MLST revisited: the gene-by-gene approach to bacterial genomics

Analysis of Antimicrobial Resistance and Genetic Correlations of Escherichia Coli in Dairy Cow Mastitis

Introduction

Escherichia coli is a widespread environmental pathogen frequently causing dairy cow mastitis. This bacterium is particularly capable of acquiring antimicrobial resistance, which can have severe impacts on animal food safety and human health. The objective of the study was to investigate antimicrobial resistance and genetic correlations of E. coli from dairy cow mastitis cases in northern China.

Material and Methods

Forty strains of E. coli from 196 mastitis milk samples were collected, susceptibility to 13 common antibiotics and the prevalence of resistance genes were tested in these strains, and the genetic characteristics were identified by multilocus sequence typing.

Results

The results showed that most isolates were multidrug resistant (MDR) (75%), and the resistance rates to cefazolin, trimethoprim-sulfamethoxazole and ampicillin were 77.5%, 55.0%, and 52.5%, respectively. The representative genes of the isolates were aadA (62.5%) and tet(B) (60.0%). Multilocus sequence typing showed 19 different sequence types (STs) and 5 clonal complexes (CCs) in the 40 isolates, mainly represented by ST10 and CC10. The strains of the same ST or CC showed a high level of genetic relatedness, but the characteristics of their antimicrobial resistance were markedly different.

Conclusion

Most E. coli isolates in the study were MDR strains. Some strains of the same ST or CC showed diverse resistance characteristics to common antimicrobials. Therefore, E. coli from dairy cow mastitis in northern China should be investigated to elucidate its antimicrobial resistance and genotypes.

Comparative Analysis of Clinical and Genomic Characteristics of Hypervirulent Klebsiella pneumoniae from Hospital and Community Settings: Experience from a Tertiary Healthcare Center in India

Hypervirulent Klebsiella pneumoniae (hvKp) is a hypermucoviscous phenotype of classical Klebsiella pneumoniae (cKp) that causes serious infections in the community. The recent emergence of multidrug-resistant hvKp isolates (producing extended-spectrum beta-lactamases and carbapenemases) along with other virulence factors in health care settings has become a clinical crisis. Here, we aimed to compare the distribution of virulence determinants and antimicrobial resistance (AMR) genes in relation to various sequence types (STs) among the clinical hvKp isolates from both settings, to reinforce our understanding of their epidemiology and pathogenic potential. A total of 120 K. pneumoniae isolates confirmed by matrix-assisted laser desorption ionization-time of flight mass spectrometry were selected. hvKp was phenotypically identified by string test and genotypically confirmed by the presence of the iucA gene using PCR. Molecular characterization of hvKp isolates was done by whole-genome sequencing (WGS). Of the K. pneumoniae isolates, 11.6% (14/120) isolates were confirmed as hvKp by PCR (9.1% [11/120] string positive and 3.3% [4/120] positive by both methods); these were predominantly isolated from bloodstream infection (50%, 7/14), urinary tract infection (29%, 4/14), and respiratory tract infection (21%, 3/14). For all 14 hvKp infections, for 14.2% the source was in the community and for 85.7% the source was a health care setting. Two virulent plasmids were identified by WGS among the hvKp isolates from both settings. K64 was found to be the commonest capsular serotype (28.5%, 4/14), and ST2096 was the most common ST (28.5%, 4/14) by WGS. Two new STs were revealed: ST231 (reported to cause outbreaks) and ST43. The genome of one isolate was determined to be carrying AMR genes (blaCTX-M-15, blaNDM-1, blaNDM-5, blaOXA-181, blaOXA-232, etc.) in addition to virulence genes, highlighting the clonal spread of hvKp in both community and health care settings. IMPORTANCE To date, studies comparing the genomic characteristics of hospital- and community-acquired hvKp were very few in India. In this study, we analyzed the clinical and genomic characteristics of hvKp isolates from hospital and community settings. ST2096 was found as the most common ST along with novel STs ST231 and ST43. Our study also revealed the genome is simultaneously carrying AMR as well as virulence genes in isolates from both settings, highlighting the emergence of MDR hvKp STs integrated with virulence genes in both community and health care settings. Thus, hvKp may present a serious global threat, and essential steps are needed to prevent its further dissemination.

EnteroBase: hierarchical clustering of 100 000s of bacterial genomes into species/subspecies and populations

The definition of bacterial species is traditionally a taxonomic issue while bacterial populations are identified by population genetics. These assignments are species specific, and depend on the practitioner. Legacy multilocus sequence typing is commonly used to identify sequence types (STs) and clusters (ST Complexes). However, these approaches are not adequate for the millions of genomic sequences from bacterial pathogens that have been generated since 2012. EnteroBase (http://enterobase.warwick.ac.uk) automatically clusters core genome MLST allelic profiles into hierarchical clusters (HierCC) after assembling annotated draft genomes from short-read sequences. HierCC clusters span core sequence diversity from the species level down to individual transmission chains. Here we evaluate HierCC's ability to correctly assign 100 000s of genomes to the species/subspecies and population levels for Salmonella, Escherichia, Clostridoides, Yersinia, Vibrio and Streptococcus. HierCC assignments were more consistent with maximum-likelihood super-trees of core SNPs or presence/absence of accessory genes than classical taxonomic assignments or 95% ANI. However, neither HierCC nor ANI were uniformly consistent with classical taxonomy of Streptococcus. HierCC was also consistent with legacy eBGs/ST Complexes in Salmonella or Escherichia and with O serogroups in Salmonella. Thus, EnteroBase HierCC supports the automated identification of and assignment to species/subspecies and populations for multiple genera. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Molecular Epidemiology of Clinical Carbapenem-Resistant Acinetobacter baumannii-calcoaceticus complex Isolates in Tertiary Care Hospitals in Java and Sulawesi Islands, Indonesia

Carbapenem-resistant Acinetobacter baumannii (A. baumannii)-calcoaceticus complex (CRAb-cc) is an important pathogen causing nosocomial infections worldwide; however, molecular epidemiology of the A. baumannii-calcoaceticus complex in Indonesian hospitals is scarce. This study aimed to determine the clonal relatedness of CRAb-cc in two tertiary care hospitals in Malang and Manado in Indonesia. The CRAb-cc isolates from routine clinical cultures in two tertiary care hospitals in Malang and Manado were identified using the Vitek2^® system (bioMérieux, Lyon, France). Multi-locus variable-number tandem-repeat analysis (MLVA) typing, multi-locus sequence typing (MLST), clonal complex (CC), and phylogenetic tree analysis were conducted for a subset of isolates. Seventy-three CRAb-cc isolates were collected. The CRAb-cc isolates were frequently found among lower-respiratory-tract specimens. We detected the MLVA type (MT) 1, MT3, and MT4 CRAB-cc isolates belonging to the sequence type (ST) 642, and CC1 was the predominant clone in this study. In conclusion, we identified the clonal relatedness of A. baumannii-calcoaceticus complex isolates in two tertiary care hospitals in Malang and Manado in Indonesia. Further study is required to investigate the clinical importance and distribution of ST642 in Indonesian hospitals for developing prevention and control measures.

Prevalence and Population Diversity of Listeria monocytogenes Isolated from Dairy Cattle Farms in the Cantabria Region of Spain

Simple Summary

The origin and prevalence of Listeria monocytogenes was studied in dairy cattle farms in order to examine its diversity and determine its possible persistence in manure. The utilization of manure for agricultural purposes is common in many countries. While properly treated and managed manure is an effective and safe fertilizer, foodborne illness outbreaks can occur, as many of the most prominent foodborne pathogens are carried by healthy livestock. It is, therefore, necessary to study the origin and persistence of zoonotic agents in general and of L. monocytogenes in particular, in order to avoid recirculation in farms and reduce risk for human populations.

Abstract

Listeria monocytogenes is an opportunistic pathogen that is widely distributed in the environment. Here we show the prevalence and transmission of L. monocytogenes in dairy farms in the Cantabria region, on the northern coast of Spain. A total of 424 samples was collected from 14 dairy farms (5 organic and 9 conventional) and 211 L. monocytogenes isolates were recovered following conventional microbiological methods. There were no statistically significant differences in antimicrobial resistance ratios between organic and conventional farms. A clonal relationship among the isolates was assessed by pulsed field gel electrophoresis (PFGE) analysis and 64 different pulsotypes were obtained. Most isolates (89%, n = 187) were classified as PCR serogroup IVb by using a multiplex PCR assay. In this case, 45 isolates of PCR serogroup IVb were whole genome-sequenced to perform a further analysis at genomic level. In silico MLST analysis showed the presence of 12 sequence types (ST), of which ST1, ST54 and ST666 were the most common. Our data indicate that the environment of cattle farms retains a high incidence of L. monocytogenes, including subtypes involved in human listeriosis reports and outbreaks. This pathogen is shed in the feces and could easily colonize dairy products, as a result of fecal contamination. Effective herd and manure management are needed in order to prevent possible outbreaks.

What Can Genetics Do for the Control of Infectious Diseases in Aquaculture?

Simple Summary

Infectious diseases place an economic burden on aquaculture and a limitation to its growth. This state-of-the-art review describes the application of genetics and genomics as novel tools to control infectious disease in aquaculture.

Abstract

Infectious diseases place an economic burden on aquaculture and a limitation to its growth. An innovative approach to mitigate their impact on production is breeding for disease resistance: selection for domestication, family-based selection, marker-assisted selection, and more recently, genomic selection. Advances in genetics and genomics approaches to the control of infectious diseases are key to increasing aquaculture efficiency, profitability, and sustainability and to reducing its environmental footprint. Interaction and co-evolution between a host and pathogen can, however, turn breeding to boost infectious disease resistance into a potential driver of pathogenic change. Parallel molecular characterization of the pathogen and its virulence and antimicrobial resistance genes is therefore essential to understand pathogen evolution over time in response to host immunity, and to apply appropriate mitigation strategies.

Prevalence, distribution, enterotoxin profiles, antimicrobial resistance, and genetic diversity of Bacillus cereus group isolates from lettuce farms in Korea

Lettuce wraps are popular in Korean cuisine for their high nutritional value and versatility as healthy additions to multiple dishes. Microbial contamination of lettuce is a major concern, as lettuce is consumed fresh without cooking. Among foodborne pathogens, the spore-forming, facultative anaerobic bacterium, Bacillus cereus is one of the frequently detected pathogen in lettuce in Korea. In this study, we investigated the prevalence and distribution of Bacillus cereus strains in lettuce production farms and further evaluated the enterotoxin gene profiles, antibiotic susceptibility, multidrug resistance pattern, and genetic differences among the B. cereus group isolates. Of the 140 samples isolated from 10 lettuce production farms, 30 samples (21.42%) were positive for B. cereus in which 19 (31.6%) and 10 (23.25%) were from soil and lettuce, respectively. The enterotoxin patterns A (hblCDA, nheABC, entFM, and cytK genes) and B (hblCDA, nheABC, and entFM genes) accounted for 50% and 20% of all the isolates, whereas the emetic gene cesB was not detected in any of the B. cereus group isolates. Antibiotic susceptibility testing of the B. cereus group isolates revealed that all the strains were predominantly resistant to β-lactam antibiotics except imipenem and generally susceptible to most of the non β-lactam antibiotics, including gentamycin, streptomycin, chloramphenicol, and tetracycline. ERIC-PCR and MLST analysis revealed high genetic diversity among the 30 B. cereus group isolates, which belonged to 26 different sequence types (STs) and seven new STs. Moreover, isolates with identical STs exhibited similar patterns of antibiotic resistance and enterotoxin profiles. Results of this study indicate a high prevalence of B. cereus group isolates in lettuce production farms in the Republic of Korea.

Antibiotic resistance genes in the gut microbiota of mothers and linked neonates with or without sepsis from low- and middle-income countries

Early development of the microbiome has been shown to affect general health and physical development of the infant and, although some studies have been undertaken in high-income countries, there are few studies from low- and middle-income countries. As part of the BARNARDS study, we examined the rectal microbiota of 2,931 neonates (term used up to 60 d) with clinical signs of sepsis and of 15,217 mothers screening for bla_CTX-M-15, bla_NDM, bla_KPC and bla_OXA-48-like genes, which were detected in 56.1%, 18.5%, 0% and 4.1% of neonates’ rectal swabs and 47.1%, 4.6%, 0% and 1.6% of mothers’ rectal swabs, respectively. Carbapenemase-positive bacteria were identified by MALDI-TOF MS and showed a high diversity of bacterial species (57 distinct species/genera) which exhibited resistance to most of the antibiotics tested. Escherichia coli, Klebsiella pneumoniae and Enterobacter cloacae/E. cloacae complex, the most commonly found isolates, were subjected to whole-genome sequencing analysis and revealed close relationships between isolates from different samples, suggesting transmission of bacteria between neonates, and between neonates and mothers. Associations between the carriage of antimicrobial resistance genes (ARGs) and healthcare/environmental factors were identified, and the presence of ARGs was a predictor of neonatal sepsis and adverse birth outcomes.

Analysis of gut microbiota of mothers and its neonates—as part of the BARNARDS study—reveals associations between β-lactamase gene carriage and neonatal sepsis risk in low-income settings.

Virulence, antimicrobial susceptibility, and phylogenetic analysis of Cronobacter sakazakii isolates of food origins from Jordan

AIMS

to characterize a collection of Cronobacter sakazakii isolates collected from various origins in Jordan.

METHODS AND RESULTS

the isolates were characterized using 16S rRNA sequencing, DNA microarray, multi-locus sequence typing (MLST), O-serotyping, virulence gene identification, and antibiotic susceptibility testing. The identities and phylogenetic relatedness revealed that C. sakazakii sequence type 4 (ST4) and Csak O:1 serotype was the most prevalent STs and serovars among these C. sakazakii strains. PCR screening of putative virulence genes showed that the siderophore-interacting protein gene (sip) and iron acquisition gene clusters (eitCBAD and iucABCD/iutA) were the most detected genes with noticeable variability in the type 6 secretion system (T6SS) and filamentous hemagglutinin/adhesion (FHA) gene loci. The antibiotic resistance profiles revealed that the majority of the isolates were susceptible to all antibiotics used despite harboring a class C β-lactamase resistance gene.

CONCLUSIONS

the results described in this report provide additional insights about the considerable genotypic and phenotypic heterogeneity within C. sakazakii.

SIGNIFICANCE AND IMPACT OF THE STUDY

the information reported in this study might be of great value in understanding the origins of C. sakazakii isolates, in addition to their diversity and variability, which might be helpful in preventing future outbreaks of this pathogen.

Core Genome Multilocus Sequence Typing Scheme for Improved Characterization and Epidemiological Surveillance of Pathogenic Brucella

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

Analysis of the Taxonomy, Synteny, and Virulence Factors for Soft Rot Pathogen Pectobacterium aroidearum in Amorphophallus konjac Using Comparative Genomics

Bacterial soft rot is a devastating disease for a wide range of crops, vegetables, and ornamental plants including konjac (Amorphophallus konjac). However, the pangenome and genomic plasticity of the konjac soft rot pathogens is little explored. In this study, we reported the complete genome sequences of 11 bacterial isolates that can cause typical soft rot symptoms in konjac by in vitro and in vivo pathogenicity tests. Based on in silico DNA-DNA hybridization, average nucleotide identity and phylogenomic analysis, all 11 isolates were determined to be Pectobacterium aroidearum. In addition, synteny analysis of these genomes revealed considerable chromosomal inversions, one of which is triggered by homologous recombination of ribose operon. Pangenome analysis and COG enrichment analysis showed that the pangenome of P. aroidearum is open and that accessory genes are enriched in replication, recombination, and repair. Variations in type IV secretion system and type VI secretion system were found, while plant cell wall degrading enzymes were conserved. Furthermore, sequence analyses also provided evidence for the presence of a type V secretion system in Pectobacterium. These findings advance our understanding of the pathogenicity determinants, genomic plasticity, and evolution of P. aroidearum.

A comprehensive resource for Bordetella genomic epidemiology and biodiversity studies

The genus Bordetella includes bacteria that are found in the environment and/or associated with humans and other animals. A few closely related species, including Bordetella pertussis, are human pathogens that cause diseases such as whooping cough. Here, we present a large database of Bordetella isolates and genomes and develop genotyping systems for the genus and for the B. pertussis clade. To generate the database, we merge previously existing databases from Oxford University and Institut Pasteur, import genomes from public repositories, and add 83 newly sequenced B. bronchiseptica genomes. The public database currently includes 2582 Bordetella isolates and their provenance data, and 2085 genomes ( https://bigsdb.pasteur.fr/bordetella/ ). We use core-genome multilocus sequence typing (cgMLST) to develop genotyping systems for the whole genus and for B. pertussis, as well as specific schemes to define antigenic, virulence and macrolide resistance profiles. Phylogenetic analyses allow us to redefine evolutionary relationships among known Bordetella species, and to propose potential new species. Our database provides an expandable resource for genotyping of environmental and clinical Bordetella isolates, thus facilitating evolutionary and epidemiological research on whooping cough and other Bordetella infections.

Epidemiological and Genetic Characteristics of Clinical Carbapenem-Resistant Acinetobacter baumannii Strains Collected Countrywide from Hospital Intensive Care Units (ICUs) in China

Acinetobacter baumannii is one of the key Gram-negative pathogens that can cause serious nosocomial infections. In China, a large proportion of clinical A. baumannii strains are multidrug resistant, among which strains resistant to carbapenems are particularly worrisome, as infections caused by such strains may limit the choice of existing antibiotics. We conducted a nationwide and genome-based surveillance on the prevalence and antibiotic susceptibility profile of carbapenem-resistant A. baumannii (CRAB) strains collected from intensive care units (ICUs) in hospitals in different provinces and investigated the routes of transmission and mechanism of resistance by whole-genome sequencing and phylogenetic analysis. We found that CRAB strains were prevalent in 71.4% (55/77) of the ICUs surveyed. Clonal spread of CRAB was found in 37.6% (29/77) of ICUs and a total of 22 different clones were identified. Most clones were transmissible within one ICU, but up to six clones could be detected in at least three hospitals. In addition, carbapenem-hydrolysing class D β-lactamases (CHDL) were found to be mainly responsible for carbapenem-resistance in A. baumannii and the ST2 global-clone is the predominant type of CRAB in China. Importantly, we found that CRAB isolates currently exhibited extremely low rate of resistance to colistin (0.4%) and tigecycline (2.5%), but a high rate of resistance to ceftazidime-avibactam (70.2%). Findings in this work shall facilitate development of appropriate antimicrobial regimens for treatment of CRAB infections. Further surveillance and research on the evolutionary and epidemiological features of clinical CRAB strains are necessary.

A Machine Learning Model for Food Source Attribution of Listeria monocytogenes

Despite its low morbidity, listeriosis has a high mortality rate due to the severity of its clinical manifestations. The source of human listeriosis is often unclear. In this study, we investigate the ability of machine learning to predict the food source from which clinical Listeria monocytogenes isolates originated. Four machine learning classification algorithms were trained on core genome multilocus sequence typing data of 1212 L. monocytogenes isolates from various food sources. The average accuracies of random forest, support vector machine radial kernel, stochastic gradient boosting, and logit boost were found to be 0.72, 0.61, 0.7, and 0.73, respectively. Logit boost showed the best performance and was used in model testing on 154 L. monocytogenes clinical isolates. The model attributed 17.5 % of human clinical cases to dairy, 32.5% to fruits, 14.3% to leafy greens, 9.7% to meat, 4.6% to poultry, and 18.8% to vegetables. The final model also provided us with genetic features that were predictive of specific sources. Thus, this combination of genomic data and machine learning-based models can greatly enhance our ability to track L. monocytogenes from different food sources.

A dual barcoding approach to bacterial strain nomenclature: Genomic taxonomy of Klebsiella pneumoniae strains

Sublineages (SLs) within microbial species can differ widely in their ecology and pathogenicity, and their precise definition is important in basic research and for industrial or public health applications. Widely accepted strategies to define SLs are currently missing, which confuses communication in population biology and epidemiological surveillance. Here, we propose a broadly applicable genomic classification and nomenclature approach for bacterial strains, using the prominent public health threat Klebsiella pneumoniae as a model. Based on a 629-gene core genome multilocus sequence typing (cgMLST) scheme, we devised a dual barcoding system that combines multilevel single linkage (MLSL) clustering and life identification numbers (LINs). Phylogenetic and clustering analyses of >7,000 genome sequences captured population structure discontinuities, which were used to guide the definition of 10 infraspecific genetic dissimilarity thresholds. The widely used 7-gene multilocus sequence typing (MLST) nomenclature was mapped onto MLSL SLs (threshold: 190 allelic mismatches) and clonal group (threshold: 43) identifiers for backwards nomenclature compatibility. The taxonomy is publicly accessible through a community-curated platform (https://bigsdb.pasteur.fr/klebsiella), which also enables external users’ genomic sequences identification. The proposed strain taxonomy combines two phylogenetically informative barcode systems that provide full stability (LIN codes) and nomenclatural continuity with previous nomenclature (MLSL). This species-specific dual barcoding strategy for the genomic taxonomy of microbial strains is broadly applicable and should contribute to unify global and cross-sector collaborative knowledge on the emergence and microevolution of bacterial pathogens.

Phylogenomic Analysis of Salmonella enterica subsp. enterica Serovar Bovismorbificans from Clinical and Food Samples Using Whole Genome Wide Core Genes and kmer Binning Methods to Identify Two Distinct Polyphyletic Genome Pathotypes

Salmonella enterica subsp. enterica serovar Bovismorbificans has caused multiple outbreaks involving the consumption of produce, hummus, and processed meat products worldwide. To elucidate the intra-serovar genomic structure of S. Bovismorbificans, a core-genome analysis with 2690 loci (based on 150 complete genomes representing Salmonella enterica serovars developed as part of this study) and a k-mer-binning based strategy were carried out on 95 whole genome sequencing (WGS) assemblies from Swiss, Canadian, and USA collections of S. Bovismorbificans strains from foodborne infections. Data mining of a digital DNA tiling array of legacy SARA and SARB strains was conducted to identify near-neighbors of S. Bovismorbificans. The core genome analysis and the k-mer-binning methods identified two polyphyletic clusters, each with emerging evolutionary properties. Four STs (2640, 142, 1499, and 377), which constituted the majority of the publicly available WGS datasets from >260 strains analyzed by k-mer-binning based strategy, contained a conserved core genome backbone with a different evolutionary lineage as compared to strains comprising the other cluster (ST150). In addition, the assortment of genotypic features contributing to pathogenesis and persistence, such as antimicrobial resistance, prophage, plasmid, and virulence factor genes, were assessed to understand the emerging characteristics of this serovar that are relevant clinically and for food safety concerns. The phylogenomic profiling of polyphyletic S. Bovismorbificans in this study corresponds to intra-serovar variations observed in S. Napoli and S. Newport serovars using similar high-resolution genomic profiling approaches and contributes to the understanding of the evolution and sequence divergence of foodborne Salmonellae. These intra-serovar differences may have to be thoroughly understood for the accurate classification of foodborne Salmonella strains needed for the uniform development of future food safety mitigation strategies.

Source Attribution of Human Campylobacteriosis Using Whole-Genome Sequencing Data and Network Analysis

Campylobacter spp. are a leading and increasing cause of gastrointestinal infections worldwide. Source attribution, which apportions human infection cases to different animal species and food reservoirs, has been instrumental in control- and evidence-based intervention efforts. The rapid increase in whole-genome sequencing data provides an opportunity for higher-resolution source attribution models. Important challenges, including the high dimension and complex structure of WGS data, have inspired concerted research efforts to develop new models. We propose network analysis models as an accurate, high-resolution source attribution approach for the sources of human campylobacteriosis. A weighted network analysis approach was used in this study for source attribution comparing different WGS data inputs. The compared model inputs consisted of cgMLST and wgMLST distance matrices from 717 human and 717 animal isolates from cattle, chickens, dogs, ducks, pigs and turkeys. SNP distance matrices from 720 human and 720 animal isolates were also used. The data were collected from 2015 to 2017 in Denmark, with the animal sources consisting of domestic and imports from 7 European countries. Clusters consisted of network nodes representing respective genomes and links representing distances between genomes. Based on the results, animal sources were the main driving factor for cluster formation, followed by type of species and sampling year. The coherence source clustering (CSC) values based on animal sources were 78%, 81% and 78% for cgMLST, wgMLST and SNP, respectively. The CSC values based on Campylobacter species were 78%, 79% and 69% for cgMLST, wgMLST and SNP, respectively. Including human isolates in the network resulted in 88%, 77% and 88% of the total human isolates being clustered with the different animal sources for cgMLST, wgMLST and SNP, respectively. Between 12% and 23% of human isolates were not attributed to any animal source. Most of the human genomes were attributed to chickens from Denmark, with an average attribution percentage of 52.8%, 52.2% and 51.2% for cgMLST, wgMLST and SNP distance matrices respectively, while ducks from Denmark showed the least attribution of 0% for all three distance matrices. The best-performing model was the one using wgMLST distance matrix as input data, which had a CSC value of 81%. Results from our study show that the weighted network-based approach for source attribution is reliable and can be used as an alternative method for source attribution considering the high performance of the model. The model is also robust across the different Campylobacter species, animal sources and WGS data types used as input.

Whole Genome Sequencing, Antibiotic Resistance, and Epidemiology Features of Nontyphoidal Salmonella Isolated From Diarrheic Children: Evidence From North China

Nontyphoidal Salmonella (NTS) in children remains a growing burden on public health and often causes children to be hospitalized with diarrheic symptoms. In this work, 260 strains of human Salmonella isolated from Jilin, China were characterized by serotypes and antimicrobial resistance using whole genome sequencing (WGS). The most prevalent serotype was Salmonella enteritidis (47.3%), followed by S. I 4,[5],12:i:- (33.1%), and Salmonella Typhimurium (7.3%). Furthermore, the consistency between resistance phenotype and genotype was confirmed. Similarly, strains harbored bla_TEM−1B and tetA genes were detected, which verified the level of resistant phenotype in β-lactams and tetracyclines. The presence of a single mutation in parC, gyrA, and qnrS1 genes corresponding to quinolones was also observed. In our work, multilocus sequence typing (MLST) and core genome multilocus sequence typing (cgMLST) were found to have a high resolution to molecular traceability, and the combination of both was conducive to practical application in an actual situation. Taking all of this into account, we suggested that the comprehensive surveillance of Salmonella infection in children should be carried out to monitor antimicrobial-resistant trends from various sources and to alert on outbreaks of foodborne diseases to protect public health.

The Notable Achievements and the Prospects of Bacterial Pathogen Genomics

Throughout the entirety of human history, bacterial pathogens have played an important role and even shaped the fate of civilizations. The application of genomics within the last 27 years has radically changed the way we understand the biology and evolution of these pathogens. In this review, we discuss how the short- (Illumina) and long-read (PacBio, Oxford Nanopore) sequencing technologies have shaped the discipline of bacterial pathogen genomics, in terms of fundamental research (i.e., evolution of pathogenicity), forensics, food safety, and routine clinical microbiology. We have mined and discuss some of the most prominent data/bioinformatics resources such as NCBI pathogens, PATRIC, and Pathogenwatch. Based on this mining, we present some of the most popular sequencing technologies, hybrid approaches, assemblers, and annotation pipelines. A small number of bacterial pathogens are of very high importance, and we also present the wealth of the genomic data for these species (i.e., which ones they are, the number of antimicrobial resistance genes per genome, the number of virulence factors). Finally, we discuss how this discipline will probably be transformed in the near future, especially by transitioning into metagenome-assembled genomes (MAGs), thanks to long-read sequencing.

Whole-genome sequence analysis of Clostridium chauvoei isolated from clinical case of black quarter (BQ) from India

Black quarter (BQ) is an infectious disease affecting cattle and small ruminants worldwide caused by Gram-positive anaerobic bacterium Clostridium chauvoei. In this study, a draft genome sequence of C. chauvoei NIVEDIBQ1 strain isolated from clinical case of black quarter was analyzed. Sequence analysis indicated that genome had 2653 predicted coding DNA sequences, harbored numerous genes, mobile genetic elements for pathogenesis, and virulence factors. Computational analysis revealed that strain contained 30 virulence-associated genes. An intact genomic region highly similar to the Clostridium phage was present in the genome. Presence of CRISPR systems and the transposon components likely contribute to the genome plasticity. Strain encode diverse spectrum of degradative carbohydrate-active enzymes (CAZymes). Comparative SNP analysis revealed that the genomes of the C. chauvoei strains analyzed were highly conserved. Phylogenetic analysis of strains and available genome (n = 21) based on whole-genome multi-locus sequence typing (wgMLST) and core orthologous genes showed the clustering of strains into two different clusters suggesting geographical links.

LmTraceMap: A Listeria monocytogenes fast-tracing platform for global surveillance

Listeria monocytogenes can cause listeriosis, and people with hypoimmunity such as pregnant women, infants and fetuses are at high risk of invasive infection. Although the incidence of listeriosis is low, the fatality rate is high. Therefore, continual surveillance and rapid epidemiological investigation are crucial for addressing L. monocytogenes. Because of the popularity of next-generation sequencing, obtaining the whole-genome sequence of a bacterium is easy. Several genome-based typing methods are available, and core-genome multilocus sequence typing (cgMLST) is the most recognized methods. Using cgMLST typing to compare L. monocytogenes whole-genome sequences (WGS) with those obtained across distinct regions is beneficial. However, the concern is how to incorporate the powerful cgMLST method into investigations, such as by using source tracing. Herein, we present an easy-to-use web service called–LmTraceMap (http://lmtracemap.cgu.edu.tw/hua_map/test/upload.php; http://120.126.17.192/hua_map/test/upload.php) that can help public-health professionals rapidly trace closely related isolates worldwide and visually inspect them in search results on a world map with labeled epidemiological data. We expect the proposed service to improve the convenience of public health investigations.

Annotated Whole-Genome Multilocus Sequence Typing Schema for Scalable High-Resolution Typing of Streptococcus pyogenes

Streptococcus pyogenes is a major human pathogen with high genetic diversity, largely created by recombination and horizontal gene transfer, making it difficult to use single nucleotide polymorphism (SNP)-based genome-wide analyses for surveillance. Using a gene-by-gene approach on 208 complete genomes of S. pyogenes , a novel whole-genome multilocus sequence typing (wgMLST) schema was developed, comprising 3,044 target loci.

Systems biology approach to functionally assess the Clostridioides difficile pangenome reveals genetic diversity with discriminatory power

SignificanceClostridioides difficile infections are the most common source of hospital-acquired infections and are responsible for an extensive burden on the health care system. Strains of the C. difficile species comprise diverse lineages and demonstrate genome variability, with advantageous trait acquisition driving the emergence of endemic lineages. Here, we present a systems biology analysis of C. difficile that evaluates strain-specific genotypes and phenotypes to investigate the overall diversity of the species. We develop a strain typing method based on similarity of accessory genomes to identify and contextualize genetic loci capable of discriminating between strain groups.

Molecular characterization of zoonotic Brucella species isolated from animal and human samples in Iran

Brucellosis is an endemic infection in Iran and represents a serious health problem in humans and livestock causing important economic losses. The objective of this study was to undertake molecular characterization of Brucella spp. isolated from humans and livestock in several provinces of Iran including by multi-locus sequence typing (MLST), in order to understand the genotypes circulating in Iran and their relationship to genotypes globally. A total of 23 Brucella isolates were isolated from eight milk samples (seven cows, and one camel), human blood samples (seven), bovine lymph nodes (two), and samples from aborted fetuses (three sheep, two cows, and one goat). Phenotypic and molecular identification of Brucella isolates was performed on all isolated bacteria and showed that all were either Brucella melitensis or Brucella abortus. B. melitensis was associated with ovine/caprine and camel samples, most human isolates, and a significant minority of cattle isolates. In contrast B. abortus from livestock was associated only with isolations from bovine samples, as well as a single human sample. These results indicate that both B. melitensis and B. abortus contribute to the human brucellosis burden in Iran. B. melitensis isolates comprised three MLST-9 genotypes, the common and globally distributed ST8, a single representative of ST7, and several additional examples of ST102, a genotype previously only reported in a single isolate from a human brucellosis case believed to be acquired through travel to Iran. B. abortus isolates represented two globally common MLST-9 genotypes (ST1 and ST2), with relationships to biotype and other PCR-based typing methods consistent with previous observations. The results provide the basis for further studies examining the molecular epidemiology of Brucella circulating in Iran and the relationships of local isolates to those present globally.

Systems-Based Approach for Optimization of Assembly-Free Bacterial MLST Mapping

Epidemiological surveillance of bacterial pathogens requires real-time data analysis with a fast turnaround, while aiming at generating two main outcomes: (1) species-level identification and (2) variant mapping at different levels of genotypic resolution for population-based tracking and surveillance, in addition to predicting traits such as antimicrobial resistance (AMR). Multi-locus sequence typing (MLST) aids this process by identifying sequence types (ST) based on seven ubiquitous genome-scattered loci. In this paper, we selected one assembly-dependent and one assembly-free method for ST mapping and applied them with the default settings and ST schemes they are distributed with, and systematically assessed their accuracy and scalability across a wide array of phylogenetically divergent Public Health-relevant bacterial pathogens with available MLST databases. Our data show that the optimal k-mer length for stringMLST is species-specific and that genome-intrinsic and -extrinsic features can affect the performance and accuracy of the program. Although suitable parameters could be identified for most organisms, there were instances where this program may not be directly deployable in its current format. Next, we integrated stringMLST into our freely available and scalable hierarchical-based population genomics platform, ProkEvo, and further demonstrated how the implementation facilitates automated, reproducible bacterial population analysis.

Classification of Environmental Strains from Order to Genus Levels Using Lipid and Protein MALDI-ToF Fingerprintings and Chemotaxonomic Network Analysis

During the last two decades, MALDI-ToF mass spectrometry has become an efficient and widely-used tool for identifying clinical isolates. However, its use for classification and identification of environmental microorganisms remains limited by the lack of reference spectra in current databases. In addition, the interpretation of the classical dendrogram-based data representation is more difficult when the quantity of taxa or chemotaxa is larger, which implies problems of reproducibility between users. Here, we propose a workflow including a concurrent standardized protein and lipid extraction protocol as well as an analysis methodology using the reliable spectra comparison algorithm available in MetGem software. We first validated our method by comparing protein fingerprints of highly pathogenic bacteria from the Robert Koch Institute (RKI) open database and then implemented protein fingerprints of environmental isolates from French Guiana. We then applied our workflow for the classification of a set of protein and lipid fingerprints from environmental microorganisms and compared our results to classical genetic identifications using 16S and ITS region sequencing for bacteria and fungi, respectively. We demonstrated that our protocol allowed general classification at the order and genus level for bacteria whereas only the Botryosphaeriales order can be finely classified for fungi.

Leclercia pneumoniae sp. nov., a bacterium isolated from clinical specimen in Leipzig, Germany

Strain 49125T was isolated from an infant with pneumonia and septicaemia at the Leipzig University Hospital. Phenotypic and genomic traits were investigated. The strain's biochemical profile and its MALDI-TOF spectrogram did not differ from comparative samples of Leclercia adecarboxylata , thus far the sole member of the Leclercia species. A circular genome with a size of 4.4 Mbp and a G+C content of 55.0 mol% was reconstructed using hybrid Illumina and Nanopore sequencing. Phylogenetic analysis was based on 172 marker genes and validated using a k-mer-based search against a large genome collection including subsequent in silico DNA–DNA hybridization. Whole genome average nucleotide identity to any described species was below 95%, suggesting that strain 49125T represents a new species, for which we propose the name Leclercia pneumoniae sp. nov. with the type strain 49125T (=LMG 32245T=DSM 112336T).

In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes

Background

Whole genome sequencing analyzed by core genome multi-locus sequence typing (cgMLST) is widely used in surveillance of the pathogenic bacteria Listeria monocytogenes. Given the heterogeneity of available bioinformatics tools to define cgMLST alleles, our aim was to identify parameters influencing the precision of cgMLST profiles.

Methods

We used three L. monocytogenes reference genomes from different phylogenetic lineages and assessed the impact of in vitro (i.e. tested genomes, successive platings, replicates of DNA extraction and sequencing) and in silico parameters (i.e. targeted depth of coverage, depth of coverage, breadth of coverage, assembly metrics, cgMLST workflows, cgMLST completeness) on cgMLST precision made of 1748 core loci. Six cgMLST workflows were tested, comprising assembly-based (BIGSdb, INNUENDO, GENPAT, SeqSphere and BioNumerics) and assembly-free (i.e. kmer-based MentaLiST) allele callers. Principal component analyses and generalized linear models were used to identify the most impactful parameters on cgMLST precision.

Results

The isolate’s genetic background, cgMLST workflows, cgMLST completeness, as well as depth and breadth of coverage were the parameters that impacted most on cgMLST precision (i.e. identical alleles against reference circular genomes). All workflows performed well at ≥40X of depth of coverage, with high loci detection (> 99.54% for all, except for BioNumerics with 97.78%) and showed consistent cluster definitions using the reference cut-off of ≤7 allele differences.

Conclusions

This highlights that bioinformatics workflows dedicated to cgMLST allele calling are largely robust when paired-end reads are of high quality and when the sequencing depth is ≥40X.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08437-4.

Systematic review of Listeria monocytogenes from food and clinical samples in Chinese mainland from 2010 to 2019

Listeria monocytogenes, a foodborne pathogen, can cause human listeriosis. Listeriosis is a potentially fatal gastrointestinal illness, which is closely related to the spread of food to humans. We review the literature published during 2010 to 2019 to better understand the prevalence of L. monocytogenes in food products, incidence of human listeriosis, and their characteristics in Chinese mainland. We found the main sequence types (STs) strains from foods are similar globally, and the prevalence of L. monocytogenes from raw meat was the highest among all food products. The most common STs in food products and clinical cases were ST9 (serogroup Ⅰ.2) strains and ST87 (serogroup Ⅱ.2) strains, respectively. The ST87 strains being the most common STs of clinical cases might be related to the exist of Listeria pathogenicity islands 4 genes and Chinese eating habits for ready to eat foods, among which the prevalence of ST87 strain was the highest in ready to eat food. Therefore, more research should be conducted to explore the reasons for the L. monocytogenes isolates differences in food and clinic sources. Meanwhile, more research should be conducted to explore the reasons for differences among the L. monocytogenes isolates in food and clinical sources.

Mechanisms of biodiversity between Campylobacter sequence types in a flock of broiler-breeder chickens

Commercial poultry flocks frequently harbor the dangerous bacterial pathogen Campylobacter. As exclusion efforts frequently fail, there is interest in potential ecologically informed solutions. A long-term study of Campylobacter sequence types was used to investigate the competitive framework of the Campylobacter metacommunity and understand how multiple sequence types simultaneously co-occur in a flock of chickens. A combination of matrix and patch-occupancy models was used to estimate parameters describing the competition, transmission, and mortality of each sequence type. It was found that Campylobacter sequence types form a strong hierarchical framework within a flock of chickens and occupied a broad spectrum of transmission-mortality trade-offs. Upon further investigation of how biodiversity is thus maintained within the flock, it was found that the demographic capabilities of Campylobacter, such as mortality and transmission, could not explain the broad biodiversity of sequence types seen, suggesting that external factors such as host-bird health and seasonality are important elements in maintaining biodiversity of Campylobacter sequence types.

Phylogeny and potential virulence of cryptic clade Escherichia coli species complex isolates derived from an arable field trial

Analysis of Escherichia coli taxonomy has expanded into a species-complex with the identification of divergent cryptic clades. A key question is the evolutionary trajectory of these clades and their relationship to isolates of clinical or veterinary importance. Since they have some environmental association, we screened a collection of E. coli isolated from a long-term spring barley field trial for their presence. While most isolates clustered into the enteric-clade, four of them clustered into Clade-V, and one in Clade-IV. The Clade -V isolates shared >96% intra-clade average nucleotide sequence identity but <91% with other clades. Although pan-genomics analysis confirmed their taxonomy as Clade -V (E. marmotae), retrospective phylogroup PCR did not discriminate them correctly. Differences in metabolic and adherence gene alleles occurred in the Clade -V isolates compared to E. coli sensu scricto. They also encoded the bacteriophage phage-associated cyto-lethal distending toxin (CDT) and antimicrobial resistance (AMR) genes, including an ESBL, blaOXA-453. Thus, the isolate collection encompassed a genetic diversity, and included cryptic clade isolates that encode potential virulence factors. The analysis has determined the phylogenetic relationship of cryptic clade isolates with E. coli sensu scricto and indicates a potential for horizontal transfer of virulence factors.

Genomic Analysis of Global Staphylococcus argenteus Strains Reveals Distinct Lineages With Differing Virulence and Antibiotic Resistance Gene Content

Infections due to Staphylococcus argenteus have been increasingly reported worldwide and the microbe cannot be distinguished from Staphylococcus aureus by standard methods. Its complement of virulence determinants and antibiotic resistance genes remain unclear, and how far these are distinct from those produced by S. aureus remains undetermined. In order to address these uncertainties, we have collected 132 publicly available sequences from fourteen different countries, including the United Kingdom, between 2005 and 2018 to study the global genetic structure of the population. We have compared the genomes for antibiotic resistance genes, virulence determinants and mobile genetic elements such as phages, pathogenicity islands and presence of plasmid groups between different clades. 20% (n = 26) isolates were methicillin resistant harboring a mecA gene and 88% were penicillin resistant, harboring the blaZ gene. ST2250 was identified as the most frequent strain, but ST1223, which was the second largest group, contained a marginally larger number of virulence genes compared to the other STs. Novel S. argenteus pathogenicity islands were identified in our isolates harboring tsst-1, seb, sec3, ear, selk, selq toxin genes, as well as chromosomal clusters of enterotoxin and superantigen-like genes. Strain-specific type I modification systems were widespread which would limit interstrain transfer of genetic material. In addition, ST2250 possessed a CRISPR/Cas system, lacking in most other STs. S. argenteus possesses important genetic differences from S. aureus, as well as between different STs, with the potential to produce distinct clinical manifestations.

Genomic population structure of Helicobacter pylori Shanghai isolates and identification of genomic features uniquely linked with pathogenicity

Severe Helicobacter pylori-linked gastric disorders are especially prevalent in the East Asia region. The ability of H. pylori to cause different clinical outcomes is thought to be associated with unique sets of its genetic features. However, only few genetic features have been definitively linked to specific gastrointestinal pathologies. Genome heterogeneity of clinical H. pylori strains from patients with four different gastric disorders was studied to explore the population structure and molecular genomic features and their association with pathogenicity. Population analysis showed that 92.9% of the Shanghai H. pylori isolates were clustered in the East Asia group. Among 2,866 genes detected in all genomes, 1,146 genes formed the core genome, whereas 209 unique genes were detected in individual disease groups. The unique genes of peptic ulcer and gastric cancer groups represented the inorganic ion transport and metabolism function gene clusters. Sixteen virulence genes were detected with statistically different detection rates among the four disease groups. Furthermore, 127 clustered regularly interspaced short palindromic repeats were found with significantly different rates in the four disease groups. A total of 337 putative genomic islands were identified, and three genomic islands were individually found in more than 10% of strains. The genomic islands included several metabolism-associated genes and many genes with unknown function. In total, 88 sequence types were detected among the 112 Shanghai H. pylori isolates. Our study provides an essential milestone in the mapping of specific genomic features and their functions to identify factors needed to induce specific gastric disorders in H. pylori.

A High-Throughput Short Sequence Typing Scheme for Serratia marcescens Pure Culture and Environmental DNA

Molecular typing methods are used to characterize the relatedness between bacterial isolates involved in infections. These approaches rely mostly on discrete loci or whole-genome sequencing (WGS) analyses of pure cultures. On the other hand, their application to environmental DNA profiling to evaluate epidemiological relatedness among patients and environments has received less attention. We developed a specific, high-throughput short sequence typing (HiSST) method for the opportunistic human pathogen Serratia marcescens. Genes displaying the highest polymorphism were retrieved from the core genome of 60 S. marcescens strains. Bioinformatics analyses showed that use of only three loci (within bssA, gabR, and dhaM) distinguished strains with a high level of efficiency. This HiSST scheme was applied to an epidemiological survey of S. marcescens in a neonatal intensive care unit (NICU). In a first case study, a strain responsible for an outbreak in the NICU was found in a sink drain of this unit, by using HiSST scheme and confirmed by WGS. The HiSST scheme was also applied to environmental DNA extracted from sink-environment samples. Diversity of S. marcescens was modest, with 11, 6, and 4 different sequence types (ST) of gabR, bssA, and dhaM loci among 19 sink drains, respectively. Epidemiological relationships among sinks were inferred on the basis of pairwise comparisons of ST profiles. Further research aimed at relating ST distribution patterns to environmental features encompassing sink location, utilization, and microbial diversity is needed to improve the surveillance and management of opportunistic pathogens. IMPORTANCE Serratia marcescens is an important opportunistic human pathogen, often multidrug resistant and involved in outbreaks of nosocomial infections in neonatal intensive care units. Here, we propose a quick and user-friendly method to select the best typing scheme for nosocomial outbreaks in relating environmental and clinical sources. This method, named high-throughput short sequence typing (HiSST), allows to distinguish strains and to explore the diversity profile of nonculturable S. marcescens. The application of HiSST profile analysis for environmental DNA offers new possibilities to track opportunistic pathogens, identify their origin, and relate their distribution pattern with environmental features encompassing sink location, utilization, and microbial diversity. Adaptation of the method to other opportunistic pathogens is expected to improve knowledge regarding their ecology, which is of significant interest for epidemiological risk assessment and elaborate outbreak mitigation strategies.

A machine learning-based typing scheme refinement for Listeria monocytogenes core genome multilocus sequence typing with high discriminatory power for common source outbreak tracking

Background

As whole-genome sequencing for pathogen genomes becomes increasingly popular, the typing methods of gene-by-gene comparison, such as core genome multilocus sequence typing (cgMLST) and whole-genome multilocus sequence typing (wgMLST), are being routinely implemented in molecular epidemiology. However, some intrinsic problems remain. For example, genomic sequences with varying read depths, read lengths, and assemblers influence the genome assemblies, introducing error or missing alleles into the generated allelic profiles. These errors and missing alleles might create “specious discrepancy” among closely related isolates, thus making accurate epidemiological interpretation challenging. In addition, the rapid growth of the cgMLST allelic profile database can cause problems related to storage and maintenance as well as long query search times.

Methods

We attempted to resolve these issues by decreasing the scheme size to reduce the occurrence of error and missing alleles, alleviate the storage burden, and improve the query search time. The challenge in this approach is maintaining the typing resolution when using fewer loci. We achieved this by using a popular artificial intelligence technique, XGBoost, coupled with Shapley additive explanations for feature selection. Finally, 370 loci from the original 1701 cgMLST loci of Listeria monocytogenes were selected.

Results

Although the size of the final scheme (LmScheme_370) was approximately 80% lower than that of the original cgMLST scheme, its discriminatory power, tested for 35 outbreaks, was concordant with that of the original cgMLST scheme. Although we used L. monocytogenes as a demonstration in this study, the approach can be applied to other schemes and pathogens. Our findings might help elucidate gene-by-gene–based epidemiology.

Genomic Epidemiology and Strain Taxonomy of Corynebacterium diphtheriae

Corynebacterium diphtheriae is highly transmissible and can cause large diphtheria outbreaks where vaccination coverage is insufficient. Sporadic cases or small clusters are observed in high-vaccination settings. The phylogeography and short timescale evolution of C. diphtheriae are not well understood, in part due to a lack of harmonized analytical approaches of genomic surveillance and strain tracking. We combined 1,305 genes with highly reproducible allele calls into a core genome multilocus sequence typing (cgMLST) scheme. We analyzed cgMLST gene diversity among 602 isolates from sporadic clinical cases, small clusters, or large outbreaks. We defined sublineages based on the phylogenetic structure within C. diphtheriae and strains based on the highest number of cgMLST mismatches within documented outbreaks. We performed time-scaled phylogenetic analyses of major sublineages. The cgMLST scheme showed high allele call rate in C. diphtheriae and the closely related species C. belfantii and C. rouxii. We demonstrate its utility to delineate epidemiological case clusters and outbreaks using a 25 mismatches threshold and reveal a number of cryptic transmission chains, most of which are geographically restricted to one or a few adjacent countries. Subcultures of the vaccine strain PW8 differed by up to 20 cgMLST mismatches. Phylogenetic analyses revealed a short-timescale evolutionary gain or loss of the diphtheria toxin and biovar-associated genes. We devised a genomic taxonomy of strains and deeper sublineages (defined using a 500-cgMLST-mismatch threshold), currently comprising 151 sublineages, only a few of which are geographically widespread based on current sampling. The cgMLST genotyping tool and nomenclature was made publicly accessible (https://bigsdb.pasteur.fr/diphtheria). Standardized genome-scale strain genotyping will help tracing transmission and geographic spread of C. diphtheriae. The unified genomic taxonomy of C. diphtheriae strains provides a common language for studies of ecology, evolution, and virulence heterogeneity among C. diphtheriae sublineages.

Longitudinal study of Staphylococcus aureus genotypes isolated from bovine clinical mastitis

Bovine clinical mastitis is an important problem for the dairy industry, and Staphylococcus aureus is a common mastitis-causing pathogen in many countries. Detailed knowledge on genetic variation of Staph. aureus strains within the bovine population, including changes over time, can be useful for mastitis control programs, because severity of disease and effects on milk production are at least partly strain-associated. Therefore, the major aim of this study was to compare sequence types of Staph. aureus isolated from cases of bovine clinical mastitis from 2002 to 2003 with sequence types of a more recent set of isolates collected from 2013 to 2018, using core genome multi-locus sequence typing (cgMLST). We also wanted to compare antibiotic resistance genes of isolates from the 2 sets, to identify changes that may have occurred over time in the Staph. aureus population. A total of 157 isolates of Staph. aureus, almost equally distributed between the 2 time periods, were subjected to high-throughput sequencing and cgMLST. The results showed that the most prevalent sequence types found among the 2002 to 2003 isolates belonged to the clonal complexes CC97, CC133, and CC151, and that those complexes still dominated among the isolates from 2013 to 2018. However, a population shift from CC133 to CC97 and CC151 over time was observed. Likewise, no important differences in prevalence of antibiotic resistance genes were found between the 2 sets of isolates. As expected, genes belonging to the major facilitator superfamily of transporter proteins, and multidrug and toxic compound extrusion transporters, were very common. Moreover, several genes and mutations conferring resistance to fosfomycin were present, but not in CC97 isolates. The β-lactamase gene blaZ was found in only 3 out of 81 isolates from 2002 to 2003 and 1 out of 76 isolates in 2013 to 2018. In conclusion, the results indicate that mastitis-associated Staph. aureus strains circulating among dairy cows in Sweden exhibit a remarkable genotypic persistence over a time frame of close to 15 yr.

Establishment of a Publicly Available Core Genome Multilocus Sequence Typing Scheme for Clostridium perfringens

Clostridium perfringens is a spore-forming anaerobic pathogen responsible for a variety of histotoxic and intestinal infections in humans and animals. High-resolution genotyping aiming to identify bacteria at strain level has become increasingly important in modern microbiology to understand pathogen transmission pathways and to tackle infection sources. This study aimed at establishing a publicly available genome-wide multilocus sequence-typing (MLST) scheme for C. perfringens. A total of 1,431 highly conserved core genes (1.34 megabases; 50% of the reference genome genes) were indexed for a core genome-based MLST (cgMLST) scheme for C. perfringens. The scheme was applied to 282 ecologically and geographically diverse genomes, showing that the genotyping results of cgMLST were highly congruent with the core genome-based single-nucleotide-polymorphism typing in terms of resolution and tree topology. In addition, the cgMLST provided a greater discrimination than classical MLST methods for C. perfringens. The usability of the scheme for outbreak analysis was confirmed by reinvestigating published outbreaks of C. perfringens-associated infections in the United States and the United Kingdom. In summary, a publicly available scheme and an allele nomenclature database for genomic typing of C. perfringens have been established and can be used for broad-based and standardized epidemiological studies. IMPORTANCE Global epidemiological surveillance of bacterial pathogens is enhanced by the availability of standard tools and sharing of typing data. The use of whole-genome sequencing has opened the possibility for high-resolution characterization of bacterial strains down to the clonal and subclonal levels. Core genome multilocus sequence typing is a robust system that uses highly conserved core genes for deep genotyping. The method has been successfully and widely used to describe the epidemiology of various bacterial species. Nevertheless, a cgMLST typing scheme for Clostridium perfringens is currently not publicly available. In this study, we (i) developed a cgMLST typing scheme for C. perfringens, (ii) evaluated the performance of the scheme on different sets of C. perfringens genomes from different hosts and geographic regions as well as from different outbreak situations, and, finally, (iii) made this scheme publicly available supported by an allele nomenclature database for global and standard genomic typing.

Distribution of Genes Related to Probiotic Effects Across Lacticaseibacillus rhamnosus Revealed by Population Structure

The Gram-positive Lacticaseibacillus rhamnosus has been broadly reported as capable of exerting beneficial health effects. Bacterial genomic diversity may promote niche specialization, thus creating subpatterns within populations. As L. rhamnosus advantageous effects have been widely reported at strain level and few is known regarding the distribution of beneficial genes among L. rhamnosus strains, we investigated all publicly available genomes of Lactobacillus and Lacticaseibacillus genera to study the pangenome and general population structure of L. rhamnosus. Core genome multilocus sequence typing detected eight L. rhamnosus phylogroups (PG1 to PG8). L. rhamnosus harbors an open pangenome; PG1, PG3, PG4, and PG5 exhibited highly conserved gene distribution patterns. Genes significantly associated to the PG1, which comprises L. rhamnosus GG, are mainly phage-related. The adhesion operon spaCBA-srtC1 was found in 44 (24.7%) genomes; however, considering only the PG1, the prevalence was of 65%. In PG2 the spaCBA-srtC1 prevalence was of 43%. Nevertheless, both human and milk-derived strains harbored this operon. Further, two main types of bacteriocin clusters were found (Bact1 and Bact2). Bact1 predictions indicate the presence of garQ, encoding the class II bacteriocin garvieacin Q, that is mainly present in the closely related PG8A and a PG2 subcluster. PG2 harbors two distinct subclusters, harboring either spaCBA-srtC1 or Bact1. Our findings provide novel insights on the distribution of biotechnological relevant genes across L. rhamnosus population, uncovering intra-species patterns that may bring forth the development of more efficient probiotic products.

The Possible Transmission and Potential Enterotoxicity of Bacillus cereus on Lettuce Farms in Five Chinese Provinces

Bacillus cereus is a well-characterized human pathogen that produces toxins associated with diarrheal and emetic foodborne diseases. To investigate the possible transmission of B. cereus on lettuce farms in China and determine its enterotoxicity, (I) a total of 524 samples (lettuce: 332, soil: 69, water: 57, manure: 57, pesticide: 9) were collected from 46 lettuce farms in five Chinese provinces, (II) multilocus sequence typing (MLST) was used to classify B. cereus isolates and for trace analysis, and (III) the presence of toxin genes and enterotoxins (Hbl and Nhe) was detected in 68 strains. The results showed that one hundred and sixty-one lettuce samples (48.5%) tested positive for B. cereus at levels ranging from 10 to 5.3 × 10⁴ CFU/g. Among the environmental sample categories surveyed, the highest positive rate was that of the pesticide samples at 55.6%, followed by soil samples at 52.2% and manure samples at 12.3%. Moreover, one hundred isolates of B. cereus yielded 68 different sequence types (STs) and were classified into five phylogenetic clades. Furthermore, Nhe toxin genes (nheA, nheB, nheC) were broadly distributed and identified in all 68 strains (100%), while Hbl toxin genes (hblA, hblC, hblD) were present in 61 strains (89.7%), entFM was detected in 62 strains (91.2%), and cytK was found in 29 strains (42.6%). All strains were negative for ces. As for the enterotoxin, Nhe was observed in all 68 isolates carrying nheB, while Hbl was present in 76.5% (52/68) of the strains harboring hblC. This study is the first report of possible B. cereus transmission and of its potential enterotoxicity on lettuce farms in China. The results showed that soil and pesticides are the main sources of B. cereus on lettuce farms in China, and the possible transmission routes are as follows: soil-lettuce, manure-lettuce, pesticide-lettuce, manure-soil-lettuce, and water-manure-soil-lettuce. Furthermore, the B. cereus isolates, whether from lettuce or the environment, pose a potential risk to health.

Cultivation of common bacterial species and strains from human skin, oral, and gut microbiota

BACKGROUND

Genomics-driven discoveries of microbial species have provided extraordinary insights into the biodiversity of human microbiota. In addition, a significant portion of genetic variation between microbiota exists at the subspecies, or strain, level. High-resolution genomics to investigate species- and strain-level diversity and mechanistic studies, however, rely on the availability of individual microbes from a complex microbial consortia. High-throughput approaches are needed to acquire and identify the significant species- and strain-level diversity present in the oral, skin, and gut microbiome. Here, we describe and validate a streamlined workflow for cultivating dominant bacterial species and strains from the skin, oral, and gut microbiota, informed by metagenomic sequencing, mass spectrometry, and strain profiling.

RESULTS

Of total genera discovered by either metagenomic sequencing or culturomics, our cultivation pipeline recovered between 18.1-44.4% of total genera identified. These represented a high proportion of the community composition reconstructed with metagenomic sequencing, ranging from 66.2-95.8% of the relative abundance of the overall community. Fourier-Transform Infrared spectroscopy (FT-IR) was effective in differentiating genetically distinct strains compared with whole-genome sequencing, but was less effective as a proxy for genetic distance.

CONCLUSIONS

Use of a streamlined set of conditions selected for cultivation of skin, oral, and gut microbiota facilitates recovery of dominant microbes and their strain variants from a relatively large sample set. FT-IR spectroscopy allows rapid differentiation of strain variants, but these differences are limited in recapitulating genetic distance. Our data highlights the strength of our cultivation and characterization pipeline, which is in throughput, comparisons with high-resolution genomic data, and rapid identification of strain variation.

Whole-genome sequencing and ad hoc shared genome analysis of Staphylococcus aureus isolates from a New Zealand primary school

Epidemiological studies of communicable diseases increasingly use large whole-genome sequencing (WGS) datasets to explore the transmission of pathogens. It is important to obtain an initial overview of datasets and identify closely related isolates, but this can be challenging with large numbers of isolates and imperfect sequencing. We used an ad hoc whole-genome multi locus sequence typing method to summarise data from a longitudinal study of Staphylococcus aureus in a primary school in New Zealand. Each pair of isolates was compared and the number of genes where alleles differed between isolates was tallied to produce a matrix of "allelic differences". We plotted histograms of the number of allelic differences between isolates for: all isolate pairs; pairs of isolates from different individuals; and pairs of isolates from the same individual. 340 sequenced isolates were included, and the ad hoc shared genome contained 445 genes. There were between 0 and 420 allelic differences between isolate pairs and the majority of pairs had more than 260 allelic differences. We found many genetically closely related S. aureus isolates from single individuals and a smaller number of closely-related isolates from separate individuals. Multiple S. aureus isolates from the same individual were usually very closely related or identical over the ad hoc shared genome. Siblings carried genetically similar, but not identical isolates. An ad hoc shared genome approach to WGS analysis can accommodate imperfect sequencing of the included isolates, and can provide insights into relationships between isolates in epidemiological studies with large WGS datasets containing diverse isolates.

Genome-Enabled Molecular Subtyping and Serotyping for Shiga Toxin-Producing Escherichia coli

Foodborne pathogens are a major public health burden in the United States, leading to 9.4 million illnesses annually. Since 1996, a national laboratory-based surveillance program, PulseNet, has used molecular subtyping and serotyping methods with the aim to reduce the burden of foodborne illness through early detection of emerging outbreaks. PulseNet affiliated laboratories have used pulsed-field gel electrophoresis (PFGE) and immunoassays to subtype and serotype bacterial isolates. Widespread use of serotyping and PFGE for foodborne illness surveillance over the years has resulted in the accumulation of a wealth of routine surveillance and outbreak epidemiological data. This valuable source of data has been used to understand seasonal frequency, geographic distribution, demographic information, exposure information, disease severity, and source of foodborne isolates. In 2019, PulseNet adopted whole genome sequencing (WGS) at a national scale to replace PFGE with higher-resolution methods such as the core genome multilocus sequence typing. Consequently, PulseNet's recent shift to genome-based subtyping methods has rendered the vast collection of historic surveillance data associated with serogroups and PFGE patterns potentially unusable. The goal of this study was to develop a bioinformatics method to associate the WGS data that are currently used by PulseNet for bacterial pathogen subtyping to previously characterized serogroup and PFGE patterns. Previous efforts to associate WGS to PFGE patterns relied on predicting DNA molecular weight based on restriction site analysis. However, these approaches failed owing to the non-uniform usage of genomic restriction sites by PFGE restriction enzymes. We developed a machine learning approach to classify isolates to their most probable serogroup and PFGE pattern, based on comparisons of genomic k-mer signatures. We applied our WGS classification method to 5,970 Shiga toxin-producing Escherichia coli (STEC) isolates collected as part of PulseNet's routine foodborne surveillance activities between 2003 and 2018. Our machine learning classifier is able to associate STEC WGS to higher-level serogroups with very high accuracy and lower-level PFGE patterns with somewhat lower accuracy. Taken together, these classifications support the ability of public health investigators to associate currently generated WGS data with historical epidemiological knowledge linked to serogroups and PFGE patterns in support of outbreak surveillance for food safety and public health.

Nasopharyngeal Meningococcal Carriage among Children and Adolescents in Turkey in 2018: An Unexpected High Serogroup X Carriage

Meningococcal carriage studies and transmission modeling can predict IMD epidemiology and used to define invasive meningococcal disease (IMD) control strategies. In this multicenter study, we aimed to evaluate the prevalence of nasopharyngeal Neisseria meningitidis (Nm) carriage, serogroup distribution, and related risk factors in Turkey. Nasopharyngeal samples were collected from a total of 1267 children and adolescents and were tested with rt-PCR. Nm carriage was detected in 96 participants (7.5%, 95% CI 6.1–9.0), with the peak age at 13 years (12.5%). Regarding age groups, Nm carriage rate was 7% in the 0–5 age group, was 6.9%in the 6–10 age group, was 7.9% in the 11–14 age group, and was 9.3% in the 15–18 age group. There was no statistically significant difference between the groups (p > 0.05). The serogroup distribution was as follows: 25% MenX, 9.4% MenA, 9.4% MenB, 2.1% MenC, 3.1% MenW, 2.1% for MenY, and 48.9% for non-groupable. The Nm carriage rate was higher in children with previous upper respiratory tract infections and with a high number of household members, whereas it was lower in children with antibiotic use in the last month (p < 0.05 for all). In this study, MenX is the predominant carriage strain. The geographical distribution of Nm strains varies, but serogroup distribution in the same country might change in a matter of years. Adequate surveillance and/or a proper carriage study is paramount for accurate/dynamic serogroup distribution and the impact of the proposed vaccination.

Current Developments in Diagnostic Assays for Laboratory Confirmation and Investigation of Botulism

Detection of botulinum neurotoxin or isolation of the toxin producing organism is required for the laboratory confirmation of botulism in clinical specimens. In an effort to reduce animal testing required by the gold standard method of botulinum neurotoxin detection, the mouse bioassay, many technologies have been developed to detect and characterize the causative agent of botulism. Recent advancements in these technologies have led to improvements in technical performance of diagnostic assays; however, many emerging assays have not been validated for the detection of all serotypes in complex clinical and environmental matrices. Improvements to culture protocols, endopeptidase-based assays, and a variety of immunological and molecular methods have provided laboratories with a variety of testing options to evaluate and incorporate into their testing algorithms. While significant advances have been made to improve these assays, additional work is necessary to evaluate these methods in various clinical matrices and to establish standardized criteria for data analysis and interpretation.

Comparison of Conventional Molecular and Whole-Genome Sequencing Methods for Differentiating Salmonella enterica Serovar Schwarzengrund Isolates Obtained from Food and Animal Sources

Over the last decade, Salmonella&nbsp;enterica serovar Schwarzengrund has become more prevalent in Asia, Europe, and the US with the simultaneous emergence of multidrug-resistant isolates. As these pathogens are responsible for many sporadic illnesses and chronic complications, as well as outbreaks over many countries, improved surveillance is urgently needed. For 20 years, pulsed-field gel electrophoresis (PFGE) has been the gold standard for determining bacterial relatedness by targeting genome-wide restriction enzyme polymorphisms. Despite its utility, recent studies have reported that PFGE results correlate poorly with that of closely related outbreak strains and clonally dominant endemic strains. Due to these concerns, alternative amplification-based molecular methods for bacterial strain typing have been developed, including clustered regular interspaced short palindromic repeats (CRISPR) and multilocus sequence typing (MLST). Furthermore, as the cost of sequencing continues to decrease, whole genome sequencing (WGS) is poised to replace other molecular strain typing methods. In this study, we assessed the discriminatory power of PFGE, CRISPR, MLST, and WGS methods to differentiate between 23 epidemiologically unrelated S. enterica serovar Schwarzengrund isolates collected over an 18-year period from distinct locations in Taiwan. The discriminatory index (DI) of each method for different isolates was calculated, resulting in values between 0 (not discriminatory) and 1 (highly discriminatory). Our results showed that WGS has the greatest resolution (DI = 0.982) compared to PFGE (DI = 0.938), CRISPR (DI = 0.906), and MLST (DI = 0.463) methods. In conclusion, the WGS typing approach was shown to be the most sensitive for S. enterica serovar Schwarzengrund fingerprinting.

The Distribution of Campylobacter jejuni Virulence Genes in Genomes Worldwide Derived from the NCBI Pathogen Detection Database

Campylobacter jejuni (C. jejuni) is responsible for 80% of human campylobacteriosis and is the leading cause of gastroenteritis globally. The relevant public health risks of C. jejuni are caused by particular virulence genes encompassing its virulome. We analyzed 40,371 publicly available genomes of C. jejuni deposited in the NCBI Pathogen Detection Database, combining their epidemiologic metadata with an in silico bioinformatics analysis to increase our current comprehension of their virulome from a global perspective. The collection presented a virulome composed of 126 identified virulence factors that were grouped in three clusters representing the accessory, the softcore, and the essential core genes according to their prevalence within the genomes. The multilocus sequence type distribution in the genomes was also investigated. An unexpected low prevalence of the full-length flagellin flaA and flaB locus of C. jejuni genomes was revealed, and an essential core virulence gene repertoire prevalent in more than 99.99% of genomes was identified. Altogether, this is a pioneer study regarding Campylobacter jejuni that has compiled a significant amount of data about the Multilocus Sequence Type and virulence factors concerning their global prevalence and distribution over this database.

Historical, current, and emerging tools for identification and serotyping of Shigella

The Shigella genus includes serious foodborne disease etiologic agents, with 4 species and 54 serotypes. Identification at species and serotype levels is a crucial task in microbiological laboratories. Nevertheless, the genetic similarity between Shigella spp. and Escherichia coli challenges the correct identification and serotyping of Shigella spp., with subsequent negative repercussions on surveillance, epidemiological investigations, and selection of appropriate treatments. For this purpose, multiple techniques have been developed historically ranging from phenotype-based methods and single or multilocus molecular techniques to whole-genome sequencing (WGS). To facilitate the selection of the most relevant method, we herein provide a global overview of historical and emerging identification and serotyping techniques with a particular focus on the WGS-based approaches. This review highlights the excellent discriminatory power of WGS to more accurately elucidate the epidemiology of Shigella spp., disclose novel promising genomic targets for surveillance methods, and validate previous well-established methods.