Genome wide association study of Escherichia coli bloodstream infection isolates identifies genetic determinants for the portal of entry but not fatal outcome

Association of microbiological factors with mortality in Escherichia coli bacteraemia presenting with sepsis/septic shock: a prospective cohort study

OBJECTIVES

This study aimed to determine the association of Escherichia coli microbiological factors with 30-day mortality in patients with bloodstream infection (BSI) presenting with a dysregulated response to infection (i.e. sepsis or septic shock).

METHODS

Whole-genome sequencing was performed on 224 E coli isolates of patients with sepsis/septic shock, from 22 Spanish hospitals. Phylogroup, sequence type, virulence, antibiotic resistance, and pathogenicity islands were assessed. A multivariable model for 30-day mortality including clinical and epidemiological variables was built, to which microbiological variables were hierarchically added. The predictive capacity of the models was estimated by the area under the receiver operating characteristic curve (AUROC) with 95% confidence intervals (CI).

RESULTS

Mortality at day 30 was 31% (69 patients). The clinical model for mortality included (adjusted OR; 95% CI) age (1.04; 1.02-1.07), Charlson index ≥3 (1.78; 0.95-3.32), urinary BSI source (0.30; 0.16-0.57), and active empirical treatment (0.36; 0.11-1.14) with an AUROC of 0.73 (95% CI, 0.67-0.80). Addition of microbiological factors selected clone ST95 (3.64; 0.94-14.04), eilA gene (2.62; 1.14-6.02), and astA gene (2.39; 0.87-6.59) as associated with mortality, with an AUROC of 0.76 (0.69-0.82).

DISCUSSION

Despite having a modest overall contribution, some microbiological factors were associated with increased odds of death and deserve to be studied as potential therapeutic or preventive targets.

Predicting the primary infection source of Escherichia coli bacteremia using virulence-associated genes

PURPOSE

To investigate the role of E. coli virulence-associated genes (VAGs) in predicting urinary tract infection (UTI) as the source of bacteremia in two distinct hospital populations, one with a large general catchment area and one dominated by referrals.

METHODS

E. coli bacteremias identified at Department of Clinical Microbiology (DCM), Hvidovre Hospital and DCM, Rigshospitalet in the Capital Region of Denmark from October to December 2018. Using whole genome sequencing (WGS), we identified 358 VAGs from 224 E. coli bacteremia. For predictive analysis, VAGs were paired with clinical source of UTI from local bacteremia databases.

RESULTS

VAGs strongly predicting of UTI as primary infection source of bacteremia were primarily found within the pap gene family. papX (PPV 96%, sensitivity 54%) and papGII (PPV 93%, sensitivity 56%) were found highly predictive, but showed low sensitivities. The strength of VAG predictions of UTI as source varied significantly between the two hospital populations. VAGs had weaker predictions in the tertiary referral center (Rigshospitalet), a disparity likely stemming from differences in patient population and department specialization.

CONCLUSION

WGS data was used to predict the primary source of E. coli bacteremia and is an attempt on a new and different type of infection source identification. Genomic data showed potential to be utilized to predict the primary source of infection; however, discrepancy between the best performing profile of VAGs between acute care hospitals and tertiary hospitals makes it difficult to implement in clinical practice.

Integron distribution and relationship to antimicrobial resistance in E. coli isolated from blood culture

PURPOSE

The aim of this study was to evaluate the distribution of integrons in strains of E. coli isolated from blood culture and the relationship between integrons and antimicrobial resistance.

METHODS

The study included 100 E. coli strains sent to the Medical Microbiology Laboratory from different clinics between September 2022 and June 2023. Antibiotic susceptibility was evaluated according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST). The presence of integrons was determined by the inhouse polymerase chain reaction (PCR).

RESULTS

Integron positivity was detected in 45 (45%) of isolates, and class 1 integrons were found in 41 (41%), class 2 integrons in 2 (2%), and both class 1 integrons and class 2 integrons in 2 (2%). Class 3 integron positivity was not detected. In total, 63 cases of community origin and 37 cases of hospital origin were identified. When antibiotic resistance was evaluated, the highest sensitivity was noted for amikacin (1%), meropenem (5%), imipenem (6%), and the highest resistant antibiotics were ampicillin (82%), cepfuroxime sodium (65%), and amoxicillin/clavulanate (62%), respectively. Of the 16 antimicrobial substances evaluated, 10 had an antibiotic resistance rate of over 45%. In class 1 integron-positive samples, ampicillin resistance and trimethoprim/sulfamethoxazole resistance were higher than in negative samples (p = 0.02, p = 0.0001, respectively). Fifty-one (51%) samples were found to have multiple drug resistance (MDR). In total, 59.5% of hospital-acquired isolates and 46% of community-acquired isolates were considered to be MDR. The class 1 integron positivity in MDR samples was high (p = 0.038).

CONCLUSION

The high MDR rates in both hospital-acquired and community-acquired isolates are alarming. In particular, class 1 integron monitoring is very important to prevent the spread of MDR isolates.

Word-based GWAS harnesses the rich potential of genomic data for E. coli quinolone resistance

Quinolone resistance presents a growing global health threat. We employed word-based GWAS to explore genomic data, aiming to enhance our understanding of this phenomenon. Unlike traditional variant-based GWAS analyses, this approach simultaneously captures multiple genomic factors, including single and interacting resistance mutations and genes. Analyzing a dataset of 92 genomic E. coli samples from a wastewater treatment plant in Dresden, we identified 54 DNA unitigs significantly associated with quinolone resistance. Remarkably, our analysis not only validated known mutations in gyrA and parC genes and the results of our variant-based GWAS but also revealed new (mutated) genes such as mdfA, the AcrEF-TolC multidrug efflux system, ptrB, and hisI, implicated in antibiotic resistance. Furthermore, our study identified joint mutations in 14 genes including the known gyrA gene, providing insights into potential synergistic effects contributing to quinolone resistance. These findings showcase the exceptional capabilities of word-based GWAS in unraveling the intricate genomic foundations of quinolone resistance.

Reduced ambiguity and improved interpretability of bacterial genome-wide associations using gene-cluster-centric k-mers

The wide adoption of bacterial genome sequencing and encoding both core and accessory genome variation using k-mers has allowed bacterial genome-wide association studies (GWAS) to identify genetic variants associated with relevant phenotypes such as those linked to infection. Significant limitations still remain because of k-mers being duplicated across gene clusters and as far as the interpretation of association results is concerned, which affects the wider adoption of GWAS methods on microbial data sets. We have developed a simple computational method (panfeed) that explicitly links each k-mer to their gene cluster at base-resolution level, which allows us to avoid biases introduced by a global de Bruijn graph as well as more easily map and annotate associated variants. We tested panfeed on two independent data sets, correctly identifying previously characterized causal variants, which demonstrates the precision of the method, as well as its scalable performance. panfeed is a command line tool written in the python programming language and is available at https://github.com/microbial-pangenomes-lab/panfeed.

Bacterial genome-wide association study substantiates papGII of Escherichia coli as a major risk factor for urosepsis

BACKGROUND

Urinary tract infections (UTIs) are among the most common bacterial infections worldwide, often caused by uropathogenic Escherichia coli. Multiple bacterial virulence factors or patient characteristics have been linked separately to progressive, more invasive infections. In this study, we aim to identify pathogen- and patient-specific factors that drive the progression to urosepsis by jointly analysing bacterial and host characteristics.

METHODS

We analysed 1076 E. coli strains isolated from 825 clinical cases with UTI and/or bacteraemia by whole-genome sequencing (Illumina). Sequence types (STs) were determined via srst2 and capsule loci via fastKaptive. We compared the isolates from urine and blood to confirm clonality. Furthermore, we performed a bacterial genome-wide association study (bGWAS) (pyseer) using bacteraemia as the primary clinical outcome. Clinical data were collected by an electronic patient chart review. We concurrently analysed the association of the most significant bGWAS hit and important patient characteristics with the clinical endpoint bacteraemia using a generalised linear model (GLM). Finally, we designed qPCR primers and probes to detect papGII-positive E. coli strains and prospectively screened E. coli from urine samples (n = 1657) at two healthcare centres.

RESULTS

Our patient cohort had a median age of 75.3 years (range: 18.00-103.1) and was predominantly female (574/825, 69.6%). The bacterial phylogroups B2 (60.6%; 500/825) and D (16.6%; 137/825), which are associated with extraintestinal infections, represent the majority of the strains in our collection, many of which encode a polysaccharide capsule (63.4%; 525/825). The most frequently observed STs were ST131 (12.7%; 105/825), ST69 (11.0%; 91/825), and ST73 (10.2%; 84/825). Of interest, in 12.3% (13/106) of cases, the E. coli pairs in urine and blood were only distantly related. In line with previous bGWAS studies, we identified the gene papGII (p-value < 0.001), which encodes the adhesin subunit of the E. coli P-pilus, to be associated with 'bacteraemia' in our bGWAS. In our GLM, correcting for patient characteristics, papGII remained highly significant (odds ratio = 5.27, 95% confidence interval = [3.48, 7.97], p-value < 0.001). An independent cohort of cases which we screened for papGII-carrying E. coli at two healthcare centres further confirmed the increased relative frequency of papGII-positive strains causing invasive infection, compared to papGII-negative strains (p-value = 0.033, chi-squared test).

CONCLUSIONS

This study builds on previous work linking papGII with invasive infection by showing that it is a major risk factor for progression from UTI to bacteraemia that has diagnostic potential.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

A statistical genomics framework to trace bacterial genomic predictors of clinical outcomes in Staphylococcus aureus bacteremia

Outcomes of severe bacterial infections are determined by the interplay between host, pathogen, and treatments. While human genomics has provided insights into host factors impacting Staphylococcus aureus infections, comparatively little is known about S. aureus genotypes and disease severity. Building on the hypothesis that bacterial pathoadaptation is a key outcome driver, we developed a genome-wide association study (GWAS) framework to identify adaptive mutations associated with treatment failure and mortality in S. aureus bacteremia (1,358 episodes). Our research highlights the potential of vancomycin-selected mutations and vancomycin minimum inhibitory concentration (MIC) as key explanatory variables to predict infection severity. The contribution of bacterial variation was much lower for clinical outcomes (heritability <5%); however, GWASs allowed us to identify additional, MIC-independent candidate pathogenesis loci. Using supervised machine learning, we were able to quantify the predictive potential of these adaptive signatures. Our statistical genomics framework provides a powerful means to capture adaptive mutations impacting severe bacterial infections.

Complex Regulation of Gamma-Hemolysin Expression Impacts Staphylococcus aureus Virulence

Staphylococcus aureus gamma-hemolysin CB (HlgCB) is a core-genome-encoded pore-forming toxin that targets the C5a receptor, similar to the phage-encoded Panton-Valentine leucocidin (PVL). Absolute quantification by mass spectrometry of HlgCB in 39 community-acquired pneumonia (CAP) isolates showed considerable variations in the HlgC and HlgB yields between isolates. Moreover, although HlgC and HlgB are encoded on a single operon, their levels were dissociated in 10% of the clinical strains studied. To decipher the molecular basis for the variation in hlgCB expression and protein production among strains, different regulation levels were analyzed in representative clinical isolates and reference strains. Both the HlgCB level and the HlgC/HlgB ratio were found to depend on hlgC promoter activity and mRNA processing and translation. Strikingly, only one single nucleotide polymorphism (SNP) in the 5' untranslated region (UTR) of hlgCB mRNA strongly impaired hlgC translation in the USA300 strain, leading to a strong decrease in the level of HlgC but not in HlgB. Finally, we found that high levels of HlgCB synthesis led to mortality in a rabbit model of pneumonia, correlated with the implication of the role of HlgCB in severe S. aureus CAP. Taken together, this work illustrates the complexity of virulence factor expression in clinical strains and demonstrates a butterfly effect where subtle genomic variations have a major impact on phenotype and virulence. IMPORTANCE S. aureus virulence in pneumonia results in its ability to produce several virulence factors, including the leucocidin PVL. Here, we demonstrate that HlgCB, another leucocidin, which targets the same receptors as PVL, highly contributes to S. aureus virulence in pvl-negative strains. In addition, considerable variations in HlgCB quantities are observed among clinical isolates from patients with CAP. Biomolecular analyses have revealed that a few SNPs in the promoter sequences and only one SNP in the 5' UTR of hlgCB mRNA induce the differential expression of hlgCB, drastically impacting hlgC mRNA translation. This work illustrates the subtlety of regulatory mechanisms in bacteria, especially the sometimes major effects on phenotypes of single nucleotide variation in noncoding regions.

The bacterial genetic determinants of Escherichia coli capacity to cause bloodstream infections in humans

Escherichia coli is both a highly prevalent commensal and a major opportunistic pathogen causing bloodstream infections (BSI). A systematic analysis characterizing the genomic determinants of extra-intestinal pathogenic vs. commensal isolates in human populations, which could inform mechanisms of pathogenesis, diagnostic, prevention and treatment is still lacking. We used a collection of 912 BSI and 370 commensal E. coli isolates collected in France over a 17-year period (2000-2017). We compared their pangenomes, genetic backgrounds (phylogroups, STs, O groups), presence of virulence-associated genes (VAGs) and antimicrobial resistance genes, finding significant differences in all comparisons between commensal and BSI isolates. A machine learning linear model trained on all the genetic variants derived from the pangenome and controlling for population structure reveals similar differences in VAGs, discovers new variants associated with pathogenicity (capacity to cause BSI), and accurately classifies BSI vs. commensal strains. Pathogenicity is a highly heritable trait, with up to 69% of the variance explained by bacterial genetic variants. Lastly, complementing our commensal collection with an older collection from 1980, we predict that pathogenicity continuously increased through 1980, 2000, to 2010. Together our findings imply that E. coli exhibit substantial genetic variation contributing to the transition between commensalism and pathogenicity and that this species evolved towards higher pathogenicity.

A high-throughput cytotoxicity screening platform reveals agr-independent mutations in bacteraemia-associated Staphylococcus aureus that promote intracellular persistence

Staphylococcus aureus infections are associated with high mortality rates. Often considered an extracellular pathogen, S. aureus can persist and replicate within host cells, evading immune responses, and causing host cell death. Classical methods for assessing S. aureus cytotoxicity are limited by testing culture supernatants and endpoint measurements that do not capture the phenotypic diversity of intracellular bacteria. Using a well-established epithelial cell line model, we have developed a platform called InToxSa (intracellular toxicity of S. aureus) to quantify intracellular cytotoxic S. aureus phenotypes. Studying a panel of 387 S. aureus bacteraemia isolates, and combined with comparative, statistical, and functional genomics, our platform identified mutations in S. aureus clinical isolates that reduced bacterial cytotoxicity and promoted intracellular persistence. In addition to numerous convergent mutations in the Agr quorum sensing system, our approach detected mutations in other loci that also impacted cytotoxicity and intracellular persistence. We discovered that clinical mutations in ausA, encoding the aureusimine non-ribosomal peptide synthetase, reduced S. aureus cytotoxicity, and increased intracellular persistence. InToxSa is a versatile, high-throughput cell-based phenomics platform and we showcase its utility by identifying clinically relevant S. aureus pathoadaptive mutations that promote intracellular residency.

Strain-Level Discrimination of Bacteria by Liquid Chromatography and Paper Spray Ion Mobility Mass Spectrometry

Determining bacterial identity at the strain level is critical for public health to enable proper medical treatments and reduce antibiotic resistance. Herein, we used liquid chromatography, ion mobility, and tandem MS (LC-IM-MS/MS) to distinguish Escherichia coli (E. coli) strains. Numerical multivariate statistics (principal component analysis, followed by linear discriminant analysis) showed the capability of this method to perform strain-level discrimination with prediction rates of 96.1% and 100% utilizing the negative and positive ion information, respectively. The tandem MS and LC separation proved effective in discriminating diagnostic lipid isomers in the negative mode, while IM separation was more effective in resolving lipid conformational biomarkers in the positive ion mode. Because of the clinical importance of early detection for rapid medical intervention, a faster technique, paper spray (PS)-IM-MS/MS, was used to discriminate the E. coli strains. The achieved prediction rates of the analysis of E. coli strains by PS-IM-MS/MS were 62.5% and 73.5% in the negative and positive ion modes, respectively. The strategy of numerical data fusion of negative and positive ion data increased the classification rates of PS-IM-MS/MS to 80.5%. Lipid isomers and conformers were detected, which served as strain-indicating biomarkers. The two complementary multidimensional techniques revealed biochemical differences between the E. coli strains confirming the results obtained from comparative genomic analysis. Moreover, the results suggest that PS-IM-MS/MS is a rapid, highly selective, and sensitive method for discriminating bacterial strains in environmental and food samples.

All Staphylococcus aureus bacteraemia-inducing strains can cause infective endocarditis: Results of GWAS and experimental animal studies

OBJECTIVES

We aimed at determining whether specific S. aureus strains cause infective endocarditis (IE) in the course of Staphylococcus aureus bacteraemia (SAB).

METHODS

A genome-wide association study (GWAS) including 924 S. aureus genomes from IE (274) and non-IE (650) SAB patients from international cohorts was conducted, and a subset of strains was tested with two experimental animal models of IE, one investigating the early step of bacterial adhesion to inflamed mice valves, the second evaluating the local and systemic developmental process of IE on mechanically-damaged rabbit valves.

RESULTS

The genetic profile of S. aureus IE and non-IE SAB strains did not differ when considering single nucleotide polymorphisms, coding sequences, and k-mers analysed in GWAS. In the murine inflammation-induced IE model, no difference was observed between IE and non-IE SAB strains both in terms of adhesion to the cardiac valves and in the propensity to cause IE; in the mechanical IE-induced rabbit model, there was no difference between IE and non-IE SAB strains regarding the vegetation size and CFU.

CONCLUSION

All strains of S. aureus isolated from SAB patients must be considered as capable of causing this common and lethal infection once they have accessed the bloodstream.

Staphylococcus aureus host interactions and adaptation

Invasive Staphylococcus aureus infections are common, causing high mortality, compounded by the propensity of the bacterium to develop drug resistance. S. aureus is an excellent case study of the potential for a bacterium to be commensal, colonizing, latent or disease-causing; these states defined by the interplay between S. aureus and host. This interplay is multidimensional and evolving, exemplified by the spread of S. aureus between humans and other animal reservoirs and the lack of success in vaccine development. In this Review, we examine recent advances in understanding the S. aureus-host interactions that lead to infections. We revisit the primary role of neutrophils in controlling infection, summarizing the discovery of new immune evasion molecules and the discovery of new functions ascribed to well-known virulence factors. We explore the intriguing intersection of bacterial and host metabolism, where crosstalk in both directions can influence immune responses and infection outcomes. This Review also assesses the surprising genomic plasticity of S. aureus, its dualism as a multi-mammalian species commensal and opportunistic pathogen and our developing understanding of the roles of other bacteria in shaping S. aureus colonization.

Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics

Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.

Highly Virulent and Multidrug-Resistant Escherichia coli Sequence Type 58 from a Sausage in Germany

Studies have previously described the occurrence of multidrug-resistant (MDR) Escherichia coli in human and veterinary medical settings, livestock, and, to a lesser extent, in the environment and food. While they mostly analyzed foodborne E. coli regarding phenotypic and sometimes genotypic antibiotic resistance and basic phylogenetic classification, we have limited understanding of the in vitro and in vivo virulence characteristics and global phylogenetic contexts of these bacteria. Here, we investigated in-depth an E. coli strain (PBIO3502) isolated from a pork sausage in Germany in 2021. Whole-genome sequence analysis revealed sequence type (ST)58, which has an internationally emerging high-risk clonal lineage. In addition to its MDR phenotype that mostly matched the genotype, PBIO3502 demonstrated pronounced virulence features, including in vitro biofilm formation, siderophore secretion, serum resilience, and in vivo mortality in Galleria mellonella larvae. Along with the genomic analysis indicating close phylogenetic relatedness of our strain with publicly available, clinically relevant representatives of the same ST, these results suggest the zoonotic and pathogenic character of PBIO3502 with the potential to cause infection in humans and animals. Additionally, our study highlights the necessity of the One Health approach while integrating human, animal, and environmental health, as well as the role of meat products and food chains in the putative transmission of MDR pathogens.