Genetic determinants underlying the progressive phenotype of ß-lactam/ß-lactamase inhibitor resistance in Escherichia coli.

IMPORTANCE: The increased feasibility of whole-genome sequencing has generated significant interest in using such molecular diagnostic approaches to characterize difficult-to-treat, antimicrobial-resistant (AMR) infections. Nevertheless, there are current limitations in the accurate prediction of AMR phenotypes based on existing AMR gene database approaches, which primarily correlate a phenotype with the presence/absence of a single AMR gene. Our study utilized a large cohort of cephalosporin-susceptible Escherichia coli bacteremia samples to determine how increasing the dosage of narrow-spectrum ß-lactamase-encoding genes in conjunction with other diverse ß-lactam/ß-lactamase inhibitor (BL/BLI) genetic determinants contributes to progressively more severe BL/BLI phenotypes. We were able to characterize the complexity of the genetic mechanisms underlying progressive BL/BLI resistance including the critical role of ß-lactamase encoding gene amplification. For the diverse array of AMR phenotypes with complex mechanisms involving multiple genomic factors, our study provides an example of how composite risk scores may improve understanding of AMR genotype/phenotype correlations.

Xenomake: a pipeline for processing and sorting xenograft reads from spatial transcriptomic experiments.

Xenograft models are attractive models that mimic human tumor biology and permit one to perturb the tumor microenvironment and study its drug response. Spatially resolved transcriptomics (SRT) provide a powerful way to study the organization of xenograft models, but currently there is a lack of specialized pipeline for processing xenograft reads originated from SRT experiments. Xenomake is a standalone pipeline for the automated handling of spatial xenograft reads. Xenomake handles read processing, alignment, xenograft read sorting, quantification, and connects well with downstream spatial analysis packages. We additionally show that Xenomake can correctly assign organism specific reads, reduce sparsity of data by increasing gene counts, while maintaining biological relevance for studies.

Temporal dynamics of genetically heterogeneous extended-spectrum cephalosporin-resistant Escherichia coli bloodstream infections.

Extended-spectrum cephalosporin-resistant Escherichia coli (ESC-R-Ec) is an urgent public health threat with sequence type clonal complex 131 (STc131), phylogroup B2 strains being particularly concerning as the dominant cause of ESC-R-Ec infections. To address the paucity of recent ESC-R-Ec molecular epidemiology data in the United States, we used whole-genome sequencing (WGS) to fully characterize a large cohort of invasive ESC-R-Ec at a tertiary care cancer center in Houston, Texas, collected from 2016 to 2020. During the study time frame, there were 1,154 index E. coli bloodstream infections (BSIs) of which 389 (33.7%) were ESC-R-Ec. Using time series analyses, we identified a temporal dynamic of ESC-R-Ec distinct from ESC-susceptible E. coli (ESC-S-Ec), with cases peaking in the last 6 months of the calendar year. WGS of 297 ESC-R-Ec strains revealed that while STc131 strains accounted for ~45% of total BSIs, the proportion of STc131 strains remained stable across the study time frame with infection peaks driven by genetically heterogeneous ESC-R-Ec clonal complexes. bla CTX-M variants accounted for most ß-lactamases conferring the ESC-R phenotype (89%; 220/248 index ESC-R-Ec), and amplification of bla CTX-M genes was widely detected in ESC-R-Ec strains, particularly in carbapenem non-susceptible, recurrent BSI strains. Bla CTX-M-55 was significantly enriched within phylogroup A strains, and we identified bla CTX-M-55 plasmid-to-chromosome transmission occurring across non-B2 strains. Our data provide important information regarding the current molecular epidemiology of invasive ESC-R-Ec infections at a large tertiary care cancer center and provide novel insights into the genetic basis of observed temporal variability for these clinically important pathogens. IMPORTANCE Given that E. coli is the leading cause of worldwide ESC-R Enterobacterales infections, we sought to assess the current molecular epidemiology of ESC-R-Ec using a WGS analysis of many BSIs over a 5-year period. We identified fluctuating temporal dynamics of ESC-R-Ec infections, which have also recently been identified in other geographical regions such as Israel. Our WGS data allowed us to visualize the stable nature of STc131 over the study period and demonstrate a limited but genetically diverse group of ESC-R-Ec clonal complexes are detected during infection peaks. Additionally, we provide a widespread assessment of ß-lactamase gene copy number in ESC-R-Ec infections and delineate mechanisms by which such amplifications are achieved in a diverse array of ESC-R-Ec strains. These data suggest that serious ESC-R-Ec infections are driven by a diverse array of strains in our cohort and impacted by environmental factors suggesting that community-based monitoring could inform novel preventative measures.

Temporal Dynamics of Genetically Heterogeneous Extended-Spectrum Cephalosporin Resistant Escherichia coli Bloodstream Infections.

Extended-spectrum cephalosporin resistant Escherichia coli (ESC-R- Ec ) is an urgent public health threat with sequence type clonal complex 131 (STc131), phylogroup B2 strains being particularly concerning as the dominant cause of ESC-R- Ec infections. To address the paucity of recent ESC-R- Ec molecular epidemiology data in the United States, we used whole genome sequencing (WGS) to fully characterize a large cohort of invasive ESC-R- Ec at a tertiary care cancer center in Houston, Texas collected from 2016-2020. During the study timeframe, there were 1154 index E. coli bloodstream infections (BSIs) of which 389 (33.7%) were ESC-R- Ec . Using time series analyses, we identified a temporal dynamic of ESC-R- Ec distinct from ESC-susceptible E. coli (ESC-S- Ec ), with cases peaking in the last six months of the calendar year. WGS of 297 ESC-R- Ec strains revealed that while STc131 strains accounted for ∼45% of total BSIs, the proportion of STc131 strains remained stable across the study time frame with infection peaks driven by genetically heterogeneous ESC-R- Ec clonal complexes. Bla CTX-M variants accounted for most ß-lactamases conferring the ESC-R phenotype (89%; 220/248 index ESC-R -Ec ), and amplification of bla CTX-M genes was widely detected in ESC-R- Ec strains, particularly in carbapenem non-susceptible, recurrent BSI strains. Bla CTX-M-55 was significantly enriched within phylogroup A strains, and we identified bla CTX-M-55 plasmid-to-chromosome transmission occurring across non-B2 strains. Our data provide important information regarding the current molecular epidemiology of invasive ESC-R- Ec infections at a large tertiary care cancer center and provide novel insights into the genetic basis of observed temporal variability for these clinically important pathogens. IMPORTANCE: Given that E. coli is the leading cause of worldwide ESC-R Enterobacterales infections, we sought to assess the current molecular epidemiology of ESC-R- Ec using a WGS analysis of many BSIs over a five-year period. We identified fluctuating temporal dynamics of ESC-R- Ec infections, which has also recently been identified in other geographical regions such as Israel. Our WGS data allowed us to visualize the stable nature of STc131 over the study period and demonstrate a limited, but genetically diverse group of ESC-R- Ec clonal complexes are detected during infection peaks. Additionally, we provide a widespread assessment of ß-lactamase gene copy number in ESC-R- Ec infections and delineate mechanisms by which such amplifications are achieved in a diverse array of ESC-R- Ec strains. These data suggest that serious ESC-R- Ec infections are driven by a diverse array of strains in our cohort and impacted by environmental factors suggesting that community-based monitoring could inform novel preventative measures.

Integrated analysis of population genomics, transcriptomics and virulence provides novel insights into Streptococcus pyogenes pathogenesis.

Streptococcus pyogenes causes 700 million human infections annually worldwide, yet, despite a century of intensive effort, there is no licensed vaccine against this bacterium. Although a number of large-scale genomic studies of bacterial pathogens have been published, the relationships among the genome, transcriptome, and virulence in large bacterial populations remain poorly understood. We sequenced the genomes of 2,101 emm28 S. pyogenes invasive strains, from which we selected 492 phylogenetically diverse strains for transcriptome analysis and 50 strains for virulence assessment. Data integration provided a novel understanding of the virulence mechanisms of this model organism. Genome-wide association study, expression quantitative trait loci analysis, machine learning, and isogenic mutant strains identified and confirmed a one-nucleotide indel in an intergenic region that significantly alters global transcript profiles and ultimately virulence. The integrative strategy that we used is generally applicable to any microbe and may lead to new therapeutics for many human pathogens.