extfieldsofstudy: Chemistry Medicine

text:
Mycobacterial Membrane Domain, or a Primordial Organelle?

Mycobacteria, like many other prokaryotic organisms, do not appear to have membrane-bound organelles to organize the subcellular space. Nevertheless, mycobacteria and related bacteria grow their cell envelope in a spatially controlled manner, restricting cell elongation to the polar regions of the rod-shaped cell. This spatial organization demands that de novo synthesized cell envelope components must be supplied to the polar ends of the cell. Because many cell envelope components are either lipids or built as lipid-anchored precursors, the plasma membrane is the major site of the biosynthesis. Thus, there are logistical questions of where in the plasma membrane these lipids and lipid precursors are made and how they are subsequently delivered to the growing poles of the cell. Our discovery of an intracellular membrane domain (IMD) fills in this gap. Currently available data suggest that the IMD is a membrane domain within the plasma membrane of mycobacteria, which mediates key biosynthetic reactions for cell envelope and other lipid biosynthetic reactions. Consistent with its role in polar growth, the IMD is enriched in the polar regions of actively growing cells and becomes less polarized when the cells experience non-growing conditions. We discuss how such membrane compartmentalization may be generated and maintained in a mycobacterial cell and why it has not evolved into a bona fide organelle. In a broader perspective, we suggest that segregation of biosynthetic pathways into different domains of a planar membrane could be more widespread than we currently think.

ORGANELLES VERSUS MEMBRANE DOMAINS
Membrane-bound organelles have a functional space, or lumen, created by a surrounding lipid bilayer. Eukaryotic cells are full of such organelles featuring a vast array of specialized functions. It is conceivable that such structures are needed to maintain the working or-der of highly complex eukaryotic cells. Comparatively, prokaryotic cells are generally smaller than their eukaryotic counterparts, implying that there is less of a need for membrane-bound organelles. However, there is a wealth of examples for such functional compartmentalization in prokaryotic cells as well [1][2][3][4]. It appears that cell size is not always the determinant for creating organelles; rather the complexity or the special needs of the cell might de-mand organelle formation and many bacteria are likely as complex or specialized as eukaryotic cells in executing their biological functions.
One could imagine that the evolution of an organelle can be driven either by the need for the segregated, functionally distinct lumenal space, or by the need for increased, isolated membrane surface, or both. When neither lumen nor increased surface is needed, but separate areas are required for organization within a membrane, distinct domains in a planar membrane might suffice. Sterol-and sphingolipid-enriched nanodomains, often referred as membrane rafts, are the most prominent and well-known example of lateral membrane heterogeneities in eukaryotes as well as, more recently, in prokaryotes [5][6][7][8][9]. Such membrane domains are often involved in membrane trafficking and signal transduction. In contrast, little is known about the function of membrane domains in organizing the lateral flow of metabolic reactions within a plane. In Mycobacterium smegmatis, we identified a membrane domain that mediates various segments of biosynthetic pathways ( Figure 1A and B). Given the presence of lateral heterogeneities in diverse biological membranes, we speculate that such metabolic partitions in membranes are likely widespread. However, the experimental evidence for the compartmentalized biosynthesis mediated by membrane-bound enzymes differentially localized in a planar membrane is scarce. We are aware of one example: mammalian glycosylphosphatidylinositol (GPI) biosynthesis, where a part of the pathway takes place in a mitochondria-associated membrane of the endoplasmic reticulum while the rest of the reactions take place in the regular endoplasmic reticulum membrane [10,11]. In the case of Bacillus subtilis plasma membrane, although enzymes involved in the phospholipid biosynthesis are not compartmentalized into multiple membrane regions, they are all enriched in the septal membrane [12]. In these cases, perhaps, the evolutionary pressure was such that membrane compartmentalization was needed without the demand for the creation of separate organelles. In this perspective, we will describe how we discovered a membrane domain in mycobacteria and discuss the implications of compartmentalization.

DISCOVERY OF THE IMD, A MYCOBACTERIAL MEMBRANE DOMAIN
The initial hint of mycobacterial membrane compartmentalization came from a biochemical observation [13]. Our laboratory was primarily interested in the biosynthetic pathway of unique bacterial glycosylated PIs known as phosphatidylinositol mannosides (PIMs), lipomannan and lipoarabinomannan. In the early 2000's, we worked to establish a cell-free system to examine the biosynthesis of these glycosylated PIs [14]. One strategy we took to improve the cell-free system was the fractionation of mycobacterial cell lysate by a sucrose density gradient. The expectation at the time was to isolate the plasma membrane away from other cellular contaminants such as cytoplasmic proteins. However, from this experiment, we unexpectedly found two distinct membrane fractions, which showed distinct biosynthetic activities involved in the PIM biosynthesis. The radioactive mannose donor, GDP-[ 3 H]mannose, was used to monitor PIM biosynthesis between the two fractions. We found that early intermediates such as PIM1 and AcPIM2 were produced in one fraction, while later intermediates such as AcPIM4, AcPIM5, and AcPIM6 were produced in another fraction ( Figure 1B). The membrane fraction that migrated to a lighter density region was originally named the PMf because it did not contain any of the cell wall components (i.e. Plasma Membrane free of cell wall components). The other membrane fraction that sedimented further down into a denser part of the sucrose gradient contained cell wall components including galactose, a component of arabinogalactan layer, and glycopeptidolipids, outer membrane glycolipids. Therefore, this fraction was named the PM-CW (i.e. Plasma Membrane tightly associated with the Cell Wall). Indeed, negative stain electron microscopy of the PM-CW fraction visualized large fragments and debris of cells, consistent with containing both the cell wall and the plasma membrane. In contrast, the PMf appeared to be homogenous vesicles of about 50 nm diameter [13]. Such a compartmentalized biosynthesis of PIMs was surprising because mycobacteria were not known to have membrane-bound organelles or membrane domains. As described below, evidence from more recent studies support the idea that the PMf is a membrane domain rather than a bona fide organelle, and we recently renamed the PMf to the Intracellular Membrane Domain (IMD) to highlight its functional context in the live mycobacterial cell rather than the original name PMf, which was based on its biochemical composition.

IS THE IMD FUNCTIONAL?
We have accumulated several pieces of evidence arguing in favor of the idea that the IMD is a metabolically active and dynamic structure, rather than a biochemical artifact.

PIM Biosynthesis
Our initial analysis of PIM biosynthetic activities, using a GDP-[ 3 H]mannose radiolabeling probe, suggested that the early and late portions of PIM biosynthesis are segregated between the IMD and the PM-CW (Figure 1) [13]. To provide further evidence, live, actively growing M. smegmatis cell was metabolically labeled with [ 3 H] unit is then transferred from lipid II to the growing chain of the peptidoglycan by transglycosylases such as PonA1 [19]. We recently demonstrated that enzymatically functional epitope-tagged MurG, as well as its product lipid II, are localized to the IMD (Figure 1) [20]. Strikingly, genetic knockdown of MurJ flippase resulted in a massive accumulation of lipid II in the IMD, supporting the notion that the IMD is where lipid II is produced. Lipid II is an example of an IMD substrate that is possibly transported to the PM-CW by the flippase MurJ. Such a system for simultaneous flipping and lateral translocation may be used by other substrates as well. As detailed below, the IMD may have a different fluidity from the PM-CW. It would be interesting to examine if membrane fluidity plays a role in facilitating the flipping of large polar lipids across the membrane bilayer.

Menaquinone Biosynthesis
The final pathway we analyzed for membrane compartmentalization was the biosynthesis of menaquinones, which is a lipidic electron carrier in the respiratory chain in mycobacteria. Membrane-associated enzymes, MenA, MenG, and MenJ, mediate the last three steps of the biosynthesis ( Figure 1). First, MenA transfers a polyprenyl (mainly nonaprenyl) lipid onto 1,4-dihydroxy-2-naphthoic acid, making demethylmenaquinone (DMK9). Second, the methyltransferase MenG methylates DMK9 to produce menaquinone (MK9). Finally, the reductase MenJ reduces a single double bond in the β-isoprene unit of the prenyl chain, producing the mature species termed MK9 (II-H 2 ). The proteomic analysis suggested that MenG and MenJ are enriched in the IMD (Figure 1) [17]. Lipidomics reproducibly showed slight enrichment of mature menaquinones in the IMD, supporting the notion that it is produced there [21]. The final maturation of menaquinone in the IMD could imply the functional need for the mature species within the IMD. By density gradient sedimentation of epitope-tagged MenG and MenJ, we confirmed the localization of these two enzymes to the IMD. In contrast, the first enzyme MenA was localized to the PM-CW. The MenA product, DMK9, is an electron carrier known to be functional in other bacteria [22]. However, an accumulation of DMK9 appears toxic to mycobacteria, resulting in metabolic dysregulation and the cessation of growth [21]. The accumulation of DMK9 was achieved by inducible knockdown of the downstream enzyme MenG. Since MenG is an IMD-associated enzyme, we speculate that the toxicity is due to the abnormal enrichment of DMK9 in the IMD.
These pieces of experimental evidence from biochemical assays support that the IMD is a multi-functional membrane domain with numerous metabolic processes. The proteomic analysis revealed more than 300 proteins associated with the IMD, including the ones involved in mannose for a short 10 min period, and the lysate was fractionated by density gradient sedimentation. Similar to the cell-free assay of gradient fractions, we detected the [ 3 H]mannose-labeled AcPIM2 in the IMD while more mature species such as AcPIM6 were found in the PM-CW fractions [13]. These enzymatic activities correlated well with the localization of the enzymes: PimB', which mediates the second mannose transfer of PIM biosynthesis, was enriched in the IMD ( Figure 1B), while PimE, which mediate the fifth mannose transfer, was enriched in the PM-CW [15,16]. Comparative proteomic analysis of the IMD and the PM-CW further identified PatA, the acyltransferase involved in AcPIM2 biosynthesis, as an IMD-enriched protein [17]. These observations supported that both of these membrane fractions are metabolically active and associated with different metabolic activities.

Phospholipid Biosynthesis
Comparative proteomics suggested that segments of phospholipid biosynthesis also take place in the IMD (Figure 1). Synthesis of phosphatidic acid (PA), a key intermediate of phospholipid biosynthesis, is mediated by two acyltransferases that use glycerol 3-phosphate as a starting substrate. According to the proteomic analysis, these two enzymes are both enriched in the IMD [17]. If these enzymes actively produced PA in the IMD, we considered that PA would be more enriched in the IMD. Lipidomic analysis indicated that this is indeed the case [17]. PA is then activated to CDP-diacylglycerol, which can be used for the synthesis of various phospholipids. Phosphatidylethanolamine is one of the major structural phospholipids, and is produced by sequential actions of phosphatidylserine synthase, Pss, and phosphatidylserine decarboxylase, Psd. Using a cell-free radiolabeling assay, we have shown that the enzymatic activity of Pss is enriched in the PM-CW while that of Psd is amassed in the IMD [13]. Furthermore, the proteomic analysis showed the enrichment of Psd in the IMD [17], supporting the idea that the key enzymes associated with the IMD are actively engaged in phospholipid biosynthesis.

Peptidoglycan Biosynthesis
Lipid II is the complete lipid-anchored precursor for peptidoglycan synthesis, anchoring a disaccharide-pentapeptide unit onto a polyprenol lipid linked through a pyrophosphate. The final step of lipid II synthesis is mediated by the glycosyltransferase MurG, which transfers N-acetyl glucosamine from UDP-N-acetyl glucosamine to lipid I, forming lipid II. This step takes place on the cytoplasmic side of the plasma membrane and is followed by the flippase MurJ translocation of lipid II from the cytoplasmic to the periplasmic side of the plasma membrane [18]. The de novo synthesized disaccharide-pentapeptide pole [26]. Even in chemically induced ectopic cell poles, this subpolar localization of the IMD protein was observed [17], suggesting that the IMD is critical for polar elongation of mycobacteria.
Due to the close proximity of the IMD to the cell poles, we further investigated the relationship of the IMD and cell growth. Click-iT chemistry was used to investigate the spatial relationship of the IMD to nascent peptidoglycan synthesis. Actively growing cells had enrichments of bioorthogonal peptidoglycan biosynthetic precursor incorporated intensely at the pole and weakly along the sidewall, distinct from the IMD fluorescent protein localization [27,28]. These observations were consistent with the idea that the IMD is not necessarily the site of the final peptidoglycan elongation and led us to suggest that the IMD may assist in restricting the spatial localization of cell envelope synthesis.

STRESS RESPONSE OF THE IMD
In actively growing cells, we established the IMD as a polarly enriched membrane domain, that continuously associates with the cellular growth pole. These observations supported the idea that the IMD synthesized precursors of the cell envelope, and thusly remained in close proximity to the location of their final incorporation at the polar ends. We wondered what would happen to the IMD when the cells cease their growth. Therefore, we examined the IMD in M. smegmatis during various stresses such as stationary growth phase, starvation, and antibiotic perturbation.
During stationary phase, cells continue to replicate in the absence of cell elongation, providing an ideal opportunity to investigate the IMD when polar elongation is not occurring. Indeed, when cells enter stationary phase, peptidoglycan synthesis is no longer at the polar ends, and is concentrated at the septal region [28]. Subsequently, this lack of elongation led to shorter cells when entering deeper into stationary phase. Similarly, when nutrients were removed from the environment, cell wall synthesis was refocused towards the septum of the cells, leading to the appearance of multi-septal cells. Both stationary phase and starvation saw the decrease in the IMD enrichment at the polar ends, correlating with the alteration in peptidoglycan synthesis [28].
To confirm this relationship between the IMD and the cell wall synthesis, chemical and genetic probing determined the correlative localization of these two entities. d-cycloserine is a chemical inhibitor of peptidoglycan precursor biosynthesis. A diaminopimelate auxotroph is a genetic mutant unable to produce the amino acid diaminopimelate, a key component of the mycobacterial peptidoglycan precursor. Upon stress by d-cycloserine or diaminopimelate starvation in the auxotroph, pepti-many other metabolic pathways, for which future biochemical confirmations await [17]. As mentioned above, the IMD appears as vesicles in the purified fraction under electron microscopy. But, are these IMD-associated proteins found on the same vesicle-like structures? We used gold-labeled antibodies to identify vesicles containing the endogenous protein PimB' and epitope-tagged fusion of GlfT2, an enzyme involved in galactan biosynthesis (see below and Figure 1B); both IMD proteins were found on the same vesicle-like structure. This observation was further supported by immunoprecipitation experiments in which the epitope-tagged GlfT2 pulled down endogenous PimB', but this interaction was ablated in the presence of mild detergents [17]. Collectively, these data reinforce the idea that the IMD is a distinct multifunctional membrane domain.
In contrast to the IMD, the PM-CW is purified as membrane tightly associated with the cell wall. Many cell envelope biosynthetic precursors produced in the IMD are presumably released into the PM-CW in a locally enriched manner and integrated into the supramolecular cell envelope complex. These final integration processes take place on the periplasmic side of the plasma membrane while the IMD reactions are primarily sequestered on the cytoplasmic side. This topology implies that the IMD supports cell envelope biosynthesis in the PM-CW by locally supplying necessary precursors from the opposite side of the membrane.

VISUALIZING THE SUBCELLULAR LOCALIZATION OF THE IMD
The initial biochemical analyses of metabolic compartmentalization led us to ask where in the cell the IMD is localized. Unlike many rod-shaped bacteria, which add new cell wall materials along the length of the sidewall, mycobacteria elongate primarily at the polar ends ( Figure  1A) [23][24][25]. The metabolic potential of the IMD posed as a possible platform for coordinating the many processes needed for the polar cell envelope synthesis. Therefore, we sought to study the IMD in living cells to better understand its relationship to cellular growth.
Based on our proteomic data set, we tagged relatively abundant IMD proteins with a fluorescent protein and monitored their localization in actively growing cells. An IMD protein (GlfT2) and a PM-CW protein (PimE) were tagged with the fluorescent proteins mCherry and GFP, respectively. The mCherry-GlfT2 fusion protein localized as puncta particularly enriched at the polar ends of the cell while the PimE-GFP fusion protein outlined the cell membrane and septum. These localizations suggest a specific subcellular localization of the IMD, separate from the PM-CW [17]. A previous study established GlfT2 as a subpolar protein relative to DivIVA that defines the cell ternal structures of mycobacterial cells using cryo-electron microscopy. Rapid freezing of live samples reduces the formation of artificial structures in the cell that are often produced during chemical fixation. In these recent cryo-electron microscopy images, there is no clear evidence for the presence of cytoplasmic vesicles [29][30][31][32]. Second, we created a number of strains of M. smegmatis, in which the IMD-associated proteins were fused to a fluorescent protein. We have confirmed that despite the attachment of a fluorescent protein, these enzymes remain functional. In our recent analysis using structured illumination microscopy, two such proteins, MurG-Den-dra2 and mCherry-GlfT2, were closely co-localized with each other in a single cell, and both proteins appeared as patches along the cell perimeter rather than intracytoplasmic vesicles [20]. Nonetheless, we acknowledge that fluorescent microscopy is limited in resolution and more detailed electron microscopic analysis is needed to firmly define the morphological nature of the IMD.

DO LIPIDS DRIVE THE FORMATION OF THE IMD?
Lipid composition of the IMD is distinct from that of the PM-CW [17]. However, we currently do not know if lipids drive the creation and maintenance of the membrane domain. By examining biosynthetic pathways associated with the IMD, we found many enzymes that react on polyprenol lipids as substrates. Examples include MurG in peptidoglycan precursor synthesis, Ppm1 in polyprenol-phosphate-mannose biosynthesis, WbbL1, GlfT1, and GlfT2 in galactan precursor biosynthesis, as well as, MenG and MenJ in menaquinone biosynthesis [17,20,21]. Non-sterol isoprenoids such as polyprenols can destabilize lamellar lipid bilayer by inducing hexagonal II phase formation [33][34][35], can increase membrane fluidity in in vitro systems [33,[36][37][38][39], and can induce lipid cluster formation while being incompatible with cholesterol-rich membrane rafts [37,40,41]. Therefore, it is tempting to speculate that the IMD is a polyprenol-rich membrane domain that is more fluid than the conventional plasma membrane (i.e. PM-CW). If the formation of the IMD is a lipid-driven process, proteins may be localized to the IMD by recognizing specific lipids within the IMD. Polyisoprenyl recognition sequences are found in the transmembrane domains of a variety of proteins in both eukaryotes and prokaryotes [42,43]. However, a large proportion of the IMD-associated proteins are peripheral membrane proteins without predicted transmembrane domains [17], and it remains unknown if similar lipid-binding motifs play roles in the localization of IMD proteins.
If the IMD formation is a lipid-driven process, molecules that disrupt membrane organization might have doglycan synthesis halted, and the IMD localized away from the polar ends [28]. These data support that the polar localization of IMD-associated proteins is dependent on peptidoglycan synthesis.
The localization of the IMD-associated proteins correlated to that of cell wall synthesis, even upon removal of the stress, when cells transitioned back to polar elongation. Cells affected by a stress had higher IMD localization to the sidewall, but upon recovery due to removal of the stress, relocalization of the IMD-associated proteins to the polar end was evident. Incorporation of nascent cell wall precursors was initially slower in cells recovering from stress than those logarithmically growing. This delay in elongation correlates to the transition from a sidewall-distributed IMD to a pole-enriched IMD [28]. These data suggest that the polarly focused IMD corresponds with optimally efficient cell elongation, acting as supply generator for cell envelope synthesis. Such a dynamic role of the IMD is relevant for the infection cycle of Mycobacterium tuberculosis, during which the bacterium is exposed to extreme environmental changes such as low nutrients and low oxygen in host immune cells. Our unpublished analysis indicates that M. tuberculosis has the IMD, implying a critical role of a similar membrane organization in the pathogenic species.
Notably, the delay in elongation during recovery is similar to that of cells undergoing normal cell division in which alternator and accelerator cells have been identified [23,24]. The elongation of alternator cell, which inherits slow-growing new pole from the mother cell, is delayed in comparison to that of accelerator cell, which inherits preexisting old pole from the mother cell. The maturation of the IMD at the alternator cell's new pole poses a potential explanation for the growth delay. Since the accelerator cell inherits the mature growth pole from the mother cell, it does not require additional time to reform an IMD for elongation. Similarly, the IMD localizes to ectopic growth poles that are induced by a chemical treatment [17], and this localization takes place shortly after the ectopic growth pole formation. As discussed above, the PM-CW plays the critical roles in actual integration of the materials supplied from the IMD into the cell envelope. Thus, coordination of enzymes associated with the IMD and the PM-CW is pivotal in normal growth as well as during the recovery from stress conditions.

MORPHOLOGY OF THE IMD
Biochemically purified IMD appeared as vesicles under electron microscopy. But, does the IMD membrane vesicle exist in the cell or is this formation a consequence of cell lysis? Currently, available data suggest that the latter is likely.
First, a number of recent studies visualized the in-profound impacts on the IMD localization of proteins.
Benzyl alcohol is a well-documented membrane fluidizer, which can disrupt the membrane domain organization in various biological membranes [44,45]. In particular, there is a fluid membrane, termed Region of Increased Fluidity (RIF), in Bacillus subtilis, which is conceptually similar to the IMD [45]. Strikingly, the evolutionarily conserved peptidoglycan biosynthetic enzyme MurG is associated with the Bacillus RIF and the formation of RIF was disrupted by benzyl alcohol treatment [45]. When we tested the effect of benzyl alcohol in mycobacteria, it was not bactericidal but bacteriostatic at the concentration we used. We prepared a lysate from benzyl alcohol-treated mycobacterial cells, fractionated by the density gradient, and analyzed lipid profiles by thin layer chromatography. This experiment revealed altered distributions of major lipid species in the IMD and the PM-CW. Furthermore, less MurG-Dendra2 was enriched in the IMD density fraction. Consistent with the biochemical analysis, fluorescence microscopy revealed that the polar enrichment of MurG-Dendra2 in growing cells was severely diminished upon treatment with benzyl alcohol [20]. The reorganization of MurG-Dendra2 reflected to non-polar synthesis of peptidoglycan, suggesting a connection between lipid organization and polar cell envelope growth. While further studies are needed, these initial observations indicate that lipids play key roles in structurally organizing the IMD.

CONCLUSIONS
The IMD is a metabolically active membrane domain, which acts as a localized supply generator for cell envelope elongation. However, there are many other enzymes, which are not directly linked to cell envelope elongation, associated with the IMD as well. This is exemplified by the association of menaquinone biosynthesis with the IMD, implying that the IMD is tightly linked to the central energy metabolism. How the IMD is generated, maintained, and regulated in response to changing environment is an important question for the future. Our unpublished data suggest that the IMD exists in M. tuberculosis, but evolutionary conservation of the membrane compartmentalization in other Mycobacterium and related bacteria remains unknown. Is the IMD an organelle? Perhaps not, but it may be a way for mycobacteria to organize their subcellular environment to support efficient growth and proliferation, much like how eukaryotic cells utilize their biogenic organelles for metabolic coordination.


extfieldsofstudy: Medicine Biology

text:
SREBP1-dependent de novo fatty acid synthesis gene expression is elevated in malignant melanoma and represents a cellular survival trait

de novo fatty acid biosynthesis (DNFA) is a hallmark adaptation of many cancers that supports survival, proliferation, and metastasis. Here we elucidate previously unexplored aspects of transcription regulation and clinical relevance of DNFA in cancers. We show that elevated expression of DNFA genes is characteristic of many tumor types and correlates with poor prognosis, especially in melanomas. Elevated DNFA gene expression depends on the SREBP1 transcription factor in multiple melanoma cell lines. SREBP1 predominantly binds to the transcription start sites of DNFA genes, regulating their expression by recruiting RNA polymerase II to promoters for productive transcription elongation. We find that SREBP1-regulated DNFA represents a survival trait in melanoma cells, regardless of proliferative state and oncogenic mutation status. Indeed, malignant melanoma cells exhibit elevated DNFA gene expression after the BRAF/MEK signaling pathway is blocked (e.g. by BRAF inhibitors), and DNFA expression remains higher in melanoma cells resistant to vemurafenib treatment than in untreated cells. Accordingly, DNFA pathway inhibition, whether by direct targeting of SREBP1 with antisense oligonucleotides, or through combinatorial effects of multiple DNFA enzyme inhibitors, exerts potent cytotoxic effects on both BRAFi-sensitive and -resistant melanoma cells. Altogether, these results implicate SREBP1 and DNFA enzymes as enticing therapeutic targets in melanomas.

data from 30 diverse cancer types in The Cancer Genome Atlas (TCGA). We found that DNFA enzyme expression varies widely among cancers. Four DNFA enzymes -SCD, FASN, ACLY and ACSS2 -exhibit the highest levels of mRNA expression in skin cutaneous melanoma (SKCM) compared to other tumor types, whereas expression of ACACA is less elevated in melanomas ( Supplementary Fig. 2a). We observed relatively low expression of mRNAs encoding HMGCS1 and HMGCR, two rate-limiting enzymes in the de novo cholesterol synthesis (DNCS) pathway 46 in melanomas. These results indicate that elevated DNFA expression is prevalent among tumors, significantly more so in melanomas than in most others.
To relate elevated DNFA expression with disease progression, we examined its prognostic value using Kaplan-Meier analysis. We divided patients into two groups based on the DNFA gene expression from their tumor biopsies and compared overall survival rates. We found that high expression of SCD ( Fig. 1c and Supplementary Fig. 2d,g), FASN ( Supplementary Figs 1c and 2e,h) and ACACA ( Supplementary Fig. 2b,f) significantly correlates with poor prognosis in all cancers considered collectively. The only exceptions we observed were ACLY (Supplementary Fig. 1e) and ACACA specifically with a top 10% versus bottom 10% expression cutoff ( Supplementary Fig. 2i). Elevated mRNA expression of SCD (Fig. 1d), FASN, ACLY ( Supplementary Fig. 1d,f) and ACACA (Supplementary Fig. 2c) each correlates with poor prognosis in SKCM. We observed for HMGCS1 but not HMGCR that higher expression significantly correlates with poor survival in all tumor types combined ( Supplementary Fig. 3c,e), using 20% as cutoff, however, this was not observed in SKCM ( Supplementary Fig. 3d,f).
Melanoma is the most aggressive skin cancer type. To control for potential tissue-specific upregulation, we first compared SCD expression in healthy tissues using RNA-Seq data from the Genotype-Tissue Expression (GTEx) database 47 . There, skin SCD expression is low ( Supplementary Fig. 4a); yet among tumor tissues, skin SCD expression is elevated (Fig. 1a). This contrasts with, for example, the liver, which exhibits relatively high SCD expression among healthy ( Supplementary Fig. 4a) and tumor tissues (Fig. 1a). We then compared SCD, ACLY and HMGCS1 expression using normalized RNA-Seq data from the SKCM group in TCGA and the normal skin tissue group in GTEx. SCD and ACLY mRNA expression is markedly elevated in SKCM versus healthy skin tissues ( Supplementary Fig. 4b,c), while HMGCS1 is higher in the healthy tissues ( Supplementary Fig. 4d). We performed principal component analysis (PCA) on RNA-Seq data of DNFA genes from skin tumors and healthy skin tissues ( Supplementary Fig. 4e,f), and found that skin tumors are distinct from healthy skin samples. SCD expression strongly correlates with principal component 1 (PC1) towards skin tumors. Long-chain acyl-CoA synthetase (ACSL1) is a dual function enzyme in DNFA and fatty acid oxidation pathways with low abundance in tumors 4 . When its expression is combined with other DNFA genes in PCA, ACSL1 expression strongly correlates with PC1 towards healthy tissues and results in better separation of skin tumors from healthy skin tissues ( Supplementary Fig. 4e,f). In a separate PCA, DNCS expression, particularly HMGCS1, strongly correlates with PC1 ( Supplementary Fig. 4g). Supplementary Fig. 4e-g suggests difference in lipogenic activities between skin tumors and healthy skin tissues.
Melanomas are transformed from benign, melanocytic nevi, with proliferation of melanocytes commonly triggered by BRAF V600E -activating mutation 48 . To confirm cancer-selective elevation in expression, we compared the DNFA gene expression between malignant melanoma biopsies and benign melanocytic nevus samples ( Supplementary Fig. 5a-d). We observed significantly elevated DNFA gene expression in malignant melanomas. We further analyzed single cell RNA-Seq data from melanoma samples 49. High expression of SCD, FASN, and ACACA was confined to malignant cells, with low expression in healthy adjacent tissue ( Fig. 1e and Supplementary Fig. 5e-h). Somatic mutations of BRAF and NRAS are associated with about 50% and 15% of melanomas, respectively 48 . BRAF and NRAS mutations, while being well-known risk factors and drivers of cancer onset, have limited prognostic significance for overall survival of melanoma patients 50 . There is no significant correlation between DNFA enzyme expression and common oncogenic driver mutations in SKCM (Supplementary Fig. 6a-l), suggesting that elevated DNFA expression in malignant melanomas is mechanistically unrelated to BRAF and NRAS mutation status.

SREBP1 contributes to elevated DNFA gene expression in melanoma cells. To test whether SREBP1
drives elevated DNFA enzyme expression in melanomas, we depleted the SREBP1 mRNA (SREBF1) with antisense oligonucleotides (ASOs) and siRNAs in HT-144 cells. SREBF1 depletion with siRNA and ASO agents was accompanied by decreasing protein levels of SREBP1 and DNFA enzymes (Fig. 2a). The pooled siRNA and ASO agents effectively depleted both the cytoplasmic precursor and the mature nuclear SREBP1 (Fig. 2b,c). Among six tested ASOs targeting SREBF1, ASO-1 and ASO-4 are more potent than single or pooled siRNAs for SREBF1, as 5 nM of ASOs inhibited DNFA mRNA production as effectively as 50 nM of siRNAs ( Supplementary Fig. 7b-f), even when siRNAs decreased the level of SREBF1 mRNA more than ASOs ( Supplementary Fig. 7a). ASOs may also engage in steric translation inhibition of SREBF1 mRNA 51 , which could potentially contribute to their greater potency. We found that ASO-4 inhibits DNFA gene expression commensurately with dosage ( Supplementary Fig. 7g).
To evaluate potential activators of DNFA expression, we depleted SREBF1, SREBF2, and co-activators MED15 and CREBBP 28 with siRNAs, and examined DNFA expression across three melanoma cell lines: HT-144 (Fig. 2d,e), A375 ( Supplementary Fig. 7i,j) and MEL-JUSO ( Supplementary Fig. 8a,b). We observed a similar range of mRNA reductions (50-70%) for most DNFA enzymes after SREBF1 depletion (Fig. 2d, Supplementary  Figs 7i and 8a). Depletion of MED15 and CREBBP individually or together impacts DNFA gene expression, but to a lesser extent than SREBF1 depletion ( Supplementary Figs 7i and 8a). SREBF2 depletion exerts potent effects on the expression of the DNCS genes HMGCS1 and HMGCR in HT-144 and A375 cells ( Supplementary Fig. 7h,k), in line with previous studies in hepatocytes 52 . SREBF2 also affects DNFA enzyme expression, especially in concert with SREBF1 depletion (Supplementary Fig. 8a-d). The role of SREBP2 in regulation of DNFA genes may be transitive via SREBP1 53 , since SREBF1 expression decreases after SREBF2 depletion (Fig. 2e); or it may be acting in a partially redundant manner 54 . Thus, we confirmed the transcription regulatory role of SREBP1 in promoting DNFA gene expression in multiple melanoma cell lines. ( 55 . FASN and SCD displayed increased expression at consecutive time points ( Supplementary Fig. 8c-f). SREBF1 depletion by siRNA blocked DNFA gene activation on days 3 and 5, whereas DNFA enzyme protein (Fig. 2f) and mRNA levels (Fig. 2g,h) were elevated in response to overexpression of nSREBP1a, the abundant isoform in proliferating embryonic cells and in cancers, as well as nSREBP1c, which is the predominant isoform in adult liver and adipose tissues 56 . With a longer transactivation domain, nSREBP1a interacts more avidly with co-activators and thus exhibits stronger transcription activity than nSREBP1c 27,57 . Consistently, we observed higher expression of DNFA genes after overexpressing nSREBP1a than nSREBP1c. These results indicate that SREBP1 expression controls DNFA gene expression in melanoma cells. SREBP1 directly regulates DNFA pathway genes through RNAP II recruitment and productive elongation. To characterize the transcriptome changes after SREBF1 depletion, we carried out RNA-Seq analysis after SREBF1 depletion with pooled siRNAs and individual ASOs in HT-144 cells, followed by PCA on RNA-Seq data. To identify the possible off-target effect of the ASOs, we performed RNA-Seq analyses on   (g,h) mRNAs were analyzed with RT-qPCR assay. The bar graphs show the relative expression of DNFA enzymes to that of pcDNA3 (control) transfection group. Data are expressed as mean ± SD and quantified from triplicates. One-way ANOVA tests were performed. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.
www.nature.com/scientificreports www.nature.com/scientificreports/ two constructs that target different sequence regions of SREBF1 mRNA: ASO-1 and ASO-4. The two principal components (PCs) in the PCA biplot represent over 70% of the overall gene expression changes ( Fig. 3a and Supplementary Fig. 9a). SREBF1 and SCD are among the top six contributors to data separation and they align with PC2 ( Fig. 3a, Supplementary Fig. 9b). SREBF1 siRNA, ASO-1 and ASO-4 produced similar vertical separations to all negative controls in PC2 (Fig. 3a), and they all reduced expression of FASN and SCD compared to negative controls (Supplementary Fig. 9e-g). These results indicate that the most profound effects after SREBF1 depletion by both ASOs and siRNA are on DNFA genes. ASO-1 has significant lateral separation from ASO-4 and SREBF1 siRNA on PC1 (Fig. 3a). The changes in SPIRE1 and USP9X expression are the major contributors to PC1 ( Supplementary Fig. 9c) and are only affected by ASO-1 ( Supplementary Fig. 9h,i). This result indicates that ASO-1 has specific off-target effects on SPIRE1 and USP9X. Multiple negative controls are grouped together, and ASO-4 is close to SREBF1 siRNA on the PCA biplot, consistent with the results from hierarchical clustering analysis of the same RNA-Seq dataset ( Supplementary Fig. 9d). Hence, ASO-4 has similar specificity as pooled SREBF1 siRNAs for SREBF1 depletion.
To explore the overall biological pathways affected by SREBF1 depletion, we examined differentially expressed genes (DEGs) in the RNA-Seq dataset (siSREBF1 group vs siNegative group) ( Supplementary Fig. 9j). Using gene-set enrichment analyses (GSEA) with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology (GO) terms on DEGs, we determined that the downregulated genes after SREBF1 depletion are primarily involved in fatty acid biosynthesis and lipid metabolism (Fig. 3b, and Supplementary Fig. 9k), as expected. Cellular inflammatory response pathways are significantly enriched in upregulated genes after SREBF1 depletion (Fig. 3c, and Supplementary Fig. 9l), including Toll like receptor and tumor necrosis factor (TNF) signaling pathways that mediate cytotoxicity 58 .
To assess the direct regulatory roles of SREBP1 on target genes in cancers, we analyzed public ChIP-Seq data for SREBP1 from lung cancer, breast cancer and chronic myeloid leukemia (CML) cell lines. ChIP-Seq peaks primarily localize at the proximal promoter regions around TSS ( Supplementary Fig. 10a,b). De novo motif sequences identified from SREBP1 ChIP-Seq peaks match the known SREBP1 binding motif ( Supplementary  Fig. 10c). High DNFA gene expression was observed in lung and breast cancers (Fig. 1a). We identified genes that are present in SREBP1 ChIP-Seq data from both lung cancer line A549 and breast cancer line MCF7 ( Supplementary Fig. 10d), and that are also DEGs in our RNA-Seq data. We reasoned that the "overlapping" genes common to all three data sets are likely regulated directly by SREBP1. We therefore performed functional network analysis on this subset. This analysis revealed genes in many pathways including the PI3K/AKT pathway   ChIP-qPCR signals were compared between cells cultured in 10% FBS and 1% ITS medium conditions. Data were presented as mean ± SD and quantified from triplicates. Two-way ANOVA tests were performed. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.
www.nature.com/scientificreports www.nature.com/scientificreports/ and the RNAP II elongation complex, and the expected DNFA pathways (Supplementary Fig. 10e). We then used our RNA-Seq data to divide the overlapping genes into upregulated and downregulated sets, and performed GSEA on each. The downregulated genes participate primarily in lipid metabolism pathways ( Supplementary  Fig. 10f), which confirms SREBP1 as a direct activator of DNFA genes. Inflammatory response pathways are significantly upregulated in DEGs from RNA-Seq analysis (Fig. 3c), but seem not to be direct targets of SREBP1 ( Supplementary Fig. 10g). We suspect that downregulation of DNFA pathways may change the homeostasis of cellular fatty acids and exert further impact on inflammatory response pathways as well as cell death 59 .
To elucidate the molecular mechanism of SREBP1-governed DNFA gene activation in melanoma cells, we used a chromatin immunoprecipitation (ChIP)-qPCR assay to detect occupancy of SREBP1, RNA polymerase II (RNAP II), and H3K36me3 -a histone marker associated with transcription elongation 60 on DNFA genes. SREBP1 depletion by ASO-4 diminished SREBP1, RNAP II and H3K36me3 signals at the SCD promoter ( Fig. 3d-f). We observed similar (albeit lower-magnitude) results for FASN ( Supplementary Fig. 11a-c). These ChIP-qPCR results together with the RNA-Seq data ( Supplementary Fig. 9e-g) suggest that removal of SREBP1 at DNFA promoters inhibits transcription activity and mRNA production. We performed ChIP-qPCR analyses in SREBP1-activating (1% ITS medium, no lipids) and SREBP1-repressing (10% FBS medium, with lipids) conditions. We found that 1% ITS medium dramatically increases SREBP1 occupancy at the transcription start sites (TSS) of SCD (Fig. 3g) and FASN (Supplementary Fig. 11f) in HT-144 cells. The strong RNAP II binding peaks at TSS of SCD and FASN in both 10% FBS and 1% ITS culture conditions ( Fig. 3h and Supplementary Fig. 11g) indicate promoter-proximal pausing of RNAP II 61 . Furthermore, culturing cells in 1% ITS medium increased the occupancy of actively elongating RNAP II (RNAP II S2P) ( Supplementary Fig. 11d,i), but not poised RNAP II (RNAP II S5P) 62 (Supplementary Fig. 11e,j), at the TSS as well as the gene bodies of both SCD and FASN. Accordingly, the histone marker H3K36me3 was elevated along both gene bodies in cells cultured with 1% ITS ( Fig. 3i and Supplementary Fig. 11h). These results suggest that SREBP1 binding near the TSS involves both RNAP II recruitment and stimulation of productive elongation on DNFA genes.

Essential role of DNFA in proliferation and survival of untreated and drug-resistant melanoma cells.
To evaluate the roles DNFA in cell proliferation and survival, we cultured melanoma cells in the lipid-free 1% ITS medium, using insulin as a growth factor to stimulate proliferation. The metastatic melanoma-derived cell lines HT-144 and A375 can proliferate in both 10% FBS and 1% ITS media but remain quiescent in 0% FBS medium (Fig. 4a,b). By contrast, the primary melanoma-derived cell line, MEL-JUSO, remains quiescent in both lipid-free (1% ITS and 0% FBS) media (Fig. 4c). We depleted SREBF1 with ASO-4 in several melanoma cell lines cultured under the three medium conditions, to obtain dose-response curves and IC50 values. We found that ASO-4 decreased viability of both proliferative and quiescent cells in all conditions (Fig. 4d-i). We reason that, although cancer cells may employ lipid uptake 63 , DNFA is required for cell survival regardless of external lipid availability under conditions similar to those we tested. We observed diminished viability at higher ASO concentrations (greater than 5 nM), which correlates with more efficient depletion of SREBP1 and more marked decrease of DNFA gene expression ( Supplementary Fig. 7g). Comparing the two growth factor-containing culture conditions, we find that ASO-4 is a more potent inhibitor of cell growth/survival in 1% ITS medium than in 10% FBS medium with HT-144, A375 and LOXIMVI cells. In contrast, WM1552C, MeWo and MEL-JUSO cells are relatively insensitive to ASO-4 treatment. The implication is that, although DNFA seems to be vital for cell survival, medium lipid availability may mitigate the impact of SREBP1 inhibition in cell lines that are sensitive to ASO-4.
BRAF inhibitors (BRAFi, e.g. vemurafenib) improve survival for patients with metastatic melanomas harboring the BRAF V600E mutation 64 . However, the rapid emergence of treatment-surviving tumors limits clinical benefits 65,66 . We derived two BRAFi-resistant cell lines with prolonged vemurafenib treatment: HT-144BR from a vemurafenib-sensitive cell line HT-144, and LOXIMVIBR from a vemurafenib-insensitive cell line LOXIMVI (Fig. 5a,c). Both HT-144BR and LOXIMVIBR cell lines continuously proliferate in the presence of vemurafenib (2 μM). Using cell viability assay, we found that HT-144 and HT-144BR displayed similar sensitivities to ASO-4 treatment, as did LOXIMVI and LOXIMVIBR (Fig. 5b,d). We reason that these cell lines all depend on SREBP1 for survival regardless of whether they are sensitive or resistant to vemurafenib.
To confirm that DNFA enzyme inhibition is the crucial driver for reduced cell viability, we then used small molecule inhibitors of FASN and SCD enzymes, which reportedly decreased tumor growth in preclinical studies [67][68][69] . In 10% FBS (lipid-containing) medium, FASN and SCD inhibitors decreased viability in both HT-144 and HT-144BR cells (Fig. 5e,g), although the effect was less potent than SREBF1 depletion by ASO-4. However, we observed much stronger effects on cell survival when combining the two inhibitors, confirmed by Bliss independence analysis 70 as robust positive synergy (Fig. 5f,h). DNFA thus appears vital to melanoma cell survival even in vemurafenib-resistant cells.

Continued and elevated DNFA gene expression in melanoma cells after BRAF inhibitor treatment.
To explore the role of DNFA in BRAFi resistance, we compared DNFA gene expression in untreated and vemurafenib-resistant cell lines. We observed modestly higher DNFA gene expression in the vemurafenib-resistant HT-144BR and LOXIMVIBR cells as compared with the untreated HT-144 and LOXIMVI cells (Fig. 6a,b). We then investigated the short-term impact of vemurafenib on DNFA gene expression in HT-144 cells treated with various doses of vemurafenib. After one-day treatment, vemurafenib exerted low-dose stimulation and high-dose inhibition of DNFA gene expression, exhibiting hormesis (i.e. bell-shaped dose-response curves) 71 (Fig. 6c,d, Supplementary Fig. 12a-e). We observed dose-dependent induction of PPARGC1A expression with vemurafenib treatment (Supplementary Fig. 12f) as expected, given that the BRAF/MEK pathway directly suppresses PPARGC1A expression and fatty acid oxidation in melanomas 72,73 . DNFA inhibition in response to high-dose vemurafenib treatment may correlate with onset of cell death, whereas DNFA stimulation in response to low-dose vemurafenib treatment suggests rapid cellular resistance.
www.nature.com/scientificreports www.nature.com/scientificreports/ To rule out vemurafenib-specific (perhaps off-target) effects, we evaluated dabrafenib, another BRAFi employed in clinical practice 74 . We monitored DNFA gene expression in HT-144 cells after one day treatment of dabrafenib. Cell death was less evident after high-dose dabrafenib treatment, perhaps due to lower off-target toxicity 75 . We found that expression of DNFA genes decreased after low-dose dabrafenib treatment but increased at effective high-dose treatment ( Supplementary Fig. 13a-g). Dabrafenib at 2.5 µM concentration significantly stimulated gene expression of ACLY, SCD, ACSL1 and PPARGC1a (Supplementary Fig. 13b,e,f and h).
The effectiveness of BRAF inhibition is widely attributed to downstream inhibition of MEK, and then ERK. Resistance due to reactivation of MEK/ERK bypasses that effect. In A375 cells ( Supplementary Fig. 14a-h), a cell line with reported MEK/ERK reactivation associated with vemurafenib treatment 76 , vemurafenib exerts little induction of DNFA gene expression nor dose-dependent induction of PPARGC1A. An adjuvant ERK inhibitor (ERKi, SCH772984) has been employed clinically to overcome vemurafenib resistance 77 , by directly contributing to overall BRAF/MEK/ERK pathway inhibition 78 . When combining 0.5 μM vemurafenib and 0.5 μM SCH772984  Fig. 14i). We saw evidence of a dose-response relationship between ERKi and induction of DNFA gene expression, where treatment of SCH772984 at 1 μM achieved stronger induction of DNFA gene expression ( Supplementary  Fig. 14i). Our overall interpretation is that BRAF/MEK/ERK pathway inhibition upregulates DNFA gene expression, possibly through AKT activation 79 , which then contributes to vemurafenib tolerance in melanoma cells.
To further characterize the role of SREBP1 and DNFA upregulation in response to BRAF inhibition, we combined ASO-4 and vemurafenib treatment in HT-144 cells. We observed that SREBF1 depletion abolished the SCD and ASCL1 induction accompanying vemurafenib treatment by RT-qPCR assays ( Fig. 6e-g). Finally, we investigated cell viability after co-treatment with ASO-4 and vemurafenib. ASO-4, alone or in combination with vemurafenib, effectively killed HT-144 (Fig. 6h) and A375 cells ( Supplementary Fig. 14j). However, there is a mild antagonistic effect between ASO-4 and vemurafenib at low doses according to Bliss analysis (Fig. 6i, Supplementary Fig. 14k). We regard this as corollary to DNFA stimulation by vemurafenib ( Fig. 6e-g,  Supplementary Fig. 14a-g), while noting that, consistent with our findings above for A375, vemurafenib treatment alone yielded little induction of DNFA gene expression in A375 compared to HT-144, and the antagonistic effect was correspondingly lower. In both cell lines, high-dose ASO-4 exerts dominant cell killing effect over vemurafenib in combination treatment.

Discussion
Cancers frequently exhibit reprogrammed metabolic traits such as elevated DNFA 3 that act to sustain active proliferation and cell survival under adverse conditions, and support the process of tumorigenesis and metastasis, as well as resistance to targeted therapies. The diverse genetic paths cancers take to achieve such traits have frustrated efforts to exploit them clinically [80][81][82] .
Most DNFA enzymes are primarily regulated at the transcriptional level in a coordinated manner 6 , thus the abundance of their mRNAs can be employed as a simple surrogate for DNFA activities. Our results show that elevated DNFA gene expression may serve as a prognostic marker for some cancer types, even though they are not considered onco-drivers. Moreover, increased DNFA pathway expression appears to be intrinsic to malignant cancer cell types independently of onco-drivers, including constitutively active BRAF mutants. This may be consistent with the notion of increased DNFA as an "oncosustenance" pathway, with well-definable mechanistic contributions to cancer survival and proliferation. Once the oncosustenance pathway becomes active, it may not always matter which onco-drivers acted prior to cancer onset. Indeed, it has already been suggested that malignant cancer cells may have ongoing reliance upon oncogene-induced signaling pathways, but not upon initial onco-drivers 83 . It is also possible that SREBP1 transcription auto-regulation 28 might "lock in" elevated DNFA expression in malignant cells. The scope of therapeutic investigations, which frequently focus on mutated oncogenes, could be broadened to include oncosustenance mechanisms. www.nature.com/scientificreports www.nature.com/scientificreports/ The prevalence of elevated DNFA expression in certain tumor types such as melanoma suggests the presence of survival pressure for increased lipogenesis, which may therefore represent a therapeutic linchpin. However, high doses of individual pharmacological inhibitors of SCD and FASN enzymes were reportedly required to impact cell viability in melanomas and other cancers 67,69 . This phenomenon may be attributable to compensatory upregulation of SREBP1 and corresponding elevation of DNFA pathway expression, triggered by individual DNFA enzyme inhibition 84 . However, the combined effect of multiple DNFA enzyme inhibitors is synergistic and potent, at least in vitro (Fig. 5e-h). We demonstrated in melanomas that inhibition of SREBF1 by 5 nM ASO-4 treatment results in 50% reduction in the expression of multiple DNFA genes. The potent cell death effect after ASO-4 treatment is likely due to the strong synergistic effects of 50% reduction across the entire DNFA enzymatic cascade that is coordinately regulated by SREBP1. Therefore, inhibition of multiple DNFA enzymes could be of therapeutic benefit due to a potent cumulative effect on lipogenesis, as observed with SREBP1 mRNA-inhibiting ASOs and DNFA enzyme-targeting cocktails.
Previous studies have shown that SREBP1 binding and RNAP II recruitment to DNFA gene promoters represents the primary mechanism for transcription activation 85,86 . In accord with this, we observed that RNAP II accumulated at the proximal promoter regions of SCD and FASN. Under lipid-depleted (SREBP1-activating) cell culture conditions, we observed two indications of productive transcription elongation: increased RNAP II with serine 2 phosphorylation at its C-terminal domain (RNAPII-S2p) 62 and the histone marker for transcription elongation (H3K36me3) 87 along the gene bodies of FASN and SCD. Based on these findings we suggest a two-step working model for regulation of RNAP II machinery: RNAP II recruitment to proximal promoters at lipogenic genes, followed by RNAP II release for productive elongation. This model appears to explain elevated and synchronous DNFA gene expression in melanomas, and perhaps other cell types. It is presently unclear exactly how RNAP II is released for productive elongation.
BRAF-mutated melanomas are frequently treated with vemurafenib, a targeted therapy to inhibit the oncogenic BRAF pathway. Because vemurafenib sometimes fails to inhibit MEK/ERK (key targets downstream of BRAF) 88 , current clinical regimens combine inhibitors of both BRAF and MEK and/or ERK for treating metastatic melanomas 89,90 . However, even when combined inhibition is achieved, resistance arises via genetic alterations that upregulate the PI3K/AKT pathway 91 . Our determination that elevated DNFA is mechanistically important for resistance to targeted therapies dovetails with a similar recent finding by Talebi et al. 92 . They reported that (c,d) HT-144 cells were treated with different dosages of vemurafenib for 0.5 or 1 day in 1% ITS medium. SCD expression was assayed by RT-qPCR analysis. Expression of SCD from all treatment groups was normalized to expression under DMSO treatment at day 0.5 (normalized as 1). Relative gene expression was compared between 0.5-day and 1-day treatment groups. Data were presented as mean ± SD and quantified from triplicates. Two-way ANOVA tests were performed. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. (e-g) HT-144 cells were transfected with ASO-4 (5 nM) and then treated with vemurafenib (100 nM) in 1% ITS medium for one day. RT-qPCR assay analyzed DNFA gene expression from treatment groups relative to expression under ASO-Neg and DMSO treatment at day 1 (normalized as 1). Data are presented as mean ± SD and quantified from triplicates. One-way ANOVA tests were performed. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. www.nature.com/scientificreports www.nature.com/scientificreports/ SREBP1 processing is downregulated in vemurafenib-responsive cells, while BRAFi-resistant melanoma cells maintain SREBP1 processing to protect them from ROS-induced cell death. We find that (1) BRAFi treatment is associated with DNFA stimulation in a dose-response relationship and (2) elevated DNFA gene expression is a vital survival trait of melanoma cells both before and after they achieve resistance to combined BRAF/MEK inhibition. A speculative explanation is that, compared to cells vulnerable to BRAFi treatment, resistant cells achieve a state that relies more on DNFA activities and less on BRAF activities. We suspect that increased PI3K/ AKT signaling activates SREBP1 and DNFA for survival in BRAFi-resistant melanoma cells 79 . There is ongoing investigation to demonstrate mechanisms of cell state-related drug resistance.
In summary, our work demonstrates that melanomas engage the DNFA pathway for cell survival -more so during drug resistance -and employs SREBP1 to promote transcription activation and elongation of DNFA enzyme genes. Although immunotherapy has emerged as a highly promising treatment for a subset of melanoma patients 93 , it may be hampered by significant complications 94 . SREBP1 and/or DNFA enzyme inhibition may represent potential therapeutic alternatives worthy of further exploration for the treatment of melanoma and possibly other cancer types characterized by elevated DNFA.
The BRAF inhibitor vemurafenib (S1267) and ERK inhibitor SCH772984 (S7101) were purchased from Selleck Chemicals. Dabrafenib was kindly provided by R. Corcoran at MGH. SCD inhibitor MF-438 (569406, Sigma) and FASN inhibitor GSK 2194069 (5303, Tocris) were dissolved in dimethyl sulfoxide (DMSO) to yield 50 mM stock solutions for in vitro studies. To generate vemurafenib-resistant cells, parental cells were exposed to increasing concentrations of vemurafenib (from 1 μM to 2 μM) for three months. The resistance was confirmed by measuring cell viability under vemurafenib treatment.

Plasmids, siRNAs and
Reverse transcription quantitative PCR (RT-qPCR) and RNA-Seq assays. RNAs were isolated from cultured cells using the RNeasy Mini Kit (Qiagen). RNAs were treated with RNase-free DNase (Qiagen). RNA concentrations were quantified with Qubit RNA BR Assay Kit (Thermo Fisher Scientific). One μg RNAs were used for cDNA synthesis with RNA to cDNA EcoDry Premix (TaKaRa) containing both random hexamer and oligo(dT) 18 primers (Double Primed). qPCR was carried out in triplicates on a LightCycler 480 (Roche) using LightCycler 480 SYBR Green I Master (Roche). qPCR primers were designed by MGH primer bank (https:// pga.mgh.harvard.edu/primerbank/) and the primer sequences are listed in Table 1. Relative gene expression was calculated with the 2 −ΔΔCt method 98 , and normalized to the 18S housekeeping gene. The mean of negative control samples was set to 1.

RNA-Seq and ChIP-Seq analyses.
For RNA-Seq, Illumina sequencing reads (FASTQ files) were checked with FASTQC for quality control and then aligned to the human genome (GRCh38.86). Genome index generation and sequence alignment were performed using STAR software 99 , followed by sorting and indexing of BAM files with SAMtools. Raw counts of reads mapped to genes were calculated using HT-Seq 100 . Differential expression analysis was performed using DESeq2 R package 101 . KEGG pathway analysis of differentially expressed gene lists and principal component analysis (PCA) were performed using functions within DESeq2. The complete RNA-Seq data set has been submitted to the National Center for Biotechnology Information (NCBI) in the Gene Expression Omnibus (GEO) database (series entry GSE122707). SREBP1 ChIP-Seq in multiple cancer cell lines were previously published 102 . Bam files of SREBP1 and IgG control ChIP-Seq from the same cell lines were downloaded from ENCODE (https://www.encodeproject.org). SREBP1 binding peaks were called with Model-based Analysis of ChIP-Seq (MACS) and then annotated with ChIPseeker R package 103 . We performed de novo motif analysis of the SREBP1-binding sites with HOMER software (http://homer.ucsd.edu/homer/). Overlapping genes between RNA-Seq and ChIP-Seq datasets were identified by BioVenn 104 . Pathway annotation network analysis was performed on Cytoscape using ClueGo with REACTOME pathway 105 .  Table 2. The primers used for ChIP-qPCR assays.