High-Throughput Lipidomic and Transcriptomic Analysis To Compare

Dec 19, 2016 - High-Throughput Lipidomic and Transcriptomic Analysis To Compare SP2/0, CHO, and HEK-293 Mammalian Cell Lines ... Phone: +1-4104469801...
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High-troughput Lipidomic and Transcriptomic Analysis to Compare SP2/0, CHO, and HEK-293 Mammalian Cell Lines Yue Zhang, Deniz Baycin Hizal, Amit Kumar, Joseph Priola, Michelle Bahri, Kelley M. Heffner, Miao Wang, Xianlin Han, Michael A. Bowen, and Michael J. Betenbaugh Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b02984 • Publication Date (Web): 19 Dec 2016 Downloaded from http://pubs.acs.org on December 20, 2016

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High-throughput Lipidomic and Transcriptomic Analysis to Compare SP2/0, CHO, and HEK-293 Mammalian Cell Lines Yue Zhang†, Deniz Baycin-Hizal‡, Amit Kumar†, Joseph Priola†, Michelle Bahri†, Kelley M. Heffner†, Miao Wang§, Xianlin Han§, Michael A. Bowen‡, Michael J. Betenbaugh*,† †

Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.



Antibody Discovery and Protein Engineering, MedImmune LLC, Gaithersburg, MD, 20878, USA.

§

Center for Metabolic Origins of Disease, Sanford Burnham Prebys Medical Discovery Institute, Orlando, FL, 32827, USA.

ABSTRACT: A combined lipidomics and transcriptomics analysis was performed on mouse myeloma SP2/0, Chinese Hamster Ovary (CHO) and Human Embryonic Kidney (HEK) cells in order to compare widely used mammalian expression systems. Initial thin layer chromatography (TLC) analysis indicated phosphatidylethanolamine (PE) and phosphatidylcholine (PC) were the major lipid components with lower amounts of sphingomyelin (SM) in SP2/0 compared to CHO and HEK, which was subsequently confirmed and expounded upon following mass spectrometry (MS) analysis. However, HEK contained 4-10 fold higher amounts of lyso phosphatidylethanolamine (LPE) and 2-4 fold higher amounts of lyso phosphatidylcholine (LPC) compared to SP2/0 and CHO cell lines. C18:1 of LPE followed by C16:1 (along with C16:0 for LPC) were the main contributors to the difference in LPE levels. Alternatively, the SP2/0 cell line exhibited 30-65 fold lower amounts of SM. By mapping the transcriptomics data to KEGG pathways, we found expression levels of secretory phospholipase A2 (sPLA2), lysophospholipid acyltransferase (LPEAT), lysophosphatidylcholine acyltransferase (LPCAT), and lysophospholipase (LYPLA) can contribute to the differences in LPE and LPC. Sphingomyelin synthases (SMS) and sphingomyelin phosphodiesterase (SMase) enzymes play roles in SM differences across the three cell lines. The results of this study provide insights that will aid the understanding of the physiological and secretory differences across recombinant protein production systems.

1. INTRODUCTION Monoclonal and bispecific antibodies are widely used as biotherapeutics for a variety of medical conditions, and may be needed in large quantities over long periods of time.1 Mammalian cells, such as mouse myeloma SP2/0, Chinese Hamster Ovary (CHO) and Human Embryonic Kidney (HEK), are the preferred cell types for biologics drug production.2 However, the production yields and efficiency remain a challenge for biopharmaceutical manufacturing.3 It is therefore valuable to explore the physiological pathways of these cells for future exploitation and enhancement. Acquisition and analysis of ‘omics (genomics, transcriptomics, proteomics) data can provide insights into understanding the mammalian expression systems which can aid in understanding physiological limitations for protein production. Lipidomics, for example, is the characterization and quantification of the variety of lipids found in a given sample4 and represents an emerging ’omics technology that could help users understand the intricacies of mammalian expression. To our knowledge, no large-scale comparative lipidomics analysis has yet been conducted on mainstay production cell lines. For this reason, lipidomics could represent another valuable component of ’omics technologies used to interpret cell physiology and decipher the differences in lipid-associated pathways of important cell lines. Lipids are potentially important regulators of protein production and secretion because of their involvement in energy metabolism, vesicular transport, membrane structure, dynam-

ics, and signaling.5 Lipids are typically classified as polar lipids (such as phospholipids, sphingolipids, etc.) and non-polar lipids (such as sterols, glycerolipids, free fatty acids, sterol esters, etc.). Glycerophospholipids (PLs) are important structural and functional components of biological membranes, including phosphatidylethanolamine (PE), phosphatidylcholine (PC), phosphatidylinositol (PI), phosphatidylserine (PS), phosphatidylglycerol (PG), and phosphatidic acid (PA). PLs are first formed by the de novo pathway (Kennedy pathway) using saturated and monounsaturated fatty acyl-CoAs as donors. Subsequently, the fatty acyl composition at the sn-2 position is altered for the production of polyunsaturated fatty acids (PUFA)-containing PLs in the remodeling pathway (Lands’ cycle) through the coordinated actions of phospholipase A2 (PLA2) and lysophospholipid acyltransferases (LPLATs). Cycles of deacylation and reacylation of PLs modify the fatty acid composition to generate the mature membrane with asymmetry and diversity, which is important for membrane fluidity and curvature.6 Lateral mobility (fluidity) and membrane bending (curvature) properties provide membrane flexibility to form vesicles without losing membrane integrity.7 The most common phospholipids are PC (found primarily on the outer monolayer of the membrane) and PE (found primarily on the inner monolayer of the membrane); both play a major role in membrane architecture. Furthermore, PLs have regulatory roles in cell signaling. For instance, PLs’ effect on the fluidity determines the placement of the proteins in the membrane which in turn can change protein interactions as well as signal

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transduction cascades.8 The dual function of PLs shows that their homeostasis is crucial to secretion, a critical step in protein production. These PLs are also the metabolic precursors of lysophospholipids (LPLs), such as lyso phosphatidylethanolamine (LPE) and lyso phosphatidylcholine (LPC), which result from partial hydrolysis of PLs as part of the Lands’ cycle. Sphingolipids constitute another class of structural lipids.5, 9 Sphingomyelin (SM), in addition to functioning as a structural component in biological membranes, preferentially interacts with cholesterol to form specialized membrane microdomains or “lipid rafts”.10 Ceramide has been implicated in numerous cell functions including growth, differentiation, signal transduction, proliferation, and apoptosis.11 The formation of ceramide-enriched rafts alters membrane curvature and decreases plasma membrane integrity.12 In this study, we applied lipidomics as a useful ’omics method for detailed analysis of SP2/0, CHO, and HEK expression cell lines during both exponential and stationary growth phases. We applied multiple lipid profiling techniques, including thin layer chromatography (TLC) and mass spectrometry (MS), for the characterization of key lipid metabolites and pathways. For detection of a large number of complex lipids, two-dimensional high performance thin layer chromatography (2-D HPTLC), which can separate polar lipids into different categories, was applied to increase lipid separation and resolution compared to 1D-HPTLC. Next, MS-based lipidomic analysis, which has high sensitivity and quantification, was implemented to obtain more detailed profiles on the individual lipids and different classes. Integration of lipid profiling with data from HPTLC and MS revealed that there were major differences in the lipid content across the three cell lines. By analyzing the enzymes and their related genes involved in specific lipid metabolism pathways at the transcriptome level, we were able to explain mechanistically why lipid profiles across three cell lines were different. Taken together, coupling highthroughput TLC and MS lipidomics with transcriptomics provided an improved understanding of the differences across SP2/0, CHO, and HEK cell lines that can be used to understand physiological differences across key mammalian protein production hosts and potentially guide medium formulation and metabolic cell engineering efforts in order to optimize these cells for improved production of valuable biotherapeutic drugs. 2. MATERIALS AND METHODS 2.1 Materials Mouse myeloma SP2/0 cell line was purchased from Sigma Aldrich (St. Louis, MO) and HEK-293F cell line was obtained from Life Technologies (Carlsbad, CA). CHO (in house manufacturing CHO) cell line was obtained from MedImunne, LLC. FreeStyle Expression Medium and CD CHO Medium were purchased from Thermo Fisher Scientific (Carlsbad, CA). EXCELL SP2/0 Serum-Free Medium, phosphate buffered saline (PBS) solution, 2,7-dichlorofluorescein, and HPLC grade solvents including hexane, ethanol, and water (H2O) were purchased from Sigma-Aldrich (St. Louis, MO). HPLC grade solvents including chloroform (CHCl3) and methanol (MeOH) were bought from Fisher Scientific. Acetic acid glacial (HPLC grade) was purchased from EMD. Ether (99+%, anhydrous, A.C.S. reagent) was obtained from Aldrich. HPTLC Glass Plates (Si 60 F254) was supplied by EMD Millipore (Darmstadt, Germany), USA. The BCA protein assay kit was bought from Thermo Scientific Pierce (Rockford, IL).

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2.2 Cell culture SP2/0, CHO and HEK-293F cells were cultured in 1L shake flasks (VWR International, Radnor, PA) in EX-CELL SP2/0 Serum-Free Medium, CD CHO Medium, and FreeStyle Expression Medium, respectively, under batch conditions. The flasks were shaken at 120 rpm on an orbital shaker in an incubator at 37oC and 5% CO2. Cells were seeded (day 0) at a density of 500,000 cells/mL, and harvested on day 3 (exponential phase) and day 4 (stationary phase) for harvesting of cell pellets for subsequent lipidomic profiling. Cell densities were determined using ViCell (Beckman Coulter, Indianapolis, IN). Cells were pelleted at 200 rcf, and then washed with ice-cold PBS solution three times and flash frozen on dry ice until lipid extraction was performed. 2.3 Lipid extraction and protein assay Lipids were extracted by a modified Bligh-Dyer method.13 200 million cells were homogenized in 4 ml H2O and then transferred to a 50 ml centrifuge tube. A 15 ml mixture of CHCl3-MeOH (1:2, v/v) was added on the samples and vortexed for 10 min before mixing with 5 ml CHCl3 for 1 min and 5 ml H2O for another minute. After centrifugation at 7000 rpm for 10 min, the bottom layer (lipids) was collected and then evaporated under a nitrogen stream until completely dry. The lipid extracts were weighed and re-dissolved in CHCl3 for arranging the concentration to 20 mg/mL. In the mean time, 10 million cells were used for BCA protein assay kit.; this was carried out in a 96-well microplate following the manufacturer’s protocol. 2.4 High performance thin layer chromatograph (HPTLC) method for lipid profiling Two-dimensional (2-D) HPTLC, implemented to increase the resolution compared to 1D-HPTLC, was applied to separate polar lipids into different categories. The silica HPTLC plate was activated with a CHCl3-MeOH (75: 25) solvent system and then completely dried. Lipid samples were loaded on the activated HPTLC plate with the same protein content. The samples were separated with a CHCl3-MeOH-H2O (71:25:2.5, v/v/v) solvent system and then rotated 90° and developed on a second dimension separation with a CHCl3-MeOH-Acetic acid-H2O (76:9:12:2, v/v/v/v) solvent system.14 Another method based on 1-D HPTLC was implemented using hexanediethyl ether-acetic acid (80:20:1.5, v/v/v) for non-polar lipids separation.15 The lipid bands were visualized under the UV lamp with a 0.2% ethanol solution of 2,7-dichlorofluorescein dye.16 Multiple lipid standards were also run to correctly identify the lipid spots. 2.5 Mass spectrometry (MS) method for lipid profiling A mass spectrometry-based lipid profiling method was applied to SP2/0 (exponential and stationary phases), CHO (exponential phase and stationary phases), and HEK-293 (exponential and stationary phases) cells. The cells were suspended in 300 μL of 10 times diluted PBS in an Eppendorf tube and were homogenized for 1 min by using a disposable soft tissue homogenizer. An aliquot of 25 μL was pipetted to determine the protein content (BCA protein assay kit, Thermo Scientific, Rockford, IL). The remainder of the homogenate was carefully transferred into a disposable glass culture test

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Figure 1. The schematic workflow of lipidomics and transcriptomics studies on SP2/0, CHO, and HEK-293 cell lines. tube, and a mixture of lipid internal standards was added prior to lipid extraction for quantification of all reported lipid species.

Lipid extraction was performed by using a modified Bligh and Dyer procedure as described previously. Each lipid extract was resuspended into a volume of 500 μL of chloroform/methanol (1:1, v/v) per mg of protein and flushed with nitrogen, capped, and stored at −20 °C for lipid analysis. For ESI direct infusion analysis, lipid extract was further diluted to a final concentration of ~500 fmol/µL, and the mass spectrometric analysis was performed on a QqQ mass spectrometer (Thermo TSQ VANTAGE, San Jose, CA) equipped with an automated nanospray device (TriVersa NanoMate, Advion Bioscience Ltd., Ithaca, NY) in three different modes: negative-ion ESI of lipid extracts, negative-ion ESI of lipid extracts in the presence of lithium hydroxide, and positive-ion ESI of lipid extracts in the presence of lithium hydroxide.17,18 Data processing of MS analyses was conducted by selfprogrammed Microsoft Excel macros.17 2.6 Lipid pathway analysis The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used for the analysis of lipid pathways. Illumina HighSeq was used for SP2/0 and CHO transcriptomics data, whereas HEK-293F transcriptome data was downloaded from (Marc Sultan, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM300 493). Glycerophospholipid and sphingolipid pathways were downloaded from the KEGG database and proteins in this pathway were mapped and colored using the Search & Color Pathway tool (http://www.genome.jp/kegg/tool/map_pathway2.html). Genes in these pathways were colored according to their absence or presence in the genome or transcriptome. 3. RESULTS The schematic workflow of lipidomics and transcriptomics studies on SP2/0, CHO, and HEK cell lines is illustrated in Fig. 1. Briefly, we first used a modified Bligh-Dyer method for extraction of the lipid contents from all three cell lines in both exponential and stationary phases. Next, the lipid samples were subjected to HPTLC and MS analysis for lipid profiling studies. In concert, transcriptomics data for SP2/0, CHO and

Figure 2. HPTLC analysis of lipids across SP2/0, CHO, and HEK cell lines.A. Representative fluorescence images of 2D-HPTLCresolved polar lipid spots from SP2/0 (left), CHO (middle), and HEK (right) in both exponential phase (Exp) and stationary phase (Stat) and standards (left bottom). The weight ratio of PE, PC, PS, PI, PG, PA, SM in standards is 1:1:1:1:1:1:1. B. Representative fluorescence images of neutral lipid spots of triglyceride, free fatty acid, cholesterol separated by 1D-HPTLC from SP2/0, CHO, and HEK cell lines in both Exp and Stat phases. The neutral lipid standards are shown on the right.

HEK cell lines were obtained from Illumina HighSeq and Gene Expression Omnibus for mapping to the lipid metabolic pathway using the KEGG database. By integrating the lipid profiling data from HPTLC and MS with transcriptomics data at the systems biology level, we elucidated differences in the lipid pathways of the three mammalian production cell lines and the enzymes and their related genes, which might provide an explanation for the differences in specific lipid profiles across the three cell lines. 3.1 HPTLC method for lipid profiling of SP2/0, CHO, and HEK cell lines An HPTLC method was implemented in this study to increase the resolution in lipid profiling of SP2/0, CHO, and HEK cell lines As shown in Fig 2, polar lipids (Fig. 2A) and non-polar (Fig. 2B) lipids were separated by 2-D HPTLC and 1-D HPTLC, respectively. The lipid interactions with mobile and stationary phases during the TLC run enabled lipids to be separated depending on their head groups. The lipid bands were visualized under UV light with a green fluorescing 2,7dichlorofluorescein dye. The brightness of each spot in Fig. 2 reflects the relative amount of each lipid category. Standards with known lipid moieties were pre-mixed and run on the HPTLC plates under identical conditions to correlate the relative position of the lipid spot with each lipid category. As demonstrated in Fig. 2A, we observed that PC and PE were the major lipid components, and the contents of PI, PS, PG, PA, and SM were lower in content relative to PC or PE in each cell line for both exponential or stationary phases. Additionally, by comparing the lipid content across the three cell lines, SM was observed to be lower in SP2/0 cell line compared to CHO or HEK cell lines. The differences between exponential and stationary phases of the cell lines were indistinguishable. The neutral lipid comparison shown in Fig.

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Figure 3. Principal component analysis (PCA) analysis of lipids across SP2/0, CHO, and HEK cell lines in both exponential (E) and stationary (S) phases. Clustering indicates that each cell lines exhibited distinct lipid profiles.

2B indicated higher levels of free fatty acid and lower levels of cholesterol in SP2/0 compared to CHO and HEK cell lines. Differences in the content of triglyceride were not significant across the cell lines. For further investigation of the lipid subgroups, MS analysis was subsequently performed on the lipid extracts of the three cell lines in this study. 3.2 Comparative lipidomics of SP2/0, CHO, and HEK cell lines by MS A variety of single lipid moieties from the exponential and stationary phases of SP2/0, CHO, and HEK cell lines were quantified by the Multi-dimensional mass spectrometry-based shotgun lipidomics (MDMS-SL) platform.17, 18 The output of a principal component analysis (PCA) of MS profiling data from all three cell lines is shown in Fig. 3. Each sphere corresponds to a replicate dataset for a particular cell line. The overall lipid profiles are distinguishable from cell line to cell line (e.g. SP2/0 versus CHO versus HEK) but similar for each particular cell line in a specific growth phase. The composition and amounts of each lipid were obtained by MS analysis on lipid extracts of SP2/0, CHO and HEK cells. As shown in Fig. 4, Fig. S1 and detailed in Appendix S2, PE and PC were found to be present at higher levels than other lipids in all three cell lines, consistent with the 2D-HPTLC results. Specifically, PE and PC ranged between 44-67 nmol/mg protein and 38-57 nmol/mg protein across the three cell lines, respectively, whereas other lipid amounts were less than 20 nmol/mg protein. The MS analysis allowed us to identify lipid classes with significant changes between the three cell lines. Lipids including lyso phosphatidylethanolamine (LPE), lyso phosphatidylcholine (LPC), and sphingomyelin (SM) which varied across cell lines are shown in Fig. 4, whereas, Fig. S1 shows the lipids with comparable amounts in all three cell lines. Quantitative MS data indicated that CHO and SP2/0 cell lines contained relatively lower levels of LPE and LPC compared to that of the HEK cell line as shown in Fig. 4. HEK had 10-15 nmol/mg protein of LPE, whereas CHO and SP2/0 cell lines contained approximately 1.5-2.5 nmol/mg protein of LPE. For LPC, the amount in HEK was 4.2-6.2 nmol/mg protein, but this number decreased to 1.4-2.4 nmol/mg protein in CHO and SP2/0 cell lines. Overall, HEK contained 4-10 fold higher levels of LPE and 2-4 fold higher levels of LPC compared to SP2/0 or CHO cell lines. The pvalues in Fig. 4 indicate that there are

Figure 4. MS spectra (left) and the plot of lipid amount (right) at the level of nmol/mg protein of lyso phosphatidylethanolamine (LPE)(top), lyso phosphatidylcholine (LPC)(middle) and sphingomyelin (SM)(bottom) from SP2/0, CHO, and HEK cell lines in both Exp and Stat phases. Statistically significant difference: * P < 0.05, ** P < 0.005.

statistically significant differences in LPE and LPC content between SP2/0 and HEK and CHO and HEK during the exponential phase. We did not observe any significant difference in LPE and LPC content between SP2/0 and CHO cell lines. In order to further examine if specific LPE or LPC molecules are responsible for this difference, we performed a more detailed MS analysis on the LPE and LPC components as shown in Fig. 5. This analysis revealed that C18:1 of LPE followed by C16:1 were two of the main contributors to the difference in LPE levels between HEK and the other two cell lines. These same monounsaturated lipids along with C16:0 were the main contributors to the increase in LPC in HEK. In addition to the changes in LPE and LPC, we also detected a significant reduction of SM in SP2/0 compared CHO and HEK cell lines, which is in line with the HPTLC results in Fig. 4. SP2/0 had approximately 0.2-0.3 nmol/mg protein of SM, but this number increased by 30-65 fold in CHO and HEK cell lines, reaching between 8-12 nmol/mg protein. The p-values indicate that there is a statistically significant difference in SM content between SP2/0 and the other two cell lines in both exponential and stationary phases. There was no significant difference in SM content between HEK and CHO cell lines. The minimal levels of SM with a chemical composition of C16:0, the most abundant sphingolipid in the other mammalian cells, is minimal in SP2/0 and is the principal cause for the dramatic difference in SM content between this cell line and the other two cell lines as shown in Fig. 5. 3.3 Metabolic pathway analysis of LPE, LPC, and SM

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Figure 5. Detailed quantitative MS analysis and comparison on LPE, LPC and SM components across SP2/0, CHO, and HEK cell lines in both Exp and Stat phases. “P”, “A” and “N” represent plasmenyl, plasmanyl and carboxamide, respectively.

To help explain the biochemical differences observed between cell lines, metabolic pathways, the genes of components of the pathways, and finally transcriptomics were examined in more detail. The LPE and LPC metabolism pathways of SP2/0, CHO, and HEK cell lines, obtained from murine, Chinese Hamster and human genomes, respectively, were observed as shown in Figure 6A, B. Two enzymes involved in LPE synthesis are secretory phopholipase A2 (sPLA2) and HRAS-like suppressor 3. The enzymes catalyze the hydrolysis of PE into two isomers of LPE.20,23,24 Two of the three enzymes involved in LPE degradation, lysophospholipid acyltransferase (LPEAT) and acyl-[acyl-carrier-protein]phospholipid O-acyltransferase, catalyze the esterification of LPE to PE23 and a third enzyme, lysophospholipase I/II (LYPLA I/II), catalyzes the conversion of LPE to sn-glycerol3-phosphoethanolamine. Three enzymes involved in LPC synthesis, lecithin-cholesterol acyltransferase, sPLA2, and HRASlike suppressor 3, are responsible for hydrolysis of PC into two isomers of LPC.9,20,23,24 Enzymes involved in LPC degradation are lysophosphatidylcholine acyltransferase (LPCAT) and 2-acylglycerophosphocholine O-acyltransferase; both catalyze the transformation of LPC back to PC.9,23 A third enzyme, LYPLA I/II, is responsible for the conversion of LPC to sn-glycerol-3-phosphocholine. The LPE and LPC metabolic pathways of SP2/0, CHO, and HEK cell lines are colored according to the presence or absence of each enzyme in the genome and transcriptome data. As shown in these pathways, SP2/0, CHO, and HEK cell lines do not have the genes for the

acyl-[acyl-carrier-protein]-phospholipid O-acyltransferase or 2-acylglycerophosphocholine O-acyltransferase enzymes. Aside from these two enzymes, the SP2/0 cell line exhibited mRNA expression for all other enzymes in LPE and LPC synthesis and degradation pathways. In the CHO cell line, in addition to the two missing enzymes mentioned above, the expression of LPE and LPC synthesis enzyme [HRAS-like suppressor 3] and degradation enzyme [LYPLA II] were not detected in the transcriptomics data. In HEK, the mRNA levels of the enzymes in LPE and LPC synthesis [HRAS-like suppressor 3] was also not observed. Thus, alternative synthesis and inhibition pathways for LPE and LPC exist in CHO and HEK cell lines compared to the SP2/0 cell line. We also examined mean mRNA expression and FPKM (fragments per kilobase of transcript per million mapped reads) values for each enzyme involved in LPE and LPC pathways across the three cell lines to determine which enzymes and their related genes may be responsible for the differences in LPE and LPC levels between cell lines (Table S3). HEK had more isoforms of expressed sPLA2 for LPE and LPC synthesis and lower expression of the genes involved in LPE and LPC degradation (LPEAT, LPCAT and LYPLA I/II) compared to SP2/0 and CHO cell lines as shown in Table S3. This difference may contribute to the higher LPE and LPC levels observed in HEK cells. The sphingolipid metabolic pathways of SP2/0, CHO, and HEK cell lines, including SM synthesis and degradation pathways, are presented in Figure 6C. Two of the three enzymes involved directly in SM synthesis are ceramide cholinephosphotransferase and sphingomyelin synthase (SMS), which convert ceramide to SM while the sphingosine Nacyltransferase catalyzes SM synthesis from sphingosylphosphocholine. The SM degradation pathway includes sphingomyelin phosphodiesterase (SMase), which catalyzes the hydrolysis of SM back to ceramide while phophodiesterase D catalyzes the conversion of SM to ceramide-P. The transcriptomics data of SP2/0, CHO, and HEK cell lines was mapped to the SM metabolic pathway using the KEGG database. SP2/0, CHO, and HEK cell lines do not express detectable ceramide cholinephosphotransferase or sphingomyelin phophodiesterase D at the mRNA level. Aside from these two enzymes, CHO and HEK cell lines expressed all enzymes for SM synthesis and degradation whereas the SP2/0 cell line did not express the SM synthesis enzyme sphingomyelin synthase (SMS) as detected at the mRNA level. The absence of detected SM synthase expression in SP2/0 most likely accounts for the low levels observed in this cell line. In addition, multiple isoforms of SMase for SM degradation expressed in SP2/0, as shown in Table S4, could also contribute to the low levels of SM as compared to CHO and HEK cell lines. 4. DISCUSSION The lipid compositions and differences across multiple commercially important mammalian cell lines were investigated since lipids serve multiple critical cellular functions including vesicular transport, protein secretion energy metabolism, membrane structure, and signaling.19 Furthermore, the integration of lipidomics, and transcriptomics data sets has not been previously reported for these widely-used cell lines. In the study presented here, we combined

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Figure 6. Presence or absence of genes and transcripts for enzymes responsible for lyso phosphatidylethanolamine (LPE) (A), lyso phosphatidylcholine (LPC) (B) and sphingomyelin (SM) (C) metabolic pathways of SP2/0, CHO and HEK cell lines. HPTLC and MS techniques for lipid profiling. HPTLC is a fast, direct, an relatively inexpensive method to analyze lipid contents in order to identify differences in lipids across cell lines. In our study, HPTLC showed distinct differences in SM across the three cell lines directly. However, HPTLC has some disadvantages, such as limited sensitivity and quantification, and a requirement for relatively large numbers of cells. For example, differences in LPE and LPC could not be detected due to its limited sensitivity. As a result, MS-based shotgun lipidomic analysis provided us with more detailed information and pointed out major differences in LPE, LPC, and SM between the cell lines. Significantly increased LPE and LPC were observed in HEK compared to the other two cell lines. Lysophospholipids (LPLs) play a key role in regulating membrane fluidity, curva-

ture, and tubule formation.6 Initially, only saturated or monounsaturated fatty acyl-CoAs can be used as precursors for glycerophospholipids (PLs) production through the de novo pathway (Kennedy pathway). However, there are two enzymes, phospholipase A2 (PLA2) and lysophospholipid acyltransferases (LPLAT), the coordinated actions of which elicit cycles of deacylation and reacylation of PLs at the sn-2 position of the fatty acyl. This remodeling pathway, called the Lands’ cycle, generates LPLs and modifies the fatty acid composition to provide the final mature membrane structure with asymmetry and diversity, which governs membrane fluidity and curvature. The production of LPLs also influence membrane trafficking events by altering membrane shape and binding protein function.20 The interconversion of PLs and LPLs confers negative and positive curvature, respectively, directly

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to membranes. This curvature promotes the formation of tubular and vesicular membrane carriers for transport of proteins and other molecules, which would also be a critical function in the production and secretion of endogenous as well as recombinant proteins. In addition, the generation of LPL on the outer leaflet of the membrane bilayer can stimulate or initiate outward bending of the membrane and thus contribute to membrane tubule formation.20 Also, generation of membraneassociated LPLs stimulates the fusion of biological membranes by perhaps increasing local areas of membrane fluidity or promoting non-bilayer structures that facilitate bilayer mixing.21 Therefore, LPL formation is directly responsible for inducing tubule growth of the Golgi complex and TGN membranes, and this activity may participate in both Golgi tubulemediated retrograde trafficking to the ER and the maintenance of Golgi complex architecture.22 LPC can also stabilize positive curvature of the bud during COPI vesicle and Golgi membrane tubule formation.23 HEK cell lines exhibited high levels of LPE and LPC that likely promotes membrane curvature, which can facilitate membrane tubule formation and membrane vesicle fusion and fission. Differences in the content of lipids and metabolites can result from variability in the levels of both synthase and degradative enzymes in cells, so the balance of anabolic and catabolic processes needed to be considered. In this context, a possible explanation for high levels of LPE and LPC in HEK and lower levels in SP2/0 and CHO can be explained by examining the relevant KEGG pathways (Table S3). SP2/0 expresses the enzymes for LPE and LPC synthesis and degradation while CHO exhibited depleted expression of HRAS-like suppressor 3 for LPE and LPC synthesis. While HEK cells also exhibited depleted HRAS-like suppressor 3 either, they exhibited multiple isoforms of expressed secretory phospholipase A2 (sPLA2) which is responsible for LPE and LPC synthesis as compared to the other cell lines as shown in Table S3. The sPLA2 enzymes hydrolyze the sn-2 position of glycerophospholipids to produce LPLs and fatty acids, such as LPE and LPC. Indeed, a previous study showed that sPLA2 treatment in lipoprotein-bound phospholipids could increase the LPE and LPC levels.24 Additionally, overexpression of sPLA2 enzymes in RBL mast cells has been shown to increase the release of histamine via regulated exocytosis due to the LPLs accumulation at granule-plasma membrane interfaces.25 Thus, the LPLs may play an intimate role in exocytosis and secretion processes. The sPLA2 enzymes are comprised of various types which exhibit different functions and activities during LPL formation. Groups II, III, IV, V, XII sPLA2 enzymes involved in LPE and LPC pathways were expressed in the three cell lines, but the specific genes expressed varied between cell types. Among them, Groups II, III, V, XII sPLA2 enzymes (gene names PLA2G2, 3, 5, 12) have an active site histidine and an absolute requirement of Ca2+ during the catalytic process. The rank order of the hydrolytic potency of some of these sPLA2 in lipoprotein-bound phospholipids hydrolysis is Group V > Group III > Group IIA.24, 26 Group IV sPLA2 enzymes (gene name PLA2G4) are serine esterases and sometimes require Ca2+ for membrane binding but not for catalytic activity and are almost exclusively cytoplasmic proteins.20 Cytoplasmic Ca2+-independent sPLA2 activity plays an important role in the formation of membrane tubules and various intracellular trafficking events.20 It has been reported that the Group IV sPLA2 enzyme encoded by the PLA2G4A gene is capable of

forming membrane tubules between Golgi cisternae, which provide direct continuity between cis, medial, and trans Golgi cisternae for anterograde intra-Golgi protein and membrane transport. These intra-cisternal membrane tubules are induced during times of rapidly increased secretory load.23 The HEK cell line is unique in having Group IV sPLA2 enzymes, which may enhance its intracellular membrane trafficking and fusion events. In addition to the varied expression of sPLA2 enzyme for LPE and LPC synthesis, HEK cells had lower expression of the genes involved in LPE and LPC degradation (LPEAT, LPCAT and LYPLA I/II) compared to SP2/0 and CHO cells (Table S3). This means that reduced degradation of LPE and LPC is likely to occur in HEK, also leading to high levels of LPE and LPC. Several reports showed that inhibition of LPEAT and LPCAT activities by a broad LPLAT (lysophospholipid acyltransferases) inhibitor decreased the LPE and LPC levels and enhanced Golgi tubule formation and membrane trafficking.23 Low expression of LPEAT and LPCAT in HEK may further promote membrane trafficking and tubule formation events. The SP2/0 cell line, known to secrete high levels of antibodies, showed significantly reduced SM compared to the CHO and HEK cell lines. SM is known to stiffen membranes and thus change the membrane state from a liquid to a glassy form, which can impact membrane structure, transport capability, and potentially secretory properties.27 A previous study found that degradation of SM by excess sphingomyelinase activity leads to an increase in vesiculation in red blood cells.28 SM represents nearly 85% of all sphingolipids, including 10-20% of plasma membrane lipids.29 The absence of sphingomyelin synthases (SMS) in SP2/0, but not in CHO and HEK cells, may explain the low levels of SM in SP2/0. SMS is the last enzyme in the SM synthetic pathway, which transfers the cholinephosphate head group from PC to a ceramide lipid anchor to produce SM.9, 30 This reaction is reversible, and SMS can catalyze the reaction in either direction, although the synthesis direction dominates. The mammalian SMS family is composed of two members (namely, SMS1 and SMS2) that feature the same reaction chemistry but are encoded by two distinct genes. SMS1 is found exclusively in Golgi at steady state, whereas SMS2 exists in the Golgi and plasma membrane.30b, 31 Additionally, SMS2 can use PE as the head group donor in addition to PC for SM synthesis.32 Knockdown of SMS1 in human HeLa cells has been shown to reduce SM synthase activity in Golgi, while SMS2 siRNA treatment in HeLa cells decreased SM synthase activity in the plasma membrane. Both of the treatments decreased the SM levels.33 Additionally, siRNA treatment was shown to significantly decrease SM levels in both lipid rafts on the cell membrane and plasma membrane in Huh7 and HEK cells.34 SMS1 and SMS2 siRNA treatments were shown to decrease SM levels up to 20% and 11%, respectively, compared to the control siRNA treatment. SMS1 but not SMS2 siRNA treatment caused a significant increase in the ceramide levels (10%).34 SM metabolic precursors were at a lower level in SP2/0 than the other two cell lines also led to low levels of SM in SP2/0. Besides the depletion of SMS and metabolic precursors in SP2/0 cell line, the presence of an increased amount of SMPD genes, as shown in Table S4, may result in high SM degradation and thus low levels of SM as compared to CHO and HEK cell lines. SMPD genes encode sphingomyelin phos-

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phodiesterase (SMase), which is a hydrolase enzyme responsible for breaking SM down into phosphocholine and ceramide.12 A previous study found that SMase treatment in erythrocytes decreased the SM levels and increased the ceramide formation, resulting in ceramide-associated alterations including microdomain formation and increased vesiculation.28 5. CONCLUSION The TLC and MS findings demonstrated that high levels of LPE and LPC existed in the HEK cell line and low levels of SM were observed in the SP2/0 cell line. The transcriptomic expression profiles of these three cell lines enabled us to elucidate which enzymes and related genes involved in LPE, LPC, and SM pathways are upregulated and downregulated in order to account for the differences in the lipid profiles. The findings from the transcriptomic analysis were then compared with the lipidomics in order to identify consistencies across cell lines for both ’omics platforms. Coupling high-throughput TLC and MS lipidomics with transcriptomics information provides a powerful system biology tool kit for users to gain an improved understanding of the physiological differences across important cell lines such as SP2/0, CHO, and HEK. These system inputs will be used to guide nutrient and metabolic cell engineering efforts in these cells with the goal of increasing the recombinant protein production capacity of SP2/0, CHO, HEK, and other cell lines going forward in future years.

ASSOCIATED CONTENT Abbreviations mentioned in the paper: CER, ceramide; CHCl3, chloroform; CHO, Chinese Hamster Ovary; CL, cardiolipin; Exp, exponential phase; HEK, Human Embryonic Kidney; KEGG, Kyoto Encyclopedia of Genes and Genomes; LCL, lyso cardiolipin; LPC, lyso phosphatidylcholine; LPCAT, lysophosphatidylcholine acyltransferase; LPE, lyso phosphatidylethanolamine; LPEAT, lysophospholipid acyltransferase; LPLAT, lysophospholipid acyltransferases; LPLs, lysophospholipids; LYPLA I/II, lysophospholipase I/II; MeOH, methanol; MS, mass spectrometry; PA, phosphatidic acid; PC, phosphatidylcholine; PCA, principal component analysis; PE, phosphatidylethanolamine; PG, phosphatidylglycerol; PI, phosphatidylinositol; PLA2, phospholipase A2; PLs, glycerophospholipids; PS, phosphatidylserine; SM, sphingomyelin; SMS, sphingomyelin synthases; sPLA2, secretory phospholipase A2; Stat, stationary phase; TAG, triacylglyceride; TLC, thin layer chromatography.

Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Figure S1: Quantitative MS analysis of the lipids with comparable amounts across SP2/0, CHO, and HEK cell lines in both Exp and Stat phases. Appendix S2: Detailed mass spectrometry data on lipidomic analysis for SP2/0, CHO, and HEK-293 cell lines in both exponential and stationary phases. Table S3: Summary of the enzymes involved in the metabolic pathways of LPE and LPC across SP2/0, CHO, and HEK cell lines. Table S4: Summary of the enzymes involved in the metabolic pathways of SM across SP2/0, CHO, and HEK cell lines. (PDF)

AUTHOR INFORMATION Corresponding Author

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* E-mail: [email protected], Phone: +1-4104469801. Fax: +14105165510

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT MJB and YZ acknowledge the financial support of MedImmune, LLC for funding this project.

REFERENCES (1) Walsh, G., Biopharmaceutical benchmarks 2014. Nat. Biotechnol. 2014, 32 (10), 992-1000. (2) Kumar, A.; Heffner, K. M.; Shiloach, J.; Betenbaugh, M. J.; Baycin-Hizal, D., Harnessing Chinese hamster ovary cell proteomics for biopharmaceutical processing. Pharm. Bioprocess. 2014, 2 (5), 421-435. (3) Li, F.; Vijayasankaran, N.; Shen, A.; Kiss, R.; Amanullah, A. In Cell culture processes for monoclonal antibody production, MAbs, Taylor & Francis: 2010; pp 466-479. (4) Wenk, M. R., Lipidomics: new tools and applications. Cell 2010, 143 (6), 888-895. (5) Van Meer, G.; Voelker, D. R.; Feigenson, G. W., Membrane lipids: where they are and how they behave. Nat. Rev. Mol. Cell Biol. 2008, 9 (2), 112-124. (6) (a) Shindou, H.; Hishikawa, D.; Harayama, T.; Yuki, K.; Shimizu, T., Recent progress on acyl CoA: lysophospholipid acyltransferase research. J. Lipid Res. 2009, 50 (Supplement), S46-S51; (b) Hishikawa, D.; Hashidate, T.; Shimizu, T.; Shindou, H., Diversity and function of membrane glycerophospholipids generated by the remodeling pathway in mammalian cells. J. Lipid Res. 2014, 55 (5), 799-807. (7) Karunakaran, S.; Fratti, R. A., The Lipid Composition and Physical Properties of the Yeast Vacuole Affect the Hemifusion– Fusion Transition. Traffic 2013, 14 (6), 650-662. (8) Simons, K.; Toomre, D., Lipid rafts and signal transduction. Nat .Rev. Mol. Cell Biol. 2000, 1 (1), 31-39. (9) Gibellini, F.; Smith, T. K., The Kennedy pathway—de novo synthesis of phosphatidylethanolamine and phosphatidylcholine. IUBMB Life 2010, 62 (6), 414-428. (10) Simons, K.; Ikonen, E., Functional rafts in cell membranes. Nature 1997, 387 (6633), 569-572. (11) (a) Hannun, Y. A.; Obeid, L. M., Principles of bioactive lipid signalling: lessons from sphingolipids. Nat. Rev. Mol. Cell Biol. 2008, 9 (2), 139-150; (b) Bartke, N.; Hannun, Y. A., Bioactive sphingolipids: metabolism and function. J. Lipid Res. 2009, 50 (Supplement), S91-S96; (c) Ruvolo, P. P., Intracellular signal transduction pathways activated by ceramide and its metabolites. Pharm. Res. 2003, 47 (5), 383-392. (12) Goñi, F. M.; Alonso, A., Sphingomyelinases: enzymology and membrane activity. FEBS Lett. 2002, 531 (1), 38-46. (13) Bligh, E. G.; Dyer, W. J., A rapid method of total lipid extraction and purification. Can. J. Biochem. Phys. 1959, 37 (8), 911-917. (14) Christie, W.; Han, X., Lipid Analysis: Isolation, Separation, Identification and Lipidomic Analysis 4. The Oily Press, Bridgwater, England 2010. (15) Pannkuk, E. L.; Risch, T. S.; Savary, B. J., Profiling the triacylglyceride contents in bat integumentary lipids by preparative thin layer chromatography and MALDI-TOF mass spectrometry. Journal of visualized experiments: JOVE 2013, (79). (16) Fuchs, B.; Süß, R.; Teuber, K.; Eibisch, M.; Schiller, J., Lipid analysis by thin-layer chromatography—a review of the current state. J. Chromatogr. A 2011, 1218 (19), 2754-2774. (17) Wang, M.; Han, X., Multidimensional Mass SpectrometryBased Shotgun Lipidomics. In Mass Spectrometry in Metabolomics, Raftery, D., Ed. Springer New York: 2014; Vol. 1198, pp 203-220. (18) Han, X.; Yang, K.; Gross, R. W., Multi‐dimensional mass spectrometry ‐ based shotgun lipidomics and novel strategies for lipidomic analyses. Mass Spectrum. Rev. 2012, 31 (1), 134-178.

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