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ABSTRACT An outbreak involving an extensively antibiotic-resistant Acinetobacter baumannii strain in three military treatment facilities was identified. Fifty-nine isolates recovered from 30 patients over a 4-year period were found among a large collection of isolates using core genome multilocus sequence typing (MLST). They differed by only 0 to 18 single nucleotide polymorphisms (SNPs) and carried the same resistance determinants except that the aphA6 gene was missing in 25 isolates. They represent a novel sublineage of GC1 lineage 1 that likely originated in Afghanistan. IMPORTANCE A. baumannii is recognized as one of the most important nosocomial pathogens, and carbapenem-resistant strains pose a particularly difficult treatment challenge. Outbreaks linked to this pathogen are reported worldwide, particularly during periods of societal upheaval, such as natural disasters and conflicts. Understanding how this organism enters and establishes itself within the hospital environment is key to interrupting transmission, but few genomic studies have examined these transmissions over a prolonged period. Though historical, this report provides an in-depth analysis of nosocomial transmission of this organism across continents and within and between different hospitals.

Genomic surveillance of pathogens is essential to trace infections and analyze resistance markers. Core genome multilocus sequence typing (cgMLST) facilitates genomic surveillance by simplified analysis and standardization. However, its application is limited by the poor cost-efficiency of short-read (SR) sequencing. Oxford Nanopore long-read sequencing (ONT-LR), which allows fast on-site analysis with comparatively low costs, could provide an alternative. Despite ONT-LR raw read accuracy improvement, evidence for methylation-based errors accumulates. PCR-based library preparation, suggested as a solution, presumably poses difficulties for GC-rich bacteria. We challenged ONT-LR-based cgMLST using the highly GC-rich pathogen Burkholderia pseudomallei to develop a clinically applicable workflow. Our B. pseudomallei cgMLST scheme was applied to ONT-LR data, and the results were validated against SR data. Native, rapid, and PCR-based library preparation was performed and combined with different basecalling models (SUP@bacterial-methylation, SUP@v4.2, SUP@v4.3, and SUP@v5.0) and polishing strategies (medaka_consensus, medaka_variant, r103_min_high_g360). To ensure reliability across genotypes, we included 14 sequence types and 27 genotypes. The recommended ONT-LR workflow at study initiation (SUP@v4.2, medaka_consensus) showed nearly 200 allele differences compared with the reference for specific strains. PCR-based library preparation resulted in missing targets and typing errors of up to 21 alleles. Native barcoding with SUP@v5.0 basecalling and r103_min_high_g360 polishing outperformed the PCR-based approach in all parameters reducing the error rate to a maximum of two allele differences. The optimized ONT-LR-based cgMLST workflow for B. pseudomallei integrates high resolution and ease of implementation with enhanced cost-efficiency for rapid diagnostics. The developed protocol might serve as a guideline for other GC-rich pathogens., Importance: This study highlights a significant advancement in genomic surveillance of bacterial pathogens, specifically addressing the challenges posed by the GC-rich species Burkholderia pseudomallei . Core genome multilocus sequence typing (cgMLST) is widely used for bacterial typing as it combines high resolution with simple implementation and standardization. To improve cost efficiency and thus accessibility, we changed the sequencing approach from Illumina short-read (SR) to Oxford Nanopore long-read sequencing (ONT-LR). ONT-LR-based cgMLST showed a very high error rate compared with SR-based cgMLST, most likely due to methylation-associated errors. PCR-based library preparation, which is proposed to correct these errors, did not achieve the required accuracy. In contrast, native barcoding with advanced basecalling and polishing strategies massively reduces allelic differences. This optimized ONT-LR cgMLST workflow provides a transformative solution for cost-efficient, high-resolution typing of B. pseudomallei . Furthermore, this study can serve as a guide for similarly challenging bacteria.

Brucellosis poses a significant burden to human and animal health worldwide. Robust and harmonized molecular epidemiological approaches and population studies that include routine disease screening are needed to efficiently track the origin and spread of Brucella strains. Core genome multilocus sequence typing (cgMLST) is a powerful genotyping system commonly used to delineate pathogen transmission routes for disease surveillance and control. Except for Brucella melitensis, cgMLST schemes for Brucella species are currently not established. Here, we describe a novel cgMLST scheme that covers multiple Brucella species. We first determined the phylogenetic breadth of the genus using 612 Brucella genomes. We selected 1,764 genes that were particularly well conserved and typeable in at least 98% of these genomes. We tested the new scheme on 600 genomes and found high agreement with the whole-genome-based single nucleotide polymorphism (SNP) analysis. Next, we applied the scheme to reanalyze the genome of Brucella strains from epidemiologically linked outbreaks. We demonstrated the applicability of the new scheme for high-resolution typing required in outbreak investigations as previously reported with whole-genome SNP methods. We also used the novel scheme to define the global population structure of the genus using 1,322 Brucella genomes. Finally, we demonstrated the possibility of tracing distribution of Brucella strains by performing cluster analysis of cgMLST profiles and found nearly identical cgMLST profiles in different countries. Our results show that sequencing depth of more than 40-fold is optimal for allele calling with this scheme. In summary, this study describes a novel Brucella-wide cgMLST scheme that is applicable in Brucella molecular epidemiology and helps in accurately tracking and thus controlling the sources of infection. The scheme is publicly accessible and should represent a valuable resource for laboratories with limited computational resources and bioinformatics expertise.

Diphtheria is a vaccine-preventable disease with a high potential for reemergence. One of its causative agents is Corynebacterium diphtheriae , with some strains producing diphtheria toxin. From 2011 to 2019, 57 clinical C. diphtheriae strains were isolated in Austria, either from the respiratory tract or from skin infections. The aim of this study was to investigate the genetic diversity of these C. diphtheriae isolates using whole-genome sequencing. Isolates were characterized by genome-wide comparisons using single nucleotide polymorphism analysis or core genome multilocus sequence typing and by searching sequence data for antimicrobial resistance genes and genes involved in diphtheria toxin production. The genetic diversity among the isolates was high, with no clear distribution over time or place. Corynebacterium belfantii isolates were separated from other strains and were strongly associated with respiratory infections (odds ratio [OR] = 57). Two clusters, limited in time and space, were identified. Almost 40% of strains carried resistance genes against tetracycline or sulfonamides, mostly from skin infections. Microbiological tests showed that 55% of isolates were resistant to penicillin but did not carry genes conferring β-lactam resistance. A diphtheria toxin gene with no nonsynonymous mutation was found in three isolates only. This study showed that sequencing can provide valuable information complementing routine microbiological and epidemiological investigations. It allowed us to identify unknown clusters, evaluate antimicrobial resistance more broadly, and support toxigenicity results obtained by PCR. For these reasons, C. diphtheriae surveillance could strongly benefit from the routine implementation of whole-genome sequencing., (Copyright © 2021 Schaeffer et al.)

Among enterococci, Enterococcus faecalis occurs ubiquitously, with the highest incidence of human and animal infections. The high genetic plasticity of E. faecalis complicates both molecular investigations and phylogenetic analyses. Whole-genome sequencing (WGS) enables unraveling of epidemiological linkages and putative transmission events between humans, animals, and food. Core genome multilocus sequence typing (cgMLST) aims to combine the discriminatory power of classical multilocus sequence typing (MLST) with the extensive genetic data obtained by WGS. By sequencing a representative collection of 146 E. faecalis strains isolated from hospital outbreaks, food, animals, and colonization of healthy human individuals, we established a novel cgMLST scheme with 1,972 gene targets within the Ridom SeqSphere + software. To test the E. faecalis cgMLST scheme and assess the typing performance, different collections comprising environmental and bacteremia isolates, as well as all publicly available genome sequences from the NCBI and SRA databases, were analyzed. In more than 98.6% of the tested genomes, >95% good cgMLST target genes were detected (mean, 99.2% target genes). Our genotyping results not only corroborate the known epidemiological background of the isolates but exceed previous typing resolution. In conclusion, we have created a powerful typing scheme, hence providing an international standardized nomenclature that is suitable for surveillance approaches in various sectors, linking public health, veterinary public health, and food safety in a true One Health fashion., (Copyright © 2019 Neumann et al.)