New preprint: Transcribed enhancers during M.tb infection at bioRxiv.

Schmeier Research Group // Massey University

PREPRINT · TUBERCULOSIS · ENHANCER · NCRNA

Transcribed enhancers in the macrophage immune response to Mycobacterium tuberculosis infection

Tuberculosis (TB) remains a major public health threat and cause of death worldwide. Macrophages are immune cells that compose the first line of an organism’s defence against Mycobacterium tuberculosis (M.tb), the causative agent of TB. Interactions between macrophages and M.tb define the infection outcome. Enhancers are cis-regulatory DNA elements that activate transcription of target genes and mediate various responses in macrophages. To what extent the host’s genetic response to infection is controlled by enhancers remains unexplored. We analysed the regulation by transcribed enhancers in M.tb-infected mouse bone marrow-derived macrophages. We found that transcribed enhancers have a strong influence in the M.tb infection response and mediate up-regulation of many important immune genes. We characterise highly transcriptionally induced enhancers and show that many genes acquire de novo transcribed enhancers upon M.tb infection. We report enhancers targeting known immune genes crucial for the host’s genetic response to M.tb, such as Tnf, Tnfrsf1b, Irg1, Hilpda, Ccl3, and Ccl4, and highlight transcription factors that are likely regulating these enhancers including AP-1, NF-kB, Irf1, and Rbpj. Finally, we highlight particular chromosomal domains carrying groups of highly transcriptionally induced enhancers and genes with previously unappreciated roles in M.tb infection, such as Fbxl3, Tapt1, Edn1, and Hivep1. Our study links M.tb-responsive transcription factors to activation of transcribed enhancers, which, in turn, target protein-coding immune genes upon infection. We find that many genes who respond with increased expression to M.tb are under the control of transcribed enhancers. Our findings extend current knowledge of M.tb-response regulation in macrophages and provide a basis for future functional studies on enhancer-gene interactions in this process.

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MinION Sequencing of colorectal cancer tumour microbiomes – a comparison with amplicon-based and RNA-Sequencing. PLoS One, 2020, accepted.

Molecular subtyping improves prognostication of Stage 2 colorectal cancer. BMC Cancer, 2019, 19, 1155

DeePEL: Deep learning architecture to recognize p-lncRNA and e-lncRNA promoters. In proceedings: IEEE International Conference on Bioinformatics and Biomedicine, 2019, B516, accepted.

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