Biology subjects

Wick, R. R.

Publications and source records attributed to Wick, R. R..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Diversity, functional classification and genotyping of SHV β-lactamases in Klebsiella pneumoniae

Interpreting phenotypes of blaSHV alleles in Klebsiella pneumoniae genomes is complex. While all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal blaSHV alleles or additional plasmid-borne blaSHV alleles that have extended-spectrum {beta}-lactamase (ESBL) activity and/or {beta}-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/amino acid changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases (e.g., NCBIs Reference Gene Catalog and the {beta}-lactamase database (BLDB)) over the specific functionality of individual SHV protein variants. Therefore, identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific amino-acid substitutions. We then systematically assigned SHV alleles to functional classes (wildtype, ESBL, BLI-resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with current assignments in NCBIs Reference Gene Catalog and/or BLDB (21 to wildtype, 12 to ESBL, 4 to BLI-resistant). Phylogenetic and comparative genomic analyses support that; i) SHV-1 (encoded by blaSHV-1) is the ancestral chromosomal variant; ii) ESBL and BLI-resistant variants have evolved multiple times through parallel substitution mutations; iii) ESBL variants are mostly mobilised to plasmids; iv) BLI-resistant variants mostly result from mutations in chromosomal blaSHV. We used matched genome-phenotype data from the KlebNET-GSP Genotype-Phenotype Group to identify 3,999 K. pneumoniae isolates carrying one or more blaSHV alleles but no other acquired {beta}-lactamases, with which we assessed genotype-phenotype relationships for blaSHV. This collection includes human, animal, and environmental isolates collected between 2001 to 2021 from 24 countries across six continents. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, while most omega-loop substitutions do not. Our data also provide direct support for wildtype assignment of 67 protein variants, including eight that were noted in public databases as ESBL. We reclassified these eight variants as wildtype, because they lack ESBL-associated mutations, and our phenotype data support susceptibility to 3GCs (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164, SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae from genome assemblies), whereby known and novel blaSHV alleles are classified based on causative mutations. Kleborate v2.4.1 was also updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve understanding of resistance mechanisms. Impact statementSince every K. pneumoniae genome has an intrinsic SHV {beta}-lactamase and may also carry additional mobile forms, the correct interpretation of blaSHV genes detected in genome data can be challenging and can lead to K. pneumoniae being misclassified as ESBL-producing. Here, we use matched K. pneumoniae genome and drug susceptibility data contributed from dozens of studies, together with systematic literature review of experimental evidence, to improve our understanding of blaSHV allele variation and mapping of genotype to phenotype. This study shows the value of coordinated data sharing, in this case via the KlebNET-GSP Genotype-Phenotype Group, to improve our understanding of the evolutionary history and functionality of blaSHV genes. The results are captured in an open-source AMR dictionary utilised by the Kleborate genotyping tool, that could easily be incorporated into or used to update other tools and AMR gene databases. This work is part of the wider efforts of the KlebNET-GSP group to develop and support a unified platform tailored for the analysis and interpretation of K. pneumoniae genomes by a wide range of stakeholders. Data summaryBlaSHV allele sequences and class assignments are distributed with Kleborate, v2.4.1, DOI:10.5281/zenodo.10469001. Table S1 provides a summary of blaSHV alleles, including primary accessions, class-modifying mutations, and supporting evidence for class assignments that differ from NCBIs Reference Gene Catalog or BLDB. Whole genome sequence data are publicly available as reads and/or assemblies, individual accessions are given in Table S2; corresponding genotypes and antibiotic susceptibility phenotypes and measurements are available in Tables S3 and S4, respectively.

genomics↗

bioRxiv2024

Benchmarking reveals superiority of deep learning variant callers on bacterial nanopore sequence data

Variant calling is fundamental in bacterial genomics, underpinning the identification of disease transmission clusters, the construction of phylogenetic trees, and antimicrobial resistance prediction. This study presents a comprehensive benchmarking of SNP and indel variant calling accuracy across 14 diverse bacterial species using Oxford Nanopore Technologies (ONT) and Illumina sequencing. We generate gold standard reference genomes and project variations from closely-related strains onto them, creating biologically realistic distributions of SNPs and indels. Our results demonstrate that ONT variant calls from deep learning-based tools delivered higher SNP and indel accuracy than traditional methods and Illumina, with Clair3 providing the most accurate results overall. We investigate the causes of missed and false calls, highlighting the limitations inherent in short reads and discover that ONTs traditional limitations with homopolymer-induced indel errors are absent with high-accuracy basecalling models and deep learning-based variant calls. Furthermore, our findings on the impact of read depth on variant calling offer valuable insights for sequencing projects with limited resources, showing that 10x depth is sufficient to achieve variant calls that match or exceed Illumina. In conclusion, our research highlights the superior accuracy of deep learning tools in SNP and indel detection with ONT sequencing, challenging the primacy of short-read sequencing. The reduction of systematic errors and the ability to attain high accuracy at lower read depths enhance the viability of ONT for widespread use in clinical and public health bacterial genomics.

bioinformatics↗

bioRxiv2024

How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies

It is now possible to assemble near-perfect bacterial genomes using Oxford Nanopore Technologies (ONT) long reads, but short-read polishing is still required for perfection. However, the effect of short-read depth on polishing performance is not well understood. Here, we introduce Pypolca (with default and careful parameters) and Polypolish v0.6.0 (with a new careful parameter). We then show that: (1) all polishers other than Pypolca-careful, Polypolish-default and Polypolish-careful commonly introduce false-positive errors at low depth; (2) most of the benefit of short-read polishing occurs by 25x depth; (3) Polypolish-careful never introduces false-positive errors at any depth; and (4) Pypolca-careful is the single most effective polisher. Overall, we recommend the following polishing strategies: Polypolish-careful alone when depth is very low (<5x), Polypolish-careful and Pypolca-careful when depth is low (5-25x), and Polypolish-default and Pypolca-careful when depth is sufficient (>25x). Data SummaryPypolca is open-source and freely available on Bioconda, PyPI, and GitHub (github.com/gbouras13/pypolca). Polypolish is open-source and freely available on Bioconda and GitHub (github.com/rrwick/Polypolish). All code and data required to reproduce analyses and figures are available at github.com/gbouras13/depth_vs_polishing_analysis. All FASTQ sequencing reads are available at BioProject PRJNA1042815. A detailed list of accessions can be found in Table S1.

bioinformatics↗

bioRxiv2023

Hybracter: Enabling Scalable, Automated, Complete and Accurate Bacterial Genome Assemblies

Improvements in the accuracy and availability of long-read sequencing mean that complete bacterial genomes are now routinely reconstructed using hybrid (i.e. short- and long-reads) assembly approaches. Complete genomes allow a deeper understanding of bacterial evolution and genomic variation beyond single nucleotide variants (SNVs). They are also crucial for identifying plasmids, which often carry medically significant antimicrobial resistance (AMR) genes. However, small plasmids are often missed or misassembled by long-read assembly algorithms. Here, we present Hybracter which allows for the fast, automatic, and scalable recovery of near-perfect complete bacterial genomes using a long-read first assembly approach. Hybracter can be run either as a hybrid assembler or as a long-read only assembler. We compared Hybracter to existing automated hybrid and long-read only assembly tools using a diverse panel of samples of varying levels of long-read accuracy with manually curated ground truth reference genomes. We demonstrate that Hybracter as a hybrid assembler is more accurate and faster than the existing gold standard automated hybrid assembler Unicycler. We also show that Hybracter with long-reads only is the most accurate long-read only assembler and is comparable to hybrid methods in accurately recovering small plasmids. Data SummaryO_LIHybracter is developed using Python and Snakemake as a command-line software tool for Linux and MacOS systems. C_LIO_LIHybracter is freely available under an MIT License on GitHub (https://github.com/gbouras13/hybracter) and the documentation is available at Read the Docs (https://hybracter.readthedocs.io/en/latest/). C_LIO_LIHybracter is available to install via PyPI (https://pypi.org/project/hybracter/) and Bioconda (https://anaconda.org/bioconda/hybracter). A Docker/Singularity container is also available at https://quay.io/repository/gbouras13/hybracter. C_LIO_LIAll code used to benchmark Hybracter, including the reference genomes, is publicly available on GitHub (https://github.com/gbouras13/hybracter_benchmarking) with released DOI (https://zenodo.org/doi/10.5281/zenodo.10910108) available at Zenodo. C_LIO_LIThe subsampled FASTQ files used for benchmarking are publicly available at Zenodo with DOI (https://doi.org/10.5281/zenodo.10906937). C_LIO_LIAll super accuracy simplex ATCC FASTQ reads sequenced as a part of this study can be found under BioProject PRJNA1042815. C_LIO_LIAll Hall et al. fast accuracy simplex and super accuracy duplex ATCC FASTQ read files (prior to subsampling) can be found in the SRA under BioProject PRJNA1087001. C_LIO_LIAll raw Lermaniaux et al. FASTQ read files and genomes (prior to subsampling) can be found in the SRA under BioProject PRJNA1020811. C_LIO_LIAll Staphylococcus aureus JKD6159 FASTQ read files and genomes can be found under BioProject PRJNA50759. C_LIO_LIAll Mycobacterium tuberculosis H37R2 FASTQ read files and genomes can be found under BioProject PRJNA836783. C_LIO_LIThe complete list of BioSample accession numbers for each benchmarked sample can be found in Supplementary Table 1. C_LIO_LIThe benchmarking assembly output files are publicly available on Zenodo with DOI (https://doi.org/10.5281/zenodo.10906937). C_LIO_LIAll Pypolca benchmarking outputs and code are publicly available on Zenodo with DOI (https://zenodo.org/doi/10.5281/zenodo.10072192). C_LI Impact StatementComplete bacterial genome assembly using hybrid sequencing is a routine and vital part of bacterial genomics, especially for identification of mobile genetic elements and plasmids. As sequencing becomes cheaper, easier to access and more accurate, automated assembly methods are crucial. With Hybracter, we present a new long-read first automated assembly tool that is faster and more accurate than the widely-used Unicycler. Hybracter can be used both as a hybrid assembler and with long-reads only. Additionally, it solves the problems of long-read assemblers struggling with small plasmids, with plasmid recovery from long-reads only performing on par with hybrid methods. Hybracter can natively exploit the parallelisation of high-performance computing (HPC) clusters and cloud-based environments, enabling users to assemble hundreds or thousands of genomes with one line of code. Hybracter is available freely as source code on GitHub, via Bioconda or PyPi.

bioinformatics↗

bioRxiv2022

Polishing de novo nanopore assemblies of bacteria and eukaryotes with FMLRC2

As accuracy and throughput of nanopore sequencing improves, it is increasingly common to perform long-read-first de novo genome assemblies followed by polishing with accurate short reads (Kim et al. 2021). We briefly introduce FMLRC2, the successor to the original FM-index Long Read Corrector (FMLRC), and illustrate its performance as a fast and accurate de novo assembly polisher for both microbial and eukaryotic genomes.

genomics↗

bioRxiv2022

Nanopore-only assemblies for genomic surveillance of the global priority drug-resistant pathogen, Klebsiella pneumoniae

BackgroundOxford Nanopore Technologies (ONT) sequencing has rich potential for genomic epidemiology and public health investigations of bacterial pathogens, particularly in low-resource settings and at the point of care, due to its portability and affordability. However, low base-call accuracy has limited the reliability of ONT data for critical tasks such as antimicrobial resistance (AMR) and virulence gene detection and typing, serotype prediction and cluster identification. Thus, Illumina sequencing remains the standard for genomic surveillance despite higher capital and running costs. MethodsWe tested the accuracy of ONT-only assemblies for common applied bacterial genomics tasks (genotyping and cluster detection, implemented via Kleborate, Kaptive and Pathogenwatch), using data from 54 unique Klebsiella pneumoniae isolates. ONT reads generated via MinION with R9.4 flowcells were basecalled using three alternative models (Fast, High-accuracy (HAC) and Super-accuracy (SUP), available within ONTs Guppy software), assembled with Flye and polished using Medaka. Accuracy of typing using ONT-only assemblies was compared with that of Illumina-only and hybrid ONT+Illumina assemblies, constructed from the same isolates as reference standards. ResultsThe most resource-intensive ONT-assembly approach (SUP basecalling, with or without Medaka polishing) performed best, yielding reliable capsule (K) type calls for all strains (100% exact or best matching locus), reliable multi-locus sequence type (MLST) assignment (98.3% exact match or single-locus variants), and good detection of acquired AMR genes and mutations (88% - 100% correct identification across the various drug classes). Distance-based trees generated from SUP+Medaka assemblies accurately reflected overall genetic relationships between isolates; however, the definition of outbreak clusters from ONT-only assemblies was problematic. HAC basecalling + Medaka polishing performed similarly to SUP basecalling without polishing, and polishing introduced errors into HAC- or Fast-basecalled assemblies. Therefore, we recommend investing compute resources into basecalling (SUP model) over polishing, where compute resources and/or time are limiting. ConclusionsOverall, our results show that MLST, K type and AMR determinants can be reliably identified with ONT-only data. However, cluster detection remains challenging with this technology.

genomics↗

bioRxiv2021

Linear plasmids in Klebsiella and other Enterobacteriaceae

Linear plasmids are extrachromosomal DNA that have been found in a small number of bacterial species. To date, the only linear plasmids described in the Enterobacteriaceae family belong to Salmonella, first found in Salmonella Typhi. Here, we describe a collection of 12 isolates of the Klebsiella pneumoniae species complex in which we identified linear plasmids. We used this collection to search public sequence databases and discovered an additional 74 linear plasmid sequences in a variety of Enterobacteriaceae species. Gene content analysis divided these plasmids into five distinct phylogroups, with very few genes shared across more than two phylogroups. The majority of linear plasmid-encoded genes are of unknown function, however each phylogroup carried its own unique toxin-antitoxin system and genes with homology to those encoding the ParAB plasmid stability system. Passage in vitro of the 12 linear plasmid-carrying Klebsiella isolates in our collection (which include representatives of all five phylogroups) indicated that these linear plasmids can be stably maintained, and our data suggest they can transmit between K. pneumoniae strains (including members of globally disseminated multidrug resistant clones) and also between diverse Enterobacteriaceae species. The linear plasmid sequences, and representative isolates harbouring them, are made available as a resource to facilitate future studies on the evolution and function of these novel plasmids. Significance as a BioResource to the communityThis study provides the first report of linear plasmids identified within the Klebsiella pneumoniae species complex and the first report in Enterobacteriaceae besides Salmonella.We present the first comparative analysis of linear plasmid sequences in Enterobacteriaceae, however whilst this family is highly clinically significant, the functional and/or evolutionary importance of these plasmids is not yet clear. To facilitate future studies to address these questions, we have publicly deposited (i) the collection of linear plasmid sequence data; (ii) isolates representative of each of the distinct linear plasmid phylogroups. Data SummaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary information O_LIWhole genome sequence reads from Klebsiella pneumoniae isolates sequenced in this study have been deposited in NCBI SRA under the accession numbers listed in Table S1. C_LIO_LIRepresentative annotated sequences of one linear plasmid per phylogroup have been deposited in FigShare, doi 10.26180/16729126. C_LIO_LIA copy of all linear plasmid sequences that we assembled from publicly available genome sequence reads are available in FigShare, doi 10.26180/16531365. Read accessions for these are given in Table S1. C_LIO_LIEleven representative K. pneumoniae isolates harbouring linear plasmids described in this study have been deposited with the National Collection of Type Cultures (NCTC) and are available for purchase under the NCTC accession numbers listed in Table S1.K. pneumoniae 1194/11 (representative of phylogroup B) has been deposited in the Microorganisms Collection Center, Adolfo Lutz Institute, Sao Paulo, Brazil. To request strain 1194/11 (IAL 3063, SISGEN ABBF09B), contact: Microorganisms Collection Center Culture Collection Laboratory Instituto Adolfo Lutz, Sao Paulo State Department of Health Address: Av Dr Arnaldo, 351, 10 floor, room 1020 Phone number: +55 11 3068-2884 Zip code 01246-000, Sao Paulo, Brazil E-mail: colecaoial@ial.sp.gov.br C_LIO_LIAlignments of terminal inverted repeat sequences for each phylogroup can be found in Data S1, available on FigShare, doi 10.26180/16531371. C_LI

microbiology↗

bioRxiv2021

Kaptive 2.0: updated capsule and LPS locus typing for the Klebsiella pneumoniae species complex

The outer polysaccharide capsule and lipopolysaccharide antigens are key targets for novel control strategies targeting Klebsiella pneumoniae and related taxa from the K. pneumoniae species complex (KpSC), including vaccines, phage and monoclonal antibody therapies. Given the importance and growing interest in these highly diverse surface antigens, we had previously developed Kaptive, a tool for rapidly identifying and typing capsule (K) and outer lipopolysaccharide (O) loci from whole genome sequence data. Here, we report two significant updates, now freely available in Kaptive 2.0 (github.com/katholt/kaptive); i) the addition of 16 novel K locus sequences to the K locus reference database following an extensive search of >17,000 KpSC genomes; and ii) enhanced O locus typing to enable prediction of the clinically relevant O2 antigen (sub)types, for which the genetic determinants have been recently described. We applied Kaptive 2.0 to a curated dataset of >12,000 public KpSC genomes to explore for the first time the distribution of predicted O (sub)types across species, sampling niches and clones, which highlighted key differences in the distributions that warrant further investigation. As the uptake of genomic surveillance approaches continues to expand globally, the application of Kaptive 2.0 will generate novel insights essential for the design of effective KpSC control strategies. Significance as a BioResource to the communityKlebsiella pneumoniae is a major cause of bacterial healthcare associated infections globally, with increasing rates of antimicrobial resistance, including strains with resistance to the drugs of last resort. The latter have therefore been flagged as priority pathogens for the development of novel control strategies. K. pneumoniae produce two key surface antigen sugars (capsular polysaccharide and lipopolysaccharide (LPS)) that are immunogenic and targets for novel controls such as a vaccines and phage therapy. However, there is substantial antigenic diversity in the population and relatively little is understood about the distribution of antigen types geographically and among strains causing different types of infections. Whereas laboratory-based antigen typing is difficult and rarely performed, information about the relevant synthesis loci can be readily extracted from whole genome sequence data. We have previously developed Kaptive, a freely available tool for rapid typing of Klebsiella capsule and LPS loci from genome sequences. Kaptive is now used widely in the global research community and has facilitated new insights into Klebsiella capsule and LPS diversity. Here we present an update to Kaptive facilitating i) the identification of 16 additional novel capsule loci, and ii) the prediction of immunologically relevant LPS O2 antigen subtypes. These updates will enable enhanced sero-epidemiological surveillance for K. pneumoniae, to inform the design of vaccines and other novel Klebsiella control strategies. Data summaryO_LIThe updated code and reference databases for Kaptive are available at https://github.com/katholt/Kaptive C_LIO_LIGenome accessions from which reference sequences of novel K loci were defined are listed in Supplementary Table 1, and genomes from which these loci were detected (along with the corresponding Kaptive output) are listed in Supplementary Table 2. C_LIO_LIAccessions for the genomes screened for O types/subtypes (along with the corresponding Kaptive output) are listed in Supplementary Table 3. C_LI The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Repositories1.1 RepositoriesGenome sequence from which the novel K locus KL182 was defined has been deposited under the accession JAJHNT000000000.

genomics↗

bioRxiv2021

Polypolish: short-read polishing of long-read bacterial genome assemblies

Long-read-only bacterial genome assemblies usually contain residual errors, most commonly homopolymer-length errors. Short-read polishing tools can use short reads to fix these errors, but most rely on short-read alignment which is unreliable in repeat regions. Errors in such regions are therefore challenging to fix and often remain after short-read polishing. Here we introduce Polypolish, a new short-read polisher which uses all-per-read alignments to repair errors in repeat sequences that other polishers cannot. Polypolish performed well in benchmarking tests using both simulated and real reads, and it almost never introduced errors during polishing. The best results were achieved by using Polypolish in combination with other short-read polishers. Author summaryRecent improvements in Oxford Nanopore Technologies sequencing platforms and assembly algorithms have made it easier than ever to generate complete bacterial genome sequences. However, Oxford Nanopore genome sequences suffer from errors that limit their utility in downstream analyses. To fix these errors, one can polish the genome with Illumina sequencing, exploiting the fact that Oxford Nanopore and Illumina sequencing have different error profiles. There are several polishing tools which can fix most errors in an Oxford Nanopore genome, but they struggle with errors in repetitive regions of the genome. With this in mind, we have developed a polisher, Polypolish, which uses a novel approach that allows it to fix more errors in genomic repeats. Our results show that Polypolish is both effective at repairing sequence errors and very unlikely to introduce new errors. Polypolish can often fix errors that other polishers cannot and vice versa, so the best results come from using a combination of tools. Polypolish therefore has an important role in bacterial genome assembly methods that aim for the highest possible sequence accuracy.

bioinformatics↗

bioRxiv2021

Trycycler: consensus long-read assemblies for bacterial genomes

Assembly of bacterial genomes from long-read data (generated by Oxford Nanopore or Pacific Biosciences platforms) can often be complete: a single contig for each chromosome or plasmid in the genome. However, even complete bacterial genome assemblies constructed solely from long reads still contain a variety of errors, and different assemblies of the same genome often contain different errors. Here, we present Trycycler, a tool which produces a consensus assembly from multiple input assemblies of the same genome. Benchmarking using both simulated and real sequencing reads showed that Trycycler consensus assemblies contained fewer errors than any of those constructed with a single long-read assembler. Post-assembly polishing with Medaka and Pilon further reduced errors and yielded the most accurate genome assemblies in our study. As Trycycler can require human judgement and manual intervention, its output is not deterministic, and different users can produce different Trycycler assemblies from the same input data. However, we demonstrated that multiple users with minimal training converge on similar assemblies that are consistently more accurate than those produced by automated assembly tools. We therefore recommend Trycycler+Medaka+Pilon as an ideal approach for generating high-quality bacterial reference genomes. Data availabilitySupplementary figures, tables and code can be found at: github.com/rrwick/Trycycler-paper Reads, assemblies and reference sequences can be found at: bridges.monash.edu/articles/dataset/Trycycler_paper_dataset/14890734

bioinformatics↗

bioRxiv2021

Recovery of small plasmid sequences via Oxford Nanopore sequencing

Oxford Nanopore Technologies (ONT) sequencing platforms currently offer two approaches to whole-genome native-DNA library preparation: ligation and rapid. In this study, we compared these two approaches for bacterial whole-genome sequencing, with a specific aim of assessing their ability to recover small plasmid sequences. To do so, we sequenced DNA from seven plasmid-rich bacterial isolates in three different ways: ONT ligation, ONT rapid and Illumina. Using the Illumina read depths to approximate true plasmid abundance, we found that small plasmids (<20 kbp) were underrepresented in ONT ligation read sets (by a mean factor of [~]4) but were not underrepresented in ONT rapid read sets. This effect correlated with plasmid size, with the smallest plasmids being the most underrepresented in ONT ligation read sets. We also found lower rates of chimeric reads in the rapid read sets relative to ligation read sets. These results show that when small plasmid recovery is important, ONT rapid library preparations are preferable to ligation-based protocols. Impact statementResearchers who use Oxford Nanopore Technologies (ONT) platforms to sequence bacterial genomes can currently choose from two library preparation methods. The first is a ligation-based approach, which uses ligase to attach sequencing adapters to the ends of DNA molecules. The second is a rapid approach, which uses a transposase enzyme to cleave DNA and attach adapters in a single step. There are advantages to each preparation, for example ligation can produce better yields but rapid is a simpler procedure. Our study reveals another advantage of rapid preparations: they are more effective at sequencing small plasmids. We show that sequencing of ligation-based libraries yields fewer reads derived from small plasmids, making such plasmids harder to detect in bacterial genomes. Since small plasmids can contain clinically relevant genes, including antimicrobial resistance (AMR) or virulence determinants, their exclusion could lead to unreliable conclusions that have serious consequences for AMR surveillance and prediction. We therefore recommend that researchers performing ONT-only sequencing of bacterial genomes should consider using rapid preparations whenever small plasmid recovery is important. Data summarySupplementary figures, tables, data and code can be found at: github.com/rrwick/Small-plasmid-Nanopore

bioinformatics↗

bioRxiv2020

Genomic surveillance framework and global population structure for Klebsiella pneumoniae

K. pneumoniae is a leading cause of antimicrobial-resistant (AMR) healthcare-associated infections, neonatal sepsis and community-acquired liver abscess, and is associated with chronic intestinal diseases. Its diversity and complex population structure pose challenges for analysis and interpretation of K. pneumoniae genome data. Here we introduce Kleborate, a tool for analysing genomes of K. pneumoniae and its associated species complex, which consolidates interrogation of key features of proven clinical importance. Kleborate provides a framework to support genomic surveillance and epidemiology in research, clinical and public health settings. To demonstrate its utility we apply Kleborate to analyse publicly available Klebsiella genomes, including clinical isolates from a pan-European study of carbapenemase-producing Klebsiella, highlighting global trends in AMR and virulence as examples of what could be achieved by applying this genomic framework within more systematic genomic surveillance efforts. We also demonstrate the application of Kleborate to detect and type K. pneumoniae from gut metagenomes.

genomics↗

bioRxiv2020

Genomic adaptations to an endolithic lifestyle in the coral-associated alga Ostreobium

The green alga Ostreobium is an important coral holobiont member, playing key roles in skeletal decalcification and providing photosynthate to bleached corals that have lost their dinoflagellate endosymbionts. Ostreobium lives in the corals skeleton, a low-light environment with variable pH and O{square} availability. We present the Ostreobium nuclear genome and a metatranscriptomic analysis of healthy and bleached corals to improve our understanding of Ostreobiums adaptations to its extreme environment and its roles as a coral holobiont member. The Ostreobium genome has 10,663 predicted protein-coding genes and shows adaptations for life in low and variable light conditions and other stressors in the endolithic environment. This alga presents a rich repertoire of light-harvesting complex proteins but lacks many genes for photoprotection and photoreceptors. It also has a large arsenal of genes for oxidative stress response. An expansion of extracellular peptidases suggests that Ostreobium may supplement its energy needs by feeding on the organic skeletal matrix, and a diverse set of fermentation pathways allow it to live in the anoxic skeleton at night. Ostreobium depends on other holobiont members for vitamin B12, and our metatranscriptomes identify potential bacterial sources. Metatranscriptomes showed Ostreobium becoming a dominant agent of photosynthesis in bleached corals and provided evidence for variable responses among coral samples and different Ostreobium genotypes. Our work provides a comprehensive understanding of the adaptations of Ostreobium to its extreme environment and an important genomic resource to improve our comprehension of coral holobiont resilience, bleaching and recovery.

genomics↗

bioRxiv2020

GeneMates: an R package for Detecting Horizontal Gene Co-transfer between Bacteria Using Gene-gene Associations Controlled for Population Structure

Antimicrobial resistance (AMR) in bacteria has been a global threat to public health for decades. A well-known driving force for the emergence, evolution and dissemination of genetic AMR determinants in bacterial populations is horizontal gene transfer, which is frequently mediated by mobile genetic elements (MGEs). Some MGEs can capture, maintain, and rearrange multiple AMR genes in a donor bacterium before moving them into recipients, giving rise to a phenomenon called horizontal gene co-transfer (HGcoT). This physical linkage or co-localisation between mobile AMR genes is of particular concern because it facilitates rapid dissemination of multidrug resistance within and across bacterial populations, providing opportunities for co-selection of AMR genes and limiting our therapeutic options. The study of HGcoT can be benefited from large-scale whole-genome sequencing (WGS) data, however, by far most published studies of HGcoT only consider simple co-occurrence measures, which can be confounded by strong bacterial population structure due to clonal reproduction, leading to spurious associations. To address this issue, we present GeneMates, an R package implementing a network approach to identification of HGcoT using WGS data. The package enables users to test for associations between presence-absence of bacterial genes using univariate linear mixed models controlling for population structure based on core-genome variation. Furthermore, when physical distances between genes of interest are measurable in bacterial genomes, users can evaluate distance consistency to further support their inference of putative horizontally co-transferred genes, whose co-occurrence cannot be completely explained by the population structure. We demonstrate how this package can be used to identify co-transferred AMR genes and recover known MGEs from Escherichia coli and Salmonella Typhimurium WGS data. GeneMates is accessible at github.com/wanyuac/GeneMates.

genomics↗

bioRxiv2020

Genome-resolved metagenomics and detailed geochemical speciation analyses yield new insights into microbial mercury cycling in geothermal springs

Geothermal systems emit substantial amounts of aqueous, gaseous and methylated mercury, but little is known about microbial influences on mercury speciation. Here we report results from genome-resolved metagenomics and mercury speciation analysis of acid warm springs in the Ngawha Geothermal Field (<55 {degrees}C, pH < 4.5), Northland Region, Aotearoa (New Zealand). Our aim was to identify the microorganisms genetically equipped for mercury methylation, demethylation, or Hg(II) reduction to volatile Hg(0) in these springs. Dissolved total and methylated mercury concentrations in two adjacent springs with different mercury speciation ranked among the highest reported from natural sources (250-16000 ng L-1 and 0.5-13.9 ng L-1, respectively). Total solid mercury concentrations in spring sediments ranged from 1273 to 7000 {micro}g g-1. In the context of such ultra-high mercury levels, the geothermal microbiome was unexpectedly diverse, and dominated by acidophilic and mesophilic sulfur- and iron-cycling bacteria, mercury- and arsenic-resistant bacteria, and thermophilic and acidophilic archaea. Integrating microbiome structure and metagenomic potential with geochemical constraints, we constructed a conceptual model for biogeochemical mercury cycling in geothermal springs. The model includes abiotic and biotic controls on mercury speciation, and illustrates how geothermal mercury cycling may couple to microbial community dynamics and sulfur and iron biogeochemistry. IMPORTANCELittle is currently known about biogeochemical mercury cycling in geothermal systems. This manuscript presents an important new conceptual model, supported by genome-resolved metagenomic analysis and detailed geochemical measurements. This work provides a framework for studying natural geothermal mercury emissions globally. Specifically, our findings have implications for mercury speciation in wastewaters from geothermal power plants and the potential environmental impacts of microbially and abiotically formed mercury species, particularly where mobilized in spring waters that mix with surface- or ground-waters. Furthermore, in the context of thermophilic origins for microbial mercury volatilisation, this report yields new insights into how such processes may have evolved alongside microbial mercury methylation/demethylation, and the environmental constraints imposed by the geochemistry and mineralogy of geothermal systems.

microbiology↗

bioRxiv2019

Correcting index databases improves metagenomic studies

Assessing the taxonomic composition of metagenomic samples is an important first step in understanding the biology and ecology of microbial communities in complex environments. Despite a wealth of algorithms and tools for metagenomic classification, relatively little effort has been put into the critical task of improving the quality of reference indices to which metagenomic reads are assigned. Here, we inferred the taxonomic composition of 404 publicly available metagenomes from human, marine and soil environments, using custom index databases modified according to two factors: the number of reference genomes used to build the databases, and the monophyletic strictness of species definitions. Index databases built following the NCBI taxonomic system were also compared to others using Genome Taxonomy Database (GTDB) taxonomic redefinitions. We observed a considerable increase in the rate of read classification using modified reference index databases as compared to a default NCBI RefSeq database, with up to a 4.4-, 6.4- and 2.2-fold increase in classified reads per sample for human, marine and soil metagenomes, respectively. Importantly, targeted correction for 70 common human pathogens and bacterial genera in the index database increased their specific detection levels in human metagenomes. We also show the choice of index database can influence downstream diversity and distance estimates for microbiome data. Overall, the study shows a large amount of accessible information in metagenomes remains unexploited using current methods, and that the same data analysed using different index databases could potentially lead to different conclusions. These results have implications for the power and design of individual microbiome studies, and for comparison and meta-analysis of microbiome datasets.

bioinformatics↗

bioRxiv2019

Performance of neural network basecalling tools for Oxford Nanopore sequencing

Basecalling, the computational process of translating raw electrical signal to nucleotide sequence, is of critical importance to the sequencing platforms produced by Oxford Nanopore Technologies (ONT). Here we examine the performance of different basecalling tools, looking at accuracy at the level of bases within individual reads and at majority-rules consensus basecalls in an assembly. We also investigate some additional aspects of basecalling: training using a taxon-specific dataset, using a larger neural network model and improving consensus basecalls in an assembly via additional signal-level analysis with Nanopolish. Training basecallers on taxon-specific data resulted in a significant boost in consensus accuracy, mostly due to the reduction of errors in methylation motifs. A larger neural network was able to improve both read and consensus accuracy, but at a cost to speed. Improving consensus sequences ( polishing) with Nanopolish somewhat negates the accuracy differences in basecallers, but pre-polish accuracy does have an effect on post-polish accuracy, so basecaller choice is still relevant even when Nanopolish is used.

bioinformatics↗

bioRxiv2018

Convergence of virulence and multidrug resistance in a single plasmid vector in multidrug-resistant Klebsiella pneumoniae ST15

SYNOPSISO_ST_ABSBackgroundC_ST_ABSMultidrug resistance (MDR) and hypervirulence (hv) are typically observed in separate Klebsiella pneumoniae populations. However, convergent strains with both properties have been documented and potentially pose a high risk to public health in the form of invasive infections with limited treatment options.\n\nObjectivesTo characterize the genetic determinants of virulence and antimicrobial resistance (AMR) in two ESBL-producing K. pneumoniae isolates belonging to the international MDR clone ST15.\n\nMethodsThe complete genome sequences of both isolates, including their plasmids, were resolved using Illumina and Oxford Nanopore sequencing.\n\nResultsBoth isolates carried large mosaic plasmids in which AMR and virulence loci have converged within the same vector. These closely related mosaic hv-MDR plasmids include sequences typical of the K. pneumoniae virulence plasmid 1 (KpVP-1; including aerobactin synthesis locus iuc) fused with sequences typical of IncFIIK conjugative AMR plasmids. One hv-MDR plasmid carried three MDR elements encoding the ESBL gene blaCTX-M-15 and eight other AMR genes (blaTEM, aac3-IIa, aph3-Ia, dfrA1, satA2, blaSHV, sul1, aadA1). The other carried remnants of these elements encoding blaTEM and aac3-IIa, and blaCTX-M-15 was located in a second plasmid in this isolate. The two isolates originated from patients hospitalized in Norway but have epidemiological and genomic links to Romania.\n\nConclusionsThe presence of both virulence and AMR determinants on a single vector enables simultaneous transfer in a single event and potentially rapid emergence of hv-MDR K. pneumoniae clones. This highlights the importance of monitoring for such convergence events with stringent genomic surveillance.

genomics↗