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Trigos, A. S.

Publications and source records attributed to Trigos, A. S..

2 recordsLinked to original sources

Somatic mutations in early metazoan genes disrupt regulatory links between unicellular and multicellular genes in cancer

Extensive transcriptional alterations are observed in cancer, many of which activate core biological processes established in unicellular organisms or suppress differentiation pathways formed in metazoans. Through rigorous, integrative analysis of genomics data from a range of solid tumours, we show many transcriptional changes in tumours are tied to mutations disrupting regulatory interactions between unicellular and multicellular genes within human gene regulatory networks (GRNs). Recurrent point mutations were enriched in regulator genes linking unicellular and multicellular subnetworks, while copy-number alterations affected downstream target genes in distinctly unicellular and multicellular regions of the GRN. Our results depict drivers of tumourigenesis as genes that created key regulatory links during the evolution of early multicellular life, whose dysfunction creates widespread dysregulation of primitive elements of the GRN. Several genes we identified as important in this process were associated with drug response, demonstrating the potential clinical value of our approach.

cancer biology

Collateral sensitivity to β-lactam drugs in drug-resistant tuberculosis is driven by the transcriptional wiring of BlaI operon genes

BackgroundThe evolution and spread of antimicrobial resistance is a major global public health threat. In some cases the evolution of resistance to one antimicrobial seemingly results in enhanced sensitivity to another (known as collateral sensitivity). This largely underexplored phenomenon represents a fascinating evolutionary paradigm that opens new therapeutic possibilities for patients infected with pathogens unresponsive to classical treatments. Intrinsic resistance to {beta}-lactams in Mycobacterium tuberculosis (Mtb, the causative agent of tuberculosis) has traditionally curtailed the use of these low-cost and easy-to-administer drugs for tuberculosis treatment. Recently, {beta}-lactam sensitivity has been reported in strains resistant to classical tuberculosis drug therapy, leading to a resurgence of interest in using {beta}-lactams in the clinic. Unfortunately though, there remains a limited understanding of the mechanisms driving {beta}-lactam sensitivity.\n\nMethodsWe used a novel combination of systems biology and computational approaches to characterize the molecular underpinnings of {beta}-lactam sensitivity in Mtb. We performed differential gene expression and coexpression analyses of genes previously associated with {beta}-lactam sensitivity and genes associated with resistance to classical tuberculosis drugs. Protein-protein interaction and gene regulatory network analyses were used to validate regulatory interactions between these genes, and random walks through the networks identified key mediators of these interactions. Further validation was obtained using functional in silico knockout of gene pairs.\n\nResultsOur results reveal up regulation of the key regulatory inhibitor of {beta}-lactamase production, blal, following treatment with classical drugs. Co-expression and network analyses showed direct co-regulation between genes associated with {beta}-lactam sensitivity and those associated with resistance to classical tuberculosis treatment. blal and its downstream genes (sigC and atpH) were found to be key mediators of these interactions.\n\nConclusionsOur results support the hypothesis that Mtb {beta}-lactam sensitivity is a collateral consequence of the evolution of resistance to classical tuberculosis drugs, mediated through changes to transcriptional regulation. These findings support continued exploration of {beta}-lactams for the treatment of tuberculosis, particularly for patients infected with strains resistant to classical therapies that are otherwise difficult to treat. Importantly, this work also highlights the potential of systems-level and network biology approaches to improve our understanding of collateral drug sensitivity.

microbiology