GeneMates: an R package for detecting horizontal gene co-transfer between bacteria using gene-gene associations controlled for population structure

Zoo animal manure as an overlooked reservoir of antibiotic resistance genes and multidrug-resistant bacteria

Animal fecal samples collected in the summer and winter from 11 herbivorous animals, including sable antelope (SA), long-tailed goral (LTG), and common eland (CE), at a public zoo were examined for the presence of antibiotic resistance genes (ARGs). Seven antibiotics, including meropenem and azithromycin, were used to isolate culturable multidrug-resistant (MDR) strains. The manures from three animals (SA, LTG, and CE) contained 10⁴-fold higher culturable MDR bacteria, including Chryseobacterium, Sphingobacterium, and Stenotrophomonas species, while fewer MDR bacteria were isolated from manure from water buffalo, rhinoceros, and elephant against all tested antibiotics. Three MDR bacteria-rich samples along with composite samples were further analyzed using nanopore-based technology. ARGs including lnu(C), tet(Q), and mef(A) were common and often associated with transposons in all tested samples, suggesting that transposons carrying ARGs may play an important role for the dissemination of ARGs in our tested animals. Although several copies of ARGs such as aph(3')-IIc, bla_L1, bla_IND-3, and tet(42) were found in the sequenced genomes of the nine MDR bacteria, the numbers and types of ARGs appeared to be less than expected in zoo animal manure, suggesting that MDR bacteria in the gut of the tested animals had intrinsic resistant phenotypes in the absence of ARGs.

hgtseq: A Standard Pipeline to Study Horizontal Gene Transfer

Horizontal gene transfer (HGT) is well described in prokaryotes: it plays a crucial role in evolution, and has functional consequences in insects and plants. However, less is known about HGT in humans. Studies have reported bacterial integrations in cancer patients, and microbial sequences have been detected in data from well-known human sequencing projects. Few of the existing tools for investigating HGT are highly automated. Thanks to the adoption of Nextflow for life sciences workflows, and to the standards and best practices curated by communities such as nf-core, fully automated, portable, and scalable pipelines can now be developed. Here we present nf-core/hgtseq to facilitate the analysis of HGT from sequencing data in different organisms. We showcase its performance by analysing six exome datasets from five mammals. Hgtseq can be run seamlessly in any computing environment and accepts data generated by existing exome and whole-genome sequencing projects; this will enable researchers to expand their analyses into this area. Fundamental questions are still open about the mechanisms and the extent or role of horizontal gene transfer: by releasing hgtseq we provide a standardised tool which will enable a systematic investigation of this phenomenon, thus paving the way for a better understanding of HGT.

Current Methods for Recombination Detection in Bacteria

The role of genetic exchanges, i.e., homologous recombination (HR) and horizontal gene transfer (HGT), in bacteria cannot be overestimated for it is a pivotal mechanism leading to their evolution and adaptation, thus, tracking the signs of recombination and HGT events is importance both for fundamental and applied science. To date, dozens of bioinformatics tools for revealing recombination signals are available, however, their pros and cons as well as the spectra of solvable tasks have not yet been systematically reviewed. Moreover, there are two major groups of software. One aims to infer evidence of HR, while the other only deals with horizontal gene transfer (HGT). However, despite seemingly different goals, all the methods use similar algorithmic approaches, and the processes are interconnected in terms of genomic evolution influencing each other. In this review, we propose a classification of novel instruments for both HR and HGT detection based on the genomic consequences of recombination. In this context, we summarize available methodologies paying particular attention to the type of traceable events for which a certain program has been designed.

Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic

SARS-CoV-2 is a single-stranded RNA betacoronavirus with a high mutation rate. The rapidly emerging SARS-CoV-2 variants could increase transmissibility and diminish vaccine protection. However, whether coinfection with multiple SARS-CoV-2 variants exists remains controversial. This study collected 12,986 and 4,113 SARS-CoV-2 genomes from the GISAID database on May 11, 2020 (GISAID20May11), and Apr 1, 2021 (GISAID21Apr1), respectively. With single-nucleotide variant (SNV) and network clique analyses, we constructed single-nucleotide polymorphism (SNP) coexistence networks and discovered maximal SNP cliques of sizes 16 and 34 in the GISAID20May11 and GISAID21Apr1 datasets, respectively. Simulating the transmission routes and SNV accumulations, we discovered a linear relationship between the size of the maximal clique and the number of coinfected variants. We deduced that the COVID-19 cases in GISAID20May11 and GISAID21Apr1 were coinfections with 3.20 and 3.42 variants on average, respectively. Additionally, we performed Nanopore sequencing on 42 COVID-19 patients and discovered recurrent heterozygous SNPs in twenty of the patients, including loci 8,782 and 28,144, which were crucial for SARS-CoV-2 lineage divergence. In conclusion, our findings reported SARS-CoV-2 variants coinfection in COVID-19 patients and demonstrated the increasing number of coinfected variants.

Alterations in chromosomal genes nfsA, nfsB, and ribE are associated with nitrofurantoin resistance in Escherichia coli from the United Kingdom

Antimicrobial resistance in enteric or urinary Escherichia coli is a risk factor for invasive E. coli infections. Due to widespread trimethoprim resistance amongst urinary E. coli and increased bacteraemia incidence, a national recommendation to prescribe nitrofurantoin for uncomplicated urinary tract infection was made in 2014. Nitrofurantoin resistance is reported in <6% urinary E. coli isolates in the UK, however, mechanisms underpinning nitrofurantoin resistance in these isolates remain unknown. This study aimed to identify the genetic basis of nitrofurantoin resistance in urinary E. coli isolates collected from north west London and then elucidate resistance-associated genetic alterations in available UK E. coli genomes. As a result, an algorithm was developed to predict nitrofurantoin susceptibility. Deleterious mutations and gene-inactivating insertion sequences in chromosomal nitroreductase genes nfsA and/or nfsB were identified in genomes of nine confirmed nitrofurantoin-resistant urinary E. coli isolates and additional 11 E. coli isolates that were highlighted by the prediction algorithm and subsequently validated to be nitrofurantoin-resistant. Eight categories of allelic changes in nfsA , nfsB , and the associated gene ribE were detected in 12412 E. coli genomes from the UK. Evolutionary analysis of these three genes revealed homoplasic mutations and explained the previously reported order of stepwise mutations. The mobile gene complex oqxAB , which is associated with reduced nitrofurantoin susceptibility, was identified in only one of the 12412 genomes. In conclusion, mutations and insertion sequences in nfsA and nfsB were leading causes of nitrofurantoin resistance in UK E. coli . As nitrofurantoin exposure increases in human populations, the prevalence of nitrofurantoin resistance in carriage E. coli isolates and those from urinary and bloodstream infections should be monitored.

The Pectobacterium pangenome, with a focus on Pectobacterium brasiliense, shows a robust core and extensive exchange of genes from a shared gene pool

BACKGROUND

Bacterial plant pathogens of the Pectobacterium genus are responsible for a wide spectrum of diseases in plants, including important crops such as potato, tomato, lettuce, and banana. Investigation of the genetic diversity underlying virulence and host specificity can be performed at genome level by using a comprehensive comparative approach called pangenomics. A pangenomic approach, using newly developed functionalities in PanTools, was applied to analyze the complex phylogeny of the Pectobacterium genus. We specifically used the pangenome to investigate genetic differences between virulent and avirulent strains of P. brasiliense, a potato blackleg causing species dominantly present in Western Europe.

RESULTS

Here we generated a multilevel pangenome for Pectobacterium, comprising 197 strains across 19 species, including type strains, with a focus on P. brasiliense. The extensive phylogenetic analysis of the Pectobacterium genus showed robust distinct clades, with most detail provided by 452,388 parsimony-informative single-nucleotide polymorphisms identified in single-copy orthologs. The average Pectobacterium genome consists of 47% core genes, 1% unique genes, and 52% accessory genes. Using the pangenome, we zoomed in on differences between virulent and avirulent P. brasiliense strains and identified 86 genes associated to virulent strains. We found that the organization of genes is highly structured and linked with gene conservation, function, and transcriptional orientation.

CONCLUSION

The pangenome analysis demonstrates that evolution in Pectobacteria is a highly dynamic process, including gene acquisitions partly in clusters, genome rearrangements, and loss of genes. Pectobacterium species are typically not characterized by a set of species-specific genes, but instead present themselves using new gene combinations from the shared gene pool. A multilevel pangenomic approach, fusing DNA, protein, biological function, taxonomic group, and phenotypes, facilitates studies in a flexible taxonomic context.