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The best whole genome assemblies are currently built from a combination of highly accurate short-read sequencing data and long-read sequencing data that can bridge repetitive and problematic regions. Oxford Nanopore Technologies (ONT) produce long-read sequencing platforms and they are continually improving their technology to obtain higher quality read data that is approaching the quality obtained from short-read platforms such as Illumina. As these innovations continue, we evaluated how much ONT read coverage produced by the Rapid Barcoding Kit v14 (SQK-RBK114) is necessary to generate high-quality hybrid and long-read-only genome assemblies for a panel of carbapenemase-producing Enterobacterales bacterial isolates. We found that 30× long-read coverage is sufficient if Illumina data are available, and that more (at least 100× long-read coverage is recommended for long-read-only assemblies. Illumina polishing is still improving single nucleotide variants (SNVs) and INDELs in long-read-only assemblies. We also examined if antimicrobial resistance genes could be accurately identified in long-read-only data, and found that Flye assemblies regardless of ONT coverage detected >96% of resistance genes at 100% identity and length. Overall, the Rapid Barcoding Kit v14 and long-read-only assemblies can be an optimal sequencing strategy (i.e., plasmid characterization and AMR detection) but finer-scale analyses (i.e., SNV) still benefit from short-read data. [ABSTRACT FROM AUTHOR]

Introduction: Antimicrobial resistance (AMR) is a major public health concern. The spread of AMR-encoding genes between enterobacteria, especially in Klebsiella pneumoniae strains, lead to failure in the treatment of most individuals. The aim of this study was to characterize multidrug resistant (MDR) clinical K. pneumoniae isolates that produce extended-spectrum ß-lactamases (ESBLs) from Algeria. Methodology: The isolates were identified using biochemical tests, and the identification was confirmed by mass spectrometry using VITEK® MS (BioMerieux, Marcy l'Etoile, France). Antibiotic susceptibility testing was assessed by the disk diffusion method. Molecular characterization was performed by whole genome sequencing (WGS) using Illumina technology. Sequenced raw reads were processed using bioinformatics parameters: FastQC, ARIBA, and Shovill-Spades. Multilocus sequence typing (MLST) was used to estimate the evolutionary relationship between isolate strains. Results: Molecular analysis resulted in the first detection of blaNDM-5 encoding K. pneumoniae in Algeria. Other resistance genes were blaTEM, blaSHV, blaCTX-M, aac(6')-Ib-cr, qnrB1, qnrB4, qnrB19, qnrS1, gyrA and parC variants. Conclusions: Our data demonstrated a very high level of resistance in clinical K. pneumoniae strains which were resistant to most common antibiotic families. This was the first detection of K. pneumoniae with the blaNDM-5 gene in Algeria. Surveillance of antibiotic use and measures for control should be implemented to reduce occurrence of AMR in clinical bacteria. [ABSTRACT FROM AUTHOR]

Background: The implementation of whole genome sequencing (WGS) by PulseNet, the molecular subtyping network for foodborne diseases, has transformed surveillance, outbreak detection, and public health laboratory practices in the United States. In 2017, the New Hampshire Public Health Laboratories, a member of PulseNet, commenced the use of WGS in tracking foodborne pathogens across the state. We present some of the initial results of New Hampshire's initiative to transition to WGS in tracking Salmonella enterica, a bacterial pathogen that is responsible for non-typhoidal foodborne infections and enteric fever. We characterize the population structure and evolutionary history of 394 genomes of isolates recovered from human clinical cases in New Hampshire from 2017 to 2020. Results: The New Hampshire S. enterica population is phylogenetically diverse, consisting of 78 sequence types (ST) and 67 serotypes. Six lineages dominate the population: ST 11 serotype Enteritidis, ST 19 Typhimurium, ST 32 Infantis, ST 118 Newport, ST 22 Braenderup, and ST 26 Thompson. Each lineage is derived from long ancestral branches in the phylogeny, suggesting their extended presence in the region and recent clonal expansion. We detected 61 genes associated with resistance to 14 antimicrobial classes. Of these, unique genes of five antimicrobial classes (aminocoumarins, aminoglycosides, fluoroquinolones, nitroimidazoles, and peptides) were detected in all genomes. Rather than a single clone carrying multiple resistance genes expanding in the state, we found multiple lineages carrying different combinations of independently acquired resistance determinants. We estimate the time to the most recent common ancestor of the predominant lineage ST 11 serotype Enteritidis (126 genomes) to be 1965 (95% highest posterior density intervals: 1927–1982). Its population size expanded until 1978, followed by a population decline until 1990. This lineage has been expanding since then. Comparison with genomes from other states reveal lack of geographical clustering indicative of long-distance dissemination. Conclusions: WGS studies of standing pathogen diversity provide critical insights into the population and evolutionary dynamics of lineages and antimicrobial resistance, which can be translated to effective public health action and decision-making. We highlight the need to strengthen efforts to implement WGS-based surveillance and genomic data analyses in state public health laboratories. [ABSTRACT FROM AUTHOR]

Background The incidence of bloodstream infections (BSIs) caused by Escherichia coli and Klebsiella pneumoniae is increasing, with substantial associated morbidity, mortality, and antimicrobial resistance. Unbiased serotyping studies to guide vaccine target selection are limited. Methods We conducted unselected, population-level genomic surveillance of bloodstream E. coli and Klebsiella pneumoniae isolates from 2008 to 2018 in Oxfordshire, United Kingdom. We supplemented this with an analysis of publicly available global sequencing data (n = 3678). Results We sequenced 3478 E. coli isolates (3278 passed quality control) and 556 K. pneumoniae isolates (535 [K-antigen] and 549 [O-antigen] passed quality control). The 4 most common E. coli O-antigens (O1/O2/O6/O25) were identified in 1499/3278 isolates; the incidence of these O-types increased over time (incidence rate ratio per year [IRRy] = 1.14, 95% confidence interval [CI]: 1.11–1.16). These O-types accounted for 616/1434 multidrug-resistant (MDR) and 173/256 extended-spectrum beta-lactamase (ESBL)-resistant isolates in Oxfordshire but only 19/90 carbapenem-resistant isolates across all studies. For Klebsiella pneumoniae , the most common O-antigens (O2v2/O1v1/O3b/O1v2) accounted for 410/549 isolates; the incidence of BSIs caused by these also increased annually (IRRy = 1.09; 95% CI: 1.05–1.12). These O-types accounted for 122/148 MDR and 106/123 ESBL isolates in Oxfordshire and 557/734 carbapenem-resistant isolates across all studies. Conversely we observed substantial capsular antigen diversity. Analysis of 3678 isolates from global studies demonstrated the generalizability of these findings. For E. coli , based on serotyping, the ExPEC4V and ExPEC10V vaccines under investigation would cover 46% and 72% of Oxfordshire isolates respectively, and 47% and 71% of MDR isolates. Conclusions O-antigen targeted vaccines may be useful in reducing the morbidity, mortality, and antimicrobial resistance associated with E. coli and K. pneumoniae BSIs. [ABSTRACT FROM AUTHOR]

Background Klebsiella pneumoniae is a critically important pathogen in the Philippines. Isolates are commonly resistant to at least 2 classes of antibiotics, yet mechanisms and spread of its resistance are not well studied. Methods A retrospective sequencing survey was performed on carbapenem-, extended spectrum beta-lactam-, and cephalosporin-resistant Klebsiella pneumoniae isolated at 20 antimicrobial resistance (AMR) surveillance sentinel sites from 2015 through 2017. We characterized 259 isolates using biochemical methods, antimicrobial susceptibility testing, and whole-genome sequencing (WGS). Known AMR mechanisms were identified. Potential outbreaks were investigated by detecting clusters from epidemiologic, phenotypic, and genome-derived data. Results Prevalent AMR mechanisms detected include bla CTX-M-15 (76.8%) and bla NDM-1 (37.5%). An epidemic IncFII(Yp) plasmid carrying bla NDM-1 was also detected in 46 isolates from 6 sentinel sites and 14 different sequence types (STs). This plasmid was also identified as the main vehicle of carbapenem resistance in 2 previously unrecognized local outbreaks of ST348 and ST283 at 2 different sentinel sites. A third local outbreak of ST397 was also identified but without the IncFII(Yp) plasmid. Isolates in each outbreak site showed identical STs and K- and O-loci, and similar resistance profiles and AMR genes. All outbreak isolates were collected from blood of children aged < 1 year. Conclusion WGS provided a better understanding of the epidemiology of multidrug resistant Klebsiella in the Philippines, which was not possible with only phenotypic and epidemiologic data. The identification of 3 previously unrecognized Klebsiella outbreaks highlights the utility of WGS in outbreak detection, as well as its importance in public health and in implementing infection control programs. [ABSTRACT FROM AUTHOR]

Background Genomic epidemiology studies of gonorrhea in the United States have primarily focused on national surveillance for antibiotic resistance, and patterns of local transmission between demographic groups of resistant and susceptible strains are unknown. Methods We analyzed a convenience sample of genome sequences, antibiotic susceptibility, and patient data from 897 gonococcal isolates cultured at the New York City (NYC) Public Health Laboratory from NYC Department of Health and Mental Hygiene (DOHMH) Sexual Health Clinic (SHC) patients, primarily in 2012–2013. We reconstructed the gonococcal phylogeny, defined transmission clusters using a 10 nonrecombinant single nucleotide polymorphism threshold, tested for clustering of demographic groups, and placed NYC isolates in a global phylogenetic context. Results The NYC gonococcal phylogeny reflected global diversity with isolates from 22/23 of the prevalent global lineages (96%). Isolates clustered on the phylogeny by patient sexual behavior (P <.001) and race/ethnicity (P <.001). Minimum inhibitory concentrations were higher across antibiotics in isolates from men who have sex with men compared to heterosexuals (P <.001) and white heterosexuals compared to black heterosexuals (P <.01). In our dataset, all large transmission clusters (≥10 samples) of N. gonorrhoeae were susceptible to ciprofloxacin, ceftriaxone, and azithromycin, and comprised isolates from patients across demographic groups. Conclusions All large transmission clusters were susceptible to gonorrhea therapies, suggesting that resistance to empiric therapy was not a main driver of spread, even as risk for resistance varied across demographic groups. Further study of local transmission networks is needed to identify drivers of transmission. [ABSTRACT FROM AUTHOR]

Whole genome sequencing (WGS) is quickly becoming the customary means for identification of antimicrobial resistance (AMR) due to its ability to obtain high resolution information about the genes and mechanisms that are causing resistance and driving pathogen mobility. By contrast, traditional phenotypic (antibiogram) testing cannot easily elucidate such information. Yet development of AMR prediction tools from genotype-phenotype data can be biased, since sampling is non-randomized. Sample provenience, period of collection, and species representation can confound the association of genetic traits with AMR. Thus, prediction models can perform poorly on new data with sampling distribution shifts. In this work -under an explicit set of causal assumptions- we evaluate the effectiveness of propensity-based rebalancing and confounding adjustment on antibiotic resistance prediction using genotype-phenotype AMR data from the Pathosystems Resource Integration Center (PATRIC). We select bacterial genotypes (encoded as k-mer signatures, i.e., DNA fragments of length k), country, year, species, and AMR phenotypes for the tetracycline drug class, preparing test data with recent genomes coming from a single country. We test boosted logistic regression (BLR) and random forests (RF) with/without bias-handling. On 10,936 instances, we find evidence of species, location and year imbalance with respect to the AMR phenotype. The crude versus bias-adjusted change in effect of genetic signatures on AMR varies but only moderately (selecting the top 20,000 out of 40+ million k-mers). The area under the receiver operating characteristic (AUROC) of the RF (0.95) is comparable to that of BLR (0.94) on both out-of-bag samples from bootstrap and the external test (n = 1085), where AUROCs do not decrease. We observe a 1 %-5 % gain in AUROC with bias-handling compared to the sole use of genetic signatures. In conclusion, we recommend using causally-informed prediction methods for modeling real-world AMR data; however, traditional adjustment or propensity-based methods may not provide advantage in all use cases and further methodological development should be sought. [ABSTRACT FROM AUTHOR]

STUDY OBJECTIVE Our understanding of the molecular dynamics driving the community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) epidemic at the whole genome level is limited. We sought to assess the use of whole genome sequencing (WGS) to evaluate the genomic diversity and genotypic prediction of antimicrobial resistance of CA-MRSA isolates from patients in South Texas. DESIGN Comparative whole genome sequencing. ISOLATES Thirteen clinical CA-MRSA isolates recovered from patients presenting with skin and soft tissue infections to nine primary care clinics in the South Texas Ambulatory Research Network between 2010 and 2013. MEASUREMENTS AND MAIN RESULTS Comparative WGS was performed on the 13 MRSA sequence type 8 clinical isolates. We compared the resistome of genes encoding for antibiotic resistance with a phenotypically derived antibiogram using standard antimicrobial susceptibility testing. The strains differed by an average of 72 single nucleotide polymorphisms (SNPs) per isolate in the core genome compared with FPR3757 (USA300, reference strain). There were a total of 623 unique SNPs in the core genome (range 47-88 SNPs per isolate). We identified 19 nonsynonymous SNPs in genes encoding proven or putative S. aureus virulence determinants in the core genome. There was complete concordance between genotypic evidence for antimicrobial resistance and the phenotypically derived antibiogram. CONCLUSION Overall, although these CA-MRSA isolates were similar on the level of clonal type, clinical syndrome, and geographic area, the strains were diverse at the genome level. Furthermore, our findings provide important proof-of-concept information for using WGS as a potential front-end screening tool for antimicrobial resistance predictions. [ABSTRACT FROM AUTHOR]