Evaluation of SNP calling methods for closely related bacterial isolates and a novel high-accuracy pipeline: BactSNP

Combination therapy delays antimicrobial resistance after adaptive laboratory evolution of Staphylococcus aureus

Antibiotic resistance, driven by misuse and overuse of antibiotics, is one of the greatest threats against human health. The antimicrobial pressure during prolonged antibiotic treatment of chronic bacterial infections selects for resistance. While antibiotic combinations may reduce resistance emergence, antibiotic-tolerant persister cells can serve as a reservoir for resistance development. Therefore, targeting these cells with anti-persister drugs might provide a novel strategy for resistance prevention. In this study, we conducted 42 days of adaptive laboratory evolution using Staphylococcus aureus exposed to rifampicin, ciprofloxacin, daptomycin, and vancomycin, alone or in combination with the anti-persister drug mitomycin C. We monitored antibiotic susceptibility daily and assessed phenotypic changes in growth and biofilm formation in evolved strains. Whole-genome sequencing revealed mutations linked to antibiotic resistance and phenotypic shifts. Rifampicin resistance developed within a few days, while ciprofloxacin and daptomycin emerged in approximately 3 weeks. Treatments with vancomycin or mitomycin C resulted in minimal changes in susceptibility. While combination therapy delayed resistance, it did not fully prevent it. Notably, the combination of rifampicin with mitomycin C maintained rifampicin susceptibility throughout the long-term evolution experiment. Sub-inhibitory antibiotic treatments selected for both previously characterized and novel mutations, including unprecedented alterations in the nucleotide excision repair system and azoreductase following mitomycin C exposure. The delayed resistance development observed with combination therapy, particularly mitomycin C's ability to suppress rifampicin resistance, suggests potential therapeutic applications. Future studies should evaluate the clinical efficacy of anti-persister drugs in preventing resistance across different bacterial pathogens and infection models.

One day in Denmark: whole-genome sequence-based analysis of Escherichia coli isolates from clinical settings

BACKGROUND

WGS can potentially be routinely used in clinical microbiology settings, especially with the increase in sequencing accuracy and decrease in cost. Escherichia coli is the most common bacterial species analysed in those settings, thus fast and accurate diagnostics can lead to reductions in morbidity, mortality and healthcare costs.

OBJECTIVES

To evaluate WGS for diagnostics and surveillance in a collection of clinical E. coli; to examine the pool of antimicrobial resistance (AMR) determinants circulating in Denmark and the most frequent STs; and to evaluate core-genome MLST (cgMLST) and SNP-based clustering approaches for detecting genetically related isolates.

METHODS

We analysed the genomes of 699 E. coli isolates collected throughout all Danish Clinical Microbiology Laboratories. We used rMLST and KmerFinder for species identification, ResFinder for prediction of AMR, and PlasmidFinder for plasmid identification. We used Center for Genomic Epidemiology MLST, cgMLSTFinder and CSI Phylogeny to perform typing and clustering analysis.

RESULTS

Genetic AMR determinants were detected in 56.2% of isolates. We identified 182 MLSTs, most frequently ST-69, ST-73, ST-95 and ST-131. Using a maximum 15-allele difference as the threshold for genetic relatedness, we identified 23 clusters. SNP-based phylogenetic analysis within clusters revealed from 0 to 13 SNPs, except two cases with 111 and 461 SNPs.

CONCLUSIONS

WGS data are useful to characterize clinical E. coli isolates, including predicting AMR profiles and subtyping in concordance with surveillance data. We have shown that it is possible to adequately cluster isolates through a cgMLST approach, but it remains necessary to define proper interpretative criteria.

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).

Genomic and pathogenicity analyses to identify the causative agent from multiple serogroups of non-O1, non-O139 Vibrio cholerae in foodborne outbreaks

In 2013, foodborne outbreaks in Japan were linked to non-O1, non-O139 Vibrio cholerae. However, laboratory tests have detected several serogroups, making it difficult to determine the causative agent. Therefore, whole-genome analyses revealed that only serogroup O144 V. cholerae possesses a genomic island with a type III secretion system (T3SS). A T3SS-deficient mutant was subsequently generated, and its pathogenicity was assessed using a rabbit ileal loop test. This led to the conclusion that serogroup O144 V. cholerae with T3SS was the causative agent of foodborne outbreaks. This study provides an illustrative example of the utilization of whole-genome data for pathogenicity and molecular epidemiological analyses in outbreak investigations.

Investigation of an Outbreak of Clostridium perfringens in Toyama, Japan, 2023 Using Single-Nucleotide Polymorphism Analysis for Genotyping

Clostridium perfringens, which produces C. perfringens enterotoxin (CPE), is a major cause of food poisoning because of its gastrointestinal toxicity. In outbreaks of C. perfringens, genotyping is important for identifying the source. We genotyped strains isolated from an outbreak of food poisoning in Toyama Prefecture in 2023, using single-nucleotide polymorphism (SNP) analysis. The strains of C. perfringens were isolated from samples of curry consumed by all the affected patients and from the feces of patients and staff worker. The enterotoxin gene (cpe) was detected in isolates from patients and curry samples. The cpe-negative isolates were found in patients who had consumed curry and in the staff worker. The results of the SNP analysis suggested that the patient and curry isolates were likely from the same source but were unlikely to be related to the staff isolates. The results of SNP and pulsed-field gel electrophoresis (PFGE) analyses were consistent, indicating that the patient and curry isolates originated from the same source. SNP analysis, a whole-genome-based genotyping method, is a promising alternative to traditional PFGE for investigating outbreaks. Further studies are needed to accumulate more experience with genotyping using SNP analysis for the epidemiological investigation of outbreaks of C. perfringens.

Whole genome sequences of nine Taylorella equigenitalis strains isolated in the Czech Republic between 1982-2021: Molecular dating suggests a common ancestor at the time of Roman Empire

Taylorella equigenitalis is the causative agent of sexually transmitted contagious equine metritis. Infections manifest as cervicitis, vaginitis and endometritis and cause temporary infertility and miscarriages of mares. While previous studies have analyzed this organism for various parameters, the evolutionary dynamics of this pathogen, including the emergence of antibiotic resistance, remains unresolved. The aim of this study was to isolate contemporary strains, determine their genome sequences, evaluate their antibiotic resistance and compare them with other strains. We determined nine complete whole genome sequences of T. equigenitalis strains, mainly from samples collected from Kladruber horses in the Czech Republic. While T. equigenitalis strains from Kladruby isolated between 1982 and 2018 were inhibited by streptomycin, contemporary strains were found to be resistant to streptomycin, suggesting the recent emergence of this mutation. In addition, we used the collection dates of Kladruber horse strains to estimate the genome substitution rate, which resulted in a scaled mean evolutionary rate of 6.9×10-7 substitutions per site per year. Analysis with other available T. equigenitalis genome sequences (n = 18) revealed similarity of the Czech T. equigenitalis genomes with the Austrian T. equigenitalis genome, and molecular dating suggested a common ancestor of all analyzed T. equigenitalis strains from 1.5-2.6 thousand years ago, dating to the first centuries A.D. Our study revealed a recently emerged streptomycin resistance in T. equigenitalis strains from Kladruber horses, emphasizing the need for antibiotic surveillance and alternative treatments. Additionally, our findings provided insights into the pathogen's evolution rate, which is important for understanding its evolution and preparing preventive strategies.

Seamless, rapid, and accurate analyses of outbreak genomic data using split k-mer analysis

Sequence variation observed in populations of pathogens can be used for important public health and evolutionary genomic analyses, especially outbreak analysis and transmission reconstruction. Identifying this variation is typically achieved by aligning sequence reads to a reference genome, but this approach is susceptible to reference biases and requires careful filtering of called genotypes. There is a need for tools that can process this growing volume of bacterial genome data, providing rapid results, but that remain simple so they can be used without highly trained bioinformaticians, expensive data analysis, and long-term storage and processing of large files. Here we describe split k-mer analysis (SKA2), a method that supports both reference-free and reference-based mapping to quickly and accurately genotype populations of bacteria using sequencing reads or genome assemblies. SKA2 is highly accurate for closely related samples, and in outbreak simulations, we show superior variant recall compared with reference-based methods, with no false positives. SKA2 can also accurately map variants to a reference and be used with recombination detection methods to rapidly reconstruct vertical evolutionary history. SKA2 is many times faster than comparable methods and can be used to add new genomes to an existing call set, allowing sequential use without the need to reanalyze entire collections. With an inherent absence of reference bias, high accuracy, and a robust implementation, SKA2 has the potential to become the tool of choice for genotyping bacteria. SKA2 is implemented in Rust and is freely available as open-source software.

Molecular typing methods to characterize Brucella spp. from animals: A review

Brucellosis is an infectious disease of animals that can infect humans. The disease causes significant economic losses and threatens human health. A timely and accurate disease diagnosis plays a vital role in the identification of brucellosis. In addition to traditional diagnostic methods, molecular methods allow diagnosis and typing of the causative agent of brucellosis. This review will discuss various methods, such as Bruce-ladder, Suiladder, high-resolution melt analysis, restriction fragment length polymorphism, multilocus sequence typing, multilocus variable-number tandem repeat analysis, and whole-genome sequencing single-nucleotide polymorphism, for the molecular typing of Brucella and discuss their advantages and disadvantages.

Mobile genetic element-driven genomic changes in a community-associated methicillin-resistant Staphylococcus aureus clone during its transmission in a regional community outbreak in Japan

Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) infections are now a public health concern in both community and healthcare settings worldwide. We previously identified a suspected case of a maternity clinic-centred outbreak of CA-MRSA skin infection in a regional community in Japan by PFGE-based analysis. In this study, we performed genome sequence-based analyses of 151 CA-MRSA isolates, which included not only outbreak-related isolates that we previously defined based on identical or similar PFGE patterns but also other isolates obtained during the same period in the same region. Our analysis accurately defined 133 isolates as outbreak-related isolates, collectively called the TDC clone. They belonged to a CA-MRSA lineage in clonal complex (CC) 30, known as the South West Pacific (SWP) clone. A high-resolution phylogenetic analysis of these isolates combined with their epidemiological data revealed that the TDC clone was already present and circulating in the region before the outbreak was recognized, and only the isolates belonging to two sublineages (named SL4 and SL5) were directly involved in the outbreak. Long persistence in patients/carriers and frequent intrahousehold transmission of the TDC clone were also revealed by this analysis. Moreover, by systematic analyses of the genome changes that occurred in this CA-MRSA clone during transmission in the community, we revealed that most variations were associated with mobile genetic elements (MGEs). Variant PFGE types were generated by alterations of prophages and genomic islands or insertion sequence (IS)-mediated insertion of a plasmid or a sequence of unknown origin. Dynamic changes in plasmid content, which were linked to changes in antimicrobial resistance profiles in specific isolates, were generated by frequent gain and loss of plasmids, most of which were self-transmissible or mobilizable. The introduction of IS256 by a plasmid (named pTDC02) into sublineage SL5 led to SL5-specific amplification of IS256, and amplified IS256 copies were involved in some of the structural changes of chromosomes and plasmids and generated variations in the repertoire of virulence-related genes in limited isolates. These data revealed how CA-MRSA genomes change during transmission in the community and how MGEs are involved in this process.

Increased resistance against tellurite is conferred by a mutation in the promoter region of uncommon tellurite resistance gene tehB in the ter-negative Shiga toxin-producing Escherichia coli O157:H7

Resistance to potassium tellurite (PT) is an important indicator in isolating Shiga toxin-producing Escherichia coli (STEC) O157:H7 and other major STEC serogroups. Common resistance determinant genes are encoded in the ter gene cluster. We found an O157:H7 isolate that does not harbor ter but is resistant to PT. One nonsynonymous mutation was found in another PT resistance gene, tehA, through whole-genome sequence analyses. To elucidate the contribution of this mutation to PT resistance, complementation of tehA and the related gene tehB in isogenic strains and quantitative RT‒PCR were performed. The results indicated that the point mutation not only changed an amino acid of tehA, but also was positioned on a putative internal promoter of tehB and increased PT resistance by elevating tehB mRNA expression. Meanwhile, the amino acid change in tehA had negligible impact on the PT resistance. Comprehensive screening revealed that 2.3% of O157:H7 isolates in Japan did not harbor the ter gene cluster, but the same mutation in tehA was not found. These results suggested that PT resistance in E. coli can be enhanced through one mutational event even in ter-negative strains.

IMPORTANCE

Selective agents are important for isolating Shiga toxin-producing Escherichia coli (STEC) because the undesirable growth of microflora should be inhibited. Potassium tellurite (PT) is a common selective agent for major STEC serotypes. In this study, we found a novel variant of PT resistance genes, tehAB, in STEC O157:H7. Molecular experiments clearly showed that one point mutation in a predicted internal promoter region of tehB upregulated the expression of the gene and consequently led to increased resistance to PT. Because tehAB genes are ubiquitous across E. coli, these results provide universal insight into PT resistance in this species.

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.

Synthetic phage-based approach for sensitive and specific detection of Escherichia coli O157

Escherichia coli O157 can cause foodborne outbreaks, with infection leading to severe disease such as hemolytic-uremic syndrome. Although phage-based detection methods for E. coli O157 are being explored, research on their specificity with clinical isolates is lacking. Here, we describe an in vitro assembly-based synthesis of vB_Eco4M-7, an O157 antigen-specific phage with a 68-kb genome, and its use as a proof of concept for E. coli O157 detection. Linking the detection tag to the C-terminus of the tail fiber protein, gp27 produces the greatest detection sensitivity of the 20 insertions sites tested. The constructed phage detects all 53 diverse clinical isolates of E. coli O157, clearly distinguishing them from 35 clinical isolates of non-O157 Shiga toxin-producing E. coli. Our efficient phage synthesis methods can be applied to other pathogenic bacteria for a variety of applications, including phage-based detection and phage therapy.

Combined usage of serodiagnosis and O antigen typing to isolate Shiga toxin-producing Escherichia coli O76:H7 from a hemolytic uremic syndrome case and genomic insights from the isolate

IMPORTANCE

Hemolytic uremic syndrome (HUS) is a life-threatening disease caused by Shiga toxin-producing Escherichia coli (STEC) infection. The treatment approaches for STEC-mediated typical HUS and atypical HUS differ, underscoring the importance of rapid and accurate diagnosis. However, specific detection methods for STECs other than major serogroups, such as O157, O26, and O111, are limited. This study focuses on the utility of PCR-based O-serotyping, serum agglutination tests utilizing antibodies against the identified Og type, and isolation techniques employing antibody-conjugated immunomagnetic beads for STEC isolation. By employing these methods, we successfully isolated a STEC strain of a minor serotype, O76:H7, from a HUS patient.

Comparison of Crohn's disease-associated adherent-invasive Escherichia coli (AIEC) from France and Hong Kong: results from the Pacific study

Association between ileal colonization by Adherent-Invasive Escherichia coli (AIEC) and Crohn's disease (CD) has been widely described in high-incidence Western countries but remains unexplored in Asian countries with a fast increase in CD incidence. In the PACIFIC study, we compared the characteristics of AIEC pathobionts retrieved from ileal biopsies of CD patients enrolled in France (FR) and Hong Kong (HK). The prevalence of AIEC was similar in France (24.5%, 25/102) and Hong Kong (30.0%, 18/60) (p = 0.44). No difference was observed between the two populations of AIEC regarding adhesion and invasion levels. When tested for antibiotic resistance, the proportion of AIEC strains resistant to ampicillin, piperacillin, tobramycin, and gentamicin was significantly higher in HK AIEC strains compared to French strains. AIEC strains from FR or HK population were both able to persist in the mice intestine (DSS-treated CEABAC10 mice model). Moreover, genomic analysis of 25 FR and 17 hK AIEC strains using next-generation sequencing revealed the co-existence of several virulence factors associated with enteric E. coli pathotypes, although no single virulence factor was significantly associated with either country of origin or AIEC status. In vitro, all AIEC strains (FR and HK) were sensitive to the EcoActive™ phage cocktail, suggesting that it could be a promising option to target AIEC in CD across the world.

Rheinheimera oceanensis sp. nov., a novel member of the genus Rheinheimera, isolated from the West Pacific Ocean

Two Gram-stain-negative, aerobic, non-motile and short-rod-shaped bacteria, designated as strains GL-53T and GL-15-2-5, were isolated from the seamount area of the West Pacific Ocean and identified using a polyphasic taxonomic approach. The growth of strains GL-53ᵀ and GL-15-2-5 occurred at pH 5.5-10.0, 4-40 °C (optimum at 28 °C) and 0-10.0 % NaCl concentrations (optimum at 0-5.0 %). On the basis of 16S rRNA gene sequence analysis, strains GL-53ᵀ and GL-15-2-5 exhibited the highest similarity to Rheinheimera lutimaris YQF-2T (98.4 %), followed by Rheinheimera pacifica KMM 1406T (98.1 %), Rheinheimera nanhaiensis E407-8T (97.4 %), Rheinheimera aestuarii H29T (97.4 %), Rheinheimera hassiensis E48T (97.2 %) and Rheinheimera aquimaris SW-353T (97.2 %). Phylogenetic analysis revealed that the isolates were affiliated with the genus Rheinheimera and represented an independent lineage. The major fatty acids were summed feature 3 (C16 : 1  ω7c and/or C16 : 1  ω6c), C16 : 0 and summed feature 8 (C18 : 1  ω7c and/or C18 : 1  ω6c). The sole isoprenoid quinone was ubiquinone 8. The major polar lipids were phosphatidylethanolamine, phosphatidylglycerol, one unidentified aminophospholipid (and one unidentified glycolipid. The DNA G+C content was 48.5 mol%. The average nucleotide identity, average amino acid identity and in silico DNA-DNA hybridization values among the genomes of strain GL-53ᵀ and the related strains in the genus Rheinheimera were 75.5-90.1 %, 67.5-93.9 % and 21.4-41.4 %, respectively. Based on their phenotypic, chemotaxonomic and genotypic properties, the two strains were identified as representing a novel species of the genus Rheinheimera, for which the name Rheinheimera oceanensis sp. nov. is proposed. The type strain is GL-53T (=KCTC 82651T=MCCC M20598T).

Atypical diarrhoeagenic Escherichia coli in milk related to a large foodborne outbreak

A foodborne outbreak related to milk cartons served in school lunches occurred in June 2021, which involved more than 1,800 cases from 25 schools. The major symptoms were abdominal pain, diarrhoea, vomiting, and fever. Although major foodborne toxins and pathogens were not detected, a specific Escherichia coli strain, serotype OUT (OgGp9):H18, was predominantly isolated from milk samples related to the outbreak and most patients tested. The strains from milk and patient stool samples were identified as the same clone by core genome multilocus sequence typing and single-nucleotide polymorphism analysis. The strain was detected in milk samples served for two days related to the foodborne outbreak at a rate of 69.6% and levels of less than ten most probable number/100 mL but not on days unrelated to the outbreak. The acid tolerance of the strain for survival in the stomach was similar to that of enterohaemorrhagic E. coli O157:H7, and the same inserts in the chu gene cluster in the acid fitness island were genetically revealed. The pathogenicity of the strain was not clear; however, it was indicated that the causative pathogen was atypical diarrhoeagenic E. coli OUT (OgGp9):H18.

In Silico Evaluation of Variant Calling Methods for Bacterial Whole-Genome Sequencing Assays

Identification and analysis of clinically relevant strains of bacteria increasingly relies on whole-genome sequencing. The downstream bioinformatics steps necessary for calling variants from short-read sequences are well-established but seldom validated against haploid genomes. We devised an in silico workflow to introduce single nucleotide polymorphisms (SNP) and indels into bacterial reference genomes, and computationally generate sequencing reads based on the mutated genomes. We then applied the method to Mycobacterium tuberculosis H37Rv, Staphylococcus aureus NCTC 8325, and Klebsiella pneumoniae HS11286, and used the synthetic reads as truth sets for evaluating several popular variant callers. Insertions proved especially challenging for most variant callers to correctly identify, relative to deletions and single nucleotide polymorphisms. With adequate read depth, however, variant callers that use high quality soft-clipped reads and base mismatches to perform local realignment consistently had the highest precision and recall in identifying insertions and deletions ranging from1 to 50 bp. The remaining variant callers had lower recall values associated with identification of insertions greater than 20 bp.

Molecular characterization and comparative genomic analysis of Acinetobacter baumannii isolated from the community and the hospital: an epidemiological study in Segamat, Malaysia

Acinetobacter baumannii is a common cause of multidrug-resistant (MDR) nosocomial infections around the world. However, little is known about the persistence and dynamics of A. baumannii in a healthy community. This study investigated the role of the community as a prospective reservoir for A. baumannii and explored possible links between hospital and community isolates. A total of 12 independent A. baumannii strains were isolated from human faecal samples from the community in Segamat, Malaysia, in 2018 and 2019. Another 15 were obtained in 2020 from patients at the co-located tertiary public hospital. The antimicrobial resistance profile and biofilm formation ability were analysed, and the relatedness of community and hospital isolates was determined using whole-genome sequencing (WGS). Antibiotic profile analysis revealed that 12 out of 15 hospital isolates were MDR, but none of the community isolates were MDR. However, phylogenetic analysis based on single-nucleotide polymorphisms (SNPs) and a pangenome analysis of core genes showed clustering between four community and two hospital strains. Such clustering of strains from two different settings based on their genomes suggests that these strains could persist in both. WGS revealed 41 potential resistance genes on average in the hospital strains, but fewer (n=32) were detected in the community strains. In contrast, 68 virulence genes were commonly seen in strains from both sources. This study highlights the possible transmission threat to public health posed by virulent A. baumannii present in the gut of asymptomatic individuals in the community.

Alteration of a Shiga toxin-encoding phage associated with a change in toxin production level and disease severity in Escherichia coli

Among the nine clades of Shiga toxin (Stx)-producing Escherichia coli O157:H7, clade 8 is thought to be highly pathogenic, as it causes severe disease more often than other clades. Two subclades have been proposed, but there are conflicting reports on intersubclade differences in Stx2 levels, although Stx2 production is a risk factor for severe disease development. The global population structure of clade 8 has also yet to be fully elucidated. Here, we present genome analyses of a global clade 8 strain set (n =510), including 147 Japanese strains sequenced in this study. The complete genome sequences of 18 of the 147 strains were determined to perform detailed clade-wide genome analyses together with 17 publicly available closed genomes. Intraclade variations in Stx2 production level and disease severity were also re-evaluated within the phylogenetic context. Based on phylogenomic analysis, clade 8 was divided into four lineages corresponding to the previously proposed SNP genotypes (SGs): SG8_30, SG8_31A, SG8_31B and SG8_32. SG8_30 and the common ancestor of the other SGs were first separated, with SG8_31A and SG8_31B emerging from the latter and SG8_32 emerging from SG8_31B. Comparison of 35 closed genomes revealed the overall structure of chromosomes and pO157 virulence plasmids and the prophage contents to be well conserved. However, Stx2a phages exhibit notable genomic diversity, even though all are integrated into the argW locus, indicating that subtype changes in Stx2a phage occurred from the γ subtype to its variant (γ_v1) in SG8_31A and from γ to δ in SG8_31B and SG8_32 via replacement of parts or almost entire phage genomes, respectively. We further show that SG8_30 strains (all carrying γ Stx2a phages) produce significantly higher levels of Stx2 and cause severe disease more frequently than SG8_32 strains (all carrying δ Stx2a phages). Clear conclusions on SG8_31A and SG8_31B cannot be made due to the small number of strains available, but as SG8_31A (carrying γ_v1 Stx2a phages) contains strains that produce much more Stx2 than SG8_30 strains, attention should also be paid to this SG.

Genetic characteristics of azithromycin-resistant Neisseria gonorrhoeae collected in Hyogo, Japan during 2015-2019

Introduction. Azithromycin (AZM) is a therapeutic drug for sexually transmitted infections and is used for Neisseria gonorrhoeae when first- and second-line drugs are not available. Recently, the susceptibility of N. gonorrhoeae against AZM has been decreasing worldwide.Hypothesis/Gap Statement. Azithromycin-resistance (AZM-R) rates among N. gonorrhoeae in Japan are increasing, and the gene mutations and epidemiological characteristics of AZM-R in N. gonorrhoeae have not been fully investigated.Aim. We determined the susceptibility to AZM and its correlation with genetic characteristics of N. gonorrhoeae.Methodology. We investigated the susceptibility to AZM and genetic characteristics of N. gonorrhoeae. Mutations in domain V of the 23S rRNA gene and mtrR were examined in 93 isolates, including 13 AZM-R isolates. Spread and clonality were examined using sequence types (STs) of multi-antigen sequence typing for N. gonorrhoeae (NG-MAST), and whole genome analysis (WGA) to identify single nucleotide polymorphisms.Results. The number of AZM-R isolates increased gradually from 2015 to 2019 in Hyogo (P=0.008). C2599T mutations in 23S rRNA significantly increased in AZM-R isolates (P<0.001). NG-MAST ST4207 and ST6762 were frequently detected in AZM-R isolates, and they had higher MICs to AZM from 6 to 24 µg/ml. The phylogenic tree-based WGA showed that all isolates with ST4207 were contained in the same clade, and isolates with ST6762 were divided into two clades, AZM-S isolates and AZM-R isolates, which were different from the cluster containing ST1407.Conclusion. Our study showed yearly increases in AZM-R rates in N. gonorrhoeae. NG-MAST ST4207 and ST6762 were not detected in our previous study in 2015 and were frequently identified in isolates with higher MICs to AZM. WGA confirmed that isolates with these STs are closely related to each other. Continued surveillance is needed to detect the emergence and confirm the spread of NG-MAST ST4207 and ST6762.

Invasion and diversity in Pseudomonas aeruginosa urinary tract infections

Introduction.P. aeruginosa is an opportunistic Gram-negative pathogen frequently isolated in urinary tract infections (UTI) affecting elderly and catheterized patients and associated with ineffective antibiotic treatment and poor clinical outcomes.

Gap statement. Invasion has been shown to play an important role in UTI caused by E. coli but has only recently been studied with P. aeruginosa. The ability of P. aeruginosa to adapt and evolve in chronic lung infections is associated with resistance to antibiotics but has rarely been studied in P. aeruginosa UTI populations.

Aim. We sought to determine whether phenotypic and genotypic heterogeneity exists in P. aeruginosa UTI isolates and whether, like urinary pathogenic Escherichia coli, these could invade human bladder epithelial cells – two factors that could complicate antibiotic treatment.

Methodology.P. aeruginosa UTI samples were obtained from five elderly patients at the Royal Liverpool University Hospital as part of routine diagnostics. Fourty isolates from each patient sample were screened for a range of phenotypes. The most phenotypically diverse isolates were genome sequenced. Gentamicin protection assays and confocal microscopy were used to determine capacity to invade bladder epithelial cells.

Results. Despite significant within-patient phenotypic differences, no UTI patient was colonized by distinct strains of P. aeruginosa. Limited genotypic differences were identified in the form of non-synonymous SNPs. Gentamicin protection assays and confocal microscopy provided evidence of P. aeruginosa’s ability to invade bladder epithelial cells.

Conclusions. Phenotypic variation and cell invasion could further complicate antibiotic treatment in some patients. More work is needed to better understand P. aeruginosa UTI pathogenesis and develop more effective treatment strategies.

Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel

Hierarchical genotyping approaches can provide insights into the source, geography and temporal distribution of bacterial pathogens. Multiple hierarchical SNP genotyping schemes have previously been developed so that new isolates can rapidly be placed within pre-computed population structures, without the need to rebuild phylogenetic trees for the entire dataset. This classification approach has, however, seen limited uptake in routine public health settings due to analytical complexity and the lack of standardized tools that provide clear and easy ways to interpret results. The BioHansel tool was developed to provide an organism-agnostic tool for hierarchical SNP-based genotyping. The tool identifies split k-mers that distinguish predefined lineages in whole genome sequencing (WGS) data using SNP-based genotyping schemes. BioHansel uses the Aho-Corasick algorithm to type isolates from assembled genomes or raw read sequence data in a matter of seconds, with limited computational resources. This makes BioHansel ideal for use by public health agencies that rely on WGS methods for surveillance of bacterial pathogens. Genotyping results are evaluated using a quality assurance module which identifies problematic samples, such as low-quality or contaminated datasets. Using existing hierarchical SNP schemes for Mycobacterium tuberculosis and Salmonella Typhi, we compare the genotyping results obtained with the k-mer-based tools BioHansel and SKA, with those of the organism-specific tools TBProfiler and genotyphi, which use gold-standard reference-mapping approaches. We show that the genotyping results are fully concordant across these different methods, and that the k-mer-based tools are significantly faster. We also test the ability of the BioHansel quality assurance module to detect intra-lineage contamination and demonstrate that it is effective, even in populations with low genetic diversity. We demonstrate the scalability of the tool using a dataset of ~8100 S. Typhi public genomes and provide the aggregated results of geographical distributions as part of the tool’s output. BioHansel is an open source Python 3 application available on PyPI and Conda repositories and as a Galaxy tool from the public Galaxy Toolshed. In a public health context, BioHansel enables rapid and high-resolution classification of bacterial pathogens with low genetic diversity.

Host Colonization as a Major Evolutionary Force Favoring the Diversity and the Emergence of the Worldwide Multidrug-Resistant Escherichia coli ST131

The emergence of multidrug-resistant Escherichia coli ST131 is a major worldwide public health problem in humans. According to the “one health” approach, this study investigated animal reservoirs of ST131, their relationships with human strains, and the genetic features associated with host colonization. High-quality genomes originating from human, avian, and canine hosts were classified on the basis of their accessory gene content using pangenomic. Pangenomic clusters and subclusters were specifically and significantly associated with hosts. The functions of clustering accessory genes were mainly enriched in functions involved in DNA acquisition, interactions, and virulence (e.g., pathogenesis, response to biotic stimulus and interaction between organisms). Accordingly, networks of cooccurrent host interaction factors were significantly associated with the pangenomic clusters and the originating hosts. The avian strains exhibited a specific content in virulence factors. Rarely found in humans, they corresponded to pathovars responsible for severe human infections. An emerging subcluster significantly associated with both human and canine hosts was evidenced. This ability to significantly colonize canine hosts in addition to humans was associated with a specific content in virulence factors (VFs) and metabolic functions encoded by a new pathogenicity island in ST131 and an improved fitness that is probably involved in its emergence. Overall, VF content, unlike the determinants of antimicrobial resistance, appeared as a key actor of bacterial host adaptation. The host dimension emerges as a major driver of genetic evolution that shapes ST131 genome, enhances its diversity, and favors its dissemination.

Generalizable characteristics of false-positive bacterial variant calls

Minimizing false positives is a critical issue when variant calling as no method is without error. It is common practice to post-process a variant-call file (VCF) using hard filter criteria intended to discriminate true-positive (TP) from false-positive (FP) calls. These are applied on the simple principle that certain characteristics are disproportionately represented among the set of FP calls and that a user-chosen threshold can maximize the number detected. To provide guidance on this issue, this study empirically characterized all false SNP and indel calls made using real Illumina sequencing data from six disparate species and 166 variant-calling pipelines (the combination of 14 read aligners with up to 13 different variant callers, plus four ‘all-in-one’ pipelines). We did not seek to optimize filter thresholds but instead to draw attention to those filters of greatest efficacy and the pipelines to which they may most usefully be applied. In this respect, this study acts as a coda to our previous benchmarking evaluation of bacterial variant callers, and provides general recommendations for effective practice. The results suggest that, of the pipelines analysed in this study, the most straightforward way of minimizing false positives would simply be to use Snippy. We also find that a disproportionate number of false calls, irrespective of the variant-calling pipeline, are located in the vicinity of indels, and highlight this as an issue for future development.

Whole-Genome Sequencing of Shiga Toxin-Producing Escherichia coli OX18 from a Fatal Hemolytic Uremic Syndrome Case

We report a fatal case of hemolytic uremic syndrome with urinary tract infection in Japan caused by Shiga toxin–producing Escherichia coli. We genotypically identified the isolate as OX18:H2. Whole-genome sequencing revealed 3 potentially pathogenic lineages (OX18:H2, H19, and H34) that have been continuously isolated in Japan.

Platanus_B: an accurate de novo assembler for bacterial genomes using an iterative error-removal process

De novo assembly of short DNA reads remains an essential technology, especially for large-scale projects and high-resolution variant analyses in epidemiology. However, the existing tools often lack sufficient accuracy required to compare closely related strains. To facilitate such studies on bacterial genomes, we developed Platanus_B, a de novo assembler that employs iterations of multiple error-removal algorithms. The benchmarks demonstrated the superior accuracy and high contiguity of Platanus_B, in addition to its ability to enhance the hybrid assembly of both short and nanopore long reads. Although the hybrid strategies for short and long reads were effective in achieving near full-length genomes, we found that short-read-only assemblies generated with Platanus_B were sufficient to obtain ≥90% of exact coding sequences in most cases. In addition, while nanopore long-read-only assemblies lacked fine-scale accuracies, inclusion of short reads was effective in improving the accuracies. Platanus_B can, therefore, be used for comprehensive genomic surveillances of bacterial pathogens and high-resolution phylogenomic analyses of a wide range of bacteria.

A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches

The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of >99% for all assays, except for spoligotyping, where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and nonprofit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.

Molecular and serological epidemiology of Leptospira infection in cats in Okinawa Island, Japan

Leptospirosis is a zoonosis caused by pathogenic Leptospira spp. Cats have been reported to be infected with Leptospira spp. and shed the bacteria in the urine. However, the importance of cats as an infection source for humans remains unclear. In this study, Leptospira infection in cats in Okinawa Prefecture, Japan, where leptospirosis is endemic, was investigated by leptospiral antibody and DNA detection using microscopic agglutination test and nested PCR, respectively. Moreover, multilocus sequence typing (MLST) and whole genome sequencing (WGS) were conducted on the Leptospira borgpetersenii serogroup Javanica isolated from cats, black rats, a mongoose, and humans. Anti-Leptospira antibodies were detected in 16.6% (40/241) of the cats tested, and the predominant reactive serogroup was Javanica. The leptospiral flaB gene was detected in 7.1% (3/42) of cat urine samples, and their sequences were identical and identified as L. borgpetersenii. MLST and WGS revealed the genetic relatedness of L. borgpetersenii serogroup Javanica isolates. This study indicated that most seropositive cats had antibodies against the serogroup Javanica and that cats excreted L. borgpetersenii in the urine after infection. Further, genetic relatedness between cat and human isolates suggests that cats may be a maintenance host for L. borgpetersenii serogroup Javanica and a source for human infection.

A Benchmark of Genetic Variant Calling Pipelines Using Metagenomic Short-Read Sequencing

Microbes live in complex communities that are of major importance for environmental ecology, public health, and animal physiology and pathology. Short-read metagenomic shotgun sequencing is currently the state-of-the-art technique for exploring these communities. With the aid of metagenomics, our understanding of the microbiome is moving from composition toward functionality, even down to the genetic variant level. While the exploration of single-nucleotide variation in a genome is a standard procedure in genomics, and many sophisticated tools exist to perform this task, identification of genetic variation in metagenomes remains challenging. Major factors that hamper the widespread application of variant-calling analysis include low-depth sequencing of individual genomes (which is especially significant for the microorganisms present in low abundance), the existence of large genomic variation even within the same species, the absence of comprehensive reference genomes, and the noise introduced by next-generation sequencing errors. Some bioinformatics tools, such as metaSNV or InStrain, have been created to identify genetic variants in metagenomes, but the performance of these tools has not been systematically assessed or compared with the variant callers commonly used on single or pooled genomes. In this study, we benchmark seven bioinformatic tools for genetic variant calling in metagenomics data and assess their performance. To do so, we simulated metagenomic reads to mimic human microbial composition, sequencing errors, and genetic variability. We also simulated different conditions, including low and high depth of coverage and unique or multiple strains per species. Our analysis of the simulated data shows that probabilistic method-based tools such as HaplotypeCaller and Mutect2 from the GATK toolset show the best performance. By applying these tools to longitudinal gut microbiome data from the Human Microbiome Project, we show that the genetic similarity between longitudinal samples from the same individuals is significantly greater than the similarity between samples from different individuals. Our benchmark shows that probabilistic tools can be used to call metagenomes, and we recommend the use of GATK's tools as reliable variant callers for metagenomic samples.

Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring

The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org .

Molecular and epidemiologic characterization of the diphtheria outbreak in Venezuela

In 2016, Venezuela faced a large diphtheria outbreak that extended until 2019. Nasopharyngeal or oropharyngeal samples were prospectively collected from 51 suspected cases and retrospective data from 348 clinical records was retrieved from 14 hospitals between November 2017 and November 2018. Confirmed pathogenic Corynebactrium isolates were biotyped. Multilocus Sequence Typing (MLST) was performed followed by next-generation-based core genome-MLST and minimum spanning trees were generated. Subjects between 10 and 19 years of age were mostly affected (n = 95; 27.3%). Case fatality rates (CFR) were higher in males (19.4%), as compared to females (15.8%). The highest CFR (31.1%) was observed among those under 5, followed by the 40 to 49 age-group (25.0%). Nine samples corresponded to C. diphtheriae and 1 to C. ulcerans. Two Sequencing Types (ST), ST174 and ST697 (the latter not previously described) were identified among the eight C. diphtheriae isolates from Carabobo state. Cg-MLST revealed only one cluster also from Carabobo. The Whole Genome Sequencing analysis revealed that the outbreak seemed to be caused by different strains with C. diphtheriae and C. ulcerans coexisting. The reemergence and length of this outbreak suggest vaccination coverage problems and an inadequate control strategy.

Whole Genome Sequencing Applied to Pathogen Source Tracking in Food Industry: Key Considerations for Robust Bioinformatics Data Analysis and Reliable Results Interpretation

Whole genome sequencing (WGS) has arisen as a powerful tool to perform pathogen source tracking in the food industry thanks to several developments in recent years. However, the cost associated to this technology and the degree of expertise required to accurately process and understand the data has limited its adoption at a wider scale. Additionally, the time needed to obtain actionable information is often seen as an impairment for the application and use of the information generated via WGS. Ongoing work towards standardization of wet lab including sequencing protocols, following guidelines from the regulatory authorities and international standardization efforts make the technology more and more accessible. However, data analysis and results interpretation guidelines are still subject to initiatives coming from distinct groups and institutions. There are multiple bioinformatics software and pipelines developed to handle such information. Nevertheless, little consensus exists on a standard way to process the data and interpret the results. Here, we want to present the constraints we face in an industrial setting and the steps we consider necessary to obtain high quality data, reproducible results and a robust interpretation of the obtained information. All of this, in a time frame allowing for data-driven actions supporting factories and their needs.

Two New Cases of Pulmonary Infection by Mycobacterium shigaense, Japan

We report 2 case-patients in Japan with Mycobacterium shigaense pulmonary infections. One patient was given aggressive treatment and the other conservative treatment, according to distinctive radiologic evidence. A close phylogenetic relationship based on whole-genome sequencing was found between strain from the conservatively treated patient and a reference strain of cutaneous origin.

Cereulide Synthetase Acquisition and Loss Events within the Evolutionary History of Group III Bacillus cereus Sensu Lato Facilitate the Transition between Emetic and Diarrheal Foodborne Pathogens

Cereulide-producing members of Bacillus cereussensu lato group III (also known as emetic B. cereus) possess cereulide synthetase, a plasmid-encoded, nonribosomal peptide synthetase encoded by the ces gene cluster. Despite the documented risks that cereulide-producing strains pose to public health, the level of genomic diversity encompassed by emetic B. cereus has never been evaluated at a whole-genome scale. Here, we employ a phylogenomic approach to characterize group III B. cereussensu lato genomes which possess ces (ces positive) alongside their closely related, ces-negative counterparts (i) to assess the genomic diversity encompassed by emetic B. cereus and (ii) to identify potential ces loss and/or gain events within the evolutionary history of the high-risk and medically relevant sequence type (ST) 26 lineage often associated with emetic foodborne illness. Using all publicly available ces-positive group III B. cereussensu lato genomes and the ces-negative genomes interspersed among them (n = 159), we show that emetic B. cereus is not clonal; rather, multiple lineages within group III harbor cereulide-producing strains, all of which share an ancestor incapable of producing cereulide (posterior probability = 0.86 to 0.89). Members of ST 26 share an ancestor that existed circa 1748 (95% highest posterior density [HPD] interval = 1246.89 to 1915.64) and first acquired the ability to produce cereulide before 1876 (95% HPD = 1641.43 to 1946.70). Within ST 26 alone, two subsequent ces gain events were observed, as well as three ces loss events, including among isolates responsible for B. cereussensu lato toxicoinfection (i.e., "diarrheal" illness).IMPORTANCEB. cereus is responsible for thousands of cases of foodborne disease each year worldwide, causing two distinct forms of illness: (i) intoxication via cereulide (i.e., emetic syndrome) or (ii) toxicoinfection via multiple enterotoxins (i.e., diarrheal syndrome). Here, we show that emetic B. cereus is not a clonal, homogenous unit that resulted from a single cereulide synthetase gain event followed by subsequent proliferation; rather, cereulide synthetase acquisition and loss is a dynamic, ongoing process that occurs across lineages, allowing some group III B. cereussensu lato populations to oscillate between diarrheal and emetic foodborne pathogens over the course of their evolutionary histories. We also highlight the care that must be taken when selecting a reference genome for whole-genome sequencing-based investigation of emetic B. cereussensu lato outbreaks, since some reference genome selections can lead to a confounding loss of resolution and potentially hinder epidemiological investigations.

Global distribution of epidemic-related Shiga toxin 2 encoding phages among enteroaggregative Escherichia coli

Since the Shiga toxin-producing enteroaggregative Escherichia coli (Stx-EAEC) O104:H4 strain caused a massive outbreak across Europe in 2011, the importance of Stx-EAEC has attracted attention from a public health perspective. Two Stx-EAEC O86 isolates were obtained from patients with severe symptoms in Japan in 1999 and 2015. To characterize the phylogeny and pathogenic potential of these Stx-EAEC O86 isolates, whole-genome sequence analyses were performed by short-and long-read sequencing. Among genetically diverse E. coli O86, the Stx-EAEC O86 isolates were clustered with the EAEC O86:H27 ST3570 subgroup. Strikingly, there were only two loci with single nucleotide polymorphisms (SNPs) between the Stx2a phage of a Japanese O86:H27 isolate and that of the European epidemic-related Stx-EAEC O104:H4 isolate. These results provide evidence of global distribution of epidemic-related Stx2a phages among various lineages of E. coli with few mutations.

Genome Comparison Identifies Different Bacillus Species in a Bast Fibre-Retting Bacterial Consortium and Provides Insights into Pectin Degrading Genes

Retting of bast fibres requires removal of pectin, hemicellulose and other non-cellulosic materials from plant stem tissues by a complex microbial community. A microbial retting consortium with high-efficiency pectinolytic bacterial strains is effective in reducing retting-time and enhancing fibre quality. We report comprehensive genomic analyses of three bacterial strains (PJRB 1, 2 and 3) of the consortium and resolve their taxonomic status, genomic features, variations, and pan-genome dynamics. The genome sizes of the strains are ~3.8 Mb with 3729 to 4002 protein-coding genes. Detailed annotations of the protein-coding genes revealed different carbohydrate-degrading CAZy classes viz. PL1, PL9, GH28, CE8, and CE12. Phylogeny and structural features of pectate lyase proteins of PJRB strains divulge their functional uniqueness and evolutionary convergence with closely related Bacillus strains. Genome-wide prediction of genomic variations revealed 12461 to 67381 SNPs, and notably many unique SNPs were localized within the important pectin metabolism genes. The variations in the pectate lyase genes possibly contribute to their specialized pectinolytic function during the retting process. These findings encompass a strong foundation for fundamental and evolutionary studies on this unique microbial degradation of decaying plant material with immense industrial significance. These have preponderant implications in plant biomass research and food industry, and also posit application in the reclamation of water pollution from plant materials.

Mycobacterium bovis: From Genotyping to Genome Sequencing

Mycobacterium bovis is the main pathogen of bovine, zoonotic, and wildlife tuberculosis. Despite the existence of programs for bovine tuberculosis (bTB) control in many regions, the disease remains a challenge for the veterinary and public health sectors, especially in developing countries and in high-income nations with wildlife reservoirs. Current bTB control programs are mostly based on test-and-slaughter, movement restrictions, and post-mortem inspection measures. In certain settings, contact tracing and surveillance has benefited from M. bovis genotyping techniques. More recently, whole-genome sequencing (WGS) has become the preferential technique to inform outbreak response through contact tracing and source identification for many infectious diseases. As the cost per genome decreases, the application of WGS to bTB control programs is inevitable moving forward. However, there are technical challenges in data analyses and interpretation that hinder the implementation of M. bovis WGS as a molecular epidemiology tool. Therefore, the aim of this review is to describe M. bovis genotyping techniques and discuss current standards and challenges of the use of M. bovis WGS for transmission investigation, surveillance, and global lineages distribution. We compiled a series of associated research gaps to be explored with the ultimate goal of implementing M. bovis WGS in a standardized manner in bTB control programs.

prewas: data pre-processing for more informative bacterial GWAS

While variant identification pipelines are becoming increasingly standardized, less attention has been paid to the pre-processing of variants prior to their use in bacterial genome-wide association studies (bGWAS). Three nuances of variant pre-processing that impact downstream identification of genetic associations include the separation of variants at multiallelic sites, separation of variants in overlapping genes, and referencing of variants relative to ancestral alleles. Here we demonstrate the importance of these variant pre-processing steps on diverse bacterial genomic datasets and present prewas, an R package, that standardizes the pre-processing of multiallelic sites, overlapping genes, and reference alleles before bGWAS. This package facilitates improved reproducibility and interpretability of bGWAS results. prewas enables users to extract maximal information from bGWAS by implementing multi-line representation for multiallelic sites and variants in overlapping genes. prewas outputs a binary SNP matrix that can be used for SNP-based bGWAS and will prevent the masking of minor alleles during bGWAS analysis. The optional binary gene matrix output can be used for gene-based bGWAS, which will enable users to maximize the power and evolutionary interpretability of their bGWAS studies. prewas is available for download from GitHub.

Typing methods based on whole genome sequencing data

Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.

Molecular analysis and epidemiological typing of Vancomycin-resistant Enterococcus outbreak strains

Outbreaks of multidrug resistant bacteria including vancomycin-resistant enterococci (VRE) in healthcare institutions are increasing in Norway, despite a low level of resistance compared to other European countries. In this study, we describe epidemiological relatedness of vancomycin-resistant Enterococcus faecium isolated during an outbreak at a Norwegian hospital in 2012–2013. During the outbreak, 9454 fecal samples were screened for VRE by culture and/or PCR. Isolates from 86 patients carrying the vanA resistance gene were characterized using pulsed-field gel electrophoresis (PFGE), MALDI-TOF mass spectrometry and single nucleotide polymorphism typing. PFGE revealed two main clusters, the first comprised 56 isolates related to an initial outbreak strain, and the second comprised 21 isolates originating from a later introduced strain, together causing two partly overlapping outbreaks. Nine isolates, including the index case were not related to the two outbreak clusters. In conclusion, the epidemiological analyses show that the outbreak was discovered by coincidence, and that infection control measures were successful. All typing methods identified the two outbreak clusters, and the experiment congruence between the MALDI-TOF and the PFGE clustering was 63.2%, with a strong correlation (r = 72.4%). Despite lower resolution compared to PFGE, MALDI-TOF may provide an efficient mean for real-time monitoring spread of infection.