of BMDM to acetylated or oxidized LDL for 24 h, stained for cellular neutral lipid content using BODIPY 493/503 and sorted low- and high-fluorescence cells by flow

cytometry. Similarly, to identify genes critical for lipid droplet degradation, cholesterol metabolism and cholesterol efflux, we exposed the BMDM to modified LDLs for 24 h followed by LDL removal and a 48-h chase. DNA from the sorted cells was deep sequenced to quantify sgRNA inserts. Bioinformatics and statistical analyses identified sgRNA inserts that were enriched in the low neutral lipid or high neutral lipid pools and generated ranked gene lists containing genes regulating cholesterol metabolism in macrophages. To validate the screen results, we made targeted gene disruptions in

BMDM followed by staining and fluorescence microscopy of BODIPY and perilipin to verify the neutral lipid phenotype and evaluate lipid droplet morphology and cellular distribution. Of note, we highlight the identification of novel genes regulating neutral lipid levels in macrophages. Emc3 encodes an endoplasmic reticulum membrane complex protein, and when disrupted led to lower cellular neutral lipid content than wildtype cells. Whereas, Atg9a, an autophagy-related protein, when disrupted leads to higher neutral lipid due to inefficient neutral lipid clearance. In addition, gene set enrichment analysis (GSEA) analysis of screen results suggest that Golgi-conserved oligomeric complex and endoplasmic reticulum membrane complex proteins are critical for LDL processing. sgRNA for genes in these gene sets were enriched in the low fluorescence population in the 24-h oxidized or acetylated LDL conditions. Further, our screens identified many genes previously characterized in modified-LDL processing such as genes regulating receptor mediated clathrin-dependent endocytosis, Golgi-to- endoplasmic reticulum trafficking, and autophagy-associated proteins as critical regulators for neutral lipids in BMDMs. Overall, these results provide new avenues for research to determine the mechanisms of cholesterol metabolisms in macrophages.

Chapter I

Introduction and Critical Analysis: Mechanisms of LDL Uptake, Lipid Droplet Biogenesis, and Lipid Droplet Degradation

Public health significance and overview of atherosclerosis pathophysiology

Atherosclerosis is the leading cause of death by cardiovascular disease in the

United States and in western societies, and in the United States annually, approximately

610,000 deaths are due to cardiovascular disease (Mozaffarian, Benjamin et al. 2015,

Benjamin, Blaha et al. 2017, CDC 2019). Around 49% of Americans are subjected to at least one risk factor associated with cardiovascular disease such as high blood pressure, high-LDL cholesterol, and smoking (Mozaffarian, Benjamin et al. 2015, CDC 2019).

However, statins (3-hydroxy-3-methylgluataryl coenzyme A (HMG-CoA) reductase inhibitors), which are widely prescribed to lower the risk of cardiovascular diseases, have low mortality prevention rates around 25% (Wilt, Bloomfield et al. 2004). This means that available treatments are ineffective for the majority of patients and highlight the need to find new therapeutic targets.

Macrophages contribute to atherosclerotic pathogenesis and may be a target for new therapeutic strategies to treat cardiovascular diseases. In the onset of atherosclerosis, circulating monocytes are localized into artery walls and differentiate to phagocytic macrophages to clear modified lipoproteins, remove debris and dead cells resulting in the macrophage “foam cells” phenotype (Tabas 2002, Mestas and Ley 2008). Foam cell accumulation is associated with plaque formation, rupture and thrombosis, thus,

increasing the risk of cardiovascular diseases (Daugherty, Rateri et al. 2008, Neele, Van

Den Bossche et al. 2015, Chistiakov, Melnichenko et al. 2017).

Significance of this work

Cholesterol metabolism in macrophages is a function of low density lipoprotein

(LDL) uptake, LDL degradation to derive free cholesterol, processing of free cholesterol by the endoplasmic reticulum to form lipid droplets, and degradation of lipid droplets for cellular needs and cholesterol efflux. Modified LDLs binds to scavenger receptors and are trafficked by clathrin-mediated endocytosis (Chen, Wang et al. 2006, Infante, Wang et al. 2008, Zani, Stephen et al. 2015). The modified LDLs are degraded by endosomal maturation and lysosomal fusion where the activity of lysosomal lipases results in cholesterol that can be directed in vesicles to plasma membrane, trans Golgi apparatus, endoplasmic reticulum or be effluxed out of the cell (Tabas 2002). Excess cholesterol is esterified to form neutral lipids that are sequestered as lipid droplets in the endoplasmic reticulum as an energy storage mechanism as well as to prevent toxicity (Su, Dove De

Fau - Major et al. 2005). Lipid droplets can be degraded via lipolysis or autophagy to derive cholesterol and free fatty acids by the action of cholesterol ester hydrolases

(Ducharme and Bickel 2008, Nguyen and Olzmann 2017). However, current knowledge of critical regulators associated with the aforementioned processes are limited and as pointed out in Walther, Farese et al. there are many unaddressed questions including: how are lipid droplets formed in the endoplasmic reticulum, what regulates the process?

How do lipases access lipid droplets during lipolysis? (Walther, Farese et al. 2012).

Thus, there is a need for furthering the understanding of cellular processing of high levels of LDL-cholesterol and the consequent impacts on total cellular levels of neutral lipid and cholesterol metabolism. To contribute towards this, we implemented a series of CRISPR-Cas9 whole-genome screens to discover critical genes for neutral lipid metabolism in modified LDL exposed mouse bone marrow-derived primary macrophages

(BMDM). Previous whole-genome screens to identify regulators of lipid droplet formation using RNA-interference (RNAi) in drosophila found ~1.5% of genes are associated with lipid droplet formation machinery and found a novel association of Arf-

COPI proteins involved in vesicular trafficking as an important determinant for lipid droplet morphology (Guo, Walther et al. 2008). However, a drawback of RNAi screens is that they have high off-target effects and low knockdown efficiency but CRISPR-Cas9 screens allow for high on target and high gene disruption efficiency (Boettcher 2015).

CRISPR-Cas9 screens are a powerful technology to access the necessity of each gene towards these processes and simultaneously identify underlying biological pathways with higher efficiency compared to other existing whole-genome screening methods

(Shalem, Sanjana et al. 2014, Chen, Sanjana et al. 2015). A comparison of CRISPR-Cas9 screens versus RNA interference screens via shRNA for identifying essential genes in myelogenous leukemia cell line K562 revealed CRISPR-Cas9 screens identified 4,532 essential genes compared to 3,130 from RNAi screens (Morgens, Deans et al. 2016).

Therefore, we developed flow cytometry-based assays to identify changes in neutral lipid metabolism in BMDMs by scrutinizing the presence of neutral lipids using fluorescence staining. These assays were combined with CRISPR-Cas9 whole-genome screens and a

powerful bioinformatics pipeline to perform comparisons with high statistical power and identify critical genes associated with these processes.

Macrophage exposure to LDL leads to elevated cholesterol trafficking, lipid droplet formation and elevated neutral lipid metabolism.

Scavenger receptors, mainly class A scavenger receptors such as macrophage scavenger receptor 1 (Msr1) and CD36, are expressed on the surface of macrophages where they bind modified LDLs and are subsequently endocytosed in clathrin-coated vesicles (Chen, Wang et al. 2006, Infante, Wang et al. 2008, Zani, Stephen et al. 2015).

LDL is degraded in lysosomes to derive cholesterol, and Niemann Pick Type C (NPC) lysosomal surface proteins are important regulators of this process (Cruz, Sugii et al.

2000, Frolov, Zielinski et al. 2003). Cholesterol binds to the N-terminal domain of NPC1 inserting it to the lysosomal membrane, and there is a bidirectional transfer between

NPC1 and its counterpart NPC2 facilitating cholesterol shuttling to the endoplasmic reticulum (Infante, Wang et al. 2008). Non-functional NPC1 in human fibroblasts and hamster ovary cells leads to the accumulation of cholesterol in late endocytic-lysosomal compartments and could potentially play a similar role in BMDMs. (Liscum 1989) (Cruz,

Sugii et al. 2000). Proteins responsible for regulating the trafficking of cholesterol from lysosomes to the cytoplasm or other organelles are yet to be elucidated (Du and Yang

2013).

Cholesterol is shuttled to the endoplasmic reticulum to be esterified and to prevent cholesterol toxicity (Tabas 2002). Cholesterol-esterification in the endoplasmic reticulum is regulated by the enzyme acyl-CoA acyltransferase (ACAT1, gene ID: Soat1) (Su,

Dove De Fau - Major et al.). Pharmacological inhibitors of ACAT1 in mice and rabbit models lead to an increase in foam cell formation and atherosclerotic plaque (Perrey,

Legendre et al. 2001, Lu, Yuan et al. 2011). The synthesized cholesteryl esters are stored within the endoplasmic reticulum phospholipid bilayers and upon reaching a certain threshold they are packaged and released to the cytosol as lipid droplets (Ohsaki, Suzuki et al. 2014). The mechanisms and regulators underlying the processes of lipid droplet biogenesis, including interactions of lipid droplets with other organelles is yet to be understood (Herker and Ott 2012, Walther, Farese et al. 2012)

Several models for the biogenesis of lipid droplets on the endoplasmic reticulum have been suggested (Thiam, Farese et al. 2014). One such model posits that lipid droplet emergence from the ER is a spontaneous physical process resulting from cholesteryl ester accumulation within the bilayers of the endoplasmic reticulum, which may lower the surface tension to a point where lipid droplets form and are released from the bilayers.

(Thiam, Farese et al. (2013). Experiments supporting the ER cup model used freeze- fracture immunocytochemistry in lipid-laden macrophages to show that emerging lipid droplets remain embedded in the endoplasmic reticulum bilayer until a critical mass is reached causing the budding off to the cytosol (Robenek, Hofnagel et al. 2006).

Lipolysis and autophagy mediate the process of lipid droplet degradation to derive cholesterol and fatty acids (Ducharme and Bickel 2008, Nguyen and Olzmann 2017).

Lipid droplet autophagy is activated by adipose triglyceride lipase (ATGL) in hepatocytes (Sathyanarayan, Mashek et al. 2017). Similarly, LC3 (an autophagosome marker) has been observed to co-localize with lipid droplets and inhibition of autophagy decreases lipid droplet delivery to lysosomes (Ouimet, Franklin et al. 2011). Degraded

LDL-C can be used for cellular energy needs or be effluxed via ABCA1 (Su, Dove De

Fau - Major et al. , Oram 2003).

LDL Receptor binding

Clathrin

Endocytosis Lysosomal degradation

Cholesterol trafficking )

Golgi

Post Golgi vesicle ER trafficking Nucleus Autophagy related proteins

Cholesteryl ester conversion and LD Cholesterol Lipid droplets biogenesis Efflux LD Degradation

Figure 1. Cholesterol trafficking and metabolism following exposure of macrophages to modified LDLs. Scavenger receptors mediate clathrin-dependent endocytosis of modified LDL followed by endocytic trafficking and fusion of LDL carrying vesicles with lysosomes. Within the lysosomes, LDL particles are degraded to derive free cholesterol which is then directed either to the plasma membrane and effluxed, or to the endoplasmic reticulum to be esterified and sequestered in lipid droplet organelles. Lipid droplets can be degraded by autophagy and/or lipolysis to derive cholesterol and free fatty acids that can be used for cellular needs or be effluxed from the cell and transported via HDL to the liver for biliary excretion.

CRISPR-Cas9 technology allows for efficient gene disruptions and whole genome screens

Clustered regularly interspaced short palindromic repeat (CRISPR) along with the endonuclease, Cas9, are part of bacterial immune system that has been successfully

adopted by scientists to achieve highly efficient gene disruption at targeted DNA loci

(Fonfara, Le Rhun et al. 2014). Here, a sequence of RNA (sgRNA) is targeted to a complementary gene of interest where a double stranded break in the DNA is created by the Cas9 endonuclease, leading to activation of DNA repair pathways such as non- homologus end-joining which is error-prone and causes insertions and deletions at a high frequency. If made in an early exon, frame shift mutations will result, disrupting the gene. (Ran, Hsu et al. 2013)

We utilized a lentiviral CRISPR-Cas9 transduction strategy to achieve efficient and high gene disruption rate in Cas9-expressing BMDMs (Shalem, Sanjana et al. 2014).

Here the use of transgenic Cas9-expressing mice to derive BMDMs that minimizes the payload in the viral particles to sgRNA and tracRNA allowing for high gene disruption efficiency. Viral particles containing sgRNA packaged in the 293T packaging cells with a high titer of viral particles were harvested as described in methods. Using this strategy we used the Brie library (Addgene) to conduct a series of CRISPR-Cas9 whole genome screens. Brie library of sgRNAs composed of ~80,000 sgRNA targeting ~20,000 protein- encoding mice genes (4 sgRNA targeting each gene) and ~1000 control sgRNAs to transduce ~100 million Cas9 expressing BMDMs per screen (Doench, Fusi et al. 2016).

Cas9 expressing BMDMs were transduced with the Brie library at a low multiplicity of infection to derive mutant populations of BMDMs. These mutant populations were exposed to modified low-density lipoproteins to increase neutral lipid metabolism and elevate lipid droplet formation for 24 h. For neutral lipid metabolism and cholesterol efflux screens post LDL exposure cells were chased for 36-48 h in LDL-free media. The lipophilic neutral lipid dye BODIPY 493/503 was used to stain neutral lipids in the

mutants followed by flow cytometry aided cell sorting into groups based on neutral lipid content. We used next generation sequencing to sequence the sgRNA inserts from sorted groups and using a powerful bioinformatics pipeline we identified critical genes associated with neutral lipid metabolism. We used CRISPR-Cas9 transduction technique to carry out single gene disruptions of identified hits from CRISPR-Cas9 whole genome screens.

In conclusion, given the public health significance and the dearth of mechanistic understandings in macrophage biology it is vital to design and implement experiments powerful to encompass all vital aspects in macrophage cholesterol metabolism. Here, we implemented highly efficient CRISPR-Cas9 whole-genome screens to identify critical genes for cholesterol metabolism and we provide ranked lists of critical genes leading high or low neutral lipids in BMDMs as well as provide evidence for their phenotypes from targeted sgRNA disruption.

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Chapter II

Identifying Critical Genes for Cholesterol Metabolism in Macrophages Using CRISPR-Cas9 Whole-Genome Screens

Introduction

Cardiovascular diseases, particularly atherosclerosis, are a leading cause of death in the United States and globally (Benjamin, Blaha et al. 2017). Currently, statins, a class of 3-hydroxy-3-methylgluataryl coenzyme A (HMG-CoA) reductase inhibitors, are widely prescribed to treat cardiovascular diseases (Baigent, Keech et al. 2005). However, statins have low mortality prevention rates (~25%) (Wilt, Bloomfield et al. 2004,

Baigent, Keech et al. 2005) thus highlighting the need for better drug targets to treat atherosclerosis. During early atherosclerosis progression, high circulating low-density lipoprotein (LDL)-cholesterol results in the accumulation of lipid-laden macrophages in the vascular intima and development of fatty streaks in artery walls (Moore and Tabas

2011). Lipid-laden macrophages are caused by high accumulations of LDL-derived cholesterol, debris and dead cells within the vascular intima (Webb and Moore 2007).

Given the key role of macrophages in mediating the progression of atherosclerosis, these cells are potential therapeutic targets for treating this disease.

In macrophages, cellular levels of free cholesterol and esterified cholesterol are a function of the rates of LDL uptake, cholesterol trafficking, lipid droplet formation, degradation, and cholesterol efflux. Macrophages endocytose native LDL via LDL receptors and endocytose modified LDL species, such as oxidized and acetylated LDL, via a number of plasma membrane receptors including scavenger receptors. LDL- receptor (LDL-R) recognizes and binds to apoprotein B100 in native LDL, while

scavenger receptors such as CD36 (scavenger receptor class-B member 3) and SR-A

(class-A scavenger receptor class-A member 1) mediate uptake of modified LDLs such as oxidized LDL (OxLDL) or acetylated LDL (AcLDL) (Chen, Wang et al. 2006, Infante,

Wang et al. 2008, Zani, Stephen et al. 2015). After endocytic trafficking to the lysosome, free cholesterol is derived from the LDL, and excess cholesterol, which is slightly polar, is esterified, thus, rendering its charge neutral. These neutral cholesterol esters are sequestered in lipid droplet organelles (Maxfield and Tabas 2005). In reverse cholesterol transport, lipid droplets are degraded by autophagy and/or lipolysis to derive free cholesterol that can be effluxed out of the cells to acceptors such as high-density lipoproteins (HDL) and subsequently delivered to the liver for biliary excretion

(Kwiterovich 2000, Su, Dove et al. 2005, Dong and Czaja 2011).The role of autophagy in the degradation of lipid droplets has been shown through association of the autophagosome marker microtubule-associated protein 1A/1B-light chain 3 (LC3) with lipid droplets, and by the demonstration that inhibition of autophagy decreases lipid droplet delivery to lysosomes (Ouimet, Franklin et al. 2011).

Early observations that high circulating HDL levels correlated with lower cardiovascular disease highlight the importance of efficient reverse cholesterol transport

(Rohatgi, Khera et al. 2014) and led to the development of drugs such as niacin, fibrates, and inhibitors of cholesterol ester transfer protein (CETP) to increase HDL (Keene, Price et al. 2014). Neutral lipid clearance by cholesteryl ester hydrolysis is the rate-limiting step in reverse cholesterol transport in lipid droplet laden-macrophages (Hutchins and

Heinecke 2015). Cholesterol ester hydrolases such as hormone-sensitive lipase (Lipe), carboxylesterase 3 (Ces3), and neutral cholesterol-ester hydrolase 1 (Nceh1) mediate the

hydrolysis of cholesterol esters (Hutchins and Heinecke 2015). Furthermore, previous work has shown that the inhibition of Nceh1 in lipid-laden macrophages leads to increased lipid droplet accumulation (Sakai, Igarashi et al. 2014). However, current understanding is limited regarding other cellular events and mechanisms critical for these processes in macrophages.

Given the public health importance of preventing atherosclerotic disease progression, and the dearth of molecular mechanistic understanding of these processes in cells of all types, but especially macrophages, we implemented a series of CRISPR-Cas9 whole genome screens to discover critical mediators of cholesterol metabolism in bone marrow-derived macrophages. CRISPR-Cas9 whole-genome screens are more powerful in identifying critical genes compared to other genome screening techniques because of its high on-target rates and high levels of complete gene disruption (Shalem, Sanjana et al. 2014, Boettcher 2015, Morgens, Deans et al. 2016). In this technology, guide RNA

(sgRNA), which are complementary to target genes, direct the Cas9 endonuclease enzyme to make double-stranded breaks in DNA leading to insertions or deletions during

DNA repair and subsequently disrupting expression of the protein (Sanjana, Shalem et al.

2014).

Here, we have identified critical genes and cellular pathways that cause defects in macrophage cholesterol metabolism by scrutinizing neutral lipid content in BMDM via a series of whole-genome CRISPR-Cas9 screens. To this end, we used a two-pronged approach whereby we identified loss-of-function or gain-of-function phenotypes in

BMDM transduced with the Brie sgRNA library under the following conditions:

1) following a 24-h AcLDL or OxLDL exposure, or

2) following 24-h AcLDL or OxLDL and a 36-48 h chase following removal of

LDL.

Specifically, in order to identify critical genes for LDL uptake, cholesterol trafficking, and lipid droplet formation, we transduced a population of BMDMs with the

Brie sgRNA library, exposed them to AcLDL or OxLDL for 24 h and stained them with the neutral lipid marker BODIPY 493/503. Using flow cytometry, we identified sgRNA enriched in low- and high-fluorescence populations corresponding to high- or low-neutral content. To identify critical genes for lipid droplet degradation and cholesterol efflux, we identified sgRNA enriched in BMDM with low or high neutral lipid following the LDL removal and the post-LDL chase. Our screens identified novel Emc3, Atg9a and organelle complexes such as the endoplasmic reticulum associated endoplasmic reticulum membrane complex and Golgi-apparatus conserved oligomeric complex, as well as known genes associated with cholesterol metabolism such as Msr1, Soat1, and, Abca1.

Methods

Reagents

BMDM were cultured in bone-marrow medium (BMM) containing Dulbecco’s Modified

Eagle Medium (ATCC 30-2002, American Type Culture Collection, Manssas, VA), 20% heat-inactivated fetal bovine serum (Atlanta Biologicals) and 30% L-cell supernatant

(Stanley and Heard 1977) a source of colony-stimulating factor-1, 10,000 IU penicillin and 10 mg/mL streptomycin (Corning, Manassas, VA), and 5.7 mM 2-mercaptoethanol.

DPBS without calcium or magnesium was purchased from GE Healthcare Life Sciences,

Pittsburgh, PA. AcLDL (Alfa Aesar, Haverhill, MA) and OxLDL were from (Alfa Aesar,

Haverhill, MA). Lipid droplets were stained with BODIPY 493/503 (4,4-Difluoro-

1,3,5,7,8-Pentamethyl-4-Bora-3a,4a-Diaza-s-Indacene) (Invitrogen). Perilipin antibody

(ab108323), was from Abcam. Cyclosporin A (30024, Sigma). Mouse Brie CRISPR knockout pooled library developed by David Root and John Doench was obtained from

Addgene (Addgene #73633) (Doench, Fusi et al. 2016). The blocking/permeabilization buffer for immunofluorescence was prepared with 1% BSA (BP1600-100, Fisher

BioReagents), 0.1% saponin (558255-100GM, EMD Millipore), 0.02% sodium azide

(J21610-22, Thermo Scientific) in DPBS

Bone marrow-derived macrophage isolation and culture

Transgenic mice with a Rosa26-Cas9 knock-in on a C57BL/6J background were received from Jackson Laboratories (Stock No. 026179, Bar Harbor, ME). Mice were euthanized using CO2, femurs were dissected from the mice and bone marrow was harvested

(Swanson 1989) by flushing Dulbecco’s phosphate buffer saline (DPBS) without calcium or magnesium (GE Healthcare Life Sciences, Pittsburgh, PA) through the bone using a needle and syringe. Cells were plated in non-tissue culture treated, sterile dishes and incubated at 37°C with 5% CO2. Additional BMM was added to the cells on day 2 post- isolation. Following cell adherence to the dish, on day 4, the medium was completely removed and fresh BMM added to the culture. For cells undergoing lentiviral transductions, viral supernatants were added to the cells on day 4-6 of culture.

CRISPR-Cas9 whole-genome screen workflow

Four sgRNA per gene ~100 000 sgRNAs total

sgRNA sgRNA

sgRNA Add modified LDL Remove modified LDL sgRNA

Cholesterol uptake, Cholesterol Puromycin processing and LD efflux by LD selection formation degradation

24 h 48 h

BODIPY staining, sorting of Cas9-expressing high and low fluorescence bone marrow-derived Pooled sgRNA library cells macrophages lentiviral transduction 24-h LDL Post-LDL-48-h chase

25% 25% 25% 25%

Fluorescence Fluorescence Input Pre-LDL Pre-sort Low High Low High

Next generation sequencing of sgRNA insert to identify enriched guides

Figure 1. Workflow of CRISPR-Cas9 whole-genome screens leading to identification of critical genes for cholesterol metabolism in bone marrow-derived macrophages. Cas9-expressing murine BMDMs were transduced with the Brie sgRNA library targeting ~20,000 protein coding genes with 4 sgRNA per gene in the mouse genome. Following puromycin selection, BMDMs were cultured for 8-10 days to deplete mRNA and proteins in gene-disrupted cells. To identify genes regulating cholesterol uptake and lipid droplet biogenesis, BMDMs were exposed to AcLDL or OxLDL for 24 h, stained with BODIPY 493/503 and high- and low-fluorescence cells were sorted. To identify genes critical for neutral lipid flux as cholesterol via lipid droplet degradation, cells were chased in culture medium for 36-48 h post LDL removal and high- and low- fluorescence cells were sorted. sgRNA inserts from the high- and low-fluorescence groups from the 24-h LDL exposure and the post-LDL48-h chase, along with sgRNA library plasmid DNA (input), BMDMs prior to LDL exposure (pre-LDL) and prior to sorting (pre-sort) samples were all sequenced by next generation sequencing. sgRNA inserts were mapped to the sgRNA library and mouse genome. Following statistical analyses, genes were ranked based on enrichment in the low- or high-fluorescence pools corresponding to high or low neutral lipid content. Low fluorescence = low neutral lipid in cells following gene disruption. High fluorescence = high neutral lipid in cells following gene-disruption.

Lentiviral transduction of Brie pooled sgRNA library

Brie library amplification, lentiviral production, and functional titer determination were performed as previously described (Joung, Konermann et al. 2017) with minor modifications. Briefly, the Brie library was amplified in Stable 3 competent E. coli

(Thermofisher) and subjected to next-generation-sequencing (NGS) to determine the

distribution of sgRNAs in the library. To produce Lentivirus, 1.8 x 106 NIH 293T cells were seeded in six 10-cm plates and transfected the following day with 6 µg sgRNA pooled library in lentiGuide-Puro (Addgene# 73633), 6 µg psPAX2 plasmid, 1 µg pVSVG plasmid, and 0.024 mg polyethyleneimine (PEI). After 48 h, the lentivirus was harvested, centrifuged, and aliquoted into multiple 15 mL tubes and stored at -80o C or -

150o C. The functional titer of the lentivirus was determined by live-cell counting after puromycin selection. For lentivirus infection, BMDM expressing Cas9-GFP were transduced with the Brie library at a multiplicity of infection (MOI) = 0.3. Approximately

2.5 x107 to 5 x107 cells were transduced with 8 x 106 or 16 x 106 transduction units

(TUs) to achieve 100-200-fold representation of each sgRNA. After 48 h, cells were selected with puromycin (5 µg/mL) for two days and were cultured for at least seven more days before the neutral lipid assay and cell sorting.

Neutral lipid assay and cell sorting

Following lentiviral transduction, sgRNA inserted cells were exposed to AcLDL (50

µg/ml) or OxLDL (100 µg/ml) for 24 h. We scrutinized neutral lipid content in two conditions: 1) 24-h LDL exposure and 2) 36-48-h chase following LDL removal. For each condition we treated cells with AcLDL for two replicate populations and treated cells with OxLDL for one replicate for each condition. Before group isolation by fluorescence activated cell sorting BMDMs were stained with 5 µM BODIPY (493/503), a neutral lipid dye staining LDs, diluted in DMEM for 5 mins, washed once with cold

DPBS (-Ca/-Mg) and detached with DPBS (-Ca/-Mg). Next, sorting was done by BD

FACs JAZZ cell sorter based on low or high BODIPY fluorescence (~5 x 106

cells/group) in each screen. The lower 25% of cells with low fluorescence and higher

25% of cells with high fluorescence were sorted in each group described below.

In each population the isolated groups of cells were as follows,

(1) High BODIPY fluorescence (High neutral lipids)

(2) Low BODIPY fluorescence (Low neutral lipids)

(3) Prior to sorting (~10%) (pre-sort)

(4) Plasmid DNA of the input brie library (input)

PCR and next-generation sequencing of gRNA inserts

Genomic DNA was extracted from unsorted and sorted cells using the GeneJET genomic

DNA extraction kit (#K0721 Thermofisher) and the sgRNA library was amplified by a single-step PCR protocol (Broad Institute) for NGS using barcoded primers with staggered sequences. PCR product from multiple PCR reactions was pooled and gel purified and quantified by Qubit Fluorometer and subjected to sequencing on Illumina

Nextseq 500 with 75 reads. Sequencing quality control from FASTQC (Andrews 2010), read count summaries and mapping data from MAGeCK-VISPR can be found in the

(Supplemental Figure 2-3). Cut adapt, version 2.3 (Martin 2011) was used to remove sequencer adapter regions to produce files which contained 20 basepair read segment of gRNA inserts with no mismatch tolerated.

Statistical analysis of sequencing data and gene ranking

Model-based Analysis of Genome-wide CRISPR-Cas9 Knockouts (MAGeCK), version

0.5.9 (Li, Xu et al. 2014), was used to map gRNA insert reads to their corresponding sgRNA inserts to the Brie library and corresponding gene names with no mismatches

tolerated. MAGeCK-RRA analysis produced a ranked list of genes by comparison of read enrichment (Li, Xu et al. 2014). Using the -count function in MAGeCK, the gene counts were tallied to produce read count tables for each group. The -test command was used to rank gRNA enriched by comparison of read counts between each group. To compare replicate screens, paired function was used (-test -paired commands). ~1000 control non- coding sgRNA inserts were specified for normalization and generating null distribution of RRA were specified by -control function. Results from MAGeCK-RRA test can be found in the Supplementary table-1. MAGeCK-VISPR (Li, Koster et al. 2015), a

MAGeCK tool that allows visualization of quality control and screen design of CRISPR-

Cas9 whole-genome screens, was used to visualize the read counts mapped to the Brie library, visualize read counts for each gRNA insert, and, generate correlation assessment of reads in each group (Supplement Figure 2F-3F).

Pathway enrichment analysis and differential gene expression analysis

Ranked lists of genes for each screen were used to identify biologically enriched pathways using gene set enrichment analysis (GSEA) available on the web-based

Integrated Differential Expression and Pathway Analysis (iDEP.9) website (Mootha,

Lindgren et al. 2003, Subramanian, Tamayo et al. 2005, Ge 2017). Briefly, GSEA groups gene sets by common biological function and compares if gene sets occur towards the top or bottom of the ranked list and assign enrichment scores. The normalized enrichment score (NES), based on gene set enrichment scores for gene set permutations, was used to compare analysis results where a positive score reflects gene sets represented

at the top of the ranked list and a negative score reflects gene sets represented towards the bottom of the list.

Lentiviral mediated CRISPR-Cas9 gene disruptions

To make targeted CRISPR-Cas9 gene disruptions for screen validation, sgRNAs from the

Brie library were selected based on previously tabulated sgRNA counts and on- and off- target scores (Doench, Fusi et al. 2016, Sanson, Hanna et al. 2018). Forward and reverse oligos for the sgRNA were synthesized, annealed and ligated into pLenti plasmid

(Sanjana, Shalem et al. 2014, Shalem, Sanjana et al. 2014). Plasmids were transfected into Stable 3 competent E. coli (Thermofisher) for amplification (Sanjana, Shalem et al.

2014). DNA was purified and sequence verified prior to lentiviral production. To produce sgRNA containing lentivirus, 7 x 105 293T cells were seeded into 6-well plates and transfected the following day with 1 µg sgRNA, 1 µg psPAX2, 60 ng pVSVG, and 4 µg of polyethyleneimine (PEI) in 100 µL DBPS. After 48 h, cell culture supernatant containing lentivirus was harvested, centrifuged to remove packing cells, and aliquoted and stored at -80o C or -150o C. Viral supernatant with 10 µM Cyclosporin A was added to Cas9-expressing BMDMs cultured in BMM for 48 h and was selected with puromycin.

Validation assays were done 8-10 days post-transduction.

Fluorescence staining and microscopy

BMDMs were cultured in 96-well plates in the confluency of 30,000 cells/well.

Following 24-h exposure to AcLDL and/or followed by post LDL 48 h chase from lipoproteins. Cells were fixed with 2% paraformaldehyde in PBS for 20 min, blocked and

permeabilized with blocking/permeabilization buffer for 10 min. Subsequently cells were stained with primary antibodies and 5 µM BODIPY in blocking/permeabilization buffer for 1 h, followed by staining with a fluorescent secondary antibody (plus nuclear stain and actin stain for downstream cell segmentation) for 45 min. Imaging was done using

ImageXpress Micro XLS widefield high-content analysis system microscope and

Olympus IX83 P2ZF microscope.

High-content image analysis and statistical methods

Image data were quantified using Cell Profiler 3.0.0 (Carpenter, Jones et al. 2006).

During imaging nine sites per well were image and images with 15-65 cells was processed. Nuclei were identified as primary objects and cell boundaries (secondary objects) were defined by phalloidin images. From the defined secondary object sum of pixel intensities of BODIPY- and perilipin-stained objects were identified as integrated intensity. Further data transformations were done using R 3.4.4 (R Development Core

Team 2018), and, the dplyr (Wickam, Francois et al. 2019), the tidyr (Wickam and Henry

2019) packages were used. Here, mean and standard deviation was calculated and object intensities that were three standard deviations from the mean of each image set were flagged as outliers and discarded. Two-way ANOVA followed by Dunnett multiple comparisons were performed using GraphPad Prism version 8.2.0 for MacOS, GraphPad

Software (San Diego, California USA) from mean integrated intensities.

Flow cytometry assay for detecting neutral lipid

BMDMs were plated on 96 well plates at 10,000 cells/well. Following 24-h exposure to

AcLDL and/or post-LDL 48-h chase were stained with 5 µM BODIPY (493/503), a

neutral lipid dye staining LDs, diluted in DMEM for 5 mins, washed once with cold

DPBS (-Ca/-Mg) and detached with DPBS (-Ca/-Mg). BMDMs were analyzed for

BODIPY (493/503) intensity using BD Accuri C6 glow cytometer

Results

CRISPR-Cas9 whole genome screens identified and ranked genes regulating the neutral lipid content of BMDMs

We conducted CRISPR-Cas9 whole genome screens (Figure 1) to identify critical genes for:

1. LDL uptake, cholesterol trafficking, and lipid droplet biogenesis by

identifying sgRNA inserts associated with low- or high-neutral lipid content

following 24-h AcLDL or OxLDL exposure. This is referred to hereafter by “24-h

LDL screens”.

2. Lipid droplet degradation and cholesterol efflux by identifying sgRNA inserts

associated with low- or high-neutral lipid content following 24-h AcLDL or

OxLDL exposure, LDL removal and a 36-48 h chase. This is referred to hereafter

by “post LDL 48-h chase screens.”

We used next generation sequencing to sequence the sgRNA inserts and quality of sequencing reads were assessed by FastQC (Supplement Figure 1). Read counts were then tabulated and mapped to the Brie library (Supplement Figure 2A-3A). Also, sgRNA that were lost from the Brie library were low as shown by input missed sgRNA

(Supplement Figure 2C-3C). The read counts were normalized (Supplement Figure 2B-

3B). and the read count distributions were analyzed as indicated by the Gini index and the

correlation matrix of reads as shown (Supplement Figure 2D-F, Supplement Figure 3D-

F).

Genes leading to low neutral lipid content in BMDMs were validated by targeted sgRNA gene disruption

We identified and ranked critical genes from the 24-h LDL screens. Comparison of sgRNA reads among the high- and low-neutral lipid groups from the 24-h LDL screens indicated the enrichment of particular genes within one of the groups (Figure 2A). This difference in enrichment of all read counts between high- and low-fluorescence groups was then statistically analyzed using MAGeCK-RRA to produce a ranked list of genes between the low- and high-neutral lipid groups (Supp. Table 1). Here, enrichment between groups were demarcated by log base 2 fold change (LFC) indicative of enrichment within high (positive LFC) or low (negative LFC) neutral lipid.

Comparison of genes enriched in AcLDL and OxLDL in the low neutral lipid populations from 24-h whole genome screens we observed that there were genes enriched only in AcLDL or only in OxLDL (Figure 2B). Stab-1, a scavenger receptor, was highly enriched in both AcLDL and OxLDL. However, Msr1 (SR-A) another scavenger receptor, was only highly enriched in the AcLDL screens. Similarly, NPC1, and adaptor proteins important clathrin-mediated endocytosis such as Ap2s1, Ap2m1 were only highly enriched in AcLDL screens. Also, it should be noted that the vacuolar ATPase, V- type pump, associated with lysosomes vital for increase pH in the compartments is highly enriched in both AcLDL and OxLDL suggesting that the lysosomal degradation of modified lipoproteins is regulated by similar machinery. Interestingly, Soat1,

acetyltransferase found in the endoplasmic reticulum , that mediates cholesterol conversion to cholesteryl esters was only enriched in the AcLDL low neutral lipid populations. These results suggest for the existence of multiple pathways for the uptake of modified LDL species depending on the modification.

Next, we selected several genes with high LFC and high ranking MAGeCK scores, including Atp6v1a, Emc3, and Soat1, that we hypothesized lead to low neutral lipid content following gene disruption by lentiviral transduction. As shown by low

BODIPY and perilipin staining intensity (Figure 2C), 24-h LDL exposure leads to significantly lower neutral lipid in the gene disrupted BMDMs compared to wildtype

BMDM or control BMDM transduced with a non-targeted sgRNA (ScramsgRNA)(data for

Scram not shown) and Emc3 and Soat1 had significantly fewer lipid droplets as indicated by perilipin immunostaining and fluorescent intensity (Figure 2D).

A B sgRNAs targeting Soat1

Low High fluorescence fluorescence

24-h-AcLDL BODIPY PLIN2 D N>3 C p<0.001 WT 800 ✱ 24H BODIPY 24H PLIN2

✱ 600 ✱ ✱

✱

400 ✱

nertdItniy(A.U.) Intensity Integrated 200 Atp6v1a

0 WT Atp6v1a Soat1 Emc3

Genotype

Soat1

Emc3

Figure 2. 24-h-LDL CRISPR-Cas9 whole genome screens identifies genes leading to low neutral lipids, and targeted sgRNA gene disruptions validate screen findings of genes associated with low neutral lipid phenotype in BMDMs. Read counts of all sgRNAs from Next-generation sequencing were processed and considered. Best performing sgRNAs were assigned a MAGeCK-RRA score based on enrichment. Ranked lists were generated based on enrichment comparison between high and low neutral lipid groups. A) Read counts from a single 24-h-LDL screen of the four sgRNAs targeting Soat1, shows that they had higher read count in low neutral lipid group compared to high neutral lipid group. B) Plot of log fold change(LFC) meeting FDR>0.1 between AcLDL and OxLDL for 24-h-LDL screens illustrated genes uniquely enriched in either AcLDL or OxLDL and those enriched in both. Here, Negative LFC is indicative of low neutral lipid and positive LFC is indicative of high neutral lipid. C) Targeted sgRNA disruption of Atp6v1a, vital for increasing luminal pH in late endo-lysosomes, leads to decreased LDL uptake resulting in less neutral lipids. Soat1 (ACAT-1), critical for converting free cholesterol to cholesterol esters, disruption leads to lower neutral lipid, however, it is not a complete disruption and it could be hypothesized that there are other enzymes compensating cholesterol conversion. Emc3, a transmembrane insertase in the endoplasmic reticulum, could potentially be vital for

lipid droplet biogenesis as its disruption leads to low neutral lipid. D) Quantification of BODIPY 493/503 and perilipin integrated intensity of the targeted gene disruptions upon exposure to 24-h AcLDL. (Error bars are representative of the standard deviation of the means of all images for a genotype, N- is from independent experiments where >100 cells for each genotype were analyzed,*p- value from Dunnette's test following Two-way ANOVA analysis of genotypes as compared to WT)

Genes leading to accumulation of neutral lipid in BMDMs post-LDL chase were identified and validated by targeted sgRNA gene disruption

We identified critical genes for the processes of neutral lipid clearance via lipid droplet degradation and cholesterol efflux from the post-LDL 48-h chase screens. Here, we compared the sgRNA reads from the high- and low-neutral lipid groups from the post-

LDL 48-h chase screens (Figure 3A). MAGeCK-RRA was used to produce a ranked list of genes between low- and high-neutral lipid groups (Supplementary Table 1). Next, we compared LFC between AcLDL and OxLDL and high overlap of highly ranked and high-

LFC hits was seen suggesting that once lipid droplets are formed the degradation machinery involved is independent of the modified LDL species leading to their formation (Figure 3B). However, there were genes uniquely enriched in either AcLDL or

OxLDL that led to accumulation of neutral lipid. Abhd5 and Aurkb only enriched in

AcLDL and Pol1rb and Dut were only enriched in OxLDL. Similarly, the comparison of

AcLDL and OxLDL illustrated that degradation of increased neutral lipids and lipid droplets are mediated mostly by autophagy. And, it was seen that autophagy associated genes such as Atg9a, Atg101, and Atg13 were highly enriched in both AcLDL and

OxLDL high neutral lipid populations following post-LDL 48-h chase.

The nutrient-sensing and cholesterol-sensing pathway were highly enriched in the highly fluorescent population post-LDL 48h chase screens suggesting that their loss of function leads to an accumulation of neutral lipids. We hypothesized that disruptions to

these will lead to high neutral lipid accumulation as they are unable to detect lipid droplets and/or efficiently process neutral lipids for efflux via lysosomal nutrient-sensing machinery. We conducted targeted gene disruptions of several vital regulators of nutrient- sensing machinery such as Tsc1, RagC, Flcn, and Atp6v1a. As shown by post-LDL 48-h chase the gene disruptions lead to higher neutral lipid and a higher number of lipid droplets as shown by perilipin immunostaining (Figure 3C). However, we were unable to quantify the immunofluorescence images using our automated Cell Profiler pipelines as our analysis relied on phalloidin staining of images to segment cells and these gene- disruptions also disrupted the cellular F-actin distribution compared to wild-type cells.

We conducted flow-cytometry analysis of BODIPY intensity (Figure 3D) and as shown the gene disruption led to higher BODIPY fluorescence.

We also conducted targeted gene disruptions of several genes with high LFC and high ranking that included Cbfb, Keap1, Vps11, Bcl6, Szt2, Tgfbr1, and Atg9a. We hypothesized that when these genes are disrupted, it will lead to high neutral lipid. As shown, the gene disruptions had significantly higher BODIPY intensity post-LDL 48-h chase compared to the wild-type and a significantly higher number of lipid droplets as shown by perilipin immunostaining (Figure 4B)

A B sgRNAs targeting Flcn

Low High fluorescence fluorescence

C 24-h-AcLDL Post 48-h-Chase D N=2 BODIPY PLIN2 BODIPY PLIN2 6.0E+5

WT WT 5.0E+5

4.0E+5 WT 3.0E+5

2.0E+5

1.0E+5

Tsc1 Tsc1 GEOMETRIC MEAN (A.U) BODIPY 0.0E+0 WT TSC1 RAGC FLCN

RagC RagC

Flcn Flcn*

Atp6v1a Atp6v1a

*Not window-levelled to WT as it is too bright

Figure 3. Post-LDL 48h chase CRISPR-Cas9 whole genome identified gene disruptions leading to accumulation of neutral lipid and targeted sgRNA gene disruptions validate screen findings by recapitulating the high-neutral lipid phenotype. Read counts of all sgRNAs from Next-generation sequencing were processed and considered. Ranked lists were generated based on enrichment comparison between high and low neutral lipid groups. A) Read counts from a single post-LDL-48-h chase screen of the four sgRNAs targeting Flcn, shows that they had higher read count in high neutral lipid group compared to low neutral lipid group. B) Plot of log fold change (LFC) meeting FDR > 0.1 between AcLDL and OxLDL for post-LDL chase screens illustrated genes uniquely enriched in either AcLDL or OxLDL and those enriched in both.. Here, Negative LFC is indicative of low neutral lipid and positive LFC is indicative of high neutral lipid. C) BODIPY 493/503 was used to stain neutral lipid and perilipin, lipid droplet associated protein, was used to identify lipid droplets After chase sgRNA disrupted BMDMs led to high neutral lipid as shown by high BODIPY intensity compared to WT. Regulators of the nutrient sensing pathway are vital for cholesterol sensing too as cell with disrupted Tsc1 by targeted sgRNA has high neutral lipids as lipid droplets post-48-h chase compared to WT. Similarly, RagC disrupted cells too have high neutral lipid as lipid droplets. However, Flcn disruption led to high neutral lipid (high BODIPY) but not high lipid droplets. In the same way, Atp6v1a disruption too leads to accumulation of neutral lipid. However, as shown previously Atp6v1a had low neutral lipid post 24h LDL exposure however overtime in culture leads to accumulation of neutral lipids too D) As shown by flow cytometry, sgRNA disruption led to high neutral lipid content after chase as confirmed by high geometric means of BODIPY intensity (N=2 is from independent experiments where at least 1x104 cells were analyzed)

A Post 48-h-Chase BODIPY PLIN2 BODIPY PLIN2 WT Bcl6

Cbfb Szt2

Keap1 Tgfbr1

Vps11 Atg9a

B N>3 ✱ p<0.001 1500 Post-LDL-48H Chase BODIPY

✱ Post-LDL-48H Chase PLIN2

✱ 1000 ✱

✱ ✱

✱ ✱ ✱

✱ ✱ ✱ ✱

✱ 500 ✱ nertdItniy(A.U.) Intensity Integrated

0 WT Cbfb Keap1 Vps11 Bcl6 Szt2 Tgfbr1 Atg9a Genotype

Figure 4. Targeted sgRNA-gene disruption validates screen findings of neutral lipid accumulation phenotype in BMDMs, Genes identified leading to accumulation of neutral lipids post-LDL-48-h chase from CRISPR-Cas9 whole-genome screens were validated by targeted sgRNA gene disruption. A) As shown sgRNA gene disruption led to high neutral lipid content post-LDL-48H chase. B) Quantification of BODIPY and perilipin integrated intensity (Error bars are representative of the standard deviation of the means of all images for a genotype, N- is from independent experiments where >100 cells for each genotype analyzed,*p-value from Dunnette's test following Two-way ANOVA analysis of genotypes as compared to WT)

Ranked lists were used to identify gene sets of enriched biological pathways

In order to identify the biological pathways and gene-sets enriched within our ranked lists of genes, we performed gene set enrichment analysis (GSEA) using

Reactome database (Figure 5A; full sets Supplementary Table 2 and Table 3). Within the

24-h AcLDL screen ranked gene list, a high number of genes from vesicle-mediated trafficking and signaling pathways such as signaling by insulin receptor, iron uptake and transport, and cilium assembly were highly enriched (Figure 5B). In the same way, Golgi transport associated pathways such as ER to Golgi anterograde transport, COPI-mediated anterograde transport, transport to Golgi and subsequent modification, and intra-Golgi traffic were highly enriched. The enrichment of Golgi-associated gene-sets points towards a strong association of the Golgi-apparatus with LDL trafficking, processing and lipid droplet biogenesis. We then examined the performance of the identified gene sets in our CRISPR-Cas9 whole-genome screens. Briefly, we extracted the genes from these pathways that had FDR < 0.1 and their respective LFC from all screens (Figure 5C).

Here, the negative log changes are associated with lower neutral lipid content and positive log fold change is associated with higher neutral lipid content for the given sgRNA. Screen performance of gene-sets identified in pathway enrichment analysis show low neutral lipid content consistent with the above-mentioned pathways and suggesting critical cellular processes underlying LDL uptake, cholesterol processing and lipid droplet biogenesis. Pathways such as signaling by insulin receptor and iron uptake transport are highly enriched as they contain components of the vacuolar ATPase complex (Figure 5C). Vacuolar ATPase H+ pump subunits, which are crucial in ATP

hydrolysis coupled transmembrane transport, the disruption of the luminal V0 subunit members Atp6v0b, Atp6v0c, Atp6v0d1 lead to lower neutral lipid content. Furthermore, the disruption of the cytoplasmic V1 subunit members Atp6v1a, Atp6v1b2, Atp6v1d,

Atp6v1e1, Atp6v1b2 had ambiguous neutral lipid content. The Golgi apparatus associated conserved oligomeric complex proteins Cog2, Cog3, Cog4, Cog6, Cog7, Cog8, and endoplasmic reticulum membrane complex proteins Emc1, Emc2, Emc3, Emc4, Emc6 and Emc7 led to low neutral lipid content in all screens. Similarly, we examined the performance of canonical pathways and machinery previously described in the literature as being vital for LDL processing and lipid droplet biogenesis (Figure 5D).

A similar GSEA analysis was carried out with the post-LDL 48-h chase screens ranked list. From the enriched Reactome pathways (Figure 6A) gene sets from regulation of PTEN gene transcription, regulates metabolic genes, macroautophagy, and activation of ATR in response to stress screen were highly enriched (Figure 6B). Similar to above, the screen performance of genes in these gene sets was analyzed (Figure 6C), and sgRNA read counts corresponding to these genes was enriched in cells sorted into the high neutral lipid pools suggesting that CRISPR/Cas9 disruption of these genes impairs efficient degradation of lipid droplets and/or efflux of cholesterol. The autophagy-related genes Atg9a, Atg13, Atg14, and Atg101 were all enriched in the post-LDL-48-h screens suggesting that autophagy machinery promotes degradation of lipid droplets and clearing of neutral lipids from macrophages.

A Down Up B Genes from AcLDL−24h screens Enriched Reactome pathways 3e-03 Reactome:R-HSA-1852241 Organelle biogenesis and maintenance 1e-03 Reactome:R-HSA-5617833 Cilium Assembly 2e-03 Reactome:R-HSA-390466 Chaperonin-mediated protein folding Vesicle−mediated transport 118 1e-03 Reactome:R-HSA-391251 Protein folding 1e-03 Reactome:R-HSA-199977 ER to Golgi Anterograde Transport 4e-04 Reactome:R-HSA-948021 Transport to the Golgi and subsequent modification 2e-03 Reactome:R-HSA-6807878 COPI-mediated anterograde transport Transport to the Golgi and subsequent modification 39 2e-04 Reactome:R-HSA-199991 Membrane Trafficking 2e-04 Reactome:R-HSA-5653656 Vesicle-mediated transport 1e-03 Reactome:R-HSA-6811438 Intra-Golgi traffic 1e-02 Reactome:R-HSA-373076 Class A/1 (Rhodopsin-like receptors) Signaling by Insulin receptor 24 9e-03 Reactome:R-HSA-500792 GPCR ligand binding 4e-03 Reactome:R-HSA-168255 Influenza Life Cycle 1e-03 Reactome:R-HSA-168254 Influenza Infection 1e-02 Reactome:R-HSA-6791226 Major pathway of rRNA processing in the nucleolus and cytosol Iron uptake and transport 17 NES 7e-03 Reactome:R-HSA-72306 tRNA processing 2.00 1e-03 Reactome:R-HSA-72172 mRNA Splicing 1.95 1e-03 Reactome:R-HSA-72163 mRNA Splicing - Major Pathway 1.90 Intra−Golgi traffic 1e-03 Reactome:R-HSA-72203 Processing of Capped Intron-Containing Pre-mRNA 15 1.85 2e-04 Reactome:R-HSA-8953854 Metabolism of RNA 6e-04 Reactome:R-HSA-73856 RNA Polymerase II Transcription Termination 6e-04 Reactome:R-HSA-109688 Cleavage of Growing Transcript in the Termination Region ER to Golgi Anterograde Transport 6e-04 Reactome:R-HSA-72187 mRNA 3'-end processing 34 1e-03 Reactome:R-HSA-72202 Transport of Mature Transcript to Cytoplasm 2e-04 Reactome:R-HSA-74160 Gene expression (Transcription) 2e-04 Reactome:R-HSA-73857 RNA Polymerase II Transcription Cilium Assembly 2e-03 Reactome:R-HSA-4839726 Chromatin organization 25 2e-03 Reactome:R-HSA-3247509 Chromatin modifying enzymes 1e-03 Reactome:R-HSA-917937 Iron uptake and transport 2e-04 Reactome:R-HSA-74752 Signaling by Insulin receptor COPI−mediated anterograde transport 22

0 30 60 90 120 Number of Genes

C Low neutral lipid High neutral lipid -1 0 1 Transport to the Golgi and subsequent modification (NES:1.9371), ER to Golgi anterograde sransport (NES:1.8769), COPI−mediated anterograde transport (NES:1.8987) Iron uptake and transport (NES:1.9551) Intra−Golgi traffic (NES:2.0096) Post OxLDL- 48h Chase Signaling by Insulin receptor (NES:2.0418) Ykt6 Rps27a Post AcLDL- 48h Chase Vps45 Pik3r4 24h OxLDL Uso1 Pik3cb 24h AcLDL Trappc4 Pik3c3 Trappc1 Nedd8 Sec31a Hmox1 Ppp6c Cand1 Mgat2 Atp6v1h Mgat1 Atp6v1g1 24h AcLDL Gosr1 Atp6v1f 24h OxLDL 24h AcLDL Post AcLDL− 48H Chase Gene Post OxLDLDynll1− 48H Chase 24h OxLDL Atp6v1e1 Post AcLDL− 48H Chase Gene Dctn2 Post OxLDL− 48H Chase Atp6v1d Copz1 Atp6v1c1 Cog8 Atp6v1b2 Cog7 Atp6v1a Cog6 Atp6v0d1 Cog4 Atp6v0c

Atp6v0b Cog3

Atp6v0a1 Cog2 −2 −10 1 2B4galt1 Log fold change Arcn1

−2 −10 1 Log fold change D

Endocytic trafficking Endoplasmic reticulum cholesterol regulators

Vps16 Soat1 Post OxLDL- 48h Chase Post AcLDL- 48h Chase

Vps11 Plin2 24h OxLDL 24h AcLDL Emc7 Stab1

Emc6 Rab7 24h AcLDL 24h OxLDL 24h AcLDL Post AcLDL− 48H Chase 24h OxLDL

Gene Emc4 Post OxLDL− 48H Chase Post AcLDL− 48H Chase Gene Pik3c3 Post OxLDL− 48H Chase

Emc3

Msr1

Emc2

Fcho2 Emc1

Ap2s1 Acaca

−2 −10 1 2 Log fold change −2 −10 Log fold change

Receptor recycling Autophagy and lipolysis

Nceh1

Rab35 Atg9a

Atg7

Atg14 24h AcLDL 24h OxLDL 24h AcLDL Post AcLDL− 48H Chase Gene Post OxLDL− 48H Chase Arf6 24h OxLDL Post AcLDL− 48H Chase Atg13 Gene Post OxLDL− 48H Chase

Atg101

Abhd5

Acap2 Abca1

−0.5 0.0 0.5 1.0 1.5 2.0 Log fold change

01 Log fold change

Figure 5. Ranked gene lists leading to low neutral lipid content can be mapped to enrichment in biological pathways and gene-sets. A) Pathway tree from Gene Set Enrichment Analysis (GSEA), shows the highly enriched biological pathways and gene-sets within the ranked list of genes from 24-h AcLDL screens within the Reactome database. B) Selected trafficking pathways were highly enriched with high number of genes within the ranked list C) sgRNA disruption of genes of these enriched pathways leads to low neutral lipids. However, some have ambiguous performance in screens. D) Disruption of canonical genes associated with processes of LDL uptake and processing, lipid droplet degradation led to neutral lipid distribution as expected. Negative log-fold change is associated with low-neutral lipid content and positive log-fold change is associated with high-neutral lipid content.

A B

Up Genes from AcLDL−48h screens Enriched Reactome pathways 1e-04 Reactome:R-HSA-68874 M/G1 Transition 1e-04 Reactome:R-HSA-69002 DNA Replication Pre-Initiation 3e-04 Reactome:R-HSA-68949 Orc1 removal from chromatin 1e-04 Reactome:R-HSA-69306 DNA Replication 1e-04 Reactome:R-HSA-69239 Synthesis of DNA Regulation of PTEN gene transcription 16 1e-04 Reactome:R-HSA-69242 S Phase 1e-04 Reactome:R-HSA-69206 G1/S Transition 1e-04 Reactome:R-HSA-453279 Mitotic G1-G1/S phases 1e-04 Reactome:R-HSA-69481 G2/M Checkpoints 1e-04 Reactome:R-HSA-68962 Activation of the pre-replicative complex 1e-04 Reactome:R-HSA-176187 Activation of ATR in response to replication stress 2e-03 Reactome:R-HSA-174417 Telomere C-strand (Lagging Strand) Synthesis Regulates Metabolic Genes 2e-03 Reactome:R-HSA-180786 Extension of Telomeres 16 1e-04 Reactome:R-HSA-69190 DNA strand elongation 2e-03 Reactome:R-HSA-69205 G1/S-Speciﬁc Transcription NES 2.10 2e-03 Reactome:R-HSA-539107 Activation of E2F1 target genes at G1/S 2.05 2e-03 Reactome:R-HSA-5693616 Presynaptic phase of homologous DNA pairing and strand exchange 2.00 9e-04 Reactome:R-HSA-5693579 Homologous DNA Pairing and Strand Exchange 1.95 2e-04 Reactome:R-HSA-72764 Eukaryotic Translation Termination 2e-04 Reactome:R-HSA-1799339 SRP-dependent cotranslational protein targeting to membrane Macroautophagy 26 1e-04 Reactome:R-HSA-2408522 Selenoamino acid metabolism 5e-04 Reactome:R-HSA-72649 Translation initiation complex formation 5e-04 Reactome:R-HSA-72662 Activation of the mRNA upon binding of the cap-binding complex and eIFs, and s 5e-04 Reactome:R-HSA-72702 Ribosomal scanning and start codon recognition 2e-04 Reactome:R-HSA-72695 Formation of the ternary complex, and subsequently, the 43S complex 1e-04 Reactome:R-HSA-1632852 Macroautophagy 1e-04 Reactome:R-HSA-5628897 TP53 Regulates Metabolic Genes 1e-03 Reactome:R-HSA-8943724 Regulation of PTEN gene transcription Activation of ATR in response to replication stress 30 8e-04 Reactome:R-HSA-73856 RNA Polymerase II Transcription Termination 8e-04 Reactome:R-HSA-109688 Cleavage of Growing Transcript in the Termination Region

0 10 20 30 Number of Genes C Regulation of PTEN gene transcription (NES:1.9017) Low neutral lipid High neutral lipid Regulates Metabolic Genes (NES:2.109) Regulation of PTEN gene transcription (NES:1.9017) -1 0 1 Post OxLDL- 48h Chase Macroautophagy (NES:2.0111) Txnrd1 Uvrag Post AcLDL- 48h Chase Tsc2 Tsc2 24h OxLDL Tsc1 Tsc1 24h AcLDL Rragc Sesn1 Rraga Rragc Rptor Rraga Rheb Rptor Pik3r4 Pik3c3 Rheb Mtor Pten Mlst8 Mtor 24h AcLDL 24h AcLDL Lamtor4 24h OxLDL Post AcLDLMlst8− 48H Chase 24h OxLDL Gene Post OxLDL− 48H Chase Post AcLDL− 48H Chase Lamtor3 Gene Lamtor4 Post OxLDL− 48H Chase Lamtor2 Lamtor1 Lamtor3 Dynll1 Lamtor2 Chmp3 Lamtor1 Becn1 Kdm1a Atg9a Hdac3 Atg7 Atg14 Hdac1 Atg13 Cycs Atg101 Bmi1 −10 1 2 3 Log fold change Akt1

−10 1 2 3 Log fold change

Figure 6. Ranked gene lists leading to accumulation of neutral lipid can be mapped to identify enriched biological pathways and gene-sets A) Pathway tree from Gene Set Enrichment Analysis (GSEA), shows the highly enriched biological pathways within the ranked list of genes from post-LDL 48-h chase screens using the Reactome database. B) Selected pathways were enriched with high number of genes within the ranked list. C) sgRNA disruption of genes of these enriched pathways leads to high neutral lipids. Negative log-fold change is associated with low-neutral lipid content and positive log-fold change is associated with high-neutral lipid content.

Discussion

In the present study, we identified and ranked genes contributing to cholesterol metabolism in BMDMs by interrogating the neutral lipid content in gene-disrupted mutants screened at two conditions. To do this, we implemented a series of CRISPR-

Cas9 whole-genome screens followed by comprehensive bioinformatics analysis, targeted gene disruptions and phenotype validations, and gene set enrichment analysis.

From our 24-h LDL screens, we identified and ranked critical genes whose disruption led to low cellular neutral lipid phenotypes (Figure 2). These genes may be regulating cellular processes such as vesicle-mediated LDL trafficking, lysosomal cholesterol processing or lipid droplet biogenesis. Similarly, in our post-LDL-48-h chase screens we identified and ranked genes leading to accumulation of neutral lipids following LDL removal. We validated post-LDL-48h chase screens result by using targeted gene disruptions (Figure 3-4) of a subset of these gene hits with results leading to low or an accumulation of neutral lipid. Our targeted sgRNA gene disruption shows that the ranked lists of genes identified from our screens are critical regulators for cholesterol metabolism. We also compared if there are differences in neutral lipid dynamics in response to AcLDL or OxLDL exposure with our screens, and we observed that there are some genes that only enriched either AcLDL or OxLDL as well as some that were common to both (Figure 2B, Figure 3B). Specifically, in 24h-LDL screens Msr1 was only enriched in AcLDL low neutral lipid population and not in OxLDL however, Stab1, another scavenger receptor was enriched in the low neutral lipid population of both suggesting that some receptors and machinery maybe sensitive to the LDL modification.

Similarly, genes of lysosomal nutrient sensing machinery were enriched in high

fluorescence high neutral lipid populations in all AcLDL and OxLDL screens in 24-h

LDL and post-LDL 48h chase screens suggesting that this machinery is crucial for events of clearing neutral lipid within BMDMs regardless of the LDL source. And, in post-LDL

48h chase screens autophagy machinery associated genes were enriched in the neutral lipid accumulated populations in both AcLDL and OxLDL highlighting autophagy mediated degradation of accumulated lipid droplets and neutral lipids. However, it should be noted that we did not perform replicate screens using OxLDL in this work.

Importantly, we identified novel genes and organelle specific protein complexes.

By GSEA analysis of ranked gene lists we were able to identify highly enriched biological pathways and gene-sets. GSEA revealed the gene-sets highly enriched in 24- h-LDL screens are associated with Golgi trafficking, Golgi to endoplasmic reticulum trafficking and ATP-hydrolysis coupled transport (Figure 5). In the same way, within our post-LDL-48-h chase ranked lists gene sets of the macroautophagy, regulation of PTEN gene transcription, regulates metabolic genes, and activation of ATR in response to stress were highly enriched (Figure 6).

LDL uptake is mediated mainly by receptor-mediated endocytosis and other cellular uptake mechanisms such as macropinocyotosis too contribute to LDL intake to cells. On exposure to LDL there is an increased localization of cholesterol to the plasma membrane, endoplasmic reticulum and, golgi apparatus and the exact regulators or the mechanisms responsible are yet to be uncovered (Maxfield and Tabas 2005). Endocytic vesicles fuse with lysosomes hydrolyzing the LDL to derive free cholesterol. According to our current understanding this process is directed by lysosomal resident NPC-1 and

NPC-2 which then facilitate transport to cellular locations such as the endoplasmic

reticulum and Golgi apparatus. At the endoplasmic reticulum cholesterol is esterified to form neutral lipids and are stored as lipid droplets by the action of ACAT1 (Soat1).

Interestingly, in our screens ACAT1 was only enriched in AcLDL and not in OxLDL which could be due to compensatory action of other proteins facilitating the formation of neutral lipids (Tabas 2002, Neculai, Schwake et al. 2013, Pfisterer, Peränen et al. 2016).

The Golgi apparatus may play a central role in the coordination of events following LDL uptake. The high enrichment of Golgi trafficking and endoplasmic reticulum associated gene-sets (Figure 5B) in low neutral lipid population in 24-h LDL screens suggests the critical association between the Golgi apparatus and the endoplasmic reticulum for the processes of LDL trafficking, processing and lipid droplet biogenesis in

BMDMs. Specifically, our gene-set analysis reveal that genes that are part of the Golgi apparatus conserved oligomeric complex (COG) are highly enriched (Figure 5C). Here,

COG lobe A proteins Cog1, Cog2, Cog4 and lobe B proteins Cog7 and Cog 8 were hits.

Previous work has shown that the conserved COG complex interacts with tethering and fusion complexes in endocytic and secretory pathways (Oka, Vasile et al. 2005, Smith and Lupashin 2008) and the trans-Golgi system is vital in sorting and recycling scavenger receptors during LDL endocytosis and cholesterol trafficking (Mori, Takahashi et al.

1994). Our screen findings suggest a possible role for COG-complex proteins in directing of cholesterol trafficking and signaling events following LDL uptake. Therefore, we hypothesize that the Golgi apparatus could have a role in directing LDL-derived cholesterol to organelles such as the endoplasmic reticulum.

Similarly, our gene-set analysis revealed that the endoplasmic reticulum membrane complex (EMC) proteins are highly enriched in the low neutral lipid

population in 24-h LDL screens (Figure 5D). Disruptions to proteins that are part of the

EMC which are transmembrane domain insertase proteins; Emc1, Emc2, Emc3, Emc4,

Emc6 and Emc7 led to low neutral lipid content in LDL rich conditions. We show that

Emc3sgRNA cells can take up LDL and form neutral lipids but significantly less than the wild-type. This inefficiency could be due to increased neutral lipid accumulation at the endoplasmic reticulum leaflets and disrupted lipid droplet biogenesis due disruption to the EMC. Thus, suggesting an important role for EMC in coordinating the processing of neutral lipids and consequently in the formation of lipid droplets in BMDMs. Previously it has been shown that EMC upregulates Soat1 (ACAT1), cholesterol esterification enzyme , facilitating lipid droplet biogenesis (Pol, Gross et al. 2014, Volkmar, Thezenas et al. 2019). We show that disruption of Soat1 leads to low neutral lipids. However, in targeted knockout experiments, Soat1sgRNA cells were not completely depleted of neutral lipid compared to wild-type but had significantly less suggesting action of multiple acyltransferases in esterification of cholesterol in the endoplasmic reticulum.

Vacuolar-ATPase (V-ATPase) pump machinery components were highly enriched in the low neutral lipid population of the 24-h LDL screens. These machinery components are vital for acidifying endocytic vesicles and promote membrane fusion in endosomal-lysosomal fusion (Kissing, Hermsen et al. 2015). We hypothesized that loss of function in these components prevents efficient degradation of LDL thus leading to overall lower uptake of LDL. Specifically, the disruption to the V0, the luminal subunit components were overall enriched in low neutral lipid populations. However, the V1 subunit, which are the cytoplasmic subunit components were enriched in the high neutral lipid population of post-LDL-48h chase screens. Previous studies have shown that the V-

ATPase is also vital for nutrient sensing as well as cholesterol sensing (Castellano,

Thelen et al. 2017) we hypothesize that V-.ATPase is vital for sensing lipid droplets and signaling for their subsequent degradation.

In reverse cholesterol transport, lipid droplets can be degraded by autophagy

(Dong and Czaja 2011) and/or lipolysis (Ducharme and Bickel 2008) to derive cholesterol which can be used for cellular needs of be effluxed to high-density lipoproteins mediated by plasma membrane bound ATP-dependent binding cassette proteins (Oram 2003). We show that targeted disruption of the autophagy-related gene,

Atg9a leads to accumulation of neutral lipid after chase (Figure 4). Similarly, we show that disruption of Tgfbr (TGF-b receptor) leads to high neutral lipid accumulation after chase (Figure 4) suggesting that TGF-b signaling somehow regulating lipid droplet degradation or cholesterol efflux. Previous studies have shown that TGF-b signaling leads to increased autophagy by upregulation of Atg5, Atg7, and Becn1 (Kiyono, Suzuki et al. 2009).

Our results show that disruption of Keap1 (Kelch Like ECH Associated Protein1) or Cul3 (Culin3), scaffold protein, which are part of the Keap1-Cul3 E3 ubiquitin ligase that polyubiquitinates Nrf2 for proteasomal degradation (Canning and Alex 2014) leads to higher neutral lipids accumulation. Additionally, disruption of Nrf2 led to low neutral lipid content. Nrf2, which is a transcription factor, plays a crucial role in macrophage response to OxLDL and to oxidative stress (Sussan, Jun et al. 2008, Mimura and Itoh

2015), suggesting a potential role for oxidative response in mediating lipid droplet degradation.

We show that disruption of nutrient sensing machinery components and their regulators such as RagA, RagC, Flcn, Tsc1, Tsc2, Atp6v1a, Lamtor1, Lamtor2, Lamtor3, and Lamtor4 leads to high neutral lipid content. Previous work has shown that nutrient sensing machinery is also vital for cholesterol sensing (Castellano, Thelen et al. 2017), but it is unclear how lysosomal sensing of cholesterol content impacts lipid droplet biology.

In conclusion, in this study we present ranked lists of critical genes leading to high or low neutral lipid content in macrophages. Using targeted sgRNA knockouts we further confirm and validate the findings from our CRISPR-Cas9 whole-genome screens by recapitulating the screen low- and high-neutral lipid phenotypes. This work contributes to improved understanding of the biological process involved in neutral lipid metabolism as well as aids in identifying potential drug targets against cardiovascular disease. Further, we confirm previously described genes associated with processes of

LDL uptake and trafficking, including genes associated with cholesterol processing and autophagy. Similarly, we present novel proteins such as Emc3 and Atg9a as critical for efficient neutral lipid metabolism in BMDMs.

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Chapter III

Conclusions

Golgi apparatus conserved oligomeric complex and endoplasmic reticulum membrane protein complex are critical for LDL processing as revealed by CRISPR-

Cas9 whole genome screens

Low-density lipoprotein (LDL) endocytosis elevates cellular cholesterol increasing localization to the plasma membrane and cholesterol esterification by endoplasmic reticulum to be sequestered as lipid droplets (Moore and Tabas 2011). The critical genes involved in trafficking LDL-cholesterol from lysosomes to other cellular destinations such as Golgi-apparatus and endoplasmic reticulum are unclear. Currently, there is evidence supporting a path for cholesterol from lysosomal compartments directly to the plasma membrane and after saturation cholesterol is redirected to the endoplasmic reticulum for sequestration as lipid droplets (Neculai, Schwake et al. 2013, Das, Brown et al. 2014). Similarly, there is evidence for cholesterol saturation in the Golgi apparatus and trafficking to plasma membrane or endoplasmic reticulum (Blanchoin, Boujemaa-

Paterski et al. 2014).

The Golgi apparatus is vital for possible scavenger receptor recycling and vesicle-mediated cholesterol trafficking to endoplasmic reticulum (Mori, Takahashi et al.

1994, Urano, Watanabe et al. 2008). In our 24-h LDL populations the Golgi apparatus conserved oligomeric complex (COG) lobe A proteins Cog1, Cog2, Cog3, Cog4, and lobe B proteins Cog7, Cog8, as well as Nrbp1, Exoc1, Mon2, and Uvrag had low neutral lipid content. Suggesting that the Golgi apparatus may have a central role in cholesterol

processing in BMDMs and disruption of any of the above genes leads to inefficient cholesterol metabolism. Further, hypertrophy of the Golgi apparatus upon exposure to

OxLDL has been shown in pigeon macrophages and THP-1 cells (Jerome, Cash et al.

1998).

Similarly, cholesterol resulting from LDL exposure is esterified in the endoplasmic reticulum to prevent toxicity. Here, the endoplasmic reticulum membrane protein complex (EMC) upregulates ACAT-1 (Soat1) acyltransferase (Pol, Gross et al.

2014, Volkmar, Thezenas et al. 2019). In our 24-h-LDL populations EMC components

Emc1, Emc2, Emc3, Emc4, Emc6, and Emc7 led to low neutral lipid. And, we show with targeted sgRNA knockout of Emc3 leads to less neutral lipid content and less lipid droplets. Thus, this work supports the current understanding that lipid droplet formation in BMDMs in the endoplasmic reticulum is coordinated by EMC complex regulation of cholesteryl ester formation via Soat1. In (Volkmar, Thezenas et al. 2019) work with

Emc6 mutants, it was seen that siRNA and sgRNA knockouts lead to a significant decrease in cholesteryl ester levels compared to wild-type. Also, in alveolar type-II cells, it has been shown that Emc3 mutants have downregulated Soat1 (Tang, Snowball et al.).

A Low fluorescence neutral lipid in sgRNA gene-disruption

Plasma membrane cholesterol

ER cholesterol LD esterification and lipid formation LDL droplet biogenesis

Emc1 Emc4 Golgi-mediated Nrbp1 Emc2 Emc6 sorting and receptor Emc3 Emc7 recycling Cog 1 Cog 4 Exoc1 Uvrag Cog 2 Cog 6 Ykt6 Rbsn Cog 3 Cog 7 Cog 8

B Low neutral lipid High neutral lipid -1 0 1 Endoplasmic reticulum membrane complex Golgi−conserved oligomeric complex

Ykt6 Emc7

Uvrag

Rbsn Emc6

Nrbp1

Exoc1 Emc4

24h AcLDL Cog8 24h AcLDL 24h OxLDL 24h OxLDL Post AcLDL− 48H Chase Post AcLDL− 48H Chase Gene Post OxLDL− 48H Chase Gene Cog7 Post OxLDL− 48H Chase Emc3

Cog6

Cog4 Emc2

Cog3

Cog2 Emc1

Cog1

−2.0 −1.5 −1.0 −0.5 0.0 −2.0 −1.5 −1.0 −0.5 0.0 0.5 value value Figure 1. Model for critical role of conserved-oligomeric complex of Golgi and endoplasmic reticulum membrane complex in LDL derived cholesterol regulation, A) Proposed trafficking route of LDL to be subsequently packaged as a lipid droplet , B) disruptions to conserved-oligomeric complex proteins and the endoplasmic reticulum membrane complex as indicated led to low neutral lipid content in 24-h-LDL screens

Model for low-density lipoprotein uptake, lipid droplet formation and degradation, and cholesterol metabolism in BMDMs

Whole genome CRISPR-Cas9 screens were able to identify critical genes associated with LDL uptake and trafficking, lipid droplet formation and degradation, and cholesterol metabolism. We show that targeted sgRNA disruption of identified hits lead to lower or higher neutral lipid content in BMDMs. Scavenger receptor-bound LDL are endocytosed in clathrin-coated vesicles. These vesicles are degraded by fusion with lysosomes to derive cholesterol. Cholesterol is then trafficked to the plasma membrane or to the endoplasmic reticulum for esterification to be sequestered as lipid droplets. This process can be reversed to derive cholesterol by degradation of lipid droplets. We show that there is a requirement for the coordinated activity of multiple pathways and their associated regulators for efficient cholesterol metabolism in BMDMs.

Low fluorescence neutral lipid in sgRNA gene-disruption High fluorescence neutral lipid in sgRNA gene-disruption LDL Receptor biding Msr1, Stab1

Clathrin

Endocytosis Ap2s1 ,Fcho2 Lysosomal degradation Atp6v0b Atp6v1a Atp6v0c Atp6v1b2 Atp6v0e Atp6v1e1 Atp6v1f Atp6v1h Rab7 Acap2, Arf6 Rabggta,Rabggtb VPS11 Cholesterol trafficking

Golgi Cog 1 Cog 7 Cog 2 Cog 8 Post Golgi vesicle ER Cog 4 Uvrag trafficking Arcn1 Nucleus

Autophagy related Nrbp1 proteins Ykt6 Emc1 Soat1 Emc3 Acaca Abca1 RagA Atp6v1a Emc6 RagC Lamtor1-4 Cholesterol Atg9a Cul3 Lipid Cholesteryl ester Efflux Flcn Atg13 Keap1 droplets conversion Hdac3 Atg14 Nrf2 LD Degradation

Figure 2. CRISPR-Cas9 whole-genome screens identify critical genes for neutral lipid metabolism in BMDMs exposed to modified LDL. sgRNA disruption of the genes shown led to low or high neutral lipid content in BMDMs indicating their critical role in LDL-endocytosis, vesicular cholesterol trafficking, cholesterol processing to generated lipid droplets, or degradation of lipid droplets.

In conclusion, this work provides a comprehensive ranked list of critical genes for understanding the vital genes and biological pathways associated with the processes of

LDL uptake, cholesterol trafficking, lipid droplet formation and degradation, and cholesterol efflux. This work can aid scientist in generating hypothesis for comprehensive studies focused on mechanistic understanding of the undelying biology as well as in identifying new therapeutic targets for treating diseases such as atherosclerosis and other cardio vascular diseases.

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Supplement A I II

B I II

Supplement-Figure-1 FastQC quality control of NGS reads, A) 75 base pair long region containing adaptor sequences and sgRNA insert was sequenced in all samples (A-I) (statistics of one such fastq file is shown) with highly accurate >99.9% base calling (A-II) (indicated by high Phred score) B) Sequences were trimmed to get 20 base pair sgRNA inserts using Cutadapt (B-I) and the sgRNA insert base calling was highly accurate as indicated by high Phred score (B-II). All fastq files from next generation sequencing was assessed using FastQC prior to and after trimming using Cutadapt and was consistently of high base calling quality.

24H AcLDL Screen 1

A B C

E F D

24H AcLDL Screen 2

A B C

E F D

24H OxLDL Screen

A B C

F D E

Supplement-Figure-2 MAGeCK-VISPR quality control of NGS reads, A) High percentage of sequencing reads from NGS FASTQ files were mapped to the Brie library in all screens. B) MAGeCK normalizes read counts before RRA analysis and read counts were uniform across screens, C) Missed gRNAs are indicative of sgRNAs found in the library but not the samples D) Gini index score is indicative of evenness of reads in the group, E) Cumulative distribution for sample reads, F) Correlation matrix for sample

Post-AcLDL-48H- Chase screen-1 A B C

D E F

Post-AcLDL-48H- Chase screen-2 A B C

D E F

Post-OxLDL-48H- Chase A B C

D E F

Supplement-Figure-3 MAGeCK-VISPR quality control of NGS reads, A) High percentage of sequencing reads from NGS FASTQ files were mapped to the Brie library in all screens. B) MAGeCK normalizes read counts before RRA analysis and read counts were uniform across screens, C) Missed gRNAs are indicative of sgRNAs found in the library but not the samples D) Gini index score is indicative of evenness of reads in the group, E) Cumulative distribution for sample reads, F) Correlation matrix for sample