A Practical Bioinformatics Workflow for Routine Analysis of Bacterial WGS Data

Genomic typing, antimicrobial resistance gene, virulence factor and plasmid replicon database for the important pathogenic bacteria Klebsiella pneumoniae

BACKGROUND

The infections of bacterial origin represent a significant problem to the public healthcare worldwide both in clinical and community settings. Recent decade was marked by limiting treatment options for bacterial infections due to growing antimicrobial resistance (AMR) acquired and transferred by various bacterial species, especially the ones causing healthcare-associated infections, which has become a dangerous issue noticed by the World Health Organization. Numerous reports shown that the spread of AMR is often driven by several species-specific lineages usually called the 'global clones of high risk'. Thus, it is essential to track the isolates belonging to such clones and investigate the mechanisms of their pathogenicity and AMR acquisition. Currently, the whole genome-based analysis is more and more often used for these purposes, including the epidemiological surveillance and analysis of mobile elements involved in resistance transfer. However, in spite of the exponential growth of available bacterial genomes, their representation usually lack uniformity and availability of supporting metadata, which creates a bottleneck for such investigations.

DESCRIPTION

In this database, we provide the results of a thorough genomic analysis of 61,857 genomes of a highly dangerous bacterial pathogen Klebsiella pneumoniae. Important isolate typing information including multilocus sequence typing (MLST) types (STs), assignment of the isolates to known global clones, capsular (KL) and lipooligosaccharide (O) types, the presence of CRISPR-Cas systems, and cgMLST profiles are given, and the information regarding the presence of AMR, virulence genes and plasmid replicons within the genomes is provided.

CONCLUSION

This database is freely available under CC BY-NC-SA at https://doi.org/10.5281/zenodo.11069018 . The database will facilitate selection of the proper reference isolate sets for any types of genome-based investigations. It will be helpful for investigations in the field of K. pneumoniae genomic epidemiology, as well as antimicrobial resistance analysis and the development of prevention measures against this important pathogen.

Whole genome sequencing and antimicrobial resistance among clinical isolates of Shigella sonnei in Addis Ababa, Ethiopia

BACKGROUND

Shigellosis is an acute gastroenteritis infection and one of Ethiopia's most common causes of morbidity and mortality, especially in children under five. Antimicrobial resistance (AMR) has spread quickly among Shigella species due to inappropriate antibiotic use, inadequacies of diagnostic facilities, and unhygienic conditions. This study aimed to characterize Shigella sonnei (S. sonnei) using whole genome sequence (WGS) analysis in Addis Ababa, Ethiopia.

METHODS

The raw reads were quality-filtered and trimmed, and a minimum length of 50bp was retained and taxonomically classified using MiniKraken version 1. The whole genome data were aligned with Antibiotic Resistance Gene (ARG) sequences of the Comprehensive Antibiotic Resistance Database (CARD) by Resistance Gene Identifier (RGI). Plasmids were analyzed using the PlasmidFinder tool version 2.1. Additionally, AMR and virulence genes were screened at the Centre for Genomic Epidemiology (CGE) web-based server.

RESULTS

All isolates in our investigation contained genes encoding blaEC-8 and blaZEG-1. Here, 60.7% of the isolates were phenotypically sensitive to cefoxitin among the blaEC-8 genes detected in the genotyping analysis, whereas all isolates were completely resistant to amoxicillin and erythromycin phenotypically. The study also identified genes that conferred resistance to trimethoprim (dfrA). Plasmid Col156 and Col (BS512) types were found in all isolates, while IncFII and Col (MG828) plasmids were only identified in one isolate.

CONCLUSION

This study found that many resistant genes were present, confirming the high variety in S. sonnei strains and hence a divergence in phylogenetic relationships. Thus, combining WGS methods for AMR prediction and strain identification into active surveillance may be beneficial for monitoring the spread of AMR in S. sonnei and detecting the potential emergence of novel variations.

First comparative genomics analysis of Corynebacterium auriscanis

BACKGROUND

Corynebacterium auriscanis is a bacterial species frequently isolated from dogs with external otitis or dermatitis and a zoonotic pathogen transmitted by dog bite. It is considered an opportunistic pathogen, but its pathogenicity mechanisms are poorly studied. Comparative genomics can identify virulence and niche factors that could contribute to understanding its lifestyle.

OBJECTIVES

The objectives of this project was to compare genomes of C. auriscanis to identify genes related to its virulence and lifestyle.

METHODS

The genome of strain 32 was sequenced using Illumina HiSeq 2500 (Illumina, CA, USA) and assembled using Unicycler. The two other non-redundant genomes from the same species available in GenBank were included in the analysis. All genomes were annotated and checked for taxonomy, assembly quality, mobile elements, CRISPR-Cas systems, and virulence and antimicrobial resistance genes. The virulence genes in the three genomes were compared to the ones from other pathogens commonly isolated with C. auriscanis.

FINDINGS

The species has 42 virulence factors that can be classified as niche factors, due to the absence of true virulence factors found in primary pathogens. The gene rbpA could confer basal levels of resistance to rifampin.

MAIN CONCLUSIONS

The absence of true virulence factors in the three genomes suggests C. auriscanis has an opportunistic pathogen lifestyle.

Development of a silkworm infection model for evaluating the virulence of Mycobacterium intracellulare subspecies estimated using phylogenetic tree analysis based on core gene data

Non-tuberculous mycobacteria (NTM) cause skin infections, respiratory diseases, and disseminated infections. Mycobacterium avium and Mycobacterium intracellulare, which are slow grown Mycobacterium, are main agents of those NTM diseases. A silkworm infection model with Mycobacterium abscessus, a rapidly growing Mycobacterium species, was established to quantitatively evaluate its virulence within a short period. However, a silkworm infection model to quantitatively evaluate the virulence of M. intracellulare has not yet been developed. In this study, we determined the virulence of M. intracellulare subspecies within 4 days using a silkworm infection model. The subspecies of M. intracellulare strains used in this study were estimated by phylogenetic tree analysis using core gene data. The median lethal dose (LD50) values, which are the dose of a pathogen required to kill half of the silkworms in a group, were determined 4 days after infection. The LD50 value of M. intracellulare subsp. chimaera DSM44623 was higher than that of M. intracellulare subsp. intracellulare ATCC13950. These results suggest that the virulence of M. intracellulare subspecies can be compared using a silkworm model within 4 days.

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.

Prevalence of Salmonella in Eggs from Conventional and Cage-Free Egg Production Systems and the Role of Consumers in Reducing Household Contamination

Salmonella is one of the leading causes of foodborne disease worldwide, usually related to contaminated poultry or poultry products, such as eggs. Since egg contamination with Salmonella depends on multiple factors that make it challenging to control, consumers' knowledge about food safety and the proper handling of eggs is crucial. The aims of the study were (1) to determine the prevalence of Salmonella in eggs from conventional and alternative production systems, (2) to characterize the Salmonella isolates according to phenotypic-genotypic and antimicrobial-resistant traits, and (3) to understand how consumers manage the hazards related to egg contamination in the household. A total of 426 egg samples were analyzed (conventional systems = 240; alternative systems = 186). Culture-based and molecular microbiological methods were used to identify Salmonella and bioinformatics analysis of whole genome sequences was used to determine the serotype and antimicrobial-resistant genes. Salmonella enterica serotype Enteritidis was detected only in eggs from alternative systems (1.1%, 2/186). Isolates showed resistance to nalidixic acid (100%, 2/2), and the aac(6')-Iaa gene and a mutation in the gyrA gene were identified in both isolates. Overall, consumers demonstrated knowledge regarding food safety; however, many still engage in practices that pose a risk of acquiring foodborne illnesses.

Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

Non-tuberculous mycobacterial disease associated with Mycobacterium montefiorense in salamanders

Introduction

Mycobacterium montefiorense is one of the causes of non-tuberculous mycobacterial infections in moray eels and salamanders. Although M. montefiorense infection could be a threat to salamanders, little information is available regarding this pathogen and associated infection. This study aimed to provide fundamental information regarding M. montefiorense and its infection in salamanders.

Methods

Nine M. montefiorense strains isolated from three species of salamanders, namely, Japanese black salamander (Hynobius nigrescens), Hakuba salamander (H. hidamontanus), and Tohoku hynobiid salamander (H. lichenatus), between 2010 and 2018, were characterized based on phenotypic and genetic examination. We also pathologically observed salamanders infected with the M. montefiorense strains, including Hakuba salamanders and Tohoku hynobiid salamanders.

Results

The microbiological and chemical characteristics of the M. montefiorense salamander and an eel strain (reference strain) matched. Susceptibility testing for antimicrobials suggested that clarithromycin may be effective. Regarding disinfectants, phtharal, peracetic acid, glutaral, sodium hypochlorite, and benzalkonium chloride may be effective. Phylogenetic analyses revealed that the strains isolated from salamanders in 2014 and 2018 were genetically closely related, which could indicate an outbreak. The main gross findings in infected salamanders include skin ulcerative lesions or nodules in the enlarged liver. Microscopically, multifocal to coalescent granulomatous lesions composed of massive macrophages containing numerous acid-fast bacilli were prominently observed in the liver.

Conclusion

This study contributes to our understanding of the genetic diversity and phenotypic characteristics of M. montefiorense, as well as the pathology of the infection.

Salmonella Infection in Pigs: Disease, Prevalence, and a Link between Swine and Human Health

Salmonella is one of the most spread foodborne pathogens worldwide, and Salmonella infections in humans still represent a global health burden. The main source of Salmonella infections in humans is represented by contaminated animal-derived foodstuffs, with pork products being one of the most important players. Salmonella infection in swine is critical not only because it is one of the main causes of economic losses in the pork industry, but also because pigs can be infected by several Salmonella serovars, potentially contaminating the pig meat production chain and thus posing a significant threat to public health globally. As of now, in Europe and in the United States, swine-related Salmonella serovars, e.g., Salmonella Typhimurium and its monophasic variant Salmonella enterica subsp. enterica 1,4,[5],12:i:-, are also frequently associated with human salmonellosis cases. Moreover, multiple outbreaks have been reported in the last few decades which were triggered by the consumption of Salmonella-contaminated pig meat. Throughout the years, changes and evolution across the pork industry may have acted as triggers for new issues and obstacles hindering Salmonella control along the food chain. Gathered evidence reinforces the importance of coordinating control measures and harmonizing monitoring programs for the efficient control of Salmonella in swine. This is necessary in order to manage outbreaks of clinical disease in pigs and also to protect pork consumers by controlling Salmonella subclinical carriage and shedding. This review provides an update on Salmonella infection in pigs, with insights on Salmonella ecology, focusing mainly on Salmonella Choleraesuis, S. Typhimurium, and S. 1,4,[5],12:i:-, and their correlation to human salmonellosis cases. An update on surveillance methods for epidemiological purposes of Salmonella infection in pigs and humans, in a "One Health" approach, will also be reported.

Bacterial Genomics and Epidemiology

Innovative technologies for Whole-Genome Sequencing (WGS) help to improve our understanding of the epidemiology and pathogenesis of bacterial infectious diseases and are becoming affordable for most microbiological laboratories [...].