Typing methods based on whole genome sequencing data

Phylogenomics of Brucella abortus isolated from African Buffalo in Kruger National Park: New perspectives on wildlife-cattle disease dynamics

In South Africa, Brucella abortus biovar 1 is the primary cause of bovine brucellosis, significantly impacting cattle production and trade. Serological studies have revealed brucellosis in African wildlife, complicating control efforts due to limited epidemiological data. In 1977, B. abortus biovar 1 was isolated from an African buffalo fetus in Kruger National Park (KNP), raising speculation that buffalo may serve as reservoir hosts. This study investigated Brucella spp. in free-ranging buffalo in KNP using serological, molecular, and bacteriological methods. Brucella abortus bv 1 was isolated from lymph nodes and spleens of three sub-adult buffalo in 2022, marking the first documented recurrence in 50 years. Phylogenomic analyses revealed connections between buffalo isolates and cattle strains from South Africa and South America, suggesting spillover and shared origins from Europe. Further genomic and epidemiological surveillance is required to clarify the role of buffalo as reservoir hosts for brucellosis.

Reference-Free Variant Calling with Local Graph Construction with ska lo (SKA)

The study of genomic variants is increasingly important for public health surveillance of pathogens. Traditional variant-calling methods from whole-genome sequencing data rely on reference-based alignment, which can introduce biases and require significant computational resources. Alignment- and reference-free approaches offer an alternative by leveraging k-mer-based methods, but existing implementations often suffer from sensitivity limitations, particularly in high mutation density genomic regions. Here, we present ska lo, a graph-based algorithm that aims to identify within-strain variants in pathogen whole-genome sequencing data by traversing a colored De Bruijn graph and building variant groups (i.e. sets of variant combinations). Through in silico benchmarking and real-world dataset analyses, we demonstrate that ska lo achieves high sensitivity in single-nucleotide polymorphism (SNP) calls while also enabling the detection of insertions and deletions, as well as SNP positioning on a reference genome for recombination analyses. These findings highlight ska lo as a simple, fast, and effective tool for pathogen genomic epidemiology, extending the range of reference-free variant-calling approaches. ska lo is freely available as part of the SKA program (https://github.com/bacpop/ska.rust).

Machine learning reveals the dynamic importance of accessory sequences for Salmonella outbreak clustering

Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the variable segments of bacterial genomes that can fluctuate significantly in gene content. However, due to the transient and hypervariable nature of many accessory elements, the value of the added resolution in outbreak investigations remains disputed. To assess the analytical value of bacterial accessory genomes in clustering epidemiologically related cases, we trained classifiers on a set of genomes collected from 24 Salmonella enterica outbreaks of food, animal, or environmental origin. The models demonstrated high precision and recall on unseen test data with near-perfect accuracy in classifying clonal and short-term outbreaks. Annotating the genomic features important for cluster classification revealed functional enrichment of molecular fingerprints in genes involved in membrane transportation, trafficking, and carbohydrate metabolism. Importantly, we discovered polymorphisms in mobile genetic elements (MGEs) and gain/loss of MGEs to be informative in defining outbreak clusters. To quantify the ability of MGE variations to cluster outbreak clones, we devised a reference-free tree-building algorithm inspired by colored de Bruijn graphs, which enabled topological comparisons between MGE and standard typing methods. Systematic evaluation of clustering MGEs on an unseen dataset of 34 Salmonella outbreaks yielded mixed results that exemplified the power of accessory sequence variations when core genomes of unrelated cases are insufficiently discriminatory, as well as the distortion of outbreak signals by microevolution events or the incomplete assembly of MGEs.

IMPORTANCE

Gene-by-gene typing is widely used to detect clusters of foodborne illnesses that share a common origin. It remains actively debated whether the inclusion of accessory sequences in bacterial typing schema is informative or deleterious for cluster definitions in outbreak investigations due to the potential confounding effects of horizontal gene transfer. By training machine learning models on a curated set of historical Salmonella outbreaks, we revealed an enriched presence of outbreak distinguishing features in a wide range of mobile genetic elements. Systematic comparison of the efficacy of clustering different accessory elements against standard sequence typing methods led to our cataloging of scenarios where accessory sequence variations were beneficial and uninformative to resolving outbreak clusters. The presented work underscores the complexity of the molecular trends in enteric outbreaks and seeks to inspire novel computational ways to exploit whole-genome sequencing data in enteric disease surveillance and management.

The Trade-Off Between Sanitizer Resistance and Virulence Genes: Genomic Insights into E. coli Adaptation

BACKGROUND

Escherichia coli is one of the most studied bacteria worldwide due to its genetic plasticity. Recently, in addition to characterizing its pathogenic potential, research has focused on understanding its resistance profile to inhibitory agents, whether these be antibiotics or sanitizers.

OBJECTIVES

The present study aimed to investigate six of the main serogroups of foodborne infection (O26, O45, O103, O111, O121, and O157) and to understand the dynamics of heterogeneity in resistance to sanitizers derived from quaternary ammonium compounds (QACs) and peracetic acid (PAA) using whole-genome sequencing (WGS).

METHODS

Twenty-four E. coli strains with varied resistance profiles to QACs and PAA were analyzed by WGS using NovaSeq6000 (150 bp Paired End reads). Bioinformatic analyses included genome assembly (Shovill), annotation via Prokka, antimicrobial resistance gene identification using Abricate, and core-genome analysis using Roary. A multifactorial multiple correspondence analysis (MCA) was conducted to explore gene-sanitizer relationships. In addition, a large-scale analysis utilizing the NCBI Pathogen Detection database involved a 2 × 2 chi-square test to examine associations between the presence of qac and stx genes.

RESULTS

The isolates exhibited varying antimicrobial resistance profiles, with O45 and O157 being the most resistant serogroups. In addition, the qac gene was identified in only one strain (S22), while four other strains carried the stx gene. Through multifactorial multiple correspondence analysis, the results obtained indicated that strains harboring genes encoding Shiga toxin (stx) presented profiles that were more likely to be sensitive to QACs. To further confirm these results, we analyzed 393,216 E. coli genomes from the NCBI Pathogen Detection database. Our results revealed a significant association (p < 0.001) between the presence of qac genes and the absence of stx1, stx2, or both toxin genes.

CONCLUSION

Our findings highlight the complexity of bacterial resistance mechanisms and suggest that non-pathogenic strains may exhibit greater tolerance to QAC sanitizer than those carrying pathogenicity genes, particularly Shiga toxin genes.

Comparative genomic and antimicrobial resistance profiles of Salmonella strains isolated from pork and human sources in Sichuan, China

Introduction

Salmonella detection in retail pork is increasing, yet studies on its antimicrobial resistance (AMR) profiles and genomic characteristics remain limited. Moreover, it is still unclear whether certain Salmonella sequence types (STs) are consistently or rarely associated with pork as a transmission source. Sichuan province, the largest pork-production region in China, provides a critical setting to investigate these dynamics.

Methods

In this study, 213 Salmonella strains isolated from pork and human sources (2019-2021) underwent phenotypic AMR testing and whole-genome sequencing (WGS).

Results

Resistance profiling revealed a higher prevalence of AMR in the pork-derived strains, particularly in veterinary-associated antibiotics. We identified STs not observed in pork in this study, such as ST23 (S. Oranienburg) and the poultry-commonly associated ST32 (S. Infantis), suggesting potential non-pork transmission routes for these Salmonella STs. To quantify sequence type diversity within each sample source, we introduced the sequencing type index (ST index = number of different STs/ total isolates). The ST index was 32% (49/153) for human-derived isolates and 20% (12/60) for pork-derived isolates. PERMANOVA analysis revealed significant differences in the structural composition of sequence types between human- and pork-derived isolates (p = 0.001), indicating that pork may harbor specific Salmonella STs more frequently.

Discussion

These findings highlight the role of pork as a reservoir for certain Salmonella STs, while also implying potential non-pork transmission pathways. The ST index represents a novel metric for assessing Salmonella diversity across different sample sources, offering a better understanding of genetic variation and transmission dynamics.

Whole-genome automated assembly pipeline for Chlamydia trachomatis strains from reference, in vitro and clinical samples using the integrated CtGAP pipeline

Whole genome sequencing (WGS) is pivotal for the molecular characterization of Chlamydia trachomatis (Ct)-the leading bacterial cause of sexually transmitted infections and infectious blindness worldwide. Ct WGS can inform epidemiologic, public health and outbreak investigations of these human-restricted pathogens. However, challenges persist in generating high-quality genomes for downstream analyses given its obligate intracellular nature and difficulty with in vitro propagation. No single tool exists for the entirety of Ct genome assembly, necessitating the adaptation of multiple programs with varying success. Compounding this issue is the absence of reliable Ct reference strain genomes. We, therefore, developed CtGAP-Chlamydia trachomatisGenome Assembly Pipeline-as an integrated 'one-stop-shop' pipeline for assembly and characterization of Ct genome sequencing data from various sources including isolates, in vitro samples, clinical swabs and urine. CtGAP, written in Snakemake, enables read quality statistics output, adapter and quality trimming, host read removal, de novo and reference-guided assembly, contig scaffolding, selective ompA, multi-locus-sequence and plasmid typing, phylogenetic tree construction, and recombinant genome identification. Twenty Ct reference genomes were also generated. Successfully validated on a diverse collection of 363 samples containing Ct, CtGAP represents a novel pipeline requiring minimal bioinformatics expertise with easy adaptation for use with other bacterial species.

Streamlining whole genome sequencing for clinical diagnostics with ONT technology

Recent advances in whole-genome sequencing (WGS) have increased the accessibility of this tool, offering substantial potential for pathogen surveillance, outbreak response, and diagnostics. However, the routine clinical adoption of WGS is hindered by factors such as high costs, technical complexity, and the requirement for bioinformatics expertise for data analysis. To address these challenges, we propose RapidONT, a workflow designed for cost-effective and accessible WGS-based pathogen analysis. RapidONT employs a mechanical shearing-based DNA extraction protocol, followed by library construction by using a multiplexing Oxford nanopore technologies (ONT) rapid barcoding kit. Flye software is used for de novo assembly without manual intervention, followed by basic assembly polishing using Medaka and Homopolish. The polished assemblies are then analyzed using the user-friendly web-based platform Pathogenwatch, which facilitates species identification, molecular typing, and antimicrobial resistance (AMR) prediction, all while requiring minimal bioinformatics expertise. The efficacy of RapidONT was evaluated using nine clinically relevant pathogens, encompassing a total of 90 gram-positive and gram-negative bacterial strains. The workflow demonstrated high accuracy in critical tasks such as multilocus sequence typing (MLST) and AMR identification, using only ONT R9.4.1 flowcell data. Notably, limitations were observed with Salmonella spp. and Neisseria gonorrhoeae. Furthermore, RapidONT enabled the generation of genomic information for 48 bacterial isolates by using a single flow cell, significantly reducing sequencing costs. This approach eliminates the need for extensive experimentation in obtaining crucial genomic information. This workflow facilitates broader WGS implementation in clinical pathogen analysis and diagnostics.

Molecular Epidemiology of Salmonella enterica Serotype Dublin Isolated from 2011 to 2022 from Veal and Dairy Cattle in Pennsylvania

The emergence of Salmonella enterica serotype Dublin (S. Dublin) presents significant challenges to animal and human health. We analyzed 109 S. Dublin isolates from bovine submissions to the Penn State Animal Diagnostic Laboratory between 2011 and 2022. Using whole genome sequencing, we assessed their phenotypic and genotypic resistance patterns and correlated these traits with case histories and pathology reports. Core-genome analysis identified cgSTs with similar allelic profiles between our isolates and those from the U.S. and Canada, while some cgSTs were unique to our study. Histopathologic findings suggest a predominance of respiratory and gastroenteric/hepatic lesions, aligning with the histopathological case definition for S. Dublin infection. Critically, all isolates were multidrug-resistant, particularly to ampicillin (87%), ceftiofur (89%), chlortetracycline (94%), oxytetracycline (94%), enrofloxacin (17%), florfenicol (94%), sulfadimethoxine (97%), and trimethoprim (20%). Plasmid genomic analysis unveiled distinct plasmid types including virulence, resistance, and hybrid plasmids, carrying unique compositions of virulence genes and antimicrobial resistance. These findings underscore the importance of managing calf movement to control the introduction and dissemination of new cgSTs in Pennsylvania and potentially nationwide. Furthermore, they emphasize the urgent need to mitigate S. Dublin transmission, combat antimicrobial resistance, and enhance surveillance efforts to effectively protect animal and human health.

Genomic analysis of Enterobacter cloacae complex from Southern Thailand reveals insights into multidrug resistance genotypes and genetic diversity

In this study, we conducted a comprehensive investigation into the Enterobacter cloacae complex (ECC), a group of notorious pathogens responsible for various hospital-acquired infections. We aimed to gain critical insights into antimicrobial resistance profiles and genomic diversity among 17 ECC isolates, which were previously collected as part of a short-term surveillance effort for 6 months in 2019. We identified two novel sequence types (ST-1936 in E. bugandensis PSU30 and ST-1937 in E. roggenkampii PSU45) among the 14 distinct STs identified in our ECC isolates. Furthermore, our expanded investigation revealed 296 novel STs within the NCBI Reference Sequence database. We identified six isolates carrying the mcr-9 gene, highlighting a significant concern in antimicrobial resistance (AMR). These genes confer a reduced susceptibility to colistin, a critical last-resort drug for the treatment of multidrug-resistant (MDR) infection. In addition to the AMR complexity, we found that three isolates carried the blaNDM gene on IncN2 plasmids, further emphasizing the urgency of monitoring and managing ECC-related infections. Our study provided evidence of intra-hospital transmission involving E. asburiae isolates PSU37, PSU39, and PSU40, all collected from the nasopharynx of three individuals in the intensive care unit (ICU) of the same hospital. These findings highlight the need for stringent infection control measures to prevent similar outbreaks and emphasize the importance of effective surveillance and management strategies to address ECC-related challenges.

Galaxy @Sciensano: a comprehensive bioinformatics portal for genomics-based microbial typing, characterization, and outbreak detection

The influx of whole genome sequencing (WGS) data in the public health and clinical diagnostic sectors has created a need for data analysis methods and bioinformatics expertise, which can be a bottleneck for many laboratories. At Sciensano, the Belgian national public health institute, an intuitive and user-friendly bioinformatics tool portal was implemented using Galaxy, an open-source platform for data analysis and workflow creation. The Galaxy @Sciensano instance is available to both internal and external scientists and offers a wide range of tools provided by the community, complemented by over 50 custom tools and pipelines developed in-house. The tool selection is currently focused primarily on the analysis of WGS data generated using Illumina sequencing for microbial pathogen typing, characterization and outbreak detection, but it also addresses specific use cases for other data types. Our Galaxy instance includes several custom-developed 'push-button' pipelines, which are user-friendly and intuitive stand-alone tools that perform complete characterization of bacterial isolates based on WGS data and generate interactive HTML output reports with key findings. These pipelines include quality control, de novo assembly, sequence typing, antimicrobial resistance prediction and several relevant species-specific assays. They are tailored for pathogens with active genomic surveillance programs, and clinical relevance, such as Escherichia coli, Listeria monocytogenes, Salmonella spp. and Mycobacterium tuberculosis. These tools and pipelines utilize internationally recognized databases such as PubMLST, EnteroBase, and the NCBI National Database of Antibiotic Resistant Organisms, which are automatically synchronized on a regular basis to ensure up-to-date results. Many of these pipelines are part of the routine activities of Belgian national reference centers and laboratories, some of which use them under ISO accreditation. This resource is publicly available for noncommercial use at https://galaxy.sciensano.be/ and can help other laboratories establish reliable, traceable and reproducible bioinformatics analyses for pathogens encountered in public health settings.

Dissemination of clinical Escherichia coli harboring the mcr-1 gene in Pakistan

Background

Colistin is an antibiotic used as a last resort to treat multidrug-resistant Gram-negative bacterial infections. Plasmid-mediated mobile colistin-resistant (mcr) genes in Escherichia coli (E. coli) are disseminated globally and are considered to be a major public health threat. This study aimed to determine the molecular characteristics of colistin-resistant Escherichia coli isolates in clinical settings in Pakistan.

Methods

A total of 240 clinical E. coli strains isolated from urine and pus cultures were collected from two hospitals in Faisalabad and analyzed for phenotypic resistance to colistin by cultivation on CHROMagar plates supplemented with colistin 2 ug/ml. Molecular characteristics of colistin-resistant isolates were analyzed using conventional PCR, whole genome sequencing, and bioinformatics analysis.

Results

PCR and whole genome analysis confirmed the presence of the mcr-1 gene in 10 E. coli isolates. The minimum inhibitory concentration for colistin ranged from 4 ug/ml to 32 ug/ml. ResFinder analysis revealed the presence of multiple resistance determinants conferring co-resistance to β-lactams, aminoglycosides, trimethoprim, sulfonamides, tetracycline, quinolones, florfenicol, and macrolides. Hybrid genomic assembly indicated that mcr-1 is carried on IncI2 plasmids. Plasmid replicon typing indicated that IncI2-type plasmids (n = 10) were the most prevalent plasmids in these strains, followed by IncFIB (n = 8), IncFIC (n = 7), IncFIA (n = 6), IncFII (4), IncQ1 (n = 3), IncI1 (n = 1), IncY (n = 1), and IncN (n = 1). The Achtman MLST typing scheme revealed a large diversity of STs among the mcr-1-positive E. coli. VirulenceFinder analysis revealed the presence of numerous virulence factors ranging from 4 to 19.

Conclusion

Our study revealed the emergence and dissemination of colistin-resistant E. coli isolates carrying mcr-1 in hospital settings, posing a potential risk to anti-infective therapy. More efforts should be taken to monitor the prevalence of mcr-1-carrying bacteria in Pakistan.

Epidemiology of Staphylococcus aureus food isolates: Comparison of conventional methods with whole genome sequencing typing methods

A variety of methods exists for typing bacteria. However, guidelines for the application and interpretation of typing tools in epidemiologic investigations of Staphylococcus aureus are lacking. This study aimed to identify appropriate typing methods for S. aureus population studies and outbreak investigation. We compared pulsed-field gel electrophoresis (PFGE), seven loci multi-locus sequence typing (MLST), core genome MLST (cgMLST), core single nucleotide polymorphism (cSNP), and enterotoxin (se/SE) profiles on 351 S. aureus isolates. The discriminatory power, concordance, and congruence of typing results were assessed. cgMLST, cSNP, and PFGE yielded the highest discrimination value, followed by se/SE typing and MLST. The best concordance of results was found between cgMLST and cSNP, while the best congruence was observed for cgMLST and cSNP with all methods, followed by PFGE with MLST. The strengths and weaknesses of each method are highlighted. For population structure, cgMLST and cSNP performed better than PFGE and MLST in terms of resolution of clusters and in phylogenetic inference. Enterotoxin profiles matched with MLST groups, suggesting the use of se/SE typing to predict MLST results. For the retrospective analysis of 31 outbreaks, all methods performed almost equally to discriminate epidemiologically related strains and can be used to unambiguously distinguish outbreak strains.

Evaluation of nationwide analysis surveillance for methicillin-resistant Staphylococcus aureus within Genomic Medicine Sweden

Background. National epidemiological investigations of microbial infections greatly benefit from the increased information gained by whole-genome sequencing (WGS) in combination with standardized approaches for data sharing and analysis.Aim. To evaluate the quality and accuracy of WGS data generated by different laboratories but analysed by joint pipelines to reach a national surveillance approach.Methods. A national methicillin-resistant Staphylococcus aureus (MRSA) collection of 20 strains was distributed to nine participating laboratories that performed in-house procedures for WGS. Raw data were shared and analysed by three pipelines: 1928 Diagnostics, JASEN (GMS pipeline) and CLC-Genomics Workbench. The outcomes were compared according to quality, correct strain identification and genetic distances.Results. One isolate contained intraspecies contamination and was excluded from further analysis. The mean sequencing depth varied between sites and technologies. However, all analysis methods identified 12 strains that belonged to one of five outbreak clusters. The cut-off definition was set to <10 allele differences for core genome multilocus sequence typing (cgMLST) and <20 genetic differences for SNP analysis in a pairwise comparison.Conclusions. MRSA isolates, which are whole genome sequenced by different laboratories and analysed using the same bioinformatic pipelines, yielded comparable results for outbreak clustering for both cgMLST and SNP, using the 1928 analysis pipeline. In this study, JASEN was best suited to analyse Illumina data and CLC to analyse within respective technology. In the future, real-time sharing of data and harmonized analysis within the Genomic Medicine Sweden consortium will further facilitate investigations of outbreaks and transmission routes.

Genetic diversity of Brucella abortus strains from cattle and water buffalo in the Italian province of Caserta

Brucella abortus is an important zoonotic pathogen that infects cattle and buffaloes. In Italy the application of eradication programs combined with vaccination has greatly contributed to reduce the incidence of brucellosis. However, despite the eradication programs brucellosis continue to persist with a high endemicity in some areas of Italy including the province of Caserta. In the present study the genomes of 44 B. abortus strains isolated from different outbreak cases that affected the province of Caserta were sequenced to characterize the genetic diversity of the Brucella strains circulating during the period from 2017 to 2022. The relatedness among these isolates was compared to 52 publicly available genomes of Italian B. abortus isolates. The results highlighted a low genetic diversity in the B. abortus population present in the Caserta area with the persistence of a low number of Brucella lineages and suggests a reduction in circulating lineages in recent years due to eradication programs.

Whole genome sequencing reveals circulation of potentially virulent Listeria innocua strains with novel genomic features in cattle farm environments in Dhaka, Bangladesh

Through the last decade, Listeria spp. has been detected in food and environmental samples in Bangladesh. However, the genomic information of this bacterium that prevails in the country remains scarce. This study analyzed the complete genome sequences of two Listeria spp. isolates obtained from cow dung and their drinking water collected from a cattle farm in Dhaka, Bangladesh. Both the isolates were identified as Listeria innocua, which shared almost identical genomic features. The genome sequences demonstrated the presence of 13 virulence genes associated with invasion (iap/cwhA, gtcA, and lpeA), surface protein anchoring (lspA), adherence (fbpA, and lap), intracellular survival (lplA1, and prsA2), peptidoglycan modification (oatA, and pdgA), and heat stress (clpC, clpE, and clpP). Additionally, the gene fosX, conferring resistance to fosfomycin, and two copper resistance-associated genes, copC and csoR, were identified in both. The genome sequences also revealed two plasmid replicons, rep25 and rep32, along with three insertion sequences [ISLmo3 (CP022021), ISLmo7 (CP006611), ISS1N (M37395)]. Notably, a composite transposon [CN_8789_ISS1N (M37395)], was detected in both L. innocua isolates, representing the first documented occurrence of this particular composite transposon in any reported Listeria species. Furthermore, the genomes contained four prophage regions [Listeria phage LP-030-2 (NC_021539), Listeria phage vB_LmoS_188 (NC_028871), Listeria phage A118 (NC_003216) and Escherichia phage RCS47 (NC_042128)]. Two CRISPR arrays were also identified, one belonging to the family type II-A. Multilocus Sequence Typing (MLST) analysis classified the L. innocua isolates of the same sequence type, ST-637. Single nucleotide polymorphism (SNP) analysis uncovered the presence of 231-340 SNPs between the L. innocua isolates and their closely related global lineage. In contrast, only 42 SNPs were identified between the two isolates, suggesting a potential transmission of L. innocua between cow dung and cattle farm water. The presence of L. innocua isolates harboring virulence genes associated with ruminant infection in the cattle farm environment of Bangladesh raises significant concerns about the potential presence of other human and animal pathogens. This poses a serious threat to the cattle farming industry. Additionally, the genomic analysis of the L. innocua isolates enhances our understanding of the evolutionary dynamics of Listeria species.

Recent developments in antibiotic resistance: an increasing threat to public health

Antibiotic resistance (ABR) is a major global health threat that puts decades of medical progress at risk. Bacteria develop resistance through various means, including modifying their targets, deactivating drugs, and utilizing efflux pump systems. The main driving forces behind ABR are excessive antibiotic use in healthcare and agriculture, environmental contamination, and gaps in the drug development process. The use of advanced detection technologies, such as next-generation sequencing (NGS), clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostics, and metagenomics, has greatly improved the identification of resistant pathogens. The consequences of ABR on public health are significant, increased mortality rates, the endangerment of modern medical procedures, and resulting in higher healthcare expenses. It has been expected that ABR could potentially drive up to 24 million individuals into extreme poverty by 2030. Mitigation strategies focus on antibiotic stewardship, regulatory measures, research incentives, and raising public awareness. Furthermore, future research directions involve exploring the potential of CRISPR-Cas9 (CRISPR-associated protein 9), nanotechnology, and big data analytics as new antibiotic solutions. This review explores antibiotic resistance, including mechanisms, recent trends, drivers, and technological advancements in detection. It also evaluates the implications for public health and presents strategies for mitigating resistance. The review emphasizes the significance of future directions and research needs, stressing the necessity for sustained and collaborative efforts to tackle this issue.

Bridging Classical Methodologies in Salmonella Investigation with Modern Technologies: A Comprehensive Review

Advancements in genomics and machine learning have significantly enhanced the study of Salmonella epidemiology. Whole-genome sequencing has revolutionized bacterial genomics, allowing for detailed analysis of genetic variation and aiding in outbreak investigations and source tracking. Short-read sequencing technologies, such as those provided by Illumina, have been instrumental in generating draft genomes that facilitate serotyping and the detection of antimicrobial resistance. Long-read sequencing technologies, including those from Pacific Biosciences and Oxford Nanopore Technologies, offer the potential for more complete genome assemblies and better insights into genetic diversity. In addition to these sequencing approaches, machine learning techniques like decision trees and random forests provide powerful tools for pattern recognition and predictive modeling. Importantly, the study of bacteriophages, which interact with Salmonella, offers additional layers of understanding. Phages can impact Salmonella population dynamics and evolution, and their integration into Salmonella genomics research holds promise for novel insights into pathogen control and epidemiology. This review revisits the history of Salmonella and its pathogenesis and highlights the integration of these modern methodologies in advancing our understanding of Salmonella.

Investigating the Quantification Capabilities of a Nanopore-Based Sequencing Platform for Food Safety Application via External Standards of Lambda DNA and Lambda Spiked Beef

Six hundred million cases of disease and roughly 420,000 deaths occur globally each year due to foodborne pathogens. Current methods to screen and identify pathogens in swine, poultry, and cattle products include immuno-based techniques (e.g., immunoassay integrated biosensors), molecular methods (e.g., DNA hybridization and PCR assays), and traditional culturing. These methods are often used in tandem to screen, quantify, and characterize samples, prolonging real-time comprehensive analysis. Next-generation sequencing (NGS) is a relatively new technology that combines DNA-sequencing chemistry and bioinformatics to generate and analyze large amounts of short- or long-read DNA sequences and whole genomes. The goal of this project was to evaluate the quantitative capabilities of the real-time NGS Oxford Nanopore Technologies' MinION sequencer through a shotgun-based sequencing approach. This investigation explored the correlation between known amounts of the analyte (lambda DNA as a pathogenic bacterial surrogate) with data output, in both the presence and absence of a background matrix (Bos taurus DNA). A positive linear correlation was observed between the concentration of analyte and the amount of data produced, number of bases sequenced, and number of reads generated in both the presence and absence of a background matrix. In the presence of bovine DNA, the sequenced data were successfully mapped to the NCBI lambda reference genome. Furthermore, the workflow from pre-extracted DNA to target identification took less than 3 h, demonstrating the potential of long-read sequencing in food safety as a rapid method for screening, identification, and quantification.

Relevance of genetic causes and environmental adaptation of Cronobacter spp. isolated from infant and follow-up formula production factories and retailed products in China: A 7-year period of continuous surveillance based on genome-wide analysis

The possible contamination routes, environmental adaptation, and genetic basis of Cronobacter spp. in infant and follow-up formula production factories and retailed products in mainland China have been determined by laboratory studies and whole-genome comparative analysis in a 7-year nationwide continuous surveillance spanning from 2012 to 2018. The 2-year continuous multicenter surveillance of the production process (conducted in 2013 and 2014) revealed that the source of Cronobacter spp. in the dry-blending process was the raw dry ingredients and manufacturing environment (particularly in the vibro sieve and vacuum cleaner), while in the combined process, the main contamination source was identified as the packing room. It is important to note that, according to the contamination control knowledge obtained from the production process surveillance, the contamination rate of retail powdered infant formula (PIF) and follow-up formula (FUF) products in China decreased significantly from 2016 onward, after improving the hygiene management practices in factories. The prevalence of Cronobacter spp. in retailed PIF and FUF in China in 2018 was dramatically reduced from 1.55 % (61/3925, in 2012) to an average as low as 0.17 % (13/7655 in 2018). Phenotype determination and genomic analysis were performed on a total of 90 Cronobacter spp. isolates obtained from the surveillance. Of the 90 isolates, only two showed resistance to either cefazolin or cefoxitin. The multilocus sequence typing results revealed that C. sakazakii sequence type 1 (ST1), ST37, and C. malonaticus ST7 were the dominant sequence types (STs) collected from the production factories, while C. sakazakii ST1, ST4, ST64, and ST8 were the main STs detected in the retailed PIF and FUF nationwide. One C. sakazakii ST4 isolate (1.1 %, 1/90) had strong biofilm-forming ability and 13 isolates (14.4 %, 13/90) had weak biofilm-forming ability. Genomic analysis revealed that Cronobacter spp. have a relatively stable core-genome and an increasing pan-genome size. Plasmid IncFIB (pCTU3) was prevalent in this genus and some contained 14 antibacterial biocide- and metal-resistance genes (BMRGs) including copper, silver, and arsenic resistant genes. Plasmid IncN_1 was predicted to contain 6 ARGs. This is the first time that a multi-drug resistance IncN_1 type plasmid has been reported in Cronobacter spp. Genomic variations with respect to BMRGs, virulence genes, antimicrobial resistance genes (ARGs), and genes involved in biofilm formation were observed among strains of this genus. There were apparent differences in copies of bcsG and flgJ between the biofilm-forming group and non-biofilm-forming group, indicating that these two genes play key roles in biofilm formation. The findings of this study have improved our understanding of the contamination characteristics and genetic basis of Cronobacter spp. in PIF and FUF and their production environment in China and provide important guidance to reduce contamination with this pathogen during the production of PIF and FUF.

Diarrheagenic Escherichia coli in Stool Specimens Collected from Patients Attending Primary Healthcare Facilities in Ethiopia: Whole-Genome Sequencing-Based Molecular Characterization

The diarrheagenic Escherichia coli (DEC) is the major cause of diarrheal diseases in Africa, including Ethiopia. However, the genetic diversity of E. coli pathotypes found in Ethiopia has not been studied well. This study aimed to characterize potential DEC belonging to enteropathogenic (EPEC), Shiga toxin-producing (STEC), enteroaggregative (EAEC), enterotoxigenic (ETEC), and enteroinvasive (EIEC) E. coli pathotypes from stool specimens of patients attending primary healthcare units (n = 260) in Addis Ababa and Hossana using whole-genome sequencing. Real-time PCR assays were used to identify DEC isolates belonging to EPEC, STEC, EAEC, ETEC, and EIEC pathotypes, which were then subjected to whole-genome sequencing on the Illumina platform. Twenty-four whole-genome nucleotide sequences of DEC strains with good enough quality were analyzed for virulence-associated genes (VAGs), antibiotic resistance genes (ARGs), phylogenetic groups, serogroups, and sequence types. The majority (62.5%) of DEC isolates belonged to the phylogenetic group B1. The identified DEC isolates belonged to 21 different serogroups and 17 different sequence types. All tested DEC isolates carried multiple VAGs and ARGs. The findings highlight the high diversity in the population structure of the studied DEC isolates, which is important for designing targeted interventions to reduce the diarrheal burden in Ethiopia.

The genetic relationship between human and pet isolates: a core genome multilocus sequence analysis of multidrug-resistant bacteria

INTRODUCTION

The global increase of multidrug-resistant organisms (MDROs) is one of the most urgent public health threats affecting both humans and animals. The One Health concept emphasizes the interconnectedness of human, animal and environmental health and highlights the need for integrated approaches to combat antimicrobial resistance (AMR). Although the sharing of environments and antimicrobial agents between companion animals and humans poses a risk for MDRO transmission, companion animals have been studied to a lesser extent than livestock animals. This study therefore used core genome multilocus sequence typing (cgMLST) to investigate the genetic relationships and putative transmission of MDROs between humans and pets.

METHODS

This descriptive integrated typing study included 252 human isolates, 53 dog isolates and 10 cat isolates collected from 2019 to 2022 at the Charité University Hospital in Berlin, Germany. CgMLST was performed to characterize methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci and multidrug-resistant gram-negative bacteria. The genetic diversity of the MDROs of the different host populations was determined and compared based on sequence type and core genome complex type.

RESULTS

Within this study the majority of samples from pets and humans was genetically distinct. However, for some isolates, the number of allelic differences identified by cgMLST was low. Two cases of putative household transmission or shared source of VR E. faecium and MDR E. coli between humans and pets were documented.

CONCLUSIONS

The interaction between humans and their pets appears to play a minor role in the spread of the MDROs studied. However, further research is needed. This study emphasizes the importance of comprehensive molecular surveillance and a multidisciplinary One Health approach to understand and contain the spread of MDROs in human and animal populations.

TRIAL REGISTRATION

The study is registered with the German Clinical Trials Register (DRKS00030009).

A molecular epidemiological and transmission analysis of Clostridioides difficile using draft whole-genome sequencing in a single hospital

BACKGROUND

The nosocomial transmission of toxin-producing Clostridioides difficile is a significant concern in infection control. C. difficile, which resides in human intestines, poses a risk of transmission, especially when patients are in close contact with medical staff.

METHODS

To investigate the nosocomial transmission of C. difficile in a single center, we analyzed the genetic relationships of the bacteria. This was done using draft whole-genome sequencing (WGS) and examining single nucleotide polymorphisms (SNPs) in core-genome, alongside data regarding the patient's hospital wards and room changes. Our retrospective analysis covered 38 strains, each isolated from a different patient, between April 2014 and January 2015.

RESULTS

We identified 38 strains that were divided into 11 sequence types (STs). ST81 was the most prevalent (n = 11), followed by ST183 (n = 10) and ST17 (n = 7). A cluster of strains that indicated suspected nosocomial transmission (SNT) was identified through SNP analysis. The draft WGS identified five clusters, with 16 of 38 strains belonging to these clusters. There were two clusters for ST81 (ST81-SNT-1 and ST81-SNT-2), two for ST183 (ST183-SNT-1 and ST183-SNT-2), and one for ST17 (ST17-SNT-1). ST183-SNT-1 was the largest SNT cluster, encompassing five patients who were associated with Wards A, B, and K. The most frequent room changer was a patient labeled Pt08, who changed rooms seven times in Ward B. Patients Pt36 and Pt10, who were also in Ward B, had multiple admissions and discharges during the study period.

CONCLUSIONS

Additional culture tests and SNP analysis of C. difficile using draft WGS revealed silent transmission within the wards, particularly in cases involving frequent room changes and repeated admissions and discharges. Monitoring C. difficile transmission using WGS-based analysis could serve as a valuable marker in infection control management.

Use of whole genome sequencing for surveillance and control of foodborne diseases: status quo and quo vadis

Improvements in sequencing quality, availability, speed and costs results in an increased presence of genomics in infectious disease applications. Nevertheless, there are still hurdles in regard to the optimal use of WGS for public health purposes. Here, we discuss the current state ("status quo") and future directions ("quo vadis") based on literature regarding the use of genomics in surveillance, hazard characterization and source attribution of foodborne pathogens. The future directions include the application of new techniques, such as machine learning and network approaches that may overcome the current shortcomings. These include the use of fixed genomic distances in cluster delineation, disentangling similarity or lack thereof in source attribution, and difficulties ascertaining function in hazard characterization. Although, the aforementioned methods can relatively easily be applied technically, an overarching challenge is the inference and biological/epidemiological interpretation of these large amounts of high-resolution data. Understanding the context in terms of bacterial isolate and host diversity allows to assess the level of representativeness in regard to sources and isolates in the dataset, which in turn defines the level of certainty associated with defining clusters, sources and risks. This also marks the importance of metadata (clinical, epidemiological, and biological) when using genomics for public health purposes.

Whole Genome Sequence Analysis of Brucella spp. from Human, Livestock, and Wildlife in South Africa

Brucellosis is an economically important zoonotic disease affecting humans, livestock, and wildlife health globally and especially in Africa. Brucella abortus and B. melitensis have been isolated from human, livestock (cattle and goat), and wildlife (sable) in South Africa (SA) but with little knowledge of the population genomic structure of this pathogen in SA. As whole genome sequencing can assist to differentiate and trace the origin of outbreaks of Brucella spp. strains, the whole genomes of retrospective isolates (n = 19) from previous studies were sequenced. Sequences were analysed using average nucleotide identity (ANI), pangenomics, and whole genome single nucleotide polymorphism (wgSNP) to trace the geographical origin of cases of brucellosis circulating in human, cattle, goats, and sable from different provinces in SA. Pangenomics analysis of B. melitensis (n = 69) and B. abortus (n = 56) was conducted with 19 strains that included B. abortus from cattle (n = 3) and B. melitensis from a human (n = 1), cattle (n = 1), goat (n = 1), Rev1 vaccine strain (n = 1), and sable (n = 12). Pangenomics analysis of B. melitensis genomes, highlighted shared genes, that include 10 hypothetical proteins and genes that encodes for acetyl-coenzyme A synthetase (acs), and acylamidase (aam) amongst the sable genomes. The wgSNP analysis confirmed the B. melitensis isolated from human was more closely related to the goat from the Western Cape Province from the same outbreak than the B. melitensis cattle sample from different cases in the Gauteng Province. The B. melitensis sable strains could be distinguished from the African lineage, constituting their own African sub-clade. The sequenced B. abortus strains clustered in the C2 lineage that is closely related to the isolates from Mozambique and Zimbabwe. This study identified genetically diverse Brucella spp. among various hosts in SA. This study expands the limited known knowledge regarding the presence of B. melitensis in livestock and humans in SA, further building a foundation for future research on the distribution of the Brucella spp. worldwide and its evolutionary background.

Outbreak detection in Harar town and Kersa district, Ethiopia using phylogenetic analysis and source attribution

BACKGROUND

Foodborne diseases (FBDs) represent a significant risk to public health, with nearly one in ten people falling ill every year globally. The large incidence of foodborne diseases in African low- and middle-income countries (LMIC) shows the immediate need for action, but there is still far to a robust and efficient outbreak detection system. The detection of outbreak heavily relies on clinical diagnosis, which are often delayed or ignored due to resource limitations and inadequate surveillance systems.

METHODS

In total, 68 samples of non-typhoidal Salmonella isolates from human, animal and environmental sources collected between November 2021 and January 2023 were analyzed using sequencing methods to infer phylogenetic relationships between the samples. A source attribution model using a machine-learning logit-boost that predicted the likely source of infection for 20 cases of human salmonellosis was also run and compared with the results of the cluster detection.

RESULTS

Three clusters of samples with close relation (SNP difference < 30) were identified as non-typhoidal Salmonella in Harar town and Kersa district, Ethiopia. These three clusters were comprised of isolates from different sources, including at least two human isolates. The isolates within each cluster showed identical serovar and sequence type (ST), with few exceptions in cluster 3. The close proximity of the samples suggested the occurrence of three potential outbreaks of non-typhoidal Salmonella in the region. The results of the source attribution model found that human cases of salmonellosis could primarily be attributed to bovine meat, which the results of the phylogenetic analysis corroborated.

CONCLUSIONS

The findings of this study suggested the occurrence of three possible outbreaks of non-typhoidal Salmonella in eastern Ethiopia, emphasizing the importance of targeted intervention of food safety protocols in LMICs. It also highlighted the potential of integrated surveillance for detecting outbreak and identifying the most probable source. Source attribution models in combination with other epidemiological methods is recommended as part of a more robust and integrated surveillance system for foodborne diseases.

Average Nucleotide Identity and Digital DNA-DNA Hybridization Analysis Following PromethION Nanopore-Based Whole Genome Sequencing Allows for Accurate Prokaryotic Typing

Whole-genome sequencing (WGS) is revolutionizing clinical bacteriology. However, bacterial typing remains investigated by reference techniques with inherent limitations. This stresses the need for alternative methods providing robust and accurate sequence type (ST) classification. This study optimized and evaluated a GridION nanopore sequencing protocol, adapted for the PromethION platform. Forty-eight Escherichia coli clinical isolates with diverse STs were sequenced to assess two alternative typing methods and resistance profiling applications. Multi-locus sequence typing (MLST) was used as the reference typing method. Genomic relatedness was assessed using Average Nucleotide Identity (ANI) and digital DNA-DNA Hybridization (DDH), and cut-offs for discriminative strain resolution were evaluated. WGS-based antibiotic resistance prediction was compared to reference Minimum Inhibitory Concentration (MIC) assays. We found ANI and DDH cut-offs of 99.3% and 94.1%, respectively, which correlated well with MLST classifications and demonstrated potentially higher discriminative resolution than MLST. WGS-based antibiotic resistance prediction showed categorical agreements of ≥ 93% with MIC assays for amoxicillin, ceftazidime, amikacin, tobramycin, and trimethoprim-sulfamethoxazole. Performance was suboptimal (68.8-81.3%) for amoxicillin-clavulanic acid, cefepime, aztreonam, and ciprofloxacin. A minimal sequencing coverage of 12× was required to maintain essential genomic features and typing accuracy. Our protocol allows the integration of PromethION technology in clinical laboratories, with ANI and DDH proving to be accurate and robust alternative typing methods, potentially offering superior resolution. WGS-based antibiotic resistance prediction holds promise for specific antibiotic classes.

Development and implementation of a core genome multilocus sequence typing scheme for Yersinia enterocolitica: a tool for surveillance and outbreak detection

Yersinia enterocolitica (Y. enterocolitica) is the most frequent etiological agent of yersiniosis and has been responsible for several national outbreaks in Norway and elsewhere. A standardized high-resolution method, such as core genome Multilocus Sequence Typing (cgMLST), is needed for pathogen traceability at the national and international levels. In this study, we developed and implemented a cgMLST scheme for Y. enterocolitica. We designed a cgMLST scheme in SeqSphere + using high-quality genomes from different Y. enterocolitica biotype sublineages. The scheme was validated if more than 95% of targets were found across all tested Y. enterocolitica: 563 Norwegian genomes collected between 2012 and 2022 and 327 genomes from public data sets. We applied the scheme to known outbreaks to establish a threshold for identifying major complex types (CTs) based on the number of allelic differences. The final cgMLST scheme included 2,582 genes with a median of 97.9% (interquartile range 97.6%-98.8%) targets found across all tested genomes. Analysis of outbreaks identified all outbreak strains using single linkage clustering at four allelic differences. This threshold identified 311 unique CTs in Norway, of which CT18, CT12, and CT5 were identified as the most frequently associated with outbreaks. The cgMLST scheme showed a very good performance in typing Y. enterocolitica using diverse data sources and was able to identify outbreak clusters. We recommend the implementation of this scheme nationally and internationally to facilitate Y. enterocolitica surveillance and improve outbreak response in national and cross-border outbreaks.

Antimicrobial Resistance in Aquaculture: Risk Mitigation within the One Health Context

The application of antimicrobials in aquaculture primarily aims to prevent and treat bacterial infections in fish, but their inappropriate use may result in the emergence of zoonotic antibiotic-resistant bacteria and the subsequent transmission of resistant strains to humans via food consumption. The aquatic environment serves as a potential reservoir for resistant bacteria, providing an ideal breeding ground for development of antimicrobial resistance (AMR). The mutual inter-connection of intensive fish-farming systems with terrestrial environments, the food processing industry and human population creates pathways for the transmission of resistant bacteria, exacerbating the problem further. The aim of this study was to provide an overview of the most effective and available risk mitigation strategies to tackle AMR in aquaculture, based on the One Health (OH) concept. The stringent antimicrobial use guidelines, promoting disease control methods like enhanced farm biosecurity measures and vaccinations, alternatives to antibiotics (ABs) (prebiotics, probiotics, immunostimulants, essential oils (EOs), peptides and phage therapy), feeding practices, genetics, monitoring water quality, and improving wastewater treatment, rather than applying excessive use of antimicrobials, can effectively prevent the development of AMR and release of resistant bacteria into the environment and food. The contribution of the environment to AMR development traditionally receives less attention, and, therefore, environmental aspects should be included more prominently in OH efforts to predict, detect and prevent the risks to health. This is of particular importance for low and middle-income countries with a lack of integration of the national AMR action plans (NAPs) with the aquaculture-producing environment. Integrated control of AMR in fisheries based on the OH approach can contribute to substantial decrease in resistance, and such is the case in Asia, where in aquaculture, the percentage of antimicrobial compounds with resistance exceeding 50% (P50) decreased from 52% to 22% within the period of the previous two decades.

Virulence-associated genes in faecal and clinical Escherichia coli isolates cultured from broiler chickens in Australia

A healthy chicken's intestinal flora harbours a rich reservoir of Escherichia coli as part of the commensal microbiota. However, some strains, known as avian pathogenic E. coli (APEC), carry specific virulence genes (VGs) that enable them to invade and cause extraintestinal infections such as avian colibacillosis. Although several VG combinations have been identified, the pathogenic mechanisms associated with APEC are ill-defined. The current study screened a subset of 88 E. coli isolates selected from 237 pre-existing isolates obtained from commercial poultry flocks in Australia. The 88 isolates were selected based on their enterobacterial repetitive intergenic consensus (ERIC) and antimicrobial resistance (AMR) profiles and included 29 E. coli isolates cultured from chickens with colibacillosis (referred to as clinical E. coli or CEC) and 59 faecal E. coli (FEC) isolates cultured from clinically healthy chickens. The isolates were screened for the presence of 35 previously reported VGs. Of these, 34 were identified, with iucA not being detected. VGs focG, hlyA and sfa/foc were only detected in FEC isolates. Eight VGs had a prevalence of 90% or above in the CEC isolates. Specifically, astA (100%); feoB (96.6%); iutA, iss, ompT, iroN and hlyF (all 93.1%); and vat (89.7%). The prevalence of these were significantly lower in FEC isolates (astA 79.7%, feoB 77.9%, iutA 52.5%, iss 45.8%, ompT 50.9%, iroN 37.3%, hlyF 50.9% and vat 42.4%). The odds ratios that each of these eight VGs were more likely to be associated with CEC than FEC ranged from 7.8 to 21.9. These eight VGs may be used to better define APEC and diagnostically detect APEC in Australia. Further investigations are needed to identify the roles of these VGs in pathogenicity.

Shiga Toxin-Producing Escherichia coli Strains from Romania: A Whole Genome-Based Description

The zoonotic Shiga toxin-producing Escherichia coli (STEC) group is unanimously regarded as exceptionally hazardous for humans. This study aimed to provide a genomic perspective on the STEC recovered sporadically from humans and have a foundation of internationally comparable data. Fifty clinical STEC isolates, representing the culture-confirmed infections reported by the STEC Reference Laboratory between 2016 and 2023, were subjected to whole-genome sequencing (WGS) analysis and sequences were interpreted using both commercial and public free bioinformatics tools. The WGS analysis revealed a genetically diverse population of STEC dominated by non-O157 serogroups commonly reported in human STEC infections in the European Union. The O26:H11 strains of ST21 lineage played a major role in the clinical disease resulting in hospitalisation and cases of paediatric HUS in Romania surpassing the O157:H7 strains. The latter were all clade 7 and mostly ST1804. Notably, among the Romanian isolates was a stx2a-harbouring cryptic clade I strain associated with a HUS case, stx2f- and stx2e-positive strains, and hybrid strains displaying a mixture of intestinal and extraintestinal virulence genes were found. As a clearer picture emerges of the STEC strains responsible for infections in Romania, further surveillance efforts are needed to uncover their prevalence, sources, and reservoirs.

Closing the gap: Oxford Nanopore Technologies R10 sequencing allows comparable results to Illumina sequencing for SNP-based outbreak investigation of bacterial pathogens

Whole-genome sequencing has become the method of choice for bacterial outbreak investigation, with most clinical and public health laboratories currently routinely using short-read Illumina sequencing. Recently, long-read Oxford Nanopore Technologies (ONT) sequencing has gained prominence and may offer advantages over short-read sequencing, particularly with the recent introduction of the R10 chemistry, which promises much lower error rates than the R9 chemistry. However, limited information is available on its performance for bacterial single-nucleotide polymorphism (SNP)-based outbreak investigation. We present an open-source workflow, Prokaryotic Awesome variant Calling Utility (PACU) (https://github.com/BioinformaticsPlatformWIV-ISP/PACU), for constructing SNP phylogenies using Illumina and/or ONT R9/R10 sequencing data. The workflow was evaluated using outbreak data sets of Shiga toxin-producing Escherichia coli and Listeria monocytogenes by comparing ONT R9 and R10 with Illumina data. The performance of each sequencing technology was evaluated not only separately but also by integrating samples sequenced by different technologies/chemistries into the same phylogenomic analysis. Additionally, the minimum sequencing time required to obtain accurate phylogenetic results using nanopore sequencing was evaluated. PACU allowed accurate identification of outbreak clusters for both species using all technologies/chemistries, but ONT R9 results deviated slightly more from the Illumina results. ONT R10 results showed trends very similar to Illumina, and we found that integrating data sets sequenced by either Illumina or ONT R10 for different isolates into the same analysis produced stable and highly accurate phylogenomic results. The resulting phylogenies for these two outbreaks stabilized after ~20 hours of sequencing for ONT R9 and ~8 hours for ONT R10. This study provides a proof of concept for using ONT R10, either in isolation or in combination with Illumina, for rapid and accurate bacterial SNP-based outbreak investigation.

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers

Foodborne illnesses, particularly those caused by Salmonella enterica with its extensive array of over 2600 serovars, present a significant public health challenge. Therefore, prompt and precise identification of S. enterica serovars is essential for clinical relevance, which facilitates the understanding of S. enterica transmission routes and the determination of outbreak sources. Classical serotyping methods via molecular subtyping and genomic markers currently suffer from various limitations, such as labour intensiveness, time consumption, etc. Therefore, there is a pressing need to develop new diagnostic techniques. Surface-enhanced Raman spectroscopy (SERS) is a non-invasive diagnostic technique that can generate Raman spectra, based on which rapid and accurate discrimination of bacterial pathogens could be achieved. To generate SERS spectra, a Raman spectrometer is needed to detect and collect signals, which are divided into two types: the expensive benchtop spectrometer and the inexpensive handheld spectrometer. In this study, we compared the performance of two Raman spectrometers to discriminate four closely associated S. enterica serovars, that is, S. enterica subsp. enterica serovar dublin, enteritidis, typhi and typhimurium. Six machine learning algorithms were applied to analyse these SERS spectra. The support vector machine (SVM) model showed the highest accuracy for both handheld (99.97%) and benchtop (99.38%) Raman spectrometers. This study demonstrated that handheld Raman spectrometers achieved similar prediction accuracy as benchtop spectrometers when combined with machine learning models, providing an effective solution for rapid, accurate and cost-effective identification of closely associated S. enterica serovars.

Antimicrobial resistance and genomic investigation of Salmonella isolated from retail foods in Guizhou, China

Introduction

Salmonella is a major foodborne pathogen worldwide that causes severe morbidity and mortality. It is mainly caused by consuming contaminated food, with retail food considered the primary source.

Methods

In Guizhou, China, 102 Salmonella strains isolated from 2016 to 2021 underwent phenotypic antimicrobial resistance testing and whole-genome sequencing (WGS) to understand Salmonella diversity, including serotypes, sequencing types (STs), antimicrobial genes, virulence genes, plasmid types, multi-locus sequence types (MLST), and core genome MLST (cgMLST).

Results and discussion

S.Typhimurium was the dominant serotype, and O:4(B) was the leading serogroup. The most prevalent genotype was ST40. Phenotypic antimicrobial resistance identified 66.7% of the sampled isolates as multi-drug resistant (MDR). S.Enteritidis (n = 7), S.Typhimurium (n = 1), S.Indiana (n = 1), S.Kentucky (n = 1), S.Uganda (n = 1), all of which were MDR, were resistant to Colistin. Resistance rates varied significantly across different strains and food types, particularly meat products exhibiting higher resistance. Notably, significant increases in resistance were observed from 2016 to 2021 for the following: ≥ 1 resistant (P = 0.001), MDR (P = 0.001), ampicillin (P = 0.001), tetracycline (P < 0.001), chloramphenicol (P = 0.030), and trimethoprim/sulfamethoxazole (P = 0.003). The marked escalation in drug resistance over the recent years, coupled with the varying resistance rates among food sources, underscores the growing public health concern. Our findings highlight the need for a coordinated approach to effectively monitor and respond to Salmonella infections in Guizhou, China.

Metagenomic sequencing sheds light on microbes putatively associated with pneumonia-related fatalities of white-tailed deer (Odocoileus virginianus)

With emerging infectious disease outbreaks in human, domestic and wild animal populations on the rise, improvements in pathogen characterization and surveillance are paramount for the protection of human and animal health, as well as the conservation of ecologically and economically important wildlife. Genomics offers a range of suitable tools to meet these goals, with metagenomic sequencing facilitating the characterization of whole microbial communities associated with emerging and endemic disease outbreaks. Here, we use metagenomic sequencing in a case-control study to identify microbes in lung tissue associated with newly observed pneumonia-related fatalities in 34 white-tailed deer (Odocoileus virginianus) in Wisconsin, USA. We identified 20 bacterial species that occurred in more than a single individual. Of these, only Clostridium novyi was found to substantially differ (in number of detections) between case and control sample groups; however, this difference was not statistically significant. We also detected several bacterial species associated with pneumonia and/or other diseases in ruminants (Mycoplasma ovipneumoniae, Trueperella pyogenes, Pasteurella multocida, Anaplasma phagocytophilum, Fusobacterium necrophorum); however, these species did not substantially differ between case and control sample groups. On average, we detected a larger number of bacterial species in case samples than controls, supporting the potential role of polymicrobial infections in this system. Importantly, we did not detect DNA of viruses or fungi, suggesting that they are not significantly associated with pneumonia in this system. Together, these results highlight the utility of metagenomic sequencing for identifying disease-associated microbes. This preliminary list of microbes will help inform future research on pneumonia-associated fatalities of white-tailed deer.

Whole Genome Sequencing: Applications in Clinical Bacteriology

The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.

A comprehensive technology strategy for microbial identification and contamination investigation in the sterile drug manufacturing facility-a case study

Objective

A comprehensive strategy for microbial identification and contamination investigation during sterile drug manufacturing was innovatively established in this study, mainly based on MALDI-TOF MS for the identification and complemented by sequencing technology on strain typing.

Methods

It was implemented to monitor the bacterial contamination of a sterile drug manufacturing facility, including its bacterial distribution features and patterns. In three months, two hundred ninety-two samples were collected covering multiple critical components of raw materials, personnel, environment, and production water.

Results

Based on our strategy, the bacterial profile across the production process was determined: 241/292 bacterial identities were obtained, and Staphylococcus spp. (40.25%), Micrococcus spp.(11.20%), Bacillus spp. (8.30%), Actinobacteria (5.81%), and Paenibacillus spp. (4.56%) are shown to be the most dominant microbial contaminants. With 75.8% species-level and 95.4% genus-level identification capability, MALDI-TOF MS was promising to be a first-line tool for environmental monitoring routine. Furthermore, to determine the source of the most frequently occurring Staphylococcus cohnii, which evidenced a widespread presence in the entire process, a more discriminating S. cohnii whole-genome SNP typing method was developed to track the transmission routes. Phylogenetic analysis based on SNP results indicated critical environment contamination is highly relevant to personnel flow in this case. The strain typing results provide robust and accurate information for the following risk assessment step and support effective preventive and corrective measures.

Conclusion

In general, the strategy presented in this research will facilitate the development of improved production and environmental control processes for the pharmaceutical industry, and give insights about how to provide more sound and reliable evidence for the optimization of its control program.

Comparative genomics of Brucella abortus and Brucella melitensis unravels the gene sharing, virulence factors and SNP diversity among the standard, vaccine and field strains

Brucella abortus and Brucella melitensis are the primary etiological agents of brucellosis in large and small ruminants, respectively. There are limited comparative genomic studies involving Brucella strains that explore the relatedness among both species. In this study, we involved strains (n=44) representing standard, vaccine and Indian field origin for pangenome, single nucleotide polymorphism (SNP) and phylogenetic analysis. Both species shared a common gene pool representing 2884 genes out of a total 3244 genes. SNP-based phylogenetic analysis indicated higher SNP diversity among B. melitensis (3824) strains in comparison to B. abortus (540) strains, and a clear demarcation was identified between standard/vaccine and field strains. The analysis for virulence genes revealed that virB3, virB7, ricA, virB5, ipx5, wbkC, wbkB, and acpXL genes were highly conserved in most of the Brucella strains. Interestingly, virB10 gene was found to have high variability among the B. abortus strains. The cgMLST analysis revealed distinct sequence types for the standard/vaccine and field strains. B. abortus strains from north-eastern India fall within similar sequence type differing from other strains. In conclusion, the analysis revealed a highly shared core genome among two Brucella species. SNP analysis revealed B. melitensis strains exhibit high diversity as compared to B. abortus strains. Strains with absence or high polymorphism of virulence genes can be exploited for the development of novel vaccine candidates effective against both B. abortus and B. melitensis.

Tracking the footsteps of Burkholderia mallei: determination of the molecular differences and potential resistance genes

Background/aim

Chemical biological radiological nuclear threats are at an important point in the agenda of world health today, as they can cause mass deaths. B. mallei attracts attention as a potential biological warfare agent due to its features such as multidrug resistance, a rapid transmission mechanism via aerosol, the absence of a complete treatment protocol for the infection it causes, and the absence of an approved vaccine for protection against the bacteria. B. mallei suspect samples must be studied by experienced personnel in biosafety level III laboratories. B mallei is a difficult and troublesome pathogen to diagnose and many unknowns about B. mallei today. Therefore, the aim of the study was to determine the molecular differences and potential resistance genes of B mallei strains.

Materials and methods

Determination of the molecular differences and potential resistance genes of B mallei strains with new bioinformatics approaches by comparatively examining the data of 29 B mallei strains, 10 of which were isolated from Türkiye, on the genome list of the National Biotechnology Information Center (NCBI).

Results

According to the genome annotations of the origins, the origin containing the highest number of CDS which is 5172 was found as the 11th strain obtained in Türkiye in 1949. The origin with the highest number of pseudogenes was determined as 23,344 (China 7) origin. Two hundred and eighty-five pseudogenes found in this strain were obtained from a knee effusion in Myanmar. According to chromosome 2 data, B. mallei strain was determined as the most similar strain to ATCC 23344, line 11 with NCTC 10229 strain, and SAVP1 strain was determined as the least similar strain. When the antimicrobial resistance gene markers of the isolates included in the study were examined, amrA and amrB, qacG ade, Burkholderia pseudomallei Omp38 were found to be carrying.

Conclusion

In terms of public health, it was thought that the data obtained as a result of our study about B mallei, which is defined as a biological weapon, is very valuable for creating treatment protocols to be applied to possible epidemics in the future. In addition, the available genetic epidemiological data of these strains belonging to a category that is dangerous to work with in a laboratory environment were reviewed.

Core-genome multilocus sequence typing and core-SNP analysis of Clostridium neonatale strains isolated in different spatio-temporal settings

IMPORTANCE

Clostridium neonatale has been isolated from the fecal samples of asymptomatic neonates and cases of necrotizing enterocolitis (NEC). Taking advantage of a large collection of independent strains isolated from different spatio-temporal settings, we developed and established a cgMLST scheme for the molecular typing of C. neonatale. Both the cgMLST and cgSNP methods demonstrate comparable discrimination power. Results indicate geographic- and temporal- independent clustering of C. neonatale NEC-associated strains. No specific cgMLST clade of C. neonatale was genetically associated with NEC.

Whole-genome sequencing of carbapenem-resistant Enterobacterales isolates in southeast Louisiana reveals persistent genetic clusters spanning multiple locations

BACKGROUND

We investigated 51 g-negative carbapenem-resistant Enterobacterales (CRE) isolates collected from 22 patients over a five-year period from six health care institutions in the Ochsner Health network in southeast Louisiana.

METHODS

Short genomic reads were generated using Illumina sequencing and assembled for each isolate. Isolates were classified as Enterobacter spp. (n = 20), Klebsiella spp. (n = 30), and Escherichia coli (n = 1) and grouped into 19 different multi-locus sequence types (MLST). Species and patient-specific core genomes were constructed representing ∼50% of the chromosomal genome.

RESULTS

We identified two sets of patients with genetically related infections; in both cases, the related isolates were collected > 6 months apart, and in one case, the isolates were collected in different locations. On the other hand, we identified four sets of patients with isolates of the same species collected within 21 days from the same location; however, none had genetically related infections. Genes associated with resistance to carbapenem drugs (blaKPC and/or blaCTX-M-15) were found in 76% of the isolates. We found three blaKPC variants (blaKPC-2, blaKPC-3, and blaKPC-4) associated with four different Enterobacter MLST variants, and two blaKPC variants (blaKPC-2, blaKPC-3) associated with seven different Klebsiella MLST variants.

CONCLUSIONS

Molecular surveillance is increasingly becoming a powerful tool to understand bacterial spread in both community and clinical settings. This study provides evidence that genetically related infections in clinical settings do not necessarily reflect temporal associations, and vice versa. Our results also highlight the regional genomic and resistance diversity within related bacterial lineages.

A core-genome multilocus sequence typing scheme for the detection of genetically related Streptococcus pyogenes clusters

The recently observed increase in invasive Streptococcus pyogenes infections causes concern in Europe. However, conventional molecular typing methods lack discriminatory power to aid investigations of outbreaks caused by S. pyogenes. Therefore, there is an urgent need for high-resolution molecular typing methods to assess genetic relatedness between S. pyogenes isolates. In the current study, we aimed to develop a novel high-resolution core-genome multilocus sequence typing (cgMLST) scheme for S. pyogenes and compared its discriminatory power to conventional molecular typing methods. The cgMLST scheme was designed with the commercial Ridom SeqSphere+ software package. To define a cluster threshold, the scheme was evaluated using publicly available data from nine defined S. pyogenes outbreaks in the United Kingdom. The cgMLST scheme was then applied to 23 isolates from a suspected S. pyogenes outbreak and 117 S. pyogenes surveillance isolates both from the Netherlands. MLST and emm-typing results were used for comparison to cgMLST results. The allelic differences between isolates from defined outbreaks ranged between 6 and 31 for isolates with the same emm-type, resulting in a proposed cluster threshold of <5 allelic differences out of 1,095 target loci. Seven out of twenty-three (30%) isolates from the suspected outbreak had an allelic difference of <2, thereby identifying a potential cluster that could not be linked to other isolates. The proposed cgMLST scheme shows a higher discriminatory ability when compared to conventional typing methods. The rapid and simple analysis workflow allows for extended detection of clusters of potential outbreak isolates and surveillance and may facilitate the sharing of sequencing results between (inter)national laboratories.

Genomic Diversity, Antimicrobial Resistance, Plasmidome, and Virulence Profiles of Salmonella Isolated from Small Specialty Crop Farms Revealed by Whole-Genome Sequencing

Salmonella is the leading cause of death associated with foodborne illnesses in the USA. Difficulty in treating human salmonellosis is attributed to the development of antimicrobial resistance and the pathogenicity of Salmonella strains. Therefore, it is important to study the genetic landscape of Salmonella, such as the diversity, plasmids, and presence antimicrobial resistance genes (AMRs) and virulence genes. To this end, we isolated Salmonella from environmental samples from small specialty crop farms (SSCFs) in Northeast Ohio from 2016 to 2021; 80 Salmonella isolates from 29 Salmonella-positive samples were subjected to whole-genome sequencing (WGS). In silico serotyping revealed the presence of 15 serotypes. AMR genes were detected in 15% of the samples, with 75% exhibiting phenotypic and genotypic multidrug resistance (MDR). Plasmid analysis demonstrated the presence of nine different types of plasmids, and 75% of AMR genes were located on plasmids. Interestingly, five Salmonella Newport isolates and one Salmonella Dublin isolate carried the ACSSuT gene cassette on a plasmid, which confers resistance to ampicillin, chloramphenicol, streptomycin, sulfonamide, and tetracycline. Overall, our results show that SSCFs are a potential reservoir of Salmonella with MDR genes. Thus, regular monitoring is needed to prevent the transmission of MDR Salmonella from SSCFs to humans.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

Bifidobacterium longum subsp. iuvenis subsp. nov., a novel subspecies isolated from the faeces of weaning infants

The species Bifidobacterium longum currently comprises four subspecies: B. longum subsp. longum , B. longum subsp. infantis , B. longum subsp. suis and B. longum subsp. suillum . Recently, several studies on B. longum suggested the presence of a separate clade containing four strains isolated from infants and one from rhesus macaque. These strains shared a phylogenetic similarity to B. longum subsp. suis DSM 20210T and B. longum subsp. suillum JCM1995T [average nucleotide identity (ANI) of 98.1 %) while showed an ANI of 96.5 % with both B. longum subsp. infantis and B. longum subsp. longum . The current work describes five novel additional B. longum strains isolated from Bangladeshi weaning infants and demonstrates their common phylogenetic origin with those of the previously proposed separated clade. Based on polyphasic taxonomic approach comprising loci multilocus sequence analysis and whole genome multilocus sequence typing, all ten examined strains have been confirmed as a distinct lineage within the species B. longum with B. longum subsp. suis and B. longum subsp. suillum as closest subspecies. Interestingly, these strains are present in weaning infants and primates as opposed to their closest relatives which have been typically isolated from pig and calves. These strains, similarly to B. longum subsp. infantis , show a common capacity to metabolize the human milk oligosaccharide 3-fucosyllactose. Moreover, they harbour a riboflavin synthesis operon, which differentiate them from their closest subspecies, B. longum subsp. suis and B. longum subsp. suillum . Based on the consistent results from genotypical, ecological and phenotypical analyses, a novel subspecies with the name Bifidobacterium longum subsp. iuvenis, with type strain NCC 5000T (=LMG 32752T=CCOS 2034T), is proposed.

Evaluation of whole and core genome multilocus sequence typing allele schemes for Salmonella enterica outbreak detection in a national surveillance network, PulseNet USA

Salmonella enterica is a leading cause of bacterial foodborne and zoonotic illnesses in the United States. For this study, we applied four different whole genome sequencing (WGS)-based subtyping methods: high quality single-nucleotide polymorphism (hqSNP) analysis, whole genome multilocus sequence typing using either all loci [wgMLST (all loci)] and only chromosome-associated loci [wgMLST (chrom)], and core genome multilocus sequence typing (cgMLST) to a dataset of isolate sequences from 9 well-characterized Salmonella outbreaks. For each outbreak, we evaluated the genomic and epidemiologic concordance between hqSNP and allele-based methods. We first compared pairwise genomic differences using all four methods. We observed discrepancies in allele difference ranges when using wgMLST (all loci), likely caused by inflated genetic variation due to loci found on plasmids and/or other mobile genetic elements in the accessory genome. Therefore, we excluded wgMLST (all loci) results from any further comparisons in the study. Then, we created linear regression models and phylogenetic tanglegrams using the remaining three methods. K-means analysis using the silhouette method was applied to compare the ability of the three methods to partition outbreak and sporadic isolate sequences. Our results showed that pairwise hqSNP differences had high concordance with cgMLST and wgMLST (chrom) allele differences. The slopes of the regressions for hqSNP vs. allele pairwise differences were 0.58 (cgMLST) and 0.74 [wgMLST (chrom)], and the slope of the regression was 0.77 for cgMLST vs. wgMLST (chrom) pairwise differences. Tanglegrams showed high clustering concordance between methods using two statistical measures, the Baker's gamma index (BGI) and cophenetic correlation coefficient (CCC), where 9/9 (100%) of outbreaks yielded BGI values ≥ 0.60 and CCCs were ≥ 0.97 across all nine outbreaks and all three methods. K-means analysis showed separation of outbreak and sporadic isolate groups with average silhouette widths ≥ 0.87 for outbreak groups and ≥ 0.16 for sporadic groups. This study demonstrates that Salmonella isolates clustered in concordance with epidemiologic data using three WGS-based subtyping methods and supports using cgMLST as the primary method for national surveillance of Salmonella outbreak clusters.

Monitoring within-farm transmission dynamics of antimicrobial-resistant Campylobacter in dairy cattle using broth microdilution and long-read whole genome sequencing

Campylobacter jejuni and Campylobacter coli are important foodborne zoonotic pathogens and cause for concern due to the increasing trend in antimicrobial resistance. A long-run surveillance study was conducted in animals from different age groups in five dairy cattle farms to investigate the within-farm diversity and transmission dynamics of resistant Campylobacter throughout time. The resistance phenotype of the circulating isolates (170 C. jejuni and 37 C. coli) was determined by broth microdilution and a selection of 56 isolates were whole genome sequenced using the Oxford-Nanopore long-fragment sequencing technology resulting in completely resolved and circularized genomes (both chromosomes and plasmids). C. jejuni was isolated from all farms while C. coli was isolated from only two farms, but resistance rates were higher in C. coli than in C. jejuni and in calves than in adult animals. Some genotypes (e.g. ST-48, gyrA_T86I/tet(O)/blaOXA-61 in farm F1; ST-12000, aadE-Cc/tet(O)/blaOXA-489 in F4) persisted throughout the study while others were only sporadically detected. Acquisition of extracellular genes from other isolates and intracellular mutational events were identified as the processes that led to the emergence of the resistant genotypes that spread within the herds. Monitoring with Oxford Nanopore Technologies sequencing helped to decipher the complex molecular epidemiology underlying the within-farm dissemination of resistant Campylobacter.

Genomic and Antimicrobial Surveillance of Campylobacter Population in Italian Poultry

Campylobacter is one of the most common foodborne diseases worldwide with increasing rates of antibiotic resistance. Most cases of campylobacteriosis can be traced back to the consumption of poultry meat. Despite many efforts to reduce contamination in farms and in slaughterhouses, the persistence of this pathogen in poultry products remains a problem. This study aimed to evaluate the genetic diversity and antibiotic resistance of 542 C. jejuni and C. coli in Italian poultry, in the framework of two National Monitoring Programs. Genomes were screened for antibiotic resistance, virulence determinants and contextualized within a global collection of C. jejuni. ST2116, ST2863 and ST 832 were the most prevalent and significantly associated with Italian poultry. A worrying increase in resistance to quinolones, fluoroquinolones and tetracycline was observed in C. jejuni, while an increased occurrence of multidrug resistant (MDR) strains and strains resistant to macrolides was detected in C. coli. Low resistance rates were found for aminoglycosides. Molecular resistance determinants were consistent with the phenotypic resistance for tetracycline and quinolones. In silico analysis revealed 119 genes associated with virulence factors, with a notably higher prevalence of some genes in ST2863 genomes. This study highlights the increased resistance to macrolides and the emergence of MDR strains for C. coli, the genetic basis of AMR and the predominance of two genotypes among Campylobacter strains isolated from the Italian poultry farms.

Update on Commonly Used Molecular Typing Methods for Clostridioides difficile

This review aims to provide a comprehensive overview of the significant Clostridioides difficile molecular typing techniques currently employed in research and medical communities. The main objectives of this review are to describe the key molecular typing methods utilized in C. difficile studies and to highlight the epidemiological characteristics of the most prevalent strains on a global scale. Geographically distinct regions exhibit distinct strain types of C. difficile, with notable concordance observed among various typing methodologies. The advantages that next-generation sequencing (NGS) offers has changed epidemiology research, enabling high-resolution genomic analyses of this pathogen. NGS platforms offer an unprecedented opportunity to explore the genetic intricacies and evolutionary trajectories of C. difficile strains. It is relevant to acknowledge that novel routes of transmission are continually being unveiled and warrant further investigation, particularly in the context of zoonotic implications and environmental contamination.

Core genome multilocus sequence typing scheme for Bacillus cereus group bacteria

Core genome multilocus sequence typing (cgMLST) employs a strategy where the set of orthologous genes common to all members of a group of organisms are used for phylogenetic analysis of the group members. The Bacillus cereus group consists of species with pathogenicity towards insect species as well as warm-blooded animals including humans. While B. cereus is an opportunistic pathogen linked to a range of human disease conditions, including emesis and diarrhoea, Bacillus thuringiensis is an entomopathogenic species with toxicity toward insect larvae, and therefore used as a biological pesticide worldwide. Bacillus anthracis is a classical obligate pathogen causing anthrax, an acute lethal condition in herbivores as well as humans, and which is endemic in many parts of the world. The group also includes a range of additional species, and B. cereus group bacteria have been subject to analysis with a wide variety of phylogenetic typing systems. Here we present, based on analyses of 173 complete genomes from B. cereus group species available in public databases, the identification of a set of 1568 core genes which were used to create a core genome multilocus typing scheme for the group which is implemented in the PubMLST system as an open online database freely available to the community. The new cgMLST system provides unprecedented resolution over existing phylogenetic analysis schemes covering the B. cereus group.

Whole Genome Sequencing for Studying Helicobacter pylori Antimicrobial Resistance

Antibiotic resistance (AMR) is an alarming concern worldwide and Helicobacter pylori, one of the most prevalent bacteria, is not an exception. With antibiotics being its primary therapy, increasing resistance leads to a higher rate of treatment failure. Understanding the genomic mechanisms of resistance to clarithromycin, levofloxacin, metronidazole, amoxicillin, tetracycline, and rifampicin through next-generation sequencing-based molecular tools, such as whole genome sequencing (WGS), can be of great value, not only to direct a patient's treatment, but also to establish and optimize treatment guidelines according to the local epidemiology and to avoid the use of inappropriate antibiotics. WGS approaches allow us to gain insight into the genomic determinants involved in AMR. To this end, different pipelines and platforms are continuously being developed. In this study, we take a more detailed view of the use and progression of WGS for in-depth study of H. pylori's AMR.