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In Silico Logical Modelling to Uncover Cooperative Interactions in Cancer.

ABSTRACT: The multistep development of cancer involves the cooperation between multiple molecular lesions, as well as complex interactions between cancer cells and the surrounding tumour microenvironment. The search for these synergistic interactions using experimental models made tremendous contributions to our understanding of oncogenesis. Yet, these approaches remain labour-intensive and challenging. To tackle such a hurdle, an integrative, multidisciplinary effort is required. In this article, we highlight the use of logical computational models, combined with experimental validations, as an effective approach to identify cooperative mechanisms and therapeutic strategies in the context of cancer biology. In silico models overcome limitations of reductionist approaches by capturing tumour complexity and by generating powerful testable hypotheses. We review representative examples of logical models reported in the literature and their validation. We then provide further analyses of our logical model of Epithelium to Mesenchymal Transition (EMT), searching for additional cooperative interactions involving inputs from the tumour microenvironment and gain of function mutations in NOTCH.

SUBMITTER: Selvaggio G

PROVIDER: S-EPMC8125147 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Bacteriophages (phages) have been proposed as alternative therapeutics for the treatment of multidrug-resistant bacterial infections. However, there are major gaps in our understanding of the molecular events in bacterial cells that control how bacteria respond to phage predation. Using the model organism Enterococcus faecalis, we used two distinct genomic approaches, namely, transposon library screening and RNA sequencing, to investigate the interaction of E. faecalis with a virulent phage. We discovered that a transcription factor encoding a LytR family response regulator controls the expression of enterococcal polysaccharide antigen (epa) genes that are involved in phage infection and bacterial fitness. In addition, we discovered that DNA mismatch repair mutants rapidly evolve phage adsorption deficiencies, underpinning a molecular basis for epa mutation during phage infection. Transcriptomic profiling of phage-infected E. faecalis revealed broad transcriptional changes influencing viral replication and progeny burst size. We also demonstrate that phage infection alters the expression of bacterial genes associated with intra- and interbacterial interactions, including genes involved in quorum sensing and polymicrobial competition. Together, our results suggest that phage predation has the potential to influence complex microbial behavior and may dictate how bacteria respond to external environmental stimuli. These responses could have collateral effects (positive or negative) on microbial communities, such as the host microbiota, during phage therapy.IMPORTANCE We lack fundamental understanding of how phage infection influences bacterial gene expression and, consequently, how bacterial responses to phage infection affect the assembly of polymicrobial communities. Using parallel genomic approaches, we have discovered novel transcriptional regulators and metabolic genes that influence phage infection. The integration of whole-genome transcriptomic profiling during phage infection has revealed the differential regulation of genes important for group behaviors and polymicrobial interactions. Our work suggests that therapeutic phages could more broadly influence bacterial community composition outside their intended host targets.

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In Silico Logical Modelling to Uncover Cooperative Interactions in Cancer.

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