April 21, 2020  |  

The use of Online Tools for Antimicrobial Resistance Prediction by Whole Genome Sequencing in MRSA and VRE.

The antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly-available web-based AMR databases, whole genome sequencing (WGS) offers the capacity for rapid detection of antibiotic resistance genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility testing results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin resistant Enterococcus (VRE) clinical isolates using publicly-available tools and databases.Clinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. Antibiotic resistance gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between WGS-predicted resistance profile and phenotypic susceptibility as well as sensitivity, specificity, positive and negative predictive values (NPV, PPV) were calculated for each antibiotic/organism combination, using the phenotypic results as the gold standard.Phenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3% with a sensitivity, specificity, PPV, NPV of 98.7% (95% CI, 97.2-99.5%), 99.6% (95 % CI, 98.8-99.9%), 99.3% (95% CI, 98.0-99.8%), 99.2% (95% CI, 98.3-99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4% and the sensitivity to 99.3% (95% CI, 98.2-99.8%) and NPV to 99.4% (95% CI, 98.4-99.8%).WGS can be used as a reliable predicator of phenotypic resistance for both MRSA and VRE using readily-available online tools.Copyright © 2019. Published by Elsevier Ltd.


April 21, 2020  |  

Genome-wide mutational biases fuel transcriptional diversity in the Mycobacterium tuberculosis complex.

The Mycobacterium tuberculosis complex (MTBC) members display different host-specificities and virulence phenotypes. Here, we have performed a comprehensive RNAseq and methylome analysis of the main clades of the MTBC and discovered unique transcriptional profiles. The majority of genes differentially expressed between the clades encode proteins involved in host interaction and metabolic functions. A significant fraction of changes in gene expression can be explained by positive selection on single mutations that either create or disrupt transcriptional start sites (TSS). Furthermore, we show that clinical strains have different methyltransferases inactivated and thus different methylation patterns. Under the tested conditions, differential methylation has a minor direct role on transcriptomic differences between strains. However, disruption of a methyltransferase in one clinical strain revealed important expression differences suggesting indirect mechanisms of expression regulation. Our study demonstrates that variation in transcriptional profiles are mainly due to TSS mutations and have likely evolved due to differences in host characteristics.


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