High Interlaboratory Reproducibility and Accuracy of Next-Generation-Sequencing-Based Bacterial Genotyping in a Ring Trial

Limitations in predicting reduced susceptibility to third generation cephalosporins in Escherichia coli based on whole genome sequence data

Prediction of antibiotic resistance from whole genome sequence (WGS) data has been proposed. However, the performance of WGS data analysis for this matter may be influenced by the resistance mechanism's biology. This study compared traditional antimicrobial susceptibility testing with whole genome sequencing for identification of extended-spectrum beta-lactamases (ESBL) in a collection of 419 Escherichia coli isolates. BLASTn-based prediction and read mapping with srst2 gave matching results, and in 381/419 (91%) isolates WGS was congruent with phenotypic testing. Incongruent results were grouped by potential explanations into biological-related and sequence analysis-related results. Biological-related explanations included weak ESBL-enzyme activity (n = 4), inconclusive phenotypic ESBL-testing (n = 4), potential loss of plasmid during subculturing (n = 7), and other resistance mechanisms than ESBL-enzymes (n = 2). Sequence analysis-related explanations were cut-off dependency for read depth (n = 5), too stringent (n = 3) and too loose cut-off for nucleotide identity and coverage (n = 13), respectively. The results reveal limitations of both traditional antibiotic susceptibility testing and sequence-based resistance prediction and highlight the need for evidence-based standards in sequence analysis.

[Assessment of available and currently applied typing methods including genome-based methods for zoonotic pathogens with a focus on Salmonella enterica]

BACKGROUND

In recent years, whole genome sequencing (WGS) in combination with bioinformatic analyses has become state of the art in evaluating the pathogenicity/resistance potential and relatedness of bacteria. WGS analysis thus represents a central tool in the investigation of the resistance and virulence potential of pathogens, as well as their dissemination via outbreak clusters and transmission chains within the framework of molecular epidemiology. In order to gain an overview of the available genotypic and phenotypic methods used for pathogen typing of Salmonella and Shiga toxin-producing and enterohemorrhagic Escherichia coli (STEC/EHEC) in Germany at state and federal level, along with the availability of WGS-based typing and corresponding analytical methods, a survey of laboratories was conducted.

METHODS

An electronic survey of laboratories working for public health protection and consumer health protection was conducted from February to June 2020.

RESULTS AND CONCLUSION

The results of the survey showed that many of the participating laboratories provide a wide range of phenotypic and molecular methods. Molecular typing is most commonly used for species identification of Salmonella. In many cases, WGS-based methods have already been established at federal and state institutions or are in the process of being established. The Illumina sequencing technology is the most widely used technology. The survey confirms the importance of molecular biology and whole genome typing technologies for laboratories in the diagnosis of bacterial zoonotic pathogens.

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.

Exploiting genomics to mitigate the public health impact of antimicrobial resistance

Antimicrobial resistance (AMR) is a major global public health threat, which has been largely driven by the excessive use of antimicrobials. Control measures are urgently needed to slow the trajectory of AMR but are hampered by an incomplete understanding of the interplay between pathogens, AMR encoding genes, and mobile genetic elements at a microbial level. These factors, combined with the human, animal, and environmental interactions that underlie AMR dissemination at a population level, make for a highly complex landscape. Whole-genome sequencing (WGS) and, more recently, metagenomic analyses have greatly enhanced our understanding of these processes, and these approaches are informing mitigation strategies for how we better understand and control AMR. This review explores how WGS techniques have advanced global, national, and local AMR surveillance, and how this improved understanding is being applied to inform solutions, such as novel diagnostic methods that allow antimicrobial use to be optimised and vaccination strategies for better controlling AMR. We highlight some future opportunities for AMR control informed by genomic sequencing, along with the remaining challenges that must be overcome to fully realise the potential of WGS approaches for international AMR control.

Multicenter Evaluation of the Acuitas ® AMR Gene Panel for Detection of an Extended Panel of Antimicrobial Resistance Genes among Bacterial Isolates

Background: The Acuitas® AMR Gene Panel is a qualitative, multiplex nucleic acid-based in vitro diagnostic test for detection and differentiation of 28 antimicrobial resistance (AMR) markers associated with not susceptible results (NS, i.e., intermediate or resistant) to one or more antimicrobial agents among cultured isolates of select Enterobacterales, Pseudomonas aeruginosa and Enterococcus faecalis. Methods: This study was conducted at four sites and included testing of 1,224 de-identified stocks created from 584 retrospectively collected isolates and 83 prospectively collected clinical isolates. The Acuitas results were compared with a combined reference standard including whole genome sequencing, organism identification and phenotypic antimicrobial susceptibility testing. Results: Positive percent agreement (PPA) for FDA-cleared AMR targets ranged from 94.4% for MCR-1 to 100% for armA, CTX-M-2, DHA, IMP, OXA-9, SHV, vanA and VEB. The negative percent agreement (NPA) for the majority of targets was ≥99%, except for AAC, AAD, CMY-41, P. aeruginosa gyrA mutant, Sul1, Sul2 and TEM targets (range: 96.5% to 98.5%). Three AMR markers did not meet FDA inclusion criteria (GES, SPM & MCR-2). For each organism, 1 to 22 AMR targets met the minimum reportable PPA/NPA and correlated with ≥80% positive predictive value with associated NS results for at least one agent (i.e., the probability of an organism carrying an AMR marker testing NS to the associated agent). Conclusion: We demonstrate that the Acuitas® AMR Gene Panel is an accurate method to detect a broad array of AMR markers among cultured isolates. The AMR markers were further associated with expected NS results for specific agent-organism combinations.

COMPARISON OF WHOLE GENOME SEQUENCE-BASED METHODS AND PCR RIBOTYPING FOR SUBTYPING OF Clostridioides difficile

Clostridioides difficile is the most common cause of antibiotic-associated gastrointestinal infections. Capillary-electrophoresis (CE)-PCR ribotyping is currently the gold standard for C. difficile typing but lacks discriminatory power to study transmission and outbreaks in detail. New molecular methods have the capacity to differentiate better and provide standardized and interlaboratory exchangeable data. Using a well-characterized collection of diverse strains (N=630; 100 unique ribotypes (RTs)), we compared the discriminatory power of core genome multilocus sequence typing (cgMLST) (SeqSphere & EnteroBase), whole genome MLST (wgMLST) (EnteroBase) and single nucleotide polymorphism (SNP) analysis. A unique cgMLST profile (>6 allele differences) was observed in 82/100 RTs, indicating that cgMLST could distinguish most, but not all, RTs. Application of cgMLST in two outbreak settings with RT078 and RT181 (known with a low intra-RT allele difference) showed no distinction between outbreak- and non-outbreak strains, in contrast to wgMLST and SNP analysis. We conclude that cgMLST has the potential to be an alternative to CE-PCR ribotyping. The method is reproducible, easy to standardize and offers higher discrimination. However, adjusted cut-off thresholds and epidemiological data are necessary to recognize outbreaks of some specific RTs. We propose to use an allelic threshold 3 alleles to identify outbreaks.

Rapid Real-Time Polymerase Chain Reaction for Salmonella Serotyping Based on Novel Unique Gene Markers by Pangenome Analysis

An accurate diagnostic method for Salmonella serovars is fundamental to preventing the spread of associated diseases. A diagnostic polymerase chain reaction (PCR)-based method has proven to be an effective tool for detecting pathogenic bacteria. However, the gene markers currently used in real-time PCR to detect Salmonella serovars have low specificity and are developed for only a few serovars. Therefore, in this study, we explored the novel unique gene markers for 60 serovars that share similar antigenic formulas and show high prevalence using pangenome analysis and developed a real-time PCR to detect them. Before exploring gene markers, the 535 Salmonella genomes were evaluated, and some genomes had serovars different from the designated serovar information. Based on these analyses, serovar-specific gene markers were explored. These markers were identified as genes present in all strains of target serovar genomes but absent in strains of other serovar genomes. Serovar-specific primer pairs were designed from the gene markers, and a real-time PCR method that can distinguish between 60 of the most common Salmonella serovars in a single 96-well plate assay was developed. As a result, real-time PCR showed 100% specificity for 199 Salmonella and 29 non-Salmonella strains. Subsequently, the method developed was applied successfully to both strains with identified serovars and an unknown strain, demonstrating that real-time PCR can accurately detect serovars of strains compared with traditional serotyping methods, such as antisera agglutination. Therefore, our method enables rapid and economical Salmonella serotyping compared with the traditional serotyping method.

Genomic population structure associated with repeated escape of Salmonella enterica ATCC14028s from the laboratory into nature

Salmonella enterica serovar Typhimurium strain ATCC14028s is commercially available from multiple national type culture collections, and has been widely used since 1960 for quality control of growth media and experiments on fitness (“laboratory evolution”). ATCC14028s has been implicated in multiple cross-contaminations in the laboratory, and has also caused multiple laboratory infections and one known attempt at bioterrorism. According to hierarchical clustering of 3002 core gene sequences, ATCC14028s belongs to HierCC cluster HC20_373 in which most internal branch lengths are only one to three SNPs long. Many natural Typhimurium isolates from humans, domesticated animals and the environment also belong to HC20_373, and their core genomes are almost indistinguishable from those of laboratory strains. These natural isolates have infected humans in Ireland and Taiwan for decades, and are common in the British Isles as well as the Americas. The isolation history of some of the natural isolates confirms the conclusion that they do not represent recent contamination by the laboratory strain, and 10% carry plasmids or bacteriophages which have been acquired in nature by HGT from unrelated bacteria. We propose that ATCC14028s has repeatedly escaped from the laboratory environment into nature via laboratory accidents or infections, but the escaped micro-lineages have only a limited life span. As a result, there is a genetic gap separating HC20_373 from its closest natural relatives due to a divergence between them in the late 19^th century followed by repeated extinction events of escaped HC20_373.

Clades of closely related bacteria exist in nature. Individual isolates from such clades are often distinguishable by genomic sequencing because genomic sequence differences can be acquired over a few years due to neutral drift and natural selection. The evolution of laboratory strains is often largely frozen, physically due to storage conditions and genetically due to long periods of storage. Thus, laboratory strains can normally be readily distinguished from natural isolates because they show much less diversity. However, laboratory strain ATCC14028s shows modest levels of sequence diversity because it has been shipped around the world to multiple laboratories and is routinely used for analyses of laboratory evolution. Closely related natural isolates also exist, but their genetic diversity is not dramatically greater at the core genome level. Indeed, many scientists doubt that such isolates are natural, and interpret them as undetected contamination by the laboratory strain. We present data indicating that ATCC14028s has repeatedly escaped from the laboratory through inadvertent contamination of the environment, infection of technical staff and deliberate bioterrorism. The escapees survive in nature long enough that some acquire mobile genomic elements by horizontal gene transfer, but eventually they go extinct. As a result, even extensive global databases of natural isolates lack closely related isolates whose ancestors diverged from ATCC14028s within the last 100 years.

Staphylococcus aureus and Cystic Fibrosis-A Close Relationship. What Can We Learn from Sequencing Studies?

Staphylococcus aureus is next to Pseudomonas aeruginosa the most isolated pathogen from the airways of cystic fibrosis (CF) patients, who are often infected by a dominant S. aureus clone for extended periods. To be able to persist, the pathogen has to adapt to the hostile niche of the airways to counteract host defence, antibiotic therapy and the competition with coinfecting pathogens. S. aureus is equipped with many virulence factors including adhesins, toxins that are localized on the chromosome, on plasmids or are phage-related. S. aureus is especially versatile and adaptation and evolution of the pathogen occurs by the acquisition of new genes by horizontal gene transfer (HGT), changes in nucleotides (single nucleotide variations, SNVs) that can cause a selective advantage for the bacteria and become fixed in subpopulations. Methicillin-resistant S. aureus are a special threat to CF patients due to the more severe lung disease occurring in infected patients. Today, with decreasing costs for sequencing, more and more studies using S. aureus isolates cultured from CF patients are being published, which use whole genome sequencing (WGS), multilocus sequence typing (MLST) or spa-sequence typing (spa-typing) to follow the population dynamics of S. aureus, elucidate the underlying mechanisms of phenotypic variants, newly acquired resistance or adaptation to the host response in this particular niche. In the first part of this review, an introduction to the genetic make-up and the pathogenesis of S. aureus with respect to CF is provided. The second part presents an overview of recent studies and their findings using genotypic methods such as single or multilocus sequencing and whole genome sequencing, which identify factors contributing to the adaptation of S. aureus and its evolution in the airways of individuals with CF.

Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study

Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling.

Centre-specific bacterial pathogen typing affects infection-control decision making

Whole-genome sequencing is becoming the de facto standard for bacterial outbreak surveillance and infection prevention. This is accompanied by a variety of bioinformatic tools and needs bioinformatics expertise for implementation. However, little is known about the concordance of reported outbreaks when using different bioinformatic workflows. In this multi-centre proficiency testing among 13 major Dutch healthcare-affiliated centres, bacterial whole-genome outbreak analysis was assessed. Centres who participated obtained two randomized bacterial datasets of Illumina sequences, a Klebsiella pneumoniae and a Vancomycin-resistant Enterococcus faecium, and were asked to apply their bioinformatic workflows. Centres reported back on antimicrobial resistance, multi-locus sequence typing (MLST), and outbreak clusters. The reported clusters were analysed using a method to compare landscapes of phylogenetic trees and calculating Kendall–Colijn distances. Furthermore, fasta files were analysed by state-of-the-art single nucleotide polymorphism (SNP) analysis to mitigate the differences introduced by each centre and determine standardized SNP cut-offs. Thirteen centres participated in this study. The reported outbreak clusters revealed discrepancies between centres, even when almost identical bioinformatic workflows were used. Due to stringent filtering, some centres failed to detect extended-spectrum beta-lactamase genes and MLST loci. Applying a standardized method to determine outbreak clusters on the reported de novo assemblies, did not result in uniformity of outbreak-cluster composition among centres.

A Quantitative Metagenomic Sequencing Approach for High-Throughput Gene Quantification and Demonstration with Antibiotic Resistance Genes

Comprehensive microbial risk assessment requires high-throughput quantification of diverse microbial risks in the environment. Current metagenomic next-generation sequencing approaches can achieve high-throughput detection of genes indicative of microbial risks but lack quantitative capabilities. This study developed and tested a quantitative metagenomic next-generation sequencing (qmNGS) approach. Numerous xenobiotic synthetic internal DNA standards were used to determine the sequencing yield (Y_seq) of the qmNGS approach, which can then be used to calculate absolute concentration of target genes in environmental samples based on metagenomic sequencing results. The qmNGS approach exhibited excellent linearity as indicated by a strong linear correlation (r² = 0.98) between spiked and detected concentrations of internal standards. High-throughput capability of the qmNGS approach was demonstrated with artificial Escherichia coli mixtures and cattle manure samples, for which 95 ± 3 and 208 ± 4 types of antibiotic resistance genes (ARGs) were detected and quantified simultaneously. The qmNGS approach was further compared with quantitative real-time PCR (qPCR) and demonstrated comparable levels of accuracy and less variation for the quantification of six target genes (16S, tetO, sulI, tetM, ermB, and qnrS). IMPORTANCE Monitoring and comprehensive assessment of microbial risks in the environment require high-throughput gene quantification. The quantitative metagenomic NGS (qmNGS) approach developed in this study incorporated numerous xenobiotic and synthetic DNA internal standard fragments into metagenomic NGS workflow, which are used to determine a new parameter called sequencing yield that relates sequence base reads to absolute concentration of target genes in the environmental samples. The qmNGS approach demonstrated excellent method linearity and comparable performance as the qPCR approach with high-throughput capability. This new qmNGS approach can achieve high-throughput and accurate gene quantification in environmental samples and has the potential to become a useful tool in monitoring and comprehensively assessing microbial risks in the environment.

Development and Validation of a Burkholderia pseudomallei Core Genome Multilocus Sequence Typing Scheme To Facilitate Molecular Surveillance

Burkholderia pseudomallei causes the severe disease melioidosis. Whole-genome sequencing (WGS)-based typing methods currently offer the highest resolution for molecular investigations of this genetically diverse pathogen. Still, its routine application in diagnostic laboratories is limited by the need for high computing power, bioinformatic skills, and variable bioinformatic approaches, with the latter affecting the results. We therefore aimed to establish and validate a WGS-based core genome multilocus sequence typing (cgMLST) scheme, applicable in routine diagnostic settings. A soft defined core genome was obtained by challenging the B. pseudomallei reference genome K96243 with 469 environmental and clinical genomes, resulting in 4,221 core and 1,351 accessory targets. The scheme was validated with 320 WGS data sets. We compared our novel typing scheme with single nucleotide polymorphism-based approaches investigating closely and distantly related strains. Finally, we applied our scheme for tracking the environmental source of a recent infection. The validation of the scheme detected >95% good cgMLST target genes in 98.4% of the genomes. Comparison with existing typing methods revealed very good concordance. Our scheme proved to be applicable to investigating not only closely related strains but also the global B. pseudomallei population structure. We successfully utilized our scheme to identify a sugarcane field as the presumable source of a recent melioidosis case. In summary, we developed a robust cgMLST scheme that integrates high resolution, maximized standardization, and fast analysis for the nonbioinformatician. Our typing scheme has the potential to serve as a routinely applicable classification system in B. pseudomallei molecular epidemiology.

A Whole-Genome-Based Gene-by-Gene Typing System for Standardized High-Resolution Strain Typing of Bacillus anthracis

Whole-genome sequencing (WGS) has been established for bacterial subtyping and is regularly used to study pathogen transmission, to investigate outbreaks, and to perform routine surveillance. Core-genome multilocus sequence typing (cgMLST) is a bacterial subtyping method that uses WGS data to provide a high-resolution strain characterization. This study aimed at developing a novel cgMLST scheme for Bacillus anthracis, a notorious pathogen that causes anthrax in livestock and humans worldwide. The scheme comprises 3,803 genes that were conserved in 57 B. anthracis genomes spanning the whole phylogeny. The scheme has been evaluated and applied to 584 genomes from 50 countries. On average, 99.5% of the cgMLST targets were detected. The cgMLST results confirmed the classical canonical single-nucleotide-polymorphism (SNP) grouping of B. anthracis into major clades and subclades. Genetic distances calculated based on cgMLST were comparable to distances from whole-genome-based SNP analysis with similar phylogenetic topology and comparable discriminatory power. Additionally, the application of the cgMLST scheme to anthrax outbreaks from Germany and Italy led to a definition of a cutoff threshold of five allele differences to trace epidemiologically linked strains for cluster typing and transmission analysis. Finally, the association of two clusters of B. anthracis with human cases of injectional anthrax in four European countries was confirmed using cgMLST. In summary, this study presents a novel cgMLST scheme that provides high-resolution strain genotyping for B. anthracis. This scheme can be used in parallel with SNP typing methods to facilitate rapid and harmonized interlaboratory comparisons, essential for global surveillance and outbreak analysis. The scheme is publicly available for application by users, including those with little bioinformatics knowledge.

An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities

Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

Validation strategy of a bioinformatics whole genome sequencing workflow for Shiga toxin-producing Escherichia coli using a reference collection extensively characterized with conventional methods

Whole genome sequencing (WGS) enables complete characterization of bacterial pathogenic isolates at single nucleotide resolution, making it the ultimate tool for routine surveillance and outbreak investigation. The lack of standardization, and the variation regarding bioinformatics workflows and parameters, however, complicates interoperability among (inter)national laboratories. We present a validation strategy applied to a bioinformatics workflow for Illumina data that performs complete characterization of Shiga toxin-producing Escherichia coli (STEC) isolates including antimicrobial resistance prediction, virulence gene detection, serotype prediction, plasmid replicon detection and sequence typing. The workflow supports three commonly used bioinformatics approaches for the detection of genes and alleles: alignment with blast+, kmer-based read mapping with KMA, and direct read mapping with SRST2. A collection of 131 STEC isolates collected from food and human sources, extensively characterized with conventional molecular methods, was used as a validation dataset. Using a validation strategy specifically adopted to WGS, we demonstrated high performance with repeatability, reproducibility, accuracy, precision, sensitivity and specificity above 95 % for the majority of all assays. The WGS workflow is publicly available as a 'push-button' pipeline at https://galaxy.sciensano.be. Our validation strategy and accompanying reference dataset consisting of both conventional and WGS data can be used for characterizing the performance of various bioinformatics workflows and assays, facilitating interoperability between laboratories with different WGS and bioinformatics set-ups.

Using core genome multilocus sequence typing (cgMLST) for vancomycin-resistant Enterococcus faecium isolates to guide infection control interventions and end an outbreak

OBJECTIVES

Until July 2016, vancomycin-resistantEnterococcus faecium (VREfm) was sporadically detected in Odense University Hospital, Denmark. After July 2016, the number of VREfm cases increased. This study aimed to apply a core genome multilocus sequence typing (cgMLST) scheme for E. faecium to type and analyse VREfm isolates collected at a single Danish hospital and to compare the results with cgMLST data from other regions of Denmark to trace transmission.

METHODS

A total of 38 VREfm clinical isolates from inpatients at the hospital in the period January 2014 through June 2017 were included in the study and analysed using whole-genome sequencing. Use of SeqSphere + software was initiated from the beginning of June 2017 to obtain MLST, cgMLST and epi curves. Admission histories were incorporated and national surveillance data on cgMLST were used to identify transmission routes.

RESULTS

Six different sequence types (STs) were identified, the most frequent being ST80, ST117 and ST203. cgMLST subdivided the 38 isolates into 18 different complex types (CTs) with 13 isolates (34%) belonging to ST80-CT993. Epi curves indicated transmission of ST80-CT993 in several departments. Transmission from patients transferred from other hospitals was not identifiable. Infection control interventions launched in one department ended the outbreak.

CONCLUSION

The high resolution of cgMLST allowed for detailed interpretation with evidence of nosocomial transmission of specific CTs. cgMLST made it easy to compare our local isolates with national findings, thereby clarifying transmission routes. Supplemented with admission histories, cgMLST targeted the epidemiological investigation and delineated the expensive and time-consuming infection control interventions.

Establishment and Evaluation of a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Pseudomonas aeruginosa

The environmental bacterium Pseudomonas aeruginosa, particularly multidrug-resistant clones, is often associated with nosocomial infections and outbreaks. Today, core genome multilocus sequence typing (cgMLST) is frequently applied to delineate sporadic cases from nosocomial transmissions. However, until recently, no cgMLST scheme for a standardized typing of P. aeruginosa was available. To establish a novel cgMLST scheme for P. aeruginosa, we initially determined the breadth of the P. aeruginosa population based on MLST data with a Bayesian approach (BAPS). Using genomic data of representative isolates for the whole population and all 12 serogroups, we extracted target genes and further refined them using a random data set of 1,000 P. aeruginosa genomes. Subsequently, we investigated reproducibility and discriminatory ability with repeatedly sequenced isolates and isolates from well-defined outbreak scenarios, respectively, and compared clustering applying two recently published cgMLST schemes. BAPS generated seven P. aeruginosa groups. To cover these and all serogroups, 15 reference strains were used to determine genes common in all strains. After refinement with the data set of 1,000 genomes, the cgMLST scheme consisted of 3,867 target genes, which are representative of the P. aeruginosa population and highly reproducible using biological replicates. We finally evaluated the scheme by reanalyzing two published outbreaks where the authors used single-nucleotide polymorphism (SNP) typing. In both cases, cgMLST was concordant with the previous SNP results and the results of the two other cgMLST schemes. In conclusion, the highly reproducible novel P. aeruginosa cgMLST scheme facilitates outbreak investigations due to the publicly available cgMLST nomenclature.

Multilocus Sequence Typing (MLST) and Whole Genome Sequencing (WGS) of Listeria monocytogenes and Listeria innocua

Nucleotide sequence-based methods focusing on the single-nucleotide polymorphisms (SNPs) of Listeria monocytogenes and L. innocua housekeeping genes (multilocus sequence typing) and in the core genome (core genome MLST) facilitate the rapid and interlaboratory comparison in open accessible databases as provided by Institute Pasteur ( https://bigsdb.web.pasteur.fr/listeria/listeria.html ). Strains can be compared on a global level and help to track forward and trace backward pathogen contamination events in food processing facilities and in outbreak scenarios.

NGS-Based S. aureus Typing and Outbreak Analysis in Clinical Microbiology Laboratories: Lessons Learned From a Swiss-Wide Proficiency Test

Whole genome sequencing (WGS) enables high resolution typing of bacteria up to the single nucleotide polymorphism (SNP) level. WGS is used in clinical microbiology laboratories for infection control, molecular surveillance and outbreak analyses. Given the large palette of WGS reagents and bioinformatics tools, the Swiss clinical bacteriology community decided to conduct a ring trial (RT) to foster harmonization of NGS-based bacterial typing. The RT aimed at assessing methicillin-susceptible Staphylococcus aureus strain relatedness from WGS and epidemiological data. The RT was designed to disentangle the variability arising from differences in sample preparation, SNP calling and phylogenetic methods. Nine laboratories participated. The resulting phylogenetic tree and cluster identification were highly reproducible across the laboratories. Cluster interpretation was, however, more laboratory dependent, suggesting that an increased sharing of expertise across laboratories would contribute to further harmonization of practices. More detailed bioinformatic analyses unveiled that while similar clusters were found across laboratories, these were actually based on different sets of SNPs, differentially retained after sample preparation and SNP calling procedures. Despite this, the observed number of SNP differences between pairs of strains, an important criterion to determine strain relatedness given epidemiological information, was similar across pipelines for closely related strains when restricting SNP calls to a common core genome defined by S. aureus cgMLST schema. The lessons learned from this pilot study will serve the implementation of larger-scale RT, as a mean to have regular external quality assessments for laboratories performing WGS analyses in a clinical setting.

Antimicrobial resistant and enteropathogenic bacteria in 'filth flies': a cross-sectional study from Nigeria

‘Filth flies’ facilitate the dispersal of pathogens between animals and humans. The objective was to study the intestinal colonization with antimicrobial resistant and enteropathogenic bacteria in ‘filth flies’ from Nigeria. Flies from Southern Nigeria were screened for extended-spectrum β-lactamase producing Enterobacterales (ESBL-E), Staphylococcus aureus, Salmonella sp., Shigella sp., Campylobacter sp. and Yersinia enterocolitica by culture. ESBL-E were tested for bla_SHV, bla_CTX-M and bla_TEM; S. aureus was screened for enterotoxins. Spa typing and multilocus sequence typing (MLST) was done for S. aureus and MLST for Escherichia coli. Of 2,000 flies, 400 were randomly collected for species identification. The most common species were Musca domestica (44.8%, 179/400), Chrysomya putoria (21.6%, 85/400) and Musca sorbens (18.8%, 75/400). Flies were colonized with S. aureus (13.8%, 275/2,000) and ESBL-E (0.8%, 16/2,000). No other enteropathogenic bacteria were detected. The enterotoxin sei was most common (26%, 70/275) in S. aureus, followed by sea (12%, n = 32/275). Four S. aureus isolates were methicillin resistant (mecA positive, t674 and t5305, ST15). The bla_CTX-M (n = 16) was the most prevalent ESBL subtype, followed by bla_TEM (n = 8). ‘Filth flies’ can carry antimicrobial resistant bacteria in Nigeria. Enterotoxin-positive S. aureus might be the main reason for food poisoning by ‘filth flies’ in the study area.

Development of Real-Time PCR Assay to Specifically Detect 22 Bifidobacterium Species and Subspecies Using Comparative Genomics

Bifidobacterium species are used as probiotics to provide beneficial effects to humans. These effects are specific to some species or subspecies of Bifidobacterium. However, some Bifidobacterium species or subspecies are not distinguished because similarity of 16S rRNA and housekeeping gene sequences within Bifidobacterium species is very high. In this study, we developed a real-time polymerase chain reaction (PCR) assay to rapidly and accurately detect 22 Bifidobacterium species by selecting genetic markers using comparative genomic analysis. A total of 210 Bifidobacterium genome sequences were compared to select species- or subspecies-specific genetic markers. A phylogenetic tree based on pan-genomes generated clusters according to Bifidobacterium species or subspecies except that two strains were not grouped with their subspecies. Based on pan-genomes constructed, species- or subspecies-specific genetic markers were selected. The specificity of these markers was confirmed by aligning these genes against 210 genome sequences. Real-time PCR could detect 22 Bifidobacterium specifically. We constructed the criterion for quantification by standard curves. To further test the developed assay for commercial food products, we monitored 26 probiotic products and 7 dairy products. Real-time PCR results and labeling data were then compared. Most of these products (21/33, 63.6%) were consistent with their label claims. Some products labeled at species level only can be detected up to subspecies level through our developed assay.

Molecular epidemiology in current times

Motivated to find options for prevention or intervention, molecular epidemiology aims to identify the host and microbial factors that determine the transmission, manifestation and progression of infectious disease. The genotyping of cultivatable bacterial strains is performed by either anonymous fingerprinting techniques or sequence-based exploration of variable genomic sites. Multilocus sequence typing of housekeeping genes and allele profiling of the core genome have become standard techniques of bacterial strain typing that may be supplemented by whole genome sequencing to explore all single nucleotide variants and/or the composition of the accessory genome. Next, novel protocols to investigate host and microbiome based upon smart third generation sequencing technologies are being developed for an effective surveillance, rapid diagnosis and real-time tracking of infectious diseases.

German-Wide Interlaboratory Study Compares Consistency, Accuracy and Reproducibility of Whole-Genome Short Read Sequencing

We compared the consistency, accuracy and reproducibility of next-generation short read sequencing between ten laboratories involved in food safety (research institutes, state laboratories, universities and companies) from Germany and Austria. Participants were asked to sequence six DNA samples of three bacterial species (Campylobacter jejuni, Listeria monocytogenes and Salmonella enterica) in duplicate, according to their routine in-house sequencing protocol. Four different types of Illumina sequencing platforms (MiSeq, NextSeq, iSeq, NovaSeq) and one Ion Torrent sequencing instrument (S5) were involved in the study. Sequence quality parameters were determined for all data sets and centrally compared between laboratories. SNP and cgMLST calling were performed to assess the reproducibility of sequence data collected for individual samples. Overall, we found Illumina short read data to be more accurate (higher base calling accuracy, fewer miss-assemblies) and consistent (little variability between independent sequencing runs within a laboratory) than Ion Torrent sequence data, with little variation between the different Illumina instruments. Two laboratories with Illumina instruments submitted sequence data with lower quality, probably due to the use of a library preparation kit, which shows difficulty in sequencing low GC genome regions. Differences in data quality were more evident after assembling short reads into genome assemblies, with Ion Torrent assemblies featuring a great number of allele differences to Illumina assemblies. Clonality of samples was confirmed through SNP calling, which proved to be a more suitable method for an integrated data analysis of Illumina and Ion Torrent data sets in this study.

Genomics of Serratia marcescens Isolates Causing Outbreaks in the Same Pediatric Unit 47 Years Apart: Position in an Updated Phylogeny of the Species

The first documented nosocomial outbreak caused by Serratia marcescens in Spain occurred in 1969 at the neonatal intensive care unit (NICU) of the tertiary La Paz Children's Hospital in Madrid, Spain, and based on the available phenotyping techniques at this time, it was considered as a monoclonal outbreak. Only 47 years later, another S. marcescens outbreak of an equivalent dimension occurred at the same NICU. The aim of the present study was to study isolates from these historical and contemporary outbreaks by phenotypic analysis and whole-genome sequencing techniques and to position these strains along with 444 publicly available S. marcescens genomes, separately comparing core genome and accessory genome contents. Clades inferred by both approaches showed high correlation, indicating that core and accessory genomes seem to evolve in the same manner for S. marcescens. Nine S. marcescens clusters were identified, and isolates were grouped in two of them according to sampling year. One exception was isolate 13F-69, the most genetically distant strain, located in a different cluster. Categorical functions in the annotated accessory genes of both collections were preserved among all isolates. No significant differences in frequency of insertion sequences in historical (0.18-0.20)-excluding the outlier strain-versus contemporary isolates (0.11-0.19) were found despite the expected resting effect. The most dissimilar isolate, 13F-69, contains a highly preserved plasmid previously described in Bordetella bronchiseptica. This strain exhibited a few antibiotic resistance genes not resulting in a resistant phenotype, suggesting the value of gene down expression in adaptation to long-term starvation.

Novel real-time PCR assay for Lactobacillus casei group species using comparative genomics

The Lactobacillus casei group, which includes the closely related species L. casei, L. paracasei, L. rhamnosus, and L. chiayiensis, has been under debate regarding its taxonomy because of the difficulty in distinguishing the species from each other. In the present study, we developed a novel real-time PCR assay for distinguishing the L. casei group species. The pan-genome, as determined by the genomes of 44 strains, comprised 6789 genes, comparative genomic analysis showed that L. casei group strains were classified by species. Based on these results, species-specific genes were identified, and primers were designed from those genes. Real-time PCR clearly distinguished each species of the L. casei group and specifically amplified only to the target species. The method was applied to 29 probiotic products, and the detected results and label claims were compared. Total 23 products were in accordance with the label claims, and the remaining products contained species different from those stated in the label claims. Our method can rapidly and accurately distinguish the L. casei group species in a single reaction. Hence, our assay can be applied to identify L. casei group species from food or environmental samples and to accurately determine the nomenclature of the species.

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories.

Genotypic Characterization of Livestock-Associated Methicillin-Resistant Staphylococcus aureus Isolates of Clonal Complex 398 in Pigsty Visitors: Transient Carriage or Persistence?

Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) of clonal complex (CC) 398 has become a rising issue for public health. While it is known that >80% of pig farmers are colonized with LA-MRSA, only a few studies have assessed the situation for humans with occasional livestock contact. Recently it was shown that over 75% of scientific fieldworkers visiting pigsties were temporarily carrying LA-MRSA. To find out whether they were transiently or permanently colonized, we used whole-genome sequencing (WGS) data to analyze the relatedness of isolates from these recurrently LA-MRSA-positive fieldworkers and from corresponding pigsties. Sequences were analyzed using in silico typing (spa and core genomic multilocus sequence typing [cgMLST]), and the BEAST software package was used to examine phylogeny. In total, 81 samples from three fieldworkers on eight different pigsties over a period of 2.5 years were sequenced. All isolates belonged to spa type t011, t034, or t2011, with different types found in the same fieldworker at different time points. Analysis of cgMLST revealed nine genotypic clusters, mostly correlating with the pigsty on which they were sampled. Fieldworker isolates clustered with the samples from farms that were visited on the same day. BEAST analysis corroborated the cgMLST-based clustering and suggests an origin of the lineage about 22 years ago. We conclude that nasal LA-MRSA colonization among humans with occasional livestock contact is common but most likely only temporary. Furthermore, we showed that the Western German LA-MRSA CC398 originated in the late 1990s and diversified into farm-specific genotypes, which stay relatively consistent over time.

Hash-Based Core Genome Multilocus Sequence Typing for Clostridium difficile

Pathogen whole-genome sequencing has huge potential as a tool to better understand infection transmission. However, rapidly identifying closely related genomes among a background of thousands of other genomes is challenging. Here, we describe a refinement to core genome multilocus sequence typing (cgMLST) in which alleles at each gene are reproducibly converted to a unique hash, or short string of letters (hash-cgMLST). This avoids the resource-intensive need for a single centralized database of sequentially numbered alleles. We test the reproducibility and discriminatory power of cgMLST/hash-cgMLST compared to those of mapping-based approaches in Clostridium difficile, using repeated sequencing of the same isolates (replicates) and data from consecutive infection isolates from six English hospitals. Hash-cgMLST provided the same results as standard cgMLST, with minimal performance penalty. Comparing 272 replicate sequence pairs using reference-based mapping, there were 0, 1, or 2 single-nucleotide polymorphisms (SNPs) between 262 (96%), 5 (2%), and 1 (<1%) of the pairs, respectively. Using hash-cgMLST, 218 (80%) of replicate pairs assembled with SPAdes had zero gene differences, and 31 (11%), 5 (2%), and 18 (7%) pairs had 1, 2, and >2 differences, respectively. False gene differences were clustered in specific genes and associated with fragmented assemblies, but were reduced using the SKESA assembler. Considering 412 pairs of infections with ≤2 SNPS, i.e., consistent with recent transmission, 376 (91%) had ≤2 gene differences and 16 (4%) had ≥4. Comparing a genome to 100,000 others took <1 min using hash-cgMLST. Hash-cgMLST is an effective surveillance tool for rapidly identifying clusters of related genomes. However, cgMLST/hash-cgMLST generate more false variants than mapping-based approaches. Follow-up mapping-based analyses are likely required to precisely define close genetic relationships.

Application of different DNA extraction procedures, library preparation protocols and sequencing platforms: impact on sequencing results

In this study three DNA extraction procedures, two library preparation protocols and two sequencing platforms were applied to analyse six bacterial cultures and their corresponding DNA obtained as part of a proficiency test. The impact of each variable on sequencing results was assessed using the following parameters: reads quality, assembly and alignment statistics; number of single nucleotide polymorphisms (SNPs), detected applying assembly- and alignment-based strategies; antimicrobial resistance genes (ARGs), identified on de novo assemblies of all sequenced genomes. The investigated nucleic acid extraction procedures, library preparation kits and sequencing platforms do not significantly affect de novo assembly statistics and number of SNPs and ARGs. The only exception was observed for two duplicates, which were associated to one PCR-based library preparation kit. Results from this comparative study can support researchers in the choice toward the available pre-sequencing and sequencing options, and might suggest further comparisons to be performed.

Pulsed-field gel electrophoresis (PFGE): A review of the "gold standard" for bacteria typing and current alternatives

Pulsed-field gel electrophoresis (PFGE) is considered the "gold standard" for bacteria typing. The method involves enzyme restriction of bacteria DNA, separation of the restricted DNA bands using a pulsed-field electrophoresis chamber, followed by clonal assignment of bacteria based on PFGE banding patterns. Various PFGE protocols have been developed for typing different bacteria, leading it to be one of the most widely used methods for phylogenetic studies, food safety surveillance, infection control and outbreak investigations. On the other hand, as PFGE is lengthy and labourious, several PCR-based typing methods can be used as alternatives for research purposes. Recently, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and whole genome sequencing (WGS) have also been proposed for bacteria typing. In fact, as WGS provides more information, such as antimicrobial resistance and virulence of the tested bacteria in comparison to PFGE, more and more laboratories are currently transitioning from PFGE to WGS for bacteria typing. Nevertheless, PFGE will remain an affordable and relevant technique for small laboratories and hospitals in years to come.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Validation of a Bioinformatics Workflow for Routine Analysis of Whole-Genome Sequencing Data and Related Challenges for Pathogen Typing in a European National Reference Center: Neisseria meningitidis as a Proof-of-Concept

Despite being a well-established research method, the use of whole-genome sequencing (WGS) for routine molecular typing and pathogen characterization remains a substantial challenge due to the required bioinformatics resources and/or expertise. Moreover, many national reference laboratories and centers, as well as other laboratories working under a quality system, require extensive validation to demonstrate that employed methods are "fit-for-purpose" and provide high-quality results. A harmonized framework with guidelines for the validation of WGS workflows does currently, however, not exist yet, despite several recent case studies highlighting the urgent need thereof. We present a validation strategy focusing specifically on the exhaustive characterization of the bioinformatics analysis of a WGS workflow designed to replace conventionally employed molecular typing methods for microbial isolates in a representative small-scale laboratory, using the pathogen Neisseria meningitidis as a proof-of-concept. We adapted several classically employed performance metrics specifically toward three different bioinformatics assays: resistance gene characterization (based on the ARG-ANNOT, ResFinder, CARD, and NDARO databases), several commonly employed typing schemas (including, among others, core genome multilocus sequence typing), and serogroup determination. We analyzed a core validation dataset of 67 well-characterized samples typed by means of classical genotypic and/or phenotypic methods that were sequenced in-house, allowing to evaluate repeatability, reproducibility, accuracy, precision, sensitivity, and specificity of the different bioinformatics assays. We also analyzed an extended validation dataset composed of publicly available WGS data for 64 samples by comparing results of the different bioinformatics assays against results obtained from commonly used bioinformatics tools. We demonstrate high performance, with values for all performance metrics >87%, >97%, and >90% for the resistance gene characterization, sequence typing, and serogroup determination assays, respectively, for both validation datasets. Our WGS workflow has been made publicly available as a "push-button" pipeline for Illumina data at https://galaxy.sciensano.be to showcase its implementation for non-profit and/or academic usage. Our validation strategy can be adapted to other WGS workflows for other pathogens of interest and demonstrates the added value and feasibility of employing WGS with the aim of being integrated into routine use in an applied public health setting.

Messages from the third International Conference on Clinical Metagenomics (ICCMg3)

Clinical metagenomics (CMg), referring to as the application of metagenomic sequencing of clinical samples in order to recover clinically-relevant information, has been rapidly evolving these last years. Following this trend, we held the third International Conference on Clinical Metagenomics (ICCMg3) in Geneva in October 2018. During the two days of the conference, several aspects of CMg were addressed, which we propose to summarize in the present manuscript. During this ICCMg3, we kept on following the progresses achieved worldwide on clinical metagenomics, but also this year in clinical genomics. Besides, the use of metagenomics in cancer diagnostic and management was addressed. Some new challenges have also been raised such as the way to report clinical (meta)genomics output to clinicians and the pivotal place of ethics in this expanding field.

Use of MALDI-TOF mass spectrometry to detect nosocomial outbreaks of Serratia marcescens and Citrobacter freundii

MALDI-TOF mass spectrometry (MS) may be used as a rapid typing method for nosocomial pathogens. Here, we evaluated MALDI-TOF MS for discrimination of hospital outbreak-related clusters of Serratia marcescens and carbapenemase-producing Citrobacter freundii. Thirty-three S. marcescens isolates collected from neonatal intensive care unit (NICU) patients, and 23 C. freundii isolates including VIM-positive isolates from a hospital colonization outbreak were measured by Vitek MS. Consensus spectra of each isolate were clustered using SARAMIS software. Genotyping was performed by whole-genome sequencing (WGS). First, a set of 21 S. marcescens isolates from 2014 with seven genotypes including three monoclonal clusters was used for the evaluation of MALDI-TOF typing. MS clustering was largely in agreement with genotyping results when the similarity cut-off for clonal identity was set on 90%. MALDI-TOF cluster analysis was then investigated for the surveillance of S. marcescens in the NICU in 2017 and demonstrated the introduction of new strains into the hospital and nosocomial transmissions. MS analysis of the C. freundii outbreak in 2016 revealed a monoclonal cluster of VIM-positive isolates and the separation of epidemiologically non-related VIM-positive and negative isolates. Two additional VIM-positive Citrobacter isolates from food samples were closely related to the large monoclonal cluster. WGS confirmed the MS results. MALDI-TOF MS may be used as a first-line typing tool for S. marcescens and C. freundii to detect transmission events in the hospital because isolates of an identical WGS type were grouped into the same MS cluster.

Genomic Alterations of Staphylococcus aureus ATCC 25923 after Prolonged Passage in the Laboratory

Staphylococcus aureus reference strain ATCC 25923 has been maintained for more than a decade in our laboratory. Genomic study revealed that the resulting strain AFIPCBER_B_8.4 has lost a 37-kb genomic fragment of the ATCC 25923 parental strain.

Staphylococcus aureus reference strain ATCC 25923 has been maintained for more than a decade in our laboratory. Genomic study revealed that the resulting strain AFIPCBER_B_8.4 has lost a 37-kb genomic fragment of the ATCC 25923 parental strain. The missing fragment showed sequence similarity to genes of bacteriophage proteins.

Accuracy of Different Bioinformatics Methods in Detecting Antibiotic Resistance and Virulence Factors from Staphylococcus aureus Whole-Genome Sequences

In principle, whole-genome sequencing (WGS) can predict phenotypic resistance directly from a genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. We compared three WGS-based bioinformatics methods (Genefinder [read based], Mykrobe [de Bruijn graph based], and Typewriter [BLAST based]) for predicting the presence/absence of 83 different resistance determinants and virulence genes and overall antimicrobial susceptibility in 1,379 Staphylococcus aureus isolates previously characterized by standard laboratory methods (disc diffusion, broth and/or agar dilution, and PCR). In total, 99.5% (113,830/114,457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fleiss' kappa = 0.98, P < 0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b). The genotypic antimicrobial susceptibility prediction matched the laboratory phenotype in 98.3% (14,224/14,464) of cases (2,720 [18.8%] resistant, 11,504 [79.5%] susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 [0.7%] phenotypically susceptible, but all bioinformatic methods reported resistance; 89 [0.6%] phenotypically resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 [0.4%] cases, 16 phenotypically resistant, 38 phenotypically susceptible). However, in 36/54 (67%) cases, the consensus genotype matched the laboratory phenotype. In this study, the choice between these three specific bioinformatic methods to identify resistance determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations; therefore, consensus methods provide some assurance.

Gene Expression Detection Assay for Cancer Clinical Use

Cancer is a genetic disease where genetic variations cause abnormally functioning genes that appear to alter expression. Proteins, the final products of gene expression, determine the phenotypes and biological processes. Therefore, detecting gene expression levels can be used for cancer diagnosis, prognosis, and treatment prediction in a clinical setting. In this review, we investigated six gene expression assay systems (qRT-PCR, DNA microarray, nCounter, RNA-Seq, FISH, and tissue microarray) that are currently being used in clinical cancer studies. Some of these methods are also commonly used in a modified way; for example, detection of DNA content or protein expression. Herein, we discuss their principles, sample preparation, design, quantification and sensitivity, data analysis, time for sample preparation and processing, and cost. We also compared these methods according to their sample selection, particularly for the feasibility of using formalin-fixed paraffin-embedded (FFPE) samples, which are routinely archived for clinical cancer studies. We intend to provide a guideline for choosing an assay method with respect to its oncological applications in a clinical setting.

Defining and Evaluating a Core Genome Multilocus Sequence Typing Scheme for Genome-Wide Typing of Clostridium difficile

Clostridium difficile, recently renamed Clostridioides difficile, is the most common cause of antibiotic-associated nosocomial gastrointestinal infections worldwide. To differentiate endogenous infections and transmission events, highly discriminatory subtyping is necessary. Today, methods based on whole-genome sequencing data are increasingly used to subtype bacterial pathogens; however, frequently a standardized methodology and typing nomenclature are missing. Here we report a core genome multilocus sequence typing (cgMLST) approach developed for C. difficile Initially, we determined the breadth of the C. difficile population based on all available MLST sequence types with Bayesian inference (BAPS). The resulting BAPS partitions were used in combination with C. difficile clade information to select representative isolates that were subsequently used to define cgMLST target genes. Finally, we evaluated the novel cgMLST scheme with genomes from 3,025 isolates. BAPS grouping (n = 6 groups) together with the clade information led to a total of 11 representative isolates that were included for cgMLST definition and resulted in 2,270 cgMLST genes that were present in all isolates. Overall, 2,184 to 2,268 cgMLST targets were detected in the genome sequences of 70 outbreak-associated and reference strains, and on average 99.3% cgMLST targets (1,116 to 2,270 targets) were present in 2,954 genomes downloaded from the NCBI database, underlining the representativeness of the cgMLST scheme. Moreover, reanalyzing different cluster scenarios with cgMLST were concordant to published single nucleotide variant analyses. In conclusion, the novel cgMLST is representative for the whole C. difficile population, is highly discriminatory in outbreak situations, and provides a unique nomenclature facilitating interlaboratory exchange.

Safety Evaluations of Bifidobacterium bifidum BGN4 and Bifidobacterium longum BORI

Over the past decade, a variety of lactic acid bacteria have been commercially available to and steadily used by consumers. However, recent studies have shown that some lactic acid bacteria produce toxic substances and display properties of virulence. To establish safety guidelines for lactic acid bacteria, the Food and Agriculture Organization of the United Nations (FAO)/World Health Organization (WHO) has suggested that lactic acid bacteria be characterized and proven safe for consumers’ health via multiple experiments (e.g., antibiotic resistance, metabolic activity, toxin production, hemolytic activity, infectivity in immune-compromised animal species, human side effects, and adverse-outcome analyses). Among the lactic acid bacteria, Bifidobacterium and Lactobacillus species are probiotic strains that are most commonly commercially produced and actively studied. Bifidobacterium bifidum BGN4 and Bifidobacterium longum BORI have been used in global functional food markets (e.g., China, Germany, Jordan, Korea, Lithuania, New Zealand, Poland, Singapore, Thailand, Turkey, and Vietnam) as nutraceutical ingredients for decades, without any adverse events. However, given that the safety of some newly screened probiotic species has recently been debated, it is crucial that the consumer safety of each commercially utilized strain be confirmed. Accordingly, this paper details a safety assessment of B. bifidum BGN4 and B. longum BORI via the assessment of ammonia production, hemolysis of blood cells, biogenic amine production, antimicrobial susceptibility pattern, antibiotic resistance gene transferability, PCR data on antibiotic resistance genes, mucin degradation, genome stability, and possession of virulence factors. These probiotic strains showed neither hemolytic activity nor mucin degradation activity, and they did not produce ammonia or biogenic amines (i.e., cadaverine, histamine or tyramine). B. bifidum BGN4 and B. longum BORI produced a small amount of putrescine, commonly found in living cells, at levels similar to or lower than that found in other foods (e.g., spinach, ketchup, green pea, sauerkraut, and sausage). B. bifidum BGN4 showed higher resistance to gentamicin than the European Food Safety Authority (EFSA) cut-off. However, this paper shows the gentamicin resistance of B. bifidum BGN4 was not transferred via conjugation with L. acidophilus ATCC 4356, the latter of which is highly susceptible to gentamicin. The entire genomic sequence of B. bifidum BGN4 has been published in GenBank (accession no.: CP001361.1), documenting the lack of retention of plasmids capable of transferring an antibiotic-resistant gene. Moreover, there was little genetic mutation between the first and 25th generations of B. bifidum BGN4. Tetracycline-resistant genes are prevalent among B. longum strains; B. longum BORI has a tet(W) gene on its chromosome DNA and has also shown resistance to tetracycline. However, this research shows that its tetracycline resistance was not transferred via conjugation with L. fermentum AGBG1, the latter of which is highly sensitive to tetracycline. These findings support the continuous use of B. bifidum BGN4 and B. longum BORI as probiotics, both of which have been reported as safe by several clinical studies, and have been used in food supplements for many years.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies

Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a “One Health” approach.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies

Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a "One Health" approach.

Molecular Epidemiology of Multidrug-Resistant Bacteria Isolated from Libyan and Syrian Patients with War Injuries in Two Bundeswehr Hospitals in Germany

Introduction

We assessed the molecular epidemiology of multidrug-resistant bacteria colonizing or infecting war-injured patients from Libya and Syria who were treated at the Bundeswehr hospitals Hamburg and Westerstede, Germany.

Methods

Enterobacteriaceae and Gram-negative rod-shaped nonfermentative bacteria with resistance against third-generation methoxyimino cephalosporins or carbapenems as well as methicillin-resistant Staphylococcus aureus (MRSA) from war-injured patients from Libya and Syria were assessed by molecular typing, i.e., spa typing for MRSA strains and rep-PCR and next-generation sequencing (NGS) for Gram-negative isolates.

Results

A total of 66 isolates were assessed – comprising 44 Enterobacteriaceae, 16 nonfermentative rod-shaped bacteria, and 6 MRSA from 22 patients – and 8 strains from an assessment of the patient environment comprising 5 Enterobacteriaceae and 3 nonfermentative rod-shaped bacteria. Although 24 out of 66 patient strains were isolated more than 3 days after hospital admission, molecular typing suggested only 7 likely transmission events in the hospitals. Identified clonal clusters primarily suggested transmission events in the country of origin or during the medical evacuation flights.

Conclusions

Nosocomial transmissions in hospital can be efficiently prevented by hygiene precautions in spite of heavy colonization. Transmission prior to hospital admission like on evacuation flights or in crises zones needs further assessment.

Validation of Whole-Genome Sequencing for Identification and Characterization of Shiga Toxin-Producing Escherichia coli To Produce Standardized Data To Enable Data Sharing

Whole-genome sequencing (WGS) is rapidly becoming the method of choice for outbreak investigations and public health surveillance of microbial pathogens. The combination of improved cluster resolution and prediction of resistance and virulence phenotypes provided by a single tool is extremely advantageous. However, the data produced are complex, and standard bioinformatics pipelines are required to translate the output into easily interpreted epidemiologically relevant information for public health action. The main aim of this study was to validate the implementation of WGS at the Scottish Escherichia coli O157/STEC Reference Laboratory (SERL) using the Public Health England (PHE) bioinformatics pipeline to produce standardized data to enable interlaboratory comparison of results generated at two national reference laboratories. In addition, we evaluated the BioNumerics whole-genome multilocus sequence typing (wgMLST) and E. coli genotyping plug-in tools using the same data set. A panel of 150 well-characterized isolates of Shiga toxin-producing E. coli (STEC) that had been sequenced and analyzed at PHE using the PHE pipeline and database (SnapperDB) was assembled to provide identification and typing data, including serotype (O:H type), sequence type (ST), virulence genes (eae and Shiga toxin [stx] subtype), and a single-nucleotide polymorphism (SNP) address. To validate the implementation of sequencing at the SERL, DNA was reextracted from the isolates and sequenced and analyzed using the PHE pipeline, which had been installed at the SERL; the output was then compared with the PHE data. The results showed a very high correlation between the data, ranging from 93% to 100%, suggesting that the standardization of WGS between our reference laboratories is possible. We also found excellent correlation between the results obtained using the PHE pipeline and BioNumerics, except for the detection of stx_2a and stx_2c when these subtypes are both carried by strains.

The Odyssey of the Ancestral Escherich Strain through Culture Collections: an Example of Allopatric Diversification

More than a century ago, Theodor Escherich isolated the bacterium that was to become Escherichia coli, one of the most studied organisms. Not long after, the strain began an odyssey and landed in many laboratories across the world. As laboratory culture conditions could be responsible for major changes in bacterial strains, we conducted a genome analysis of isolates of this emblematic strain from different culture collections (England, France, the United States, Germany). Strikingly, many discrepancies between the isolates were observed, as revealed by multilocus sequence typing (MLST), the presence of virulence-associated genes, core genome MLST, and single nucleotide polymorphism/indel analyses. These differences are correlated with the phylogeographic history of the strain and were due to an unprecedented number of mutations in coding DNA repair functions such as mismatch repair (MutL) and oxidized guanine nucleotide pool cleaning (MutT), conferring a specific mutational spectrum and leading to a mutator phenotype. The mutator phenotype was probably acquired during subculturing and corresponded to second-order selection. Furthermore, all of the isolates exhibited hypersusceptibility to antibiotics due to mutations in efflux pump- and porin-encoding genes, as well as a specific mutation in the sigma factor-encoding gene rpoS. These defects reflect a self-preservation and nutritional competence tradeoff allowing survival under the starvation conditions imposed by storage. From a clinical point of view, dealing with such mutator strains can lead microbiologists to draw false conclusions about isolate relatedness and may impact therapeutic effectiveness. IMPORTANCE Mutator phenotypes have been described in laboratory-evolved bacteria, as well as in natural isolates. Several genes can be impacted, each of them being associated with a typical mutational spectrum. By studying one of the oldest strains available, the ancestral Escherich strain, we were able to identify its mutator status leading to tremendous genetic diversity among the isolates from various collections and allowing us to reconstruct the phylogeographic history of the strain. This mutator phenotype was probably acquired during the storage of the strain, promoting adaptation to a specific environment. Other mutations in rpoS and efflux pump- and porin-encoding genes highlight the acclimatization of the strain through self-preservation and nutritional competence regulation. This strain history can be viewed as unintentional experimental evolution in culture collections all over the word since 1885, mimicking the long-term experimental evolution of E. coli of Lenski et al. (O. Tenaillon, J. E. Barrick, N. Ribeck, D. E. Deatherage, J. L. Blanchard, A. Dasgupta, G. C. Wu, S. Wielgoss, S. Cruveiller, C. Médigue, D. Schneider, and R. E. Lenski, Nature 536:165-170, 2016, https://doi.org/10.1038/nature18959) that shares numerous molecular features.

Diagnostics and laboratory role in outbreaks

PURPOSE OF REVIEW

The review describes the investigative benefits of traditional and novel molecular epidemiology techniques, while acknowledging the limitations faced by clinical laboratories seeking to implement these methods.

RECENT FINDINGS

Pulse-field gel electrophoresis and other traditional techniques remain powerful tools in outbreak investigations and continue to be used by multiple groups. Newer techniques such as matrix-assisted laser desorption/ionization-time of flight mass-spectrometry and whole genome sequencing show great promise. However, there is a lack of standardization regarding definitions for genetic relatedness, nor are there established criteria for accuracy and reproducibility. There are also challenges regarding availability of trained bioinformatics staff, and concerns regarding reimbursement.

SUMMARY

There are many tools available for molecular epidemiologic investigation. Epidemiologists and clinical laboratorians should work together to determine which testing methods are best for each institution.