Long chain monomethyl branched-chain fatty acid levels in human milk vary with gestational weight gain

Breastfeeding is an important determinant of infant health and there is immense interest in understanding its metabolite composition so that key beneficial components can be identified. The aim of this research was to measure the fatty acid composition of human milk in an Irish cohort where we examined changes depending on lactation stage and gestational weight gain trajectory. Utilizing a chromatography approach optimal for isomer separation, we identified 44 individual fatty acid species via GCMS and showed that monomethyl branched-chain fatty acids(mmBCFA's), C15:0 and C16:1 are lower in women with excess gestational weight gain versus low gestational weight gain. To further explore the potential contribution of the activity of endogenous metabolic pathways to levels of these fatty acids in milk, we administered D2O to C57BL/6J dams fed a purified lard based high fat diet (HFD) or low-fat diet during gestation and quantified the total and de novo synthesized levels of fatty acids in their milk. We found that de novo synthesis over three days can account for between 10 and 50 % of mmBCFAs in milk from dams on the low-fat diet dependent on the branched-chain fatty acid species. However, HFD fed mice had significantly decreased de novo synthesized fatty acids in milk resulting in lower total mmBCFAs and medium chain fatty acid levels. Overall, our findings highlight the diverse fatty acid composition of human milk and that human milk mmBCFA levels differ between gestational weight gain phenotypes. In addition, our data indicates that de novo synthesis contributes to mmBCFA levels in mice milk and thus may also be a contributory factor to mmBCFA levels in human milk. Given emerging data indicating mmBCFAs may be beneficial components of milk, this study contributes to our knowledge around the phenotypic factors that may impact their levels.

Norovirus NS1/2 protein increases glutaminolysis for efficient viral replication

Viruses are obligate intracellular parasites that rely on host cell metabolism for successful replication. Thus, viruses rewire host cell pathways involved in central carbon metabolism to increase the availability of building blocks for replication. However, the underlying mechanisms of virus-induced alterations to host metabolism are largely unknown. Noroviruses (NoVs) are highly prevalent pathogens that cause sporadic and epidemic viral gastroenteritis. In the present study, we uncovered several strain-specific and shared host cell metabolic requirements of three murine norovirus (MNV) strains, the acute MNV-1 strain and the persistent CR3 and CR6 strains. While all three strains required glycolysis, glutaminolysis, and the pentose phosphate pathway for optimal infection of macrophages, only MNV-1 relied on host oxidative phosphorylation. Furthermore, the first metabolic flux analysis of NoV-infected cells revealed that both glycolysis and glutaminolysis are upregulated during MNV-1 infection of macrophages. Glutamine deprivation affected the MNV lifecycle at the stage of genome replication, resulting in decreased non-structural and structural protein synthesis, viral assembly, and egress. Mechanistic studies further showed that MNV infection and overexpression of the MNV non-structural protein NS1/2 increased the enzymatic activity of the rate-limiting enzyme glutaminase. In conclusion, the inaugural investigation of NoV-induced alterations to host glutaminolysis identified the first viral regulator of glutaminolysis for RNA viruses, which increases our fundamental understanding of virus-induced metabolic alterations.

Metabolic collateral lethal target identification reveals MTHFD2 paralogue dependency in ovarian cancer

Recurrent loss-of-function deletions cause frequent inactivation of tumour suppressor genes but often also involve the collateral deletion of essential genes in chromosomal proximity, engendering dependence on paralogues that maintain similar function. Although these paralogues are attractive anticancer targets, no methodology exists to uncover such collateral lethal genes. Here we report a framework for collateral lethal gene identification via metabolic fluxes, CLIM, and use it to reveal MTHFD2 as a collateral lethal gene in UQCR11-deleted ovarian tumours. We show that MTHFD2 has a non-canonical oxidative function to provide mitochondrial NAD+, and demonstrate the regulation of systemic metabolic activity by the paralogue metabolic pathway maintaining metabolic flux compensation. This UQCR11-MTHFD2 collateral lethality is confirmed in vivo, with MTHFD2 inhibition leading to complete remission of UQCR11-deleted ovarian tumours. Using CLIM's machine learning and genome-scale metabolic flux analysis, we elucidate the broad efficacy of targeting MTHFD2 despite distinct cancer genetic profiles co-occurring with UQCR11 deletion and irrespective of stromal compositions of tumours.

Driving with Both Feet: Supplementing AKG While Inhibiting BCAT1 Leads to Synthetic Lethality in GBM

Understanding how carcinogenesis can expose cancers to synthetically lethal vulnerabilities has been an essential underpinning of development of modern anticancer therapeutics. Isocitrate dehydrogenase wild-type (IDHWT) glioblastoma multiforme (GBM), which is known to have upregulated branched-chain amino acid transaminase 1 (BCAT1) expression, has not had treatments developed to the same extent as the IDH mutant counterpart, despite making up the majority of cases. In this issue, Zhang and colleagues utilize a metabolic screen to identify α-ketoglutarate (AKG) as a synthetically lethal treatment in conjunction with BCAT1 inhibition in IDHWT GBM. These treatments synergize in a multipronged approach that limits substrate catabolism and disrupts mitochondrial homeostasis through perturbing the balance of NAD+/NADH, leading to mTORC1 inhibition and a reduction of nucleotide biosynthesis. Based on these results, the authors propose combination treatment targeting branched chain amino acid catabolism as a potential option for patients with IDHWT GBM. See related article by Zhang et al., p. 2388.

Abstract 236: Genomic loss in cancers enable discovery of metabolic targets for precision cancer therapy via multiobjective flux analysis and machine learning

Large-scale chromosomal alterations, particularly chromosomal deletions in cancer genomes confer functional advantages to cancer cells via the loss of tumor suppressor genes (TSGs). However, due to the nature of these focal and arm-level deletions, essential house-keeping genes in the neighborhood of TSGs are potentially lost. We explore the emergence of metabolic adaptations and vulnerabilities that arise due to the collateral loss of essential metabolic genes. In our previous work, we showed that genomic loss in the locus containing SMAD4 and ME2 in pancreatic ductal adenocarcinomas forces these cells to rely on ME3 to compensate for the collateral loss of ME2; thereby revealing a highly selective metabolic target in these cells. Cancer cells can not only exploit such genetic redundancies but also rely on redundancies built into their complex metabolic network to compensate for the loss of metabolic function. Importantly, there is an unexplored landscape of these genomic loss events beyond well-characterized TSGs. To address these challenges, we have developed a platform to identify patient-specific metabolic vulnerabilities emerging due to distinct patterns of genomic loss events across tumors. Our platform presents opportunities for precision-based therapeutic intervention by targeting metabolic vulnerabilities in cancer patients. It uses genomic and clinical data available in cancer patient databases to obtain candidate metabolic genes that are lost to genomic deletions in an unbiased manner. To delineate metabolic redundances and tackle the complexity of genome-scale metabolic models, we employ an innovative multi-objective metabolic flux analysis approach. The utility of this platform is demonstrated via the discovery of a novel metabolic target in a cohort of ovarian cancer patients. The predicted collateral lethal target is validated in vitro using RNA interference and small-molecule inhibitors. Furthermore, we verify the metabolic mechanism of vulnerability predicted by the algorithm using deuterium tracing experiments. The target is also validated in vivo with mice containing ovarian tumors derived from cancer cells with and without the genomic deletion. Surprisingly, the collateral lethal metabolic target was also found to exist in a subset of aggressive endometrial cancers. Finally, we developed a multi-layer machine learning model to predict occurrence of the particular genomic deletion in ovarian and endometrial cancer patients with minimal molecular information to remove the need for whole-genome sequencing data. The model was trained and tested using the publicly-available molecular data from TCGA and AACR GENIE datasets.

Citation Format: Abhinav Achreja, Tao Yu, Anjali Mittal, Srinadh Choppara, Noah Meurs, Olamide Animasahun, Jin Heon Jeon, Aradhana Mohan, Anusha Jayaraman, Reva Kulkarni, Justin Reinhold, Michele Cusato, Analisa Difeo, Xiongbin Lu, Deepak Nagrath. Genomic loss in cancers enable discovery of metabolic targets for precision cancer therapy via multiobjective flux analysis and machine learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 236.

Dairy Fat Intake, Plasma Pentadecanoic Acid, and Plasma Iso-heptadecanoic Acid Are Inversely Associated With Liver Fat in Children

OBJECTIVES

We sought to evaluate the relevance of pediatric dairy fat recommendations for children at risk for nonalcoholic fatty liver disease (NAFLD) by studying the association between dairy fat intake and the amount of liver fat. The effects of dairy fat may be mediated by odd chain fatty acids (OCFA), such as pentadecanoic acid (C15:0), and monomethyl branched chain fatty acids (BCFA), such as iso-heptadecanoic acid (iso-C17:0). Therefore, we also evaluated the association between plasma levels of OCFA and BCFA with the amount of liver fat.

METHODS

Observational, cross-sectional, community-based sample of 237 children ages 8 to 17. Dairy fat intake was assessed by 3 24-hour dietary recalls. Plasma fatty acids were measured by gas chromatography-mass spectrometry. Main outcome was hepatic steatosis measured by whole liver magnetic resonance imaging proton density fat fraction (MRI-PDFF).

RESULTS

Median dairy fat intake was 10.6 grams/day (range 0.0--44.5 g/day). Median liver MRI-PDFF was 4.5% (range 0.9%-45.1%). Dairy fat intake was inversely correlated with liver MRI-PDFF (r = -0.162; P = .012). In multivariable log linear regression, plasma C15:0 and iso-C17:0 were inverse predictors of liver MRI-PDFF (B = -0.247, P = 0.048; and B = -0.234, P = 0.009).

CONCLUSIONS

Dairy fat intake, plasma C15:0, and plasma iso-C17:0 were inversely correlated with hepatic steatosis in children. These hypothesis-generating findings should be tested through clinical trials to better inform dietary guidelines.

Tumour-reprogrammed stromal BCAT1 fuels branched-chain ketoacid dependency in stromal-rich PDAC tumours

Branched-chain amino acids (BCAAs) supply both carbon and nitrogen in pancreatic cancers, and increased levels of BCAAs have been associated with increased risk of pancreatic ductal adenocarcinomas (PDACs). It remains unclear, however, how stromal cells regulate BCAA metabolism in PDAC cells and how mutualistic determinants control BCAA metabolism in the tumour milieu. Here, we show distinct catabolic, oxidative and protein turnover fluxes between cancer-associated fibroblasts (CAFs) and cancer cells, and a marked reliance on branched-chain α-ketoacid (BCKA) in PDAC cells in stroma-rich tumours. We report that cancer-induced stromal reprogramming fuels this BCKA demand. The TGF-β-SMAD5 axis directly targets BCAT1 in CAFs and dictates internalization of the extracellular matrix from the tumour microenvironment to supply amino-acid precursors for BCKA secretion by CAFs. The in vitro results were corroborated with circulating tumour cells (CTCs) and PDAC tissue slices derived from people with PDAC. Our findings reveal therapeutically actionable targets in pancreatic stromal and cancer cells.

Quantifying Metabolic Transfer Mediated by Extracellular Vesicles Using Exo-MFA: An Integrated Empirical and Computational Platform

Extracellular vesicles (EVs) are ubiquitous nanoscale particles released from many different types of cells. They have been shown to contain proteins, DNA, RNA, miRNA, and, most recently, metabolites. These particles can travel through the intercellular space and bloodstream to have regulatory effects on distant recipients. When an EV reaches a target cell, it is taken up and degraded to release its contents for utilization within the cell. In addition to regulatory effects, EVs have been shown to supplement the high metabolic demands of recipient cells in a nutrient-deprived tumor microenvironment. We developed an integrated empirical and computational platform to quantify metabolic contribution of source cell-derived EVs to recipient cells. The versatile Exo-MFA software tool utilizes 13C stable-isotope tracing data to quantify the metabolic contributions of EVs from a source cell type on a recipient cell type. This is accomplished by creating EV-depleted culture medium, producing isotope-labeled EVs from the source cells, isolating the labeled EVs from the culture supernatant, culturing the recipient cells in the presence of the labeled EVs, and measuring the resulting metabolite levels across several time points.

Generation of Human Fatty Livers Using Custom-Engineered Induced Pluripotent Stem Cells with Modifiable SIRT1 Metabolism

The mechanisms by which steatosis of the liver progresses to non-alcoholic steatohepatitis and end-stage liver disease remain elusive. Metabolic derangements in hepatocytes controlled by SIRT1 play a role in the development of fatty liver in inbred animals. The ability to perform similar studies using human tissue has been limited by the genetic variability in man. We generated human induced pluripotent stem cells (iPSCs) with controllable expression of SIRT1. By differentiating edited iPSCs into hepatocytes and knocking down SIRT1, we found increased fatty acid biosynthesis that exacerbates fat accumulation. To model human fatty livers, we repopulated decellularized rat livers with human mesenchymal cells, fibroblasts, macrophages, and human SIRT1 knockdown iPSC-derived hepatocytes and found that the human iPSC-derived liver tissue developed macrosteatosis, acquired proinflammatory phenotype, and shared a similar lipid and metabolic profiling to human fatty livers. Biofabrication of genetically edited human liver tissue may become an important tool for investigating human liver biology and disease.

Enzyme promiscuity drives branched-chain fatty acid synthesis in adipose tissues

Fatty acid synthase (FASN) predominantly generates straight-chain fatty acids using acetyl-CoA as the initiating substrate. However, monomethyl branched-chain fatty acids (mmBCFAs) are also present in mammals but are thought to be primarily diet derived. Here we demonstrate that mmBCFAs are de novo synthesized via mitochondrial BCAA catabolism, exported to the cytosol by adipose-specific expression of carnitine acetyltransferase (CrAT), and elongated by FASN. Brown fat exhibits the highest BCAA catabolic and mmBCFA synthesis fluxes, whereas these lipids are largely absent from liver and brain. mmBCFA synthesis is also sustained in the absence of microbiota. We identify hypoxia as a potent suppressor of BCAA catabolism that decreases mmBCFA synthesis in obese adipose tissue, such that mmBCFAs are significantly decreased in obese animals. These results identify adipose tissue mmBCFA synthesis as a novel link between BCAA metabolism and lipogenesis, highlighting roles for CrAT and FASN promiscuity influencing acyl-chain diversity in the lipidome.

ATP-Citrate Lyase Controls a Glucose-to-Acetate Metabolic Switch

Mechanisms of metabolic flexibility enable cells to survive under stressful conditions and can thwart therapeutic responses. Acetyl-coenzyme A (CoA) plays central roles in energy production, lipid metabolism, and epigenomic modifications. Here, we show that, upon genetic deletion of Acly, the gene coding for ATP-citrate lyase (ACLY), cells remain viable and proliferate, although at an impaired rate. In the absence of ACLY, cells upregulate ACSS2 and utilize exogenous acetate to provide acetyl-CoA for de novo lipogenesis (DNL) and histone acetylation. A physiological level of acetate is sufficient for cell viability and abundant acetyl-CoA production, although histone acetylation levels remain low in ACLY-deficient cells unless supplemented with high levels of acetate. ACLY-deficient adipocytes accumulate lipid in vivo, exhibit increased acetyl-CoA and malonyl-CoA production from acetate, and display some differences in fatty acid content and synthesis. Together, these data indicate that engagement of acetate metabolism is a crucial, although partial, mechanism of compensation for ACLY deficiency.