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Greenberg, D. E.

Publications and source records attributed to Greenberg, D. E..

4 recordsLinked to original sources

Oligonucleotide genetics for Pseudomonas aeruginosa enables high throughput hypomorph screening

The continual advancement of genetic tools has been critical to our modern understanding of bacteria, with transposons, plasmids, and homologous recombination becoming workhorses of molecular microbiology. However, precisely specified reverse genetic approaches remain painstakingly slow and inaccessible, particularly in non-model strains. This reality is exemplified by the opportunistic pathogen, Pseudomonas aeruginosa (Pa), where conventional allelic exchange remains the dominant reverse genetic method. Here, we adapt a rapid genetic toolkit for use in Pa, relying directly on commercially available oligonucleotides (120 bases) to create precise genomic mutations through homologous recombination (i.e. oligo recombineering). Oligo Recombineering followed by Bxb-1 Integrase Targeting (ORBIT) uses a short attachment site for an integrating plasmid, which provides traditional antibiotic selection and can also carry flexible cargo. We establish Pa ORBIT works effectively for gene deletion without off target mutations, optimize protocol parameters (e.g. oligo length, electroporation), and demonstrate markerless and clean deletions. Importantly, our toolkit works well in clinical Pa strains as demonstrated by constructing efflux pump deletions in three different isolates. To test the high throughput capabilities of Pa ORBIT, we created over 160 degron-based hypomorphs (i.e. knockdowns) across 43 essential proteins in a pooled mutant library. Upon screening this library with and without antibiotics, we identify highly vulnerable essential proteins and hypomorphs that display synergy with clinical drugs. Therefore, ORBIT can be used for cutting edge low and high throughput investigations in this priority pathogen, setting the stage for answering critical basic and clinical science questions. SignificanceTo understand bacterial genomes, researchers need access to rapid, flexible, precise and high throughput genetic perturbation tools. Here we present an oligonucleotide-based method that satisfies these requirements for use in the opportunistic pathogen, Pseudomonas aeruginosa. By relying on oligos to encode genomic homology arms, no molecular cloning is required - making these tools rapid, robust, and scalable. We benchmark gene deletions in both lab and clinical strains, opening the possibility of rapid genetic studies across the P. aeruginosa pangenomic space. At high throughput, we use an oligo pool to create a mutant library of degron tagged essential proteins. These knockdowns (i.e. hypomorphs) show certain essential genes are highly vulnerable and others are synergistic with clinical drugs, providing insight into future antibiotic and co-therapy development.

microbiology↗

Genetic Determinants Underlying the Progressive Phenotype of Beta-lactam/Beta-lactamase Inhibitor Resistance in Escherichia coli

Currently, whole genome sequencing (WGS) data has not shown strong concordance with E. coli susceptibility profiles to the commonly used {beta}-lactam/{beta}-lactamase inhibitor (BL/BLI) combinations: ampicillin-sulbactam (SAM), amoxicillin-clavulanate (AMC), and piperacillin-tazobactam (TZP). Progressive resistance to these BL/BLIs in absence of cephalosporin resistance, also known as extended-spectrum resistance to BL/BLI (ESRI), has been suggested to primarily result from increased copy numbers of blaTEM variants, which is not routinely assessed in WGS data. We sought to determine whether addition of gene amplification could improve genotype-phenotype associations through WGS analysis of 147 E. coli bacteremia isolates with increasing categories of BL/BLI non-susceptibility ranging from ampicillin-susceptible to fully resistant to all three BL/BLIs. Consistent with a key role of blaTEM in ESRI, 112/134 strains (84%) with at least ampicillin non-susceptibility encoded blaTEM. Evidence of blaTEM amplification (i.e., blaTEM gene copy number estimates > 2x) was present in 40/112 (36%) strains. There were positive correlations between blaTEM copy numbers with minimum inhibitory concentrations (MICs) of AMC and TZP (P-value < 0.05), but not for SAM (P-value = 0.09). The diversity of {beta}-lactam resistance mechanisms, including non-ceftriaxone hydrolyzing blaCTX-M variants, blaOXA-1, as well as ampC and blaTEM strong promoter mutations, were greater in AMC and TZP non-susceptible strains but rarely observed within SAM and AMP non-susceptible isolates. Our study indicates a comprehensive analysis of WGS data, including {beta}-lactamase encoding gene amplification, can help categorize E. coli with AMC or TZP non-susceptibility but that discerning the transition from SAM susceptible to non-susceptible using genetic data requires further refinement. ImportanceThe 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 E. coli bacteremia samples to determine how increasing dosage of narrow-spectrum {beta}-lactamase encoding genes in conjunction with other diverse BL/BLI genetic determinants contribute 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 {beta}-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.

genomics↗

β-lactamase Amplification and Porin Loss Drive Progressive β-lactam Resistance in Recurrent ESBL Enterobacteriaceae Bacteremia

BackgroundCarbapenem resistant Enterobacterales (CRE) remain urgent antimicrobial resistance threats. Approximately half of CRE clinical isolates lack carbapenem hydrolyzing enzymes and develop carbapenem resistance through alternative mechanisms. The purpose of this study was to elucidate the development of carbapenem resistance mechanisms from clonal, recurrent extended-spectrum {beta}-lactamase positive Enterobacterales (ESBL-E) bacteremia isolates in a vulnerable patient population. MethodsThis study investigated a historical, retrospective cohort of ESBL-E bacteremia cases in the University of Texas MD Anderson Cancer Center (MDACC) from January 2015 to July 2016. Phylogenetic and comparative genomic analyses were performed to identify clonal, recurrent ESBL-E isolates developing carbapenem resistance. Oxford Nanopore Technology (ONT) long-read and Illumina short-read sequencing data were used to generate consensus assemblies and to identify signatures of mobile genetic element mediated amplification and transposition of antimicrobial resistance genes. Serial passaging experiments were performed on a set of clinical ST131 ESBL-E isolates to recapitulate in vivo observations. qPCR and qRT-PCR were used to determine respective copy number and transcript levels of {beta}-lactamase genes. Results116 ESBL-E bacteremia cases were identified, 16 of which had documented recurrent infections. Four serial, recurrent isolates displayed a carbapenem resistant phenotype, three without the acquisition of a known carbapenemase. These three isolates had non-carbapenemase-producing CRE (non-CP-CRE) mechanisms driven by IS26- and ISEcp1-mediated amplification of respective translocatable units (TU) and transposition units (TPU) harboring both blaOXA-1 and blaCTX-M variants with concomitant outer membrane porin disruption. The TU and TPU structures inserted into the open reading frames of outer membrane porin genes in a subset of non-CP-CRE isolates. Serial passage of an index ST131 ESBL-E isolate under selective carbapenem exposure resulted in chromosomal amplification of modular, TUs harboring {beta}-lactamase genes with concomitant porin inactivation, recapitulating the in vivo carbapenem resistance progression. Long-read sequencing of two additional MDACC bacteremia strains identified similar non-CP-CRE mechanisms observed in the serial isolates. ConclusionsNon-CP-CRE de novo mechanisms were the primary driver of CRE development in recurrent bacteremia cases within this vulnerable patient population. The incorporation of long-read ONT data into AMR surveillance platforms is critical to identify high-risk CRE isolates that are difficult to identify with low-resolution phenotypic and molecular characterization methods.

genomics↗

VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning

Antimicrobial resistance (AMR) is an increasing threat to public health. Current methods of determining AMR rely on inefficient phenotypic approaches, and there remains incomplete understanding of AMR mechanisms for many pathogen-antimicrobial combinations. Given the rapid, ongoing increase in availability of high density genomic data for a diverse array of bacteria, development of algorithms that could utilize genomic information to predict phenotype could both be useful clinically and assist with discovery of heretofore unrecognized AMR pathways. To facilitate understanding of the connections between DNA variation and phenotypic AMR, we developed a new bioinformatics tool, variant mapping and prediction of antibiotic resistance (VAMPr), to (1) derive gene ortholog-based sequence features for variants; (2) interrogate these explainable gene-level variants for their known or novel associations with AMR; and (3) build accurate models to predict AMR based on whole genome sequencing data. Following the Clinical & Laboratory Standards Institute (CLSI) guidelines, we curated the publicly available sequencing data for 3,393 bacterial isolates from 9 species along with AMR phenotypes for 29 antibiotics. We detected 14,615 variant genotypes and built 93 association and prediction models. The association models confirmed known genetic antibiotic resistance mechanisms, such as blaKPC and carbapenem resistance consistent with the accurate nature of our approach. The prediction models achieved high accuracies (mean accuracy of 91.1% for all antibiotic-pathogen combinations) internally through nested cross validation and were also validated using external clinical datasets. The VAMPr variant detection method, association and prediction models will be valuable tools for AMR research for basic scientists with potential for clinical applicability.

bioinformatics↗