Evaluation of WGS performance for bacterial pathogen characterization with the Illumina technology optimized for time-critical situations

Pangenomic and biochemical analyses of Helcococcus ovis reveal widespread tetracycline resistance and a novel bacterial species, Helcococcus bovis

Helcococcus ovis (H. ovis) is an opportunistic bacterial pathogen of a wide range of animal hosts including domestic ruminants, swine, avians, and humans. In this study, we sequenced the genomes of 35 Helcococcus sp. clinical isolates from the uterus of dairy cows and explored their antimicrobial resistance and biochemical phenotypes in vitro. Phylogenetic and average nucleotide identity analyses classified four Helcococcus isolates within a cryptic clade representing an undescribed species, for which we propose the name Helcococcus bovis sp. nov. By establishing this new species clade, we also resolve the longstanding question of the classification of the Tongji strain responsible for a confirmed human conjunctival infection. This strain did not neatly fit into H. ovis and is instead a member of H. bovis. We applied whole genome comparative analyses to explore the pangenome, resistome, virulome, and taxonomic diversity of the remaining 31 H. ovis isolates. An overwhelming 97% of H. ovis strains (30 out of 31) harbor mobile tetracycline resistance genes and displayed significantly increased minimum inhibitory concentrations of tetracyclines in vitro. The high prevalence of mobile tetracycline resistance genes makes H. ovis a significant antimicrobial resistance gene reservoir in our food chain. Finally, the phylogenetic distribution of co-occurring high-virulence determinant genes of H. ovis across unlinked and distant loci highlights an instance of convergent gene loss in the species. In summary, this study showed that mobile genetic element-mediated tetracycline resistance is widespread in H. ovis, and that there is evidence of co-occurring virulence factors across clades suggesting convergent gene loss in the species. Finally, we introduced a novel Helcococcus species closely related to H. ovis, called H. bovis sp. nov., which has been reported to cause infection in humans.

Genetic determinants of antimicrobial resistance in polymyxin B resistant Pseudomonas aeruginosa isolated from airways of patients with cystic fibrosis

Pseudomonas aeruginosa is the main pathogen associated with pulmonary exacerbation in patients with cystic fibrosis (CF). CF is a multisystemic genetic disease caused by mutations in the cystic fibrosis transmembrane conductance regulator gene, which mainly affects pulmonary function. P. aeruginosa isolated from individuals with CF in Brazil is not commonly associated with multidrug resistance (MDR), especially when compared to global occurrence, where the presence of epidemic clones, capable of expressing resistance to several drugs, is often reported. Due to the recent observations of MDR isolates of P. aeruginosa in our centers, combined with these characteristics, whole-genome sequencing was employed for analyses related to antimicrobial resistance, plasmid identification, search for phages, and characterization of CF clones. All isolates in this study were polymyxin B resistant, exhibiting diverse mutations and reduced susceptibility to carbapenems. Alterations in mexZ can result in the overexpression of the MexXY efflux pump. Mutations in oprD, pmrB, parS, gyrA and parC may confer reduced susceptibility to antimicrobials by affecting permeability, as observed in phenotypic tests. The phage findings led to the assumption of horizontal genetic transfer, implicating dissemination between P. aeruginosa isolates. New sequence types were described, and none of the isolates showed an association with epidemic CF clones. Analysis of the genetic context of P. aeruginosa resistance to polymyxin B allowed us to understand the different mechanisms of resistance to antimicrobials, in addition to subsidizing the understanding of possible relationships with epidemic strains that circulate among individuals with CF observed in other countries.

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.

Advancing animal tuberculosis surveillance using culture-independent long-read whole-genome sequencing

Animal tuberculosis is a significant infectious disease affecting both livestock and wildlife populations worldwide. Effective disease surveillance and characterization of Mycobacterium bovis (M. bovis) strains are essential for understanding transmission dynamics and implementing control measures. Currently, sequencing of genomic information has relied on culture-based methods, which are time-consuming, resource-demanding, and concerning in terms of biosafety. This study explores the use of culture-independent long-read whole-genome sequencing (WGS) for a better understanding of M. bovis epidemiology in African buffaloes (Syncerus caffer). By comparing two sequencing approaches, we evaluated the efficacy of Illumina WGS performed on culture extracts and culture-independent Oxford Nanopore adaptive sampling (NAS). Our objective was to assess the potential of NAS to detect genomic variants without sample culture. In addition, culture-independent amplicon sequencing, targeting mycobacterial-specific housekeeping and full-length 16S rRNA genes, was applied to investigate the presence of microorganisms, including nontuberculous mycobacteria. The sequencing quality obtained from DNA extracted directly from tissues using NAS is comparable to the sequencing quality of reads generated from culture-derived DNA using both NAS and Illumina technologies. We present a new approach that provides complete and accurate genome sequence reconstruction, culture independently, and using an economically affordable technique.

CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter

BACKGROUND

The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge.

RESULTS

To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation.

CONCLUSIONS

The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype .