Biology subjects

Comas, I.

Publications and source records attributed to Comas, I..

3 recordsLinked to original sources

bioRxiv2018

Pervasive contaminations in sequencing experiments are a major source of false genetic variability: a Mycobacterium tuberculosis meta-analysis

Contaminant DNA is a well-known confounding factor in molecular biology and in genomic repositories. Strikingly, analysis workflows for whole-genome sequencing (WGS) data usually neglect the errors introduced by potential contaminations. We performed a comprehensive evaluation of the extent and impact of contaminant DNA in WGS by analyzing more than 4,000 bacterial samples from 20 different studies. We found that contaminations are pervasive and can introduce large biases in variant analysis. We showed that these biases can translate in hundreds of false positive and negative SNPs, even for samples with slight contaminations. Studies investigating complex biological traits from sequencing data can be completely biased if contaminations are neglected during the bioinformatic analysis. We used both real and simulated data to evaluate and implement reliable, contamination-aware analysis pipelines. Our results urge for the implementation of such pipelines as sequencing technologies consolidate as a precision tool in the research and clinical context.

genomics↗

bioRxiv2018

Genomic determinants of sympatric speciation of the Mycobacterium tuberculosis complex across evolutionary timescales.

BACKGROUNDModels on how bacterial lineages differentiate increase our understanding on early bacterial speciation events and about the genetic loci involved. Here, we analyze the population genomics events leading to the emergence of the tuberculosis pathogen.\n\nRESULTSThe emergence is characterized by a combination of recombination events involving core pathogenesis functions and purifying selection on early diverging loci. We identify the phoR gene, the sensor kinase of a two-component system involved in virulence, as a key functional player subject to pervasive positive selection after the divergence of the MTBC from its ancestor. Previous evidence showed that phoR mutations played a central role in the adaptation of the pathogen to different host species. Now we show that phoR have been under selection during the early spread of human tuberculosis, during later expansions and in on-going transmission events.\n\nCONCLUSIONSOur results show that linking pathogen evolution across evolutionary and epidemiological timescales point to past and present virulence determinants.

evolutionary biology↗

bioRxiv2016

Gene expression models based on a reference laboratory strain are bad predictors of Mycobacterium tuberculosis complex transcriptional diversity.

Species of the Mycobacterium tuberculosis complex (MTBC) kill more people every year than any other infectious disease. As a consequence of its global distribution and parallel evolution with the human host the bacteria is not genetically homogeneous. The observed genetic heterogeneity has relevance at different phenotypic levels, from gene expression to epidemiological dynamics. However current systems biology datasets have focused in the laboratory reference strain H37Rv. By using large expression datasets testing the role of almost two hundred transcription factors, we have constructed computational models to grab the expression dynamics of Mycobacterium tuberculosis H37Rv genes. However, we have found that many of those transcription factors are deleted or likely dysfunctional across strains of the MTBC. In accordance, we failed to predict expression changes in strains with a different genetic background when compared with experimental data. The results highlight the importance of designing systems biology approaches that take into account the tubercle bacilli, or any other pathogen, genetic diversity if we want to identify universal targets for vaccines, diagnostics and treatments.

systems biology↗