A Simple and Robust Statistical Method to Define Genetic Relatedness of Samples Related to Outbreaks at the Genomic Scale - Application to Retrospective Salmonella Foodborne Outbreak Investigations

Genomic insights of Salmonella isolated from dry fermented sausage production chains in Spain and France

The presence of Salmonella in dry fermented sausages is source of recalls and outbreaks. The genomic diversity of 173 Salmonella isolates from the dry fermented sausage production chains (pig carcasses, pork, and sausages) from France and Spain were investigated through their core phylogenomic relationships and accessory genome profiles. Ten different serovars and thirteen sequence type profiles were identified. The most frequent serovar from sausages was the monophasic variant of S. Typhimurium (1,4,[5],12:i:-, 72%) while S. Derby was in pig carcasses (51%). Phylogenomic clusters found in S. 1,4,[5],12:i:-, S. Derby, S. Rissen and S. Typhimurium serovars identified closely related isolates, with less than 10 alleles and 20 SNPs of difference, displaying Salmonella persistence along the pork production chain. Most of the S. 1,4,[5],12:i:- contained the Salmonella genomic island-4 (SGI-4), Tn21 and IncFIB plasmid. More than half of S. Derby strains contained the SGI-1 and Tn7. S. 1,4,[5],12:i:- genomes carried the most multidrug resistance genes (91% of the strains), whereas extended-spectrum β-lactamase genes were found in Typhimurium and Derby serovars. Salmonella monitoring and characterization in the pork production chains, specially S. 1,4,[5],12:i:- serovar, is of special importance due to its multidrug resistance capacity and persistence in dry fermented sausages.

Isolation, Identification, Antimicrobial Resistance, Genotyping, and Whole-Genome Sequencing Analysis of Salmonella Enteritidis Isolated from a Food-Poisoning Incident

Salmonella enterica is a common pathogen in humans and animals that causes food poisoning and infection, threatening public health safety. We aimed to investigate the genome structure, drug resistance, virulence characteristics, and genetic relationship of a Salmonella strain isolated from patients with food poisoning. The pathogen strain 21A was collected from the feces of patients with food poisoning, and its minimum inhibitory concentration against commonly used antibiotics was determined using the strip test and Kirby-Bauer disk methods. Subsequently, WGS analysis was used to reveal the genome structural characteristics and the carrying status of resistance genes and virulence genes of strain 21A. In addition, an MLST-based minimum spanning tree and an SNP-based systematic spanning tree were constructed to investigate its genetic evolutionary characteristics. The strain 21A was identified by mass spectrometry as S. enterica, which was found to show resistance to ampicillin, piperacillin, sulbactam, levofloxacin, and ciprofloxacin. The WGS and bioinformatics analyses revealed this strain as Salmonella Enteritidis belonging to ST11, which is common in China, containing various resistance genes and significant virulence characteristics. Strain 21A was closely related to the SJTUF strains, a series strains from animal, food and clinical sources, as well as from Shanghai, China, which were located in the same evolutionary clade. According to the genetic makeup of strain 21A, the change G > A was found to be the most common variation. We have comprehensively analyzed the genomic characteristics, drug resistance phenotype, virulence phenotype, and genetic evolution relationship of S. Enteritidis strain 21A, which will contribute towards an in-depth understanding of the pathogenic mechanism of S. Enteritidis and the effective prevention and control of foodborne diseases.

Virulence Factors and Antimicrobial Resistance of Uropathogenic Escherichia coli EQ101 UPEC Isolated from UTI Patient in Quetta, Balochistan, Pakistan

Infectious diseases have been tremendously increasing as the organisms of even normal flora become opportunistic and cause an infection, and Escherichia coli (E. coli EQ101) is one of them. Urinary tract infections are caused by various microorganisms, but Escherichia coli is the primary cause of almost 70%-90% of all UTIs. It has multiple strains, possessing diverse virulence factors, contributing to its pathogenicity. Furthermore, these virulent strains also can cause overlapping pathogenesis by sharing resistance and virulence factors among each other. The current study is aimed at analyzing the genetic variants associated with multi-drug-resistant (MDR) E. coli using the whole genome sequencing platform. The study includes 100 uropathogenic Escherichia coli (UPEC) microorganisms obtained from urine samples out of which 44% were multi-drug-resistant (MDR) E. coli. Bacteria have been isolated and antimicrobial susceptibility test (AST) was determined by disk diffusion method on the Mueller-Hinton agar plate as recommended by the Clinical and Laboratory Standards Institute (CLSI) 2020, and one isolate has been selected which shows resistance to most of the antibiotics, and that isolate has been analyzed by whole genome sequencing (WGS), accompanied by data and phylogenetic analysis, respectively. Organisms were showing resistance against ampicillin (10 μg), cefixime (5 μg), ceftriaxone (30 μg), nalidixic acid (30 μg), ciprofloxacin (5 μg), and ofloxacin (5 μg) on antimicrobial susceptibility test. WGS were done on selected isolate which identified 25 virulence genes (air, astA, chuA, fyuA, gad, hra, iha, irp2, iss, iucC, iutA, kpsE, kpsMII_K1, lpfA, mchF, ompT, papA_F43, sat, senB, sitA, terC, traT, usp, vat, and yfcV) and seven housekeeping genes (adk, fumC, gyrB, icd, mdh, purA, and recA). Among resistance genes, seven genes (TolC, emrR, evgA, qacEdelta1, H-NS, cpxA, and mdtM) were identified to be involved in antibiotic efflux, three AMR genes (aadA5, mphA, and CTX-M-15) were involved in antibiotic inactivation, and two genes (sul1 and dfrA14) were found to be involved in antibiotic drug replacement. Our data identified antibiotic resistance and virulence genes of the isolate. We suggest further research work to establish region-based resistance profile in comparison with the global resistance pattern.

Tell me if you prefer bovine or poultry sectors and I'll tell you who you are: Characterization of Salmonella enterica subsp. enterica serovar Mbandaka in France

Introduction

In north-western France, Salmonella enterica susp. enterica serovar Mbandaka (S. Mbandaka) is most frequently isolated from bovine and dairy samples. While this serovar most often results in asymptomatic carriage, for a number of years it has caused episodes of abortions, which have serious economic consequences for the sector. Interestingly, this serovar is also isolated from Gallus gallus in the same geographic zone. Despite its prevalence in bovines in north-western France, S. Mbandaka has not been broadly studied at the genomic level, and its prevalence and host adaptation are still not fully understood.

Methods

In this study, we analyzed the genomic diversity of 304 strains of S. Mbandaka isolated from the bovine and poultry sectors in this area over a period of 5 years. A phylogenetic analysis was carried out and two approaches were followed to identify conserved genes and mutations related to host associations. The first approach targeted the genes compiled in the MEGARESv2, Resfinder, VFDB and SPI databases. Plasmid and phage contents were also investigated. The second approach refers to an in-house algorithm developed for this study that computes sensitivity, specificity, and accuracy of accessory genes and core variants according to predefined genomes groups.

Results and discussion

All the analyzed strains belong to the multi-locus sequence type profile ST413, and the phylogenomic analysis revealed main clustering by host (bovine and poultry), emphasizing the circulation of 12 different major clones, of which seven circulate in poultry and five in the bovine sector in France and a likely food production chain adaptation of these clones. All strains present resistance determinants including heavy metals and biocides that could explain the ability of this serovar to survive and persist in the environment, within herds, and in food processing plants. To explore the wild animal contribution to the spread of this serovar in north-western France, we retrieved S. Mbandaka genomes isolated from wild birds from EnteroBase and included them in the phylogenomic analysis together with our collection. Lastly, screening of accessory genes and major variants allowed us to identify conserved specific mutations characteristic of each major cluster. These mutations could be used to design useful probes for food safety surveillance.

Large-scale comparative genomics to refine the organization of the global Salmonella enterica population structure

The White-Kauffmann-Le Minor (WKL) scheme is the most widely used Salmonella typing scheme for reporting the disease prevalence of the enteric pathogen. With the advent of whole-genome sequencing (WGS), in silico methods have increasingly replaced traditional serotyping due to reproducibility, speed and coverage. However, despite integrating genomic-based typing by in silico serotyping tools such as SISTR, in silico serotyping in certain contexts remains ambiguous and insufficiently informative. Specifically, in silico serotyping does not attempt to resolve polyphyly. Furthermore, in spite of the widespread acknowledgement of polyphyly from genomic studies, the prevalence of polyphyletic serovars is not well characterized. Here, we applied a genomics approach to acquire the necessary resolution to classify genetically discordant serovars and propose an alternative typing scheme that consistently reflect natural Salmonella populations. By accessing the unprecedented volume of bacterial genomic data publicly available in GenomeTrakr and PubMLST databases (>180 000 genomes representing 723 serovars), we characterized the global Salmonella population structure and systematically identified putative non-monophyletic serovars. The proportion of putative non-monophyletic serovars was estimated higher than previous reports, reinforcing the inability of antigenic determinants to depict the complexity of Salmonella evolutionary history. We explored the extent of genetic diversity masked by serotyping labels and found significant intra-serovar molecular differences across many clinically important serovars. To avoid false discovery due to incorrect in silico serotyping calls, we cross-referenced reported serovar labels and concluded a low error rate in in silico serotyping. The combined application of clustering statistics and genome-wide association methods demonstrated effective characterization of stable bacterial populations and explained functional differences. The collective methods adopted in our study have practical values in establishing genomic-based typing nomenclatures for an entire microbial species or closely related subpopulations. Ultimately, we foresee an improved typing scheme to be a hybrid that integrates both genomic and antigenic information such that the resolution from WGS is leveraged to improve the precision of subpopulation classification while preserving the common names defined by the WKL scheme.

Polyphyly in widespread Salmonella enterica serovars and using genomic proximity to choose the best reference genome for bioinformatics analyses

Salmonella is the most common cause of gastroenteritis in the world. Over the past 5 years, whole-genome analysis has led to the high-resolution characterization of clinical and foodborne Salmonella responsible for typhoid fever, foodborne illness or contamination of the agro-food chain. Whole-genome analyses are simplified by the availability of high-quality, complete genomes for mapping analysis and for calculating the pairwise distance between genomes, but unfortunately some difficulties may still remain. For some serovars, the complete genome is not available, or some serovars are polyphyletic and knowing the serovar alone is not sufficient for choosing the most appropriate reference genome. For these serovars, it is essential to identify the genetically closest complete genome to be able to carry out precise genome analyses. In this study, we explored the genomic proximity of 650 genomes of the 58 Salmonella enterica subsp. enterica serovars most frequently isolated in humans and from the food chain in the United States (US) and in Europe (EU), with a special focus on France. For each serovar, to take into account their genomic diversity, we included all the multilocus sequence type (MLST) profiles represented in EnteroBase with 10 or more genomes (on 19 July 2021). A phylogenetic analysis using both core- and pan-genome approaches was carried out to identify the genomic proximity of all the Salmonella studied and 20 polyphyletic serovars that have not yet been described in the literature. This study determined the genetic proximity between all 58 serovars studied and revealed polyphyletic serovars, their genomic lineages and MLST profiles. Finally, we enhanced the open-access databases with 73 new genomes and produced a list of high-quality complete reference genomes for 48 S. enterica subsp. enterica serovars among the most isolated in the US, EU, and France.

A retrospective and regional approach assessing the genomic diversity of Salmonella Dublin

From a historically rare serotype, Salmonella enterica subsp. enterica Dublin slowly became one of the most prevalent Salmonella in cattle and raw milk cheese in some regions of France. We present a retrospective genomic analysis of 480 S. Dublin isolates to address the context, evolutionary dynamics, local diversity and the genesis processes of regional S. Dublin outbreaks events between 2015 and 2017. Samples were clustered and assessed for correlation against metadata including isolation date, isolation matrices, geographical origin and epidemiological hypotheses. Significant findings can be drawn from this work. We found that the geographical distance was a major factor explaining genetic groups in the early stages of the cheese production processes (animals, farms) while down-the-line transformation steps were more likely to host genomic diversity. This supports the hypothesis of a generalised local persistence of strains from animal to finished products, with occasional migration. We also observed that the bacterial surveillance is representative of diversity, while targeted investigations without genomics evidence often included unrelated isolates. Combining both approaches in phylogeography methods allows a better representation of the dynamics, of outbreaks.

A European-wide dataset to uncover adaptive traits of Listeria monocytogenes to diverse ecological niches

Listeria monocytogenes (Lm) is a ubiquitous bacterium that causes listeriosis, a serious foodborne illness. In the nature-to-human transmission route, Lm can prosper in various ecological niches. Soil and decaying organic matter are its primary reservoirs. Certain clonal complexes (CCs) are over-represented in food production and represent a challenge to food safety. To gain new understanding of Lm adaptation mechanisms in food, the genetic background of strains found in animals and environment should be investigated in comparison to that of food strains. Twenty-one partners, including food, environment, veterinary and public health laboratories, constructed a dataset of 1484 genomes originating from Lm strains collected in 19 European countries. This dataset encompasses a large number of CCs occurring worldwide, covers many diverse habitats and is balanced between ecological compartments and geographic regions. The dataset presented here will contribute to improve our understanding of Lm ecology and should aid in the surveillance of Lm. This dataset provides a basis for the discovery of the genetic traits underlying Lm adaptation to different ecological niches.

Measurement(s)	whole genome sequencing
Technology Type(s)	Illumina Sequencing
Factor Type(s)	Multi-locus sequence types • Geographic location • Animal associated environment isolates • Food product and food production environment isolates
Sample Characteristic - Organism	Listeria monocytogenes
Sample Characteristic - Environment	Farm • Ruminant • Agricultural soil • Wild animals • food processing building • dairy food product • meat or meat product (from mammal) (us cfr) • chicken meat food product • fish food product • vegetable or vegetable product (us cfr)
Sample Characteristic - Location	Europe

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.

Salmonella enterica subsp. enterica Welikade: guideline for phylogenetic analysis of serovars rarely involved in foodborne outbreaks

BACKGROUND

Salmonella spp. is a major foodborne pathogen with a wide variety of serovars associated with human cases and food sources. Nevertheless, in Europe a panel of ten serovars is responsible for up to 80% of confirmed human cases. Clustering studies by single nucleotide polymorphism (SNP) core-genome phylogenetic analysis of outbreaks due to these major serovars are simplified by the availability of many complete genomes in the free access databases. This is not the case for outbreaks due to less common serovars, such as Welikade, for which no reference genomes are available. In this study, we propose a method to solve this problem. We propose to perform a core genome MLST (cgMLST) analysis based on hierarchical clustering using the free-access EnteroBase to select the most suitable genome to use as a reference for SNP phylogenetic analysis. In this study, we applied this protocol to a retrospective analysis of a Salmonella enterica serovar Welikade (S. Welikade) foodborne outbreak that occurred in France in 2016. Finally, we compared the cgMLST and SNP analyses. SNP phylogenetic reconstruction was carried out considering the effect of recombination events identified by the ClonalFrameML tool. The accessory genome was also explored by phage content and virulome analyses.

RESULTS

Our findings revealed high clustering concordance using cgMLST and SNP analyses. Nevertheless, SNP analysis allowed for better assessment of the genetic distance among strains. The results revealed epidemic clones of S. Welikade circulating within the poultry and dairy sectors in France, responsible for sporadic and non-sporadic human cases between 2012 and 2019.

CONCLUSIONS

This study increases knowledge on this poorly described serovar and enriches public genome databases with 42 genomes from human and non-human S. Welikade strains, including the isolate collected in 1956 in Sri Lanka, which gave the name to this serovar. This is the first genomic analysis of an outbreak due to S. Welikade described to date.

SARS-CoV-2 surveillance in Italy through phylogenomic inferences based on Hamming distances derived from pan-SNPs, -MNPs and -InDels

BACKGROUND

Faced with the ongoing global pandemic of coronavirus disease, the 'National Reference Centre for Whole Genome Sequencing of microbial pathogens: database and bioinformatic analysis' (GENPAT) formally established at the 'Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise' (IZSAM) in Teramo (Italy) is in charge of the SARS-CoV-2 surveillance at the genomic scale. In a context of SARS-CoV-2 surveillance requiring correct and fast assessment of epidemiological clusters from substantial amount of samples, the present study proposes an analytical workflow for identifying accurately the PANGO lineages of SARS-CoV-2 samples and building of discriminant minimum spanning trees (MST) bypassing the usual time consuming phylogenomic inferences based on multiple sequence alignment (MSA) and substitution model.

RESULTS

GENPAT constituted two collections of SARS-CoV-2 samples. The first collection consisted of SARS-CoV-2 positive swabs collected by IZSAM from the Abruzzo region (Italy), then sequenced by next generation sequencing (NGS) and analyzed in GENPAT (n = 1592), while the second collection included samples from several Italian provinces and retrieved from the reference Global Initiative on Sharing All Influenza Data (GISAID) (n = 17,201). The main results of the present work showed that (i) GENPAT and GISAID detected the same PANGO lineages, (ii) the PANGO lineages B.1.177 (i.e. historical in Italy) and B.1.1.7 (i.e. 'UK variant') are major concerns today in several Italian provinces, and the new MST-based method (iii) clusters most of the PANGO lineages together, (iv) with a higher dicriminatory power than PANGO lineages, (v) and faster that the usual phylogenomic methods based on MSA and substitution model.

CONCLUSIONS

The genome sequencing efforts of Italian provinces, combined with a structured national system of NGS data management, provided support for surveillance SARS-CoV-2 in Italy. We propose to build phylogenomic trees of SARS-CoV-2 variants through an accurate, discriminant and fast MST-based method avoiding the typical time consuming steps related to MSA and substitution model-based phylogenomic inference.

Serotyping, MLST, and Core Genome MLST Analysis of Salmonella enterica From Different Sources in China During 2004-2019

Salmonella enterica (S. enterica) is an important foodborne pathogen, causing food poisoning and human infection, and critically threatening food safety and public health. Salmonella typing is essential for bacterial identification, tracing, epidemiological investigation, and monitoring. Serotyping and multilocus sequence typing (MLST) analysis are standard bacterial typing methods despite the low resolution. Core genome MLST (cgMLST) is a high-resolution molecular typing method based on whole genomic sequencing for accurate bacterial tracing. We investigated 250 S. enterica isolates from poultry, livestock, food, and human sources in nine provinces of China from 2004 to 2019 using serotyping, MLST, and cgMLST analysis. All S. enterica isolates were divided into 36 serovars using slide agglutination. The major serovars in order were Enteritidis (31 isolates), Typhimurium (29 isolates), Mbandaka (23 isolates), and Indiana (22 isolates). All strains were assigned into 43 sequence types (STs) by MLST. Among them, ST11 (31 isolates) was the primary ST. Besides this, a novel ST, ST8016, was identified, and it was different from ST40 by position 317 C → T in dnaN. Furthermore, these 250 isolates were grouped into 185 cgMLST sequence types (cgSTs) by cgMLST. The major cgST was cgST235530 (11 isolates), and only three cgSTs contained isolates from human and other sources, indicating a possibility of cross-species infection. Phylogenetic analysis indicated that most of the same serovar strains were putatively homologous except Saintpaul and Derby due to their multilineage characteristics. In addition, serovar I 4,[5],12:i:- and Typhimurium isolates have similar genomic relatedness on the phylogenetic tree. In conclusion, we sorted out the phenotyping and genotyping diversity of S. enterica isolates in China during 2004-2019 and clarified the temporal and spatial distribution characteristics of Salmonella from different hosts in China in the recent 16 years. These results greatly supplement Salmonella strain resources, genetic information, and traceability typing data; facilitate the typing, traceability, identification, and genetic evolution analysis of Salmonella; and therefore, improve the level of analysis, monitoring, and controlling of foodborne microorganisms in China.

Decentralized Investigation of Bacterial Outbreaks Based on Hashed cgMLST

Whole-genome sequencing (WGS)-based outbreak investigation has proven to be a valuable method for the surveillance of bacterial pathogens. Its utility has been successfully demonstrated using both gene-by-gene (cgMLST or wgMLST) and single-nucleotide polymorphism (SNP)-based approaches. Among the obstacles of implementing a WGS-based routine surveillance is the need for an exchange of large volumes of sequencing data, as well as a widespread reluctance to share sequence and metadata in public repositories, together with a lacking standardization of suitable bioinformatic tools and workflows. To address these issues, we present chewieSnake, an intuitive and simple-to-use cgMLST workflow. ChewieSnake builds on the allele calling software chewBBACA and extends it by the concept of allele hashing. The resulting hashed allele profiles can be readily compared between laboratories without the need of a central allele nomenclature. The workflow fully automates the computation of the allele distance matrix, cluster membership, and phylogeny and summarizes all important findings in an interactive HTML report. Furthermore, chewieSnake can join allele profiles generated at different laboratories and identify shared clusters, including a stable and intercommunicable cluster nomenclature, thus facilitating a joint outbreak investigation. We demonstrate the feasibility of the proposed approach with a thorough method comparison using publically available sequencing data for Salmonella enterica. However, chewieSnake is readily applicable to all bacterial taxa, provided that a suitable cgMLST scheme is available. The workflow is freely available as an open-source tool and can be easily installed via conda or docker.

Comparative phenotypic, genotypic and genomic analyses of Bacillus thuringiensis associated with foodborne outbreaks in France

Bacillus thuringiensis (Bt) belongs to the Bacillus cereus (Bc) group, well known as an etiological agent of foodborne outbreaks (FBOs). Bt distinguishes itself from other Bc by its ability to synthesize insecticidal crystals. However, the search for these crystals is not routinely performed in food safety or clinical investigation, and the actual involvement of Bt in the occurrence of FBOs is not known. In the present study, we reveal that Bt was detected in the context of 49 FBOs declared in France between 2007 and 2017. In 19 of these FBOs, Bt was the only microorganism detected, making it the most likely causal agent. Searching for its putative origin of contamination, we noticed that more than 50% of Bt isolates were collected from dishes containing raw vegetables, in particular tomatoes (48%). Moreover, the genomic characterization of isolates showed that most FBO-associated Bt isolates exhibited a quantified genomic proximity to Bt strains, used as biopesticides, especially those from subspecies aizawai and kurstaki. Taken together, these results strengthen the hypothesis of an agricultural origin for the Bt contamination and call for further investigations on Bt pesticides.