scholarly journals GBS-SBG - GBS Serotyping by Genome Sequencing

2021 ◽  
Vol 7 (12) ◽  
Author(s):  
Suma Tiruvayipati ◽  
Wen Ying Tang ◽  
Timothy M. S. Barkham ◽  
Swaine L. Chen
Keyword(s):  
Genome Sequencing ◽  
Type Species ◽  
Neonatal Meningitis ◽  
Data Types ◽  
Data Set ◽  
Short Read ◽  
Content Type ◽  
Link Type ◽  
Group B ◽  
Reported Data

Group B Streptococcus (GBS; Streptococcus agalactiae ) is the most common cause of neonatal meningitis and a rising cause of sepsis in adults. Recently, it has also been shown to cause foodborne disease. As with many other bacteria, the polysaccharide capsule of GBS is antigenic, enabling its use for strain serotyping. Recent advances in DNA sequencing have made sequence-based typing attractive (as has been implemented for several other bacteria, including Escherichia coli , Klebsiella pneumoniae species complex, Streptococcus pyogenes , and others). For GBS, existing WGS-based serotyping systems do not provide complete coverage of all known GBS serotypes (specifically including subtypes of serotype III), and none are simultaneously compatible with the two most common data types, raw short reads and assembled sequences. Here, we create a serotyping database (GBS-SBG, GBS Serotyping by Genome Sequencing), with associated scripts and running instructions, that can be used to call all currently described GBS serotypes, including subtypes of serotype III, using both direct short-read- and assembly-based typing. We achieved higher concordance using GBS-SBG on a previously reported data set of 790 strains. We further validated GBS-SBG on a new set of 572 strains, achieving 99.8% concordance with PCR-based molecular serotyping using either short-read- or assembly-based typing. The GBS-SBG package is publicly available and will hopefully accelerate and simplify serotyping by sequencing for GBS.

scholarly journals GBS-SBG - GBS Serotyping by Genome Sequencing

2021 ◽  
Author(s):  
Suma Tiruvayipati ◽  
Wen Ying Tang ◽  
Timothy M.S. Barkham ◽  
Swaine L Chen
Keyword(s):  
Genome Sequencing ◽  
Streptococcus Agalactiae ◽  
Group B Streptococcus ◽  
Neonatal Meningitis ◽  
Data Types ◽  
Complete Coverage ◽  
Data Set ◽  
Short Read ◽  
Group B ◽  
Reported Data

Group B Streptococcus agalactiae (GBS; Streptococcus agalactiae) is the most common cause of neonatal meningitis and a rising cause of sepsis in adults. Recently, it has also been shown to cause foodborne disease. As with many other bacteria, the polysaccharide capsule of GBS is antigenic, enabling its use for strain serotyping. Recent advances in DNA sequencing have made sequence-based typing attractive (as has been implemented for several other bacteria, including Escherichia coli, Klebsiella pneumoniae species complex, Streptococcus pyogenes, and others). For GBS, existing WGS-based serotyping systems do not provide complete coverage of all known GBS serotypes (specifically including subtypes of serotype III), and none are simultaneously compatible with the two most common data types, raw short reads and assembled sequences. Here, we create a serotyping database (GBS-SBG, GBS Serotyping by Genome Sequencing), with associated scripts and running instructions, that can be used to call all currently described GBS serotypes, including subtypes of serotype III, using both direct short-read- and assembly-based typing. We achieved higher concordance using GBS-SBG on a previously reported data set of 790 strains. We further validated GBS-SBG on a new set of 572 strains, achieving 99.8% concordance with PCR-based molecular serotyping using either short-read- or assembly-based typing. The GBS-SBG package is publicly available and will accelerate and simplify serotyping by sequencing for GBS.

scholarly journals d-Serine induces distinct transcriptomes in diverse Escherichia coli pathotypes

Microbiology ◽  
2021 ◽  
Vol 167 (10) ◽  
Author(s):  
James P. R. Connolly ◽  
Natasha C. A. Turner ◽  
Jennifer C. Hallam ◽  
Patricia T. Rimbi ◽  
Tom Flett ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Type Species ◽  
Pathogenic Bacteria ◽  
Neonatal Meningitis ◽  
Published Data ◽  
Toxic Metabolite ◽  
Transcriptional Responses ◽  
Content Type ◽  
E Coli ◽  
Link Type

Appropriate interpretation of environmental signals facilitates niche specificity in pathogenic bacteria. However, the responses of niche-specific pathogens to common host signals are poorly understood. d-Serine (d-ser) is a toxic metabolite present in highly variable concentrations at different colonization sites within the human host that we previously found is capable of inducing changes in gene expression. In this study, we made the striking observation that the global transcriptional response of three Escherichia coli pathotypes – enterohaemorrhagic E. coli (EHEC), uropathogenic E. coli (UPEC) and neonatal meningitis-associated E. coli (NMEC) – to d-ser was highly distinct. In fact, we identified no single differentially expressed gene common to all three strains. We observed the induction of ribosome-associated genes in extraintestinal pathogens UPEC and NMEC only, and the induction of purine metabolism genes in gut-restricted EHEC, and UPEC indicating distinct transcriptional responses to a common signal. UPEC and NMEC encode dsdCXA – a genetic locus required for detoxification and hence normal growth in the presence of d-ser. Specific transcriptional responses were induced in strains accumulating d-ser (WT EHEC and UPEC/NMEC mutants lacking the d-ser-responsive transcriptional activator DsdC), corroborating the notion that d-ser is an unfavourable metabolite if not metabolized. Importantly, many of the UPEC-associated transcriptome alterations correlate with published data on the urinary transcriptome, supporting the hypothesis that d-ser sensing forms a key part of urinary niche adaptation in this pathotype. Collectively, our results demonstrate distinct pleiotropic responses to a common metabolite in diverse E. coli pathotypes, with important implications for niche selectivity.

scholarly journals Harmonization of whole-genome sequencing for outbreak surveillance of Enterobacteriaceae and Enterococci

2021 ◽  
Vol 7 (7) ◽  
Author(s):  
Casper Jamin ◽  
Sien De Koster ◽  
Stefanie van Koeveringe ◽  
Dieter De Coninck ◽  
Klaas Mensaert ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Type Species ◽  
De Novo ◽  
Whole Genome ◽  
Data Generation ◽  
Sequencing Data ◽  
Content Type ◽  
Link Type ◽  
Antimicrobial Resistance Genes

Whole-genome sequencing (WGS) is becoming the de facto standard for bacterial typing and outbreak surveillance of resistant bacterial pathogens. However, interoperability for WGS of bacterial outbreaks is poorly understood. We hypothesized that harmonization of WGS for outbreak surveillance is achievable through the use of identical protocols for both data generation and data analysis. A set of 30 bacterial isolates, comprising of various species belonging to the Enterobacteriaceae family and Enterococcus genera, were selected and sequenced using the same protocol on the Illumina MiSeq platform in each individual centre. All generated sequencing data were analysed by one centre using BioNumerics (6.7.3) for (i) genotyping origin of replications and antimicrobial resistance genes, (ii) core-genome multi-locus sequence typing (cgMLST) for Escherichia coli and Klebsiella pneumoniae and whole-genome multi-locus sequencing typing (wgMLST) for all species. Additionally, a split k-mer analysis was performed to determine the number of SNPs between samples. A precision of 99.0% and an accuracy of 99.2% was achieved for genotyping. Based on cgMLST, a discrepant allele was called only in 2/27 and 3/15 comparisons between two genomes, for E. coli and K. pneumoniae, respectively. Based on wgMLST, the number of discrepant alleles ranged from 0 to 7 (average 1.6). For SNPs, this ranged from 0 to 11 SNPs (average 3.4). Furthermore, we demonstrate that using different de novo assemblers to analyse the same dataset introduces up to 150 SNPs, which surpasses most thresholds for bacterial outbreaks. This shows the importance of harmonization of data-processing surveillance of bacterial outbreaks. In summary, multi-centre WGS for bacterial surveillance is achievable, but only if protocols are harmonized.

scholarly journals Evaluation of whole-genome sequencing-based subtyping methods for the surveillance of Shigella spp. and the confounding effect of mobile genetic elements in long-term outbreaks

2021 ◽  
Vol 7 (11) ◽  
Author(s):  
Isabelle Bernaquez ◽  
Christiane Gaudreau ◽  
Pierre A. Pilon ◽  
Sadjia Bekal
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Type Species ◽  
Core Genome ◽  
Outbreak Detection ◽  
Whole Genome ◽  
Content Type ◽  
Link Type ◽  
Interpretation Criteria

Many public health laboratories across the world have implemented whole-genome sequencing (WGS) for the surveillance and outbreak detection of foodborne pathogens. PulseNet-affiliated laboratories have determined that most single-strain foodborne outbreaks are contained within 0–10 multi-locus sequence typing (MLST)-based allele differences and/or core genome single-nucleotide variants (SNVs). In addition to being a food- and travel-associated outbreak pathogen, most Shigella spp. cases occur through continuous person-to-person transmission, predominantly involving men who have sex with men (MSM), leading to long-term and recurrent outbreaks. Continuous transmission patterns coupled to genetic evolution under antibiotic treatment pressure require an assessment of existing WGS-based subtyping methods and interpretation criteria for cluster inclusion/exclusion. An evaluation of 4 WGS-based subtyping methods [SNVPhyl, coreMLST, core genome MLST (cgMLST) and whole-genome MLST (wgMLST)] was performed on 9 foodborne-, travel- and MSM-related retrospective outbreaks from a collection of 91 Shigella flexneri and 232  Shigella sonnei isolates to determine the methods’ epidemiological concordance, discriminatory power, robustness and ability to generate stable interpretation criteria. The discriminatory powers were ranked as follows: coreMLST<SNVPhyl<cgMLST<wgMLST (range: 0.970–1.000). The genetic differences observed for non-MSM-related Shigella spp. outbreaks respect the standard 0–10 allele/SNV guideline; however, mobile genetic element (MGE)-encoded loci caused inflated genetic variation and discrepant phylogenies for prolonged MSM-related S. sonnei outbreaks via wgMLST. The S. sonnei correlation coefficients of wgMLST were also the lowest at 0.680, 0.703 and 0.712 for SNVPhyl, coreMLST and cgMLST, respectively. Plasmid maintenance, mobilization and conjugation-associated genes were found to be the main source of genetic distance inflation in addition to prophage-related genes. Duplicated alleles arising from the repeated nature of IS elements were also responsible for many false cg/wgMLST differences. The coreMLST approach was shown to be the most robust, followed by SNVPhyl and wgMLST for inter-laboratory comparability. Our results highlight the need for validating species-specific subtyping methods based on microbial genome plasticity and outbreak dynamics in addition to the importance of filtering confounding MGEs for cluster detection.

scholarly journals Genomic surveillance of Escherichia coli and Klebsiella spp. in hospital sink drains and patients

2020 ◽  
Vol 6 (7) ◽  
Author(s):  
Bede Constantinides ◽  
Kevin K. Chau ◽  
T. Phuong Quan ◽  
Gillian Rodger ◽  
Monique I. Andersson ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Type Species ◽  
Whole Genome ◽  
Content Type ◽  
E Coli ◽  
Link Type ◽  
Antimicrobial Resistance Genes

Escherichia coli and Klebsiella spp. are important human pathogens that cause a wide spectrum of clinical disease. In healthcare settings, sinks and other wastewater sites have been shown to be reservoirs of antimicrobial-resistant E. coli and Klebsiella spp., particularly in the context of outbreaks of resistant strains amongst patients. Without focusing exclusively on resistance markers or a clinical outbreak, we demonstrate that many hospital sink drains are abundantly and persistently colonized with diverse populations of E. coli , Klebsiella pneumoniae and Klebsiella oxytoca , including both antimicrobial-resistant and susceptible strains. Using whole-genome sequencing of 439 isolates, we show that environmental bacterial populations are largely structured by ward and sink, with only a handful of lineages, such as E. coli ST635, being widely distributed, suggesting different prevailing ecologies, which may vary as a result of different inputs and selection pressures. Whole-genome sequencing of 46 contemporaneous patient isolates identified one (2 %; 95 % CI 0.05–11 %) E. coli urine infection-associated isolate with high similarity to a prior sink isolate, suggesting that sinks may contribute to up to 10 % of infections caused by these organisms in patients on the ward over the same timeframe. Using metagenomics from 20 sink-timepoints, we show that sinks also harbour many clinically relevant antimicrobial resistance genes including bla CTX-M, bla SHV and mcr, and may act as niches for the exchange and amplification of these genes. Our study reinforces the potential role of sinks in contributing to Enterobacterales infection and antimicrobial resistance in hospital patients, something that could be amenable to intervention. This article contains data hosted by Microreact.

scholarly journals Using whole-genome sequencing to assess the diversity of Paenibacillus larvae within an outbreak and a beekeeping operation

2021 ◽  
Vol 7 (12) ◽  
Author(s):  
Bojan Papić ◽  
Majda Golob ◽  
Irena Zdovc ◽  
Jana Avberšek ◽  
Metka Pislak Ocepek ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Type Species ◽  
Epidemiological Data ◽  
Paenibacillus Larvae ◽  
Whole Genome ◽  
Single Linkage ◽  
Content Type ◽  
Link Type ◽  
Cluster Distance

The spore-forming bacterium Paenibacillus larvae is the causative agent of American foulbrood (AFB), a devastating disease of honeybees (Apis mellifera). In the present study, we used whole-genome sequencing (WGS) to investigate an extensive outbreak of AFB in northwestern Slovenia in 2019. A total of 59 P . larvae isolates underwent WGS, of which 40 originated from a single beekeeping operation, to assess the diversity of P. larvae within the beekeeping operation, apiary and colony. By applying a case-specific single-linkage threshold of 34 allele differences (AD), whole-genome multilocus sequence typing (wgMLST) identified two outbreak clusters represented by ERIC II-ST11 clones. All isolates from a single beekeeping operation fell within cluster 1 and the median pairwise AD between them was 10 (range=1–22). The median pairwise AD for apiaries of the same beekeeping operation ranged from 8 to 11 (min.=1, max.=22). For colonies of the same apiary and honey samples from these colonies, the median pairwise AD ranged from 8 to 14 (min.=1, max.=20). The maximum within-cluster distance was 33 pairwise AD for cluster 1 and 44 for cluster 2 isolates. The minimum distance between the outbreak-related and non-related isolates was 37 AD, confirming the importance of associated epidemiological data for delineating outbreak clusters. The observed transmission events could be explained by the activities of honeybees and beekeepers. The present study provides insight into the genetic diversity of P. larvae at different levels and thus provides information for future AFB surveillance.

scholarly journals Streptococcus pneumoniae, S. pyogenes and S. agalactiae membrane phospholipid remodelling in response to human serum

Microbiology ◽  
2021 ◽  
Vol 167 (5) ◽  
Author(s):  
Luke R. Joyce ◽  
Ziqiang Guan ◽  
Kelli L. Palmer
Keyword(s):  
Streptococcus Pneumoniae ◽  
Human Serum ◽  
Type Species ◽  
Cellular Membrane ◽  
Defined Medium ◽  
Content Type ◽  
Link Type ◽  
Streptococcal Species ◽  
Group A ◽  
Group B

Streptococcus pneumoniae , S. pyogenes (Group A Streptococcus ; GAS) and S. agalactiae (Group B Streptococcus ; GBS) are major aetiological agents of diseases in humans. The cellular membrane, a crucial site in host–pathogen interactions, is poorly characterized in streptococci. Moreover, little is known about whether or how environmental conditions influence their lipid compositions. Using normal phase liquid chromatography coupled with electrospray ionization MS, we characterized the phospholipids and glycolipids of S. pneumoniae , GAS and GBS in routine undefined laboratory medium, streptococcal defined medium and, in order to mimic the host environment, defined medium supplemented with human serum. In human serum-supplemented medium, all three streptococcal species synthesize phosphatidylcholine (PC), a zwitterionic phospholipid commonly found in eukaryotes but relatively rare in bacteria. We previously reported that S. pneumoniae utilizes the glycerophosphocholine (GPC) biosynthetic pathway to synthesize PC. Through substrate tracing experiments, we confirm that GAS and GBS scavenge lysoPC, a major metabolite in human serum, thereby using an abbreviated GPC pathway for PC biosynthesis. Furthermore, we found that plasmanyl-PC is uniquely present in the GBS membrane during growth with human serum, suggesting GBS possesses unusual membrane biochemical or biophysical properties. In summary, we report cellular lipid remodelling by the major pathogenic streptococci in response to metabolites present in human serum.

scholarly journals Streptococcus lutetiensis neonatal meningitis with empyema

2021 ◽  
Vol 3 (9) ◽  
Author(s):  
Allen T. Yu ◽  
Kate Shapiro ◽  
Christy A. Beneri ◽  
Lisa S. Wilks-Gallo
Keyword(s):  
United States ◽  
Neonatal Sepsis ◽  
Type Species ◽  
The United States ◽  
Neonatal Meningitis ◽  
Content Type ◽  
Link Type ◽  
First Case

Streptococcus lutetiensis has been known to cause sepsis in adults, but only one case regarding neonatal sepsis has been reported internationally, with no sequelae. We report the first case of neonatal bacteremia and meningitis with empyema caused by S. lutetiensis in the United States.

scholarly journals Re-identification of strains deposited as Pseudomonas aeruginosa, Pseudomonas fluorescens and Pseudomonas putida in GenBank based on whole genome sequences

2020 ◽  
Vol 70 (11) ◽  
pp. 5958-5963
Author(s):  
Yuh Morimoto ◽  
Mari Tohya ◽  
Zulipiya Aibibula ◽  
Tadashi Baba ◽  
Hiroyuki Daida ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Genome Sequencing ◽  
Dna Hybridization ◽  
Type Species ◽  
Whole Genome ◽  
Average Nucleotide Identity ◽  
Genome Sequences ◽  
Content Type ◽  
Link Type

The taxonomic classification of Pseudomonas species has been revised and updated several times. This study utilized average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) cutoff values of 95 and 70 %, respectively, to re-identify the species of strains deposited in GenBank as P. aeruginosa , P. fluorescens and P. putida . Of the 264 deposited P. aeruginosa strains, 259 were correctly identified as P. aeruginosa , but the remaining five were not. All 28 deposited P. fluorescens strains had been incorrectly identified as P. fluorescens . Four of these strains were re-identified, including two as P. kilonensis and one each as P. aeruginosa and P. brassicacearum , but the remaining 24 could not be re-identified. Similarly, all 35 deposited P. putida strains had been incorrectly identified as P. putida . Nineteen of these strains were re-identified, including 12 as P. alloputida , four as P. asiatica and one each as P. juntendi , P. monteilii and P. mosselii . These results strongly suggest that Pseudomonas bacteria should be identified using ANI and dDDH analyses based on whole genome sequencing when Pseudomonas species are initially deposited in GenBank/DDBJ/EMBL databases.

scholarly journals Neisseria gonorrhoeae clustering to reveal major European whole-genome-sequencing-based genogroups in association with antimicrobial resistance

2020 ◽  
Author(s):  
Miguel Pinto ◽  
Vítor Borges ◽  
Joana Isidro ◽  
João Carlos Rodrigues ◽  
Luís Vieira ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Neisseria Gonorrhoeae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Type Species ◽  
Transmitted Disease ◽  
Epidemiological Surveillance ◽  
Whole Genome ◽  
Content Type ◽  
Link Type

Neisseria gonorrhoeae , the bacterium responsible for the sexually transmitted disease gonorrhoea, has shown an extraordinary ability to develop antimicrobial resistance (AMR) to multiple classes of antimicrobials. With no available vaccine, managing N. gonorrhoeae infections demands effective preventive measures, antibiotic treatment and epidemiological surveillance. The latter two are progressively being supported by the generation of whole-genome sequencing (WGS) data on behalf of national and international surveillance programmes. In this context, this study aims to perform N. gonorrhoeae clustering into genogroups based on WGS data, for enhanced prospective laboratory surveillance. Particularly, it aims to identify the major circulating WGS-genogroups in Europe and to establish a relationship between these and AMR. Ultimately, it enriches public databases by contributing with WGS data from Portuguese isolates spanning 15 years of surveillance. A total of 3791 carefully inspected N. gonorrhoeae genomes from isolates collected across Europe were analysed using a gene-by-gene approach (i.e. using cgMLST). Analysis of cluster composition and stability allowed the classification of isolates into a two-step hierarchical genogroup level determined by two allelic distance thresholds revealing cluster stability. Genogroup clustering in general agreed with available N. gonorrhoeae typing methods [i.e. MLST (multilocus sequence typing), NG-MAST ( N. gonorrhoeae multi-antigen sequence typing) and PubMLST core-genome groups], highlighting the predominant genogroups circulating in Europe, and revealed that the vast majority of the genogroups present a dominant AMR profile. Additionally, a non-static gene-by-gene approach combined with a more discriminatory threshold for potential epidemiological linkage enabled us to match data with previous reports on outbreaks or transmission chains. In conclusion, this genogroup assignment allows a comprehensive analysis of N. gonorrhoeae genetic diversity and the identification of the WGS-based genogroups circulating in Europe, while facilitating the assessment (and continuous monitoring) of their frequency, geographical dispersion and potential association with specific AMR signatures. This strategy may benefit public-health actions through the prioritization of genogroups to be controlled, the identification of emerging resistance carriage, and the potential facilitation of data sharing and communication.

Sign in / Sign up

Export Citation Format

Share Document