Background: N‐4 cytidine acetylation (ac4C) is an epitranscriptomics modification catalyzed by N‐acetyltransferase 10 (NAT10); important for cellular mRNA stability, rRNA biogenesis, cell proliferation and epithelial to mesenchymal transition (EMT). However, whether other crucial pathways are regulated by NAT10‐dependent ac4C modification in cancer cells remains unclear. Therefore, in this study, we explored the impact of NAT10 depletion in cancer cells using unbiased RNA‐seq.Methods: High‐throughput sequencing of knockdown NAT10 in cancer cells was conducted to identify enriched pathways. Acetylated RNA immunoprecipitation‐seq (acRIP‐seq) and RIP‐PCR were used to map and determine ac4C levels of RNA. Exogenous palmitate uptake assay was conducted to assess NAT10 knockdown cancer cells using Oil Red O staining and lipid content analysis. Gas‐chromatography–tandem mass spectroscopy (GC/MS) was used to perform untargeted lipidomics.Results: High‐throughput sequencing of NAT10 knockdown in cancer cells revealed fatty acid (FA) metabolism as the top enriched pathway through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in differentially downregulated genes. FA metabolic genes such as ELOLV6, ACSL1, ACSL3, ACSL4, ACADSB and ACAT1 were shown to be stabilised via NAT10‐dependent ac4C RNA acetylation. Additionally, NAT10 depletion was shown to significantly reduce the levels of overall lipid content, triglycerides and total cholesterol. Further, NAT10 depletion in palmitate‐loaded cancer cells showed decrease in ac4C levels across the RNA transcripts of FA metabolic genes. In untargeted lipidomics, 496 out of 2 279 lipids were statistically significant in NAT10 depleted cancer cells, of which pathways associated with FA metabolism are the most enriched.Conclusions: Conclusively, our results provide novel insights into the impact of NAT10‐mediated ac4C modification as a crucial regulatory factor during FA metabolism and showed the benefit of targeting NAT10 for cancer treatment.

Information regarding transcriptome and metabolome has significantly contributed to identifying potential therapeutic targets for the management of a variety of cancers. Obesity has profound effects on both cancer cell transcriptome and metabolome that can affect the outcome of cancer therapy. The information regarding the potential effects of obesity on breast cancer (BC) transcriptome, metabolome, and its integration to identify novel pathways related to disease progression are still elusive. We assessed the whole blood transcriptome and serum metabolome, as circulating metabolites, of obese BC patients compared them with non-obese BC patients. In these patients' samples, 186 significant differentially expressed genes (DEGs) were identified, comprising 156 upregulated and 30 downregulated. The expressions of these gene were confirmed by qRT-PCR. Furthermore, 96 deregulated metabolites were identified as untargeted metabolomics in the same group of patients. These detected DEGs and deregulated metabolites enriched in many cellular pathways. Further investigation, by integration analysis between transcriptomics and metabolomics data at the pathway levels, revealed seven unique enriched pathways in obese BC patients when compared with non-obese BC patients, which may provide resistance for BC cells to dodge the circulating immune cells in the blood. In conclusion, this study provides information on the unique pathways altered at transcriptome and metabolome levels in obese BC patients that could provide an important tool for researchers and contribute further to knowledge on the molecular interaction between obesity and BC. Further studies are needed to confirm this and to elucidate the exact underlying mechanism for the effects of obesity on the BC initiation or/and progression.

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Venetoclax (ABT199) is a selective B-cell lymphoma 2 (BCL-2) inhibitor. The US FDA recently approved it to be used in combination with low-dose cytarabine or hypomethylating agents in acute myeloid leukemia (AML) or elderly patients non-eligible for chemotherapy. However, acquiring resistance to venetoclax in AML patients is the primary cause of treatment failure. To understand the molecular mechanisms inherent in the resistance to BCL-2 inhibitors, we generated a venetoclax-resistant cell line model and assessed the consequences of this resistance on its metabolic pathways. Untargeted metabolomics data displayed a notable impact of resistance on the PI3K/AKT pathway, the Warburg effect, glycolysis, the TCA cycle, and redox metabolism. The resistant cells showed increased NADPH and reduced glutathione levels, switching their energy metabolism towards glycolysis. PI3K/AKT pathway inhibition shifted resistant cells towards oxidative phosphorylation (OXPHOS). Our results provide a metabolic map of resistant cells that can be used to design novel metabolic targets to challenge venetoclax resistance in AML.