scholarly journals Molecular subtyping for source tracking of Escherichia coli using core genome multilocus sequence typing at a food manufacturing plant

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261352
Author(s):  
Ayaka Nakamura ◽  
Hajime Takahashi ◽  
Maki Arai ◽  
Tomoki Tsuchiya ◽  
Shohei Wada ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Intermediate Product ◽  
Multilocus Sequence Typing ◽  
Production Line ◽  
Core Genome ◽  
Source Tracking ◽  
Manufacturing Plant ◽  
Drainage Ditch ◽  
Food Manufacturing ◽  
Manufacturing Location

When harmful bacteria are detected in the final product at a food manufacturing plant, it is necessary to identify and eliminate the source of contamination so that it does not occur again. In the current study, the source of contamination was tracked using core genome multilocus sequence typing (cgMLST) analysis in cases where Escherichia coli was detected in the final product at a food manufacturing plant. cgMLST analysis was performed on 40 strains of E. coli collected from the environment [floor (26 strains), drainage ditch (5 strains), container (4 strains), post-heating production line (1 strain)] and products [final product (3 strains) and intermediate product (1 strain)]. In total, 40 E. coli isolates were classified into 17 genogroups by cgMLST analysis. The 4 E. coli strains isolated from the intermediate and final products were classified into two genogroups (I and II). Certain isolates collected from the environment also belonged to those genogroups, it was possible to estimate the transmission of E. coli in the manufacturing plant. Thus, the dynamics of E. coli in the food manufacturing location were clarified by using cgMLST analysis. In conclusion, our results indicate that cgMLST analysis can be effectively used for hygiene management at food manufacturing locations.

Development and evaluation of a core genome multilocus sequence typing (cgMLST) scheme for Brucella spp.

2019 ◽  
Vol 67 ◽  
pp. 38-43 ◽  
Author(s):  
Jagadesan Sankarasubramanian ◽  
Udayakumar S. Vishnu ◽  
Paramasamy Gunasekaran ◽  
Jeyaprakash Rajendhran
Keyword(s):  
Multilocus Sequence Typing ◽  
Core Genome

scholarly journals To catch a hijacker: abundance, evolution and genetic diversity of P4-like bacteriophage satellites

2021 ◽  
Vol 377 (1842) ◽  
Author(s):  
Jorge A. Moura de Sousa ◽  
Eduardo P. C. Rocha
Keyword(s):  
Escherichia Coli ◽  
Molecular Mechanisms ◽  
Core Genome ◽  
Mobile Genetic Elements ◽  
Abundance Distribution ◽  
Theme Issue ◽  
Genetic Elements ◽  
The Core ◽  
Antagonistic Interactions ◽  
Variable Genes

Bacteriophages (phages) are bacterial parasites that can themselves be parasitized by phage satellites. The molecular mechanisms used by satellites to hijack phages are sometimes understood in great detail, but the origins, abundance, distribution and composition of these elements are poorly known. Here, we show that P4-like elements are present in more than 30% of the genomes of Enterobacterales, and in almost half of those of Escherichia coli , sometimes in multiple distinct copies. We identified over 1000 P4-like elements with very conserved genetic organization of the core genome and a few hotspots with highly variable genes. These elements are never found in plasmids and have very little homology to known phages, suggesting an independent evolutionary origin. Instead, they are scattered across chromosomes, possibly because their integrases are often exchanged with other elements. The rooted phylogenies of hijacking functions are correlated and suggest longstanding coevolution. They also reveal broad host ranges in P4-like elements, as almost identical elements can be found in distinct bacterial genera. Our results show that P4-like phage satellites constitute a very distinct, widespread and ancient family of mobile genetic elements. They pave the way for studying the molecular evolution of antagonistic interactions between phages and their satellites. This article is part of the theme issue ‘The secret lives of microbial mobile genetic elements’.

Genomic and phenotypic analysis of heat and sanitizer resistance in Escherichia coli from beef in relation to the locus of heat resistance

2021 ◽  
Author(s):  
Xianqin Yang ◽  
Frances Tran ◽  
Peipei Zhang ◽  
Hui Wang
Keyword(s):  
Escherichia Coli ◽  
Heat Resistance ◽  
Phylogenetic Relationships ◽  
Core Genome ◽  
Elevated Temperatures ◽  
Resistant Bacteria ◽  
Phenotypic Analysis ◽  
Decimal Reduction Time ◽  
E Coli ◽  
Clade 1

The locus of heat resistance (LHR) can confer heat resistance to Escherichia coli to various extents. This study investigated the phylogenetic relationships, and genomic and phenotypic characteristics of E. coli with or without LHR recovered from beef by direct plating or from enrichment broth at 42°C. LHR-positive E. coli isolates (n=24) were whole genome-sequenced by short- and long-reads. LHR-negative isolates (n=18) from equivalent sources as LHR-positive isolates were short-read sequenced. All isolates were assessed for decimal reduction time at 60°C ( D 60°C ) and susceptibility to E-SAN and Perox-E. Selected isolates were evaluated for growth at 42°C. The LHR-positive and negative isolates were well separated on the core genome tree, with 22/24 of the positive isolates clustering into three clades. Isolates within clade 1 and 2, despite their different D 60°C values, were clonal, as determined by subtyping (MLST, core genome MLST, and serotyping). Isolates within each clade are of one serotype. The LHR-negative isolates were genetically diverse. The LHR-positive isolates had a larger (p<0.001) median genome size by 0.3 Mbp (5.0 vs 4.7 Mbp), and overrepresentation of genes in plasmid maintenance, stress response and cryptic prophages, but underrepresentation of genes involved in epithelial attachment and virulence. All LHR-positive isolates harbored a chromosomal copy of LHR, and all clade 2 isolates had an additional partial copy of LHR on conjugative plasmids. The growth rates at 42°C were 0.71±0.02 and 0.65±0.02 logOD h −1 for LHR-positive and negative isolates. No meaningful difference in sanitizer susceptibility was noted between LHR-positive and negative isolates. Importance Resistant bacteria are serious food safety and public health concerns. Heat resistance conferred by the LHR varies largely among different strains. The findings in this study show that genomic background and composition of LHR, in addition to the presence of LHR, play an important role in the degree of heat resistance in E. coli , and that strains with certain genetic background are more likely to acquire and maintain the LHR. Also, caution should be exercised when recovering E. coli at elevated temperatures as the presence of LHR may confer growth advantages to some strains. Interestingly, the LHR harboring strains seem to have evolved further from their primary animal host to adapt to their secondary habitat, as reflected by fewer genes in virulence and epithelial attachment. The phylogenetic relationships among the isolates point towards multiple mechanisms for acquiring LHR, likely prior to their deposition on meat.

scholarly journals Establishment and evaluation of a core genome multilocus sequence typing scheme for whole-genome sequence-based typing of Pseudomonas aeruginosa

2020 ◽  
pp. JCM.01987-20
Author(s):  
Hauke Tönnies ◽  
Karola Prior ◽  
Dag Harmsen ◽  
Alexander Mellmann
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Multilocus Sequence Typing ◽  
Core Genome ◽  
Target Genes ◽  
Multidrug Resistant ◽  
Population Based ◽  
Whole Genome Sequence ◽  
Nucleotide Polymorphisms ◽  
Environmental Bacterium ◽  
Random Dataset

The environmental bacterium Pseudomonas aeruginosa, in particular 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 for all 12 serogroups, we extracted target genes and further refined them using a random dataset 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 dataset of 1,000 genomes, the cgMLST scheme consisted of 3,867 target genes, which are representative for 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 polymorphisms (SNPs) typing. In both cases cgMLST was concordant to the previous SNP results and to 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.

Core Genome Allelic Profiles of Clinical Klebsiella pneumoniae Strains Using a Random Forest Algorithm Based on Multilocus Sequence Typing Scheme for Hypervirulence Analysis

2020 ◽  
Vol 221 (Supplement_2) ◽  
pp. S263-S271 ◽  
Author(s):  
Peng Lan ◽  
Qiucheng Shi ◽  
Ping Zhang ◽  
Yan Chen ◽  
Rushuang Yan ◽  
...  
Keyword(s):  
Random Forest ◽  
Klebsiella Pneumoniae ◽  
Multilocus Sequence Typing ◽  
Operating Characteristic ◽  
Core Genome ◽  
Characteristic Curve ◽  
Random Forest Algorithm ◽  
The Core ◽  
Model Based ◽  
Operating Characteristic Curve

Abstract Background Hypervirulent Klebsiella pneumoniae (hvKP) infections can have high morbidity and mortality rates owing to their invasiveness and virulence. However, there are no effective tools or biomarkers to discriminate between hvKP and nonhypervirulent K. pneumoniae (nhvKP) strains. We aimed to use a random forest algorithm to predict hvKP based on core-genome data. Methods In total, 272 K. pneumoniae strains were collected from 20 tertiary hospitals in China and divided into hvKP and nhvKP groups according to clinical criteria. Clinical data comparisons, whole-genome sequencing, virulence profile analysis, and core genome multilocus sequence typing (cgMLST) were performed. We then established a random forest predictive model based on the cgMLST scheme to prospectively identify hvKP. The random forest is an ensemble learning method that generates multiple decision trees during the training process and each decision tree will output its own prediction results corresponding to the input. The predictive ability of the model was assessed by means of area under the receiver operating characteristic curve. Results Patients in the hvKP group were younger than those in the nhvKP group (median age, 58.0 and 68.0 years, respectively; P &lt; .001). More patients in the hvKP group had underlying diabetes mellitus (43.1% vs 20.1%; P &lt; .001). Clinically, carbapenem-resistant K. pneumoniae was less common in the hvKP group (4.1% vs 63.8%; P &lt; .001), whereas the K1/K2 serotype, sequence type (ST) 23, and positive string tests were significantly higher in the hvKP group. A cgMLST-based minimal spanning tree revealed that hvKP strains were scattered sporadically within nhvKP clusters. ST23 showed greater genome diversification than did ST11, according to cgMLST-based allelic differences. Primary virulence factors (rmpA, iucA, positive string test result, and the presence of virulence plasmid pLVPK) were poor predictors of the hypervirulence phenotype. The random forest model based on the core genome allelic profile presented excellent predictive power, both in the training and validating sets (area under receiver operating characteristic curve, 0.987 and 0.999 in the training and validating sets, respectively). Conclusions A random forest algorithm predictive model based on the core genome allelic profiles of K. pneumoniae was accurate to identify the hypervirulent isolates.

scholarly journals Epidemiological investigation of an Acinetobacter baumannii outbreak using core genome multilocus sequence typing

2019 ◽  
Vol 17 ◽  
pp. 245-249 ◽  
Author(s):  
Carolina Venditti ◽  
Antonella Vulcano ◽  
Silvia D’Arezzo ◽  
Cesare Ernesto Maria Gruber ◽  
Marina Selleri ◽  
...  
Keyword(s):  
Acinetobacter Baumannii ◽  
Multilocus Sequence Typing ◽  
Core Genome ◽  
Epidemiological Investigation
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