Biology subjects

Page, A. J.

Publications and source records attributed to Page, A. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Enteroaggregative Escherichia clade I from Nigeria

Escherichia coli, the Escherichia type species, is present in mammalian and avian intestinal microbiota, and includes both commensals and pathogens. Other Escherichia species are understudied because they are less commonly associated with human disease and because of paucity of tools that can correctly delineate them from E. coli. However, other species of this genus including Escherichia albertii and Escherichia fergusonii are repeatedly reported as diarrhoeagenic. We hypothesized that some bacteria fitting the definition of enteroaggregative E. coli (EAEC) belong to species other than E. coli. We used phylogeny to determine the species of 2,818 Escherichia genomes from diarrhoea epidemiology studies in Nigeria. Phylogeny speciation was confirmed using GTDB-tk and ClermonTyping. Virulence genes were detected using ARIBA/Virulencefinder database and multilocus sequence typing performed using the Achtman scheme. Fourteen non-coli Escherichia genomes were identified-- Escherichia clade I ST485 (11), Escherichia ruysiae ST5792 (2) and Escherichia fergusonii ST5636 (1). All the Escherichia clade I ST485 carry EAEC virulence genes aap, aar, astA and air, as well as hlyF, eatA, tsh, traT, and chuA virulence genes. Interestingly, 62% of enteroaggregative Escherichia clade I ST485 genomes listed on Enterobase are from Africa isolates, despite only 3% of genomes overall coming from the continent. Our results suggest that non-coli Escherichia species are infrequently isolated from human stool, but, when they are, they are misidentified as E. coli so that their significance is largely overlooked. Escherichia clade I ST485 is a globally disseminated enteroaggregative Escherichia clade I lineage that is common in Africa. Author SummaryEscherichia clade I are rarely associated with disease and because of the difficulty in differentiating them from Escherichia coli in routine laboratory, they are often misidentified as Escherichia coli leading to the underestimation of their impact on the burden of disease. Additionally, some clones of Escherichia clade I also carry genetic markers that have been used to define Enteroaggregative Escherichia coli (EAEC), a cause of persistent diarrhoea in developing countries and travellers diarrhoea in developed economies. EAEC has also been associated with malnutrition and poor growth among children in developing economies. We here describe clones of Escherichia clade I (ST485) that carries enteroaggregative genes and in some cases, recovered from diarrhoeal cases. We show from genomes deposited on Enterobase and our study, that this clone is globally disseminated, often associated with human infections and often misidentified as Escherichia coli. We also describe other non-coli Escherichia other than Escherichia clade I isolated from humans. We suggest that the Escherichia clade I clone carrying enteroaggregative genes may be described as Enteroaggregative Escherichia clade I.

microbiology↗

bioRxiv2026

Micro-engineered Konjac Glucomannan-Montmorillonite Hybrids as Multifunctional Biomaterials for Addressing Diet-Induced Obesity in Mice

The growing prevalence of obesity necessitates innovative treatments. This study investigates a spray-dried konjac glucomannan-montmorillonite (KGM-MMT) hybrid designed to combine the fermentable, satiety-promoting effects of KGM with the lipid-binding and anti-inflammatory properties of MMT. In HFD-fed mice treated for 42 days with 2% w/w KGM-MMT, body weight gain was reduced by 7.6%, with an AUC of 5094[{+/-}[52.95, compared to 5513[{+/-}[81.35 in HFD controls (p < 0.0001). Serum IL-6 concentrations were reduced by 97% (p = 0.0002), while blood glucose decreased by 46% (p < 0.0001), outperforming reductions seen with MMT (24%, p = 0.0271) and KGM (16%, ns). Gut microbiota profiling demonstrated a significant 6.2-log[ fold increase in Lactobacillaceae (p = 0.023) and a 2.4-log[ fold increase in Enterococcaceae (p = 0.015) with KGM-MMT treatment. Predicted functional shifts revealed a 1.9-fold increase in short-chain fatty acid synthesis pathways and a 5.4-fold increase in bile acid deconjugation. Although the KGM-MMT hybrid did not consistently outperform its individual components in all measurements within the current study, it generally consolidated their metabolic benefits within a single dosage form. These findings support the utility of spray-dried KGM-MMT as a gut-targeted dietary strategy with additive effects on metabolic health. Future studies should explore underlying mechanisms and dosage effects of the hybrid formulation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/701163v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@738445org.highwire.dtl.DTLVardef@1f0d465org.highwire.dtl.DTLVardef@86e5aorg.highwire.dtl.DTLVardef@184fba8_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LISpray-dried KGM-MMT reduced HFD-induced weight gain by 7.6% in obese mice C_LIO_LISerum IL-6 and glucose levels decreased by 97% and 46%, respectively C_LIO_LI6.2-log[J and 2.4-log[J increases in Lactobacillaceae & Enterococcaceae relative abundance C_LIO_LIBile acid deconjugation and SCFA pathways increased 5.4- and 1.9-fold C_LIO_LIKGM-MMT microparticles offer additive gut-targeted benefits in metabolic disease C_LI

bioengineering↗

bioRxiv2024

Genomic Epidemiology of SARS-CoV-2 in Norfolk, UK, March 2020 - December 2022

BackgroundIn the UK, the COVID-19 Genomics UK Consortium (COG-UK) established a real time national genomic surveillance system during the COVID-19 pandemic, producing centralised data for monitoring SARS-CoV-2. As a COG-UK partner, Quadram Institute Bioscience (QIB) in Norfolk sequenced over 87,000 SARS-CoV-2 genomes, contributing to the region becoming densely sequenced. Retrospective analysis of SARS-CoV-2 lineage dynamics in this region may contribute to preparedness for future pandemics. Methods29,406 SARS-CoV-2 whole genome sequences and corresponding metadata from Norfolk were extracted from the COG-UK dataset, sampled between March 2020 and December 2022, representing 9.9% of regional COVID-19 cases. Sequences were lineage typed using Pangolin, and subsequent lineage analysis carried out in R using RStudio and related packages, including graphical analysis using ggplot2. Results401 global lineages were identified, with 69.8% appearing more than once and 31.2% over ten times. Temporal clustering identified six lineage communities based on first lineage emergence. Alpha, Delta, and Omicron variants of concern (VOC) accounted for 8.6%, 34.9% and 48.5% of sequences respectively. These formed four regional epidemic waves alongside the remaining lineages which appeared in the early pandemic prior to VOC designation and were termed pre-VOC lineages. Regional comparison highlighted variability in VOC epidemic wave dates dependent on location. ConclusionThis study is the first to assess SARS-CoV-2 diversity in Norfolk across a large timescale within the COVID-19 pandemic. SARS-CoV-2 was both highly diverse and dynamic throughout the Norfolk region between March 2020 - December 2022, with a strong VOC presence within the latter two thirds of the study period. The study also displays the utility of incorporating genomic epidemiological methods into pandemic response. Data summaryThe COG-UK collection of SARS-CoV-2 sequences and metadata are available for public download on their archive website under the Latest sequence data heading . Sequence names for all sequences used from this dataset alongside GISAID accession numbers where present are available in Supplementary Table 1. Impact statementWe extracted 29,406 regional Norfolk based SARS-CoV-2 sequences from the COG-UK SARS-CoV-2 dataset and revealed significant regional diversity and dynamic emergence of variant of concern (VOC) epidemic waves - spanning Alpha, Delta and Omicron lineages. We also applied statistical modelling to complement genomic methodology, with temporal clustering of significant first lineage emergences chronologically matching VOC waves and subwaves. The study highlights the importance of integration of genomic epidemiology into public health strategies for pandemic response, and the utility of using this data for retrospective research.

genomics↗

bioRxiv2024

hAMRonization: Enhancing antimicrobial resistance prediction using the PHA4GE AMR detection specification and tooling

The detection of antimicrobial resistance (AMR) markers directly from genomic or metagenomic data is becoming a standard clinical and public health procedure. This has resulted in the development of a number of different bioinformatic AMR prediction tools. Although many may implement similar principles, these tools differ significantly in their supported inputs, search algorithms, parameterisation, and underlying reference databases. Each of these tools generates a report of detected AMR genes or variants in a distinct, non-standard, format. This presents a huge barrier to the comparison of results and to the modularity of tools for AMR gene prediction within bioinformatic workflows. In collaboration with 17 public health laboratories across 10 countries, the Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) data structures working group has developed and piloted a standardized output specification for the bioinformatic detection of AMR from microbial genomes. In this report, we discuss hAMRonization, a python package and command-line utility, which implements PHA4GEs AMR specification to combine the outputs of disparate antimicrobial resistance gene detection tools into a single unified format. hAMRonization can be easily extended and currently supports 18 different tools (both species-agnostic and species-specific) for the detection of genes and/or variants conferring AMR. The harmonized reports are available in tabular form, JSON format or through an interactive HTML file (e.g., https://maguire-lab.github.io/assets/interactive_report_demo.html) that can be opened within the browser for navigable data exploration. As of 2024-03-07 hAMRonization has been downloaded [~]12,500 times, incorporated into >9 public bioinformatic tools and workflows, and been internally adopted by several national and international public health groups. The hAMRonization tool and underlying specification are open-source and freely available through PyPI, conda and GitHub (https://github.com/pha4ge/hAMRonization).

bioinformatics↗

bioRxiv2023

Scalable neighbour search and alignment with uvaia

Despite millions of SARS-CoV-2 genomes being sequenced and shared globally, manipulating such data sets is still challenging, especially selecting sequences for focused phylogenetic analysis. We present a novel method, uvaia, which is based on partial and exact sequence similarity for quickly extracting database sequences similar to query sequences of interest. Many SARS-CoV-2 phylogenetic analyses rely on very low numbers of ambiguous sites as a measure of quality since ambiguous sites do not contribute to single nucleotide polymorphism (SNP) differences, which uvaia alleviates by using measures of sequence similarity that consider partially ambiguous sites. Such fine-grained definition of similarity allows not only for better phylogenetic analyses, but also for improved classification and biogeographical inferences. Uvaia works natively with compressed files, can use multiple cores and efficiently utilises memory, being able to analyse large data sets on a standard desktop.

bioinformatics↗

bioRxiv2022

Characterisation of neonatal Staphylococcus capitis NRCS-A isolates compared with non NRCS-A Staphylococcus capitis from neonates and adults.

Staphylococcus capitis is a frequent cause of Late-Onset Sepsis (LOS) in neonates admitted to Neonatal Intensive Care Units (NICU). The NRCS-A clone of S. capitis has been isolated from NICUs globally although the reasons for the global success of this clone are not understood. We analysed a collection of S. capitis colonising babies admitted to two NICUs, one in the UK and one in Germany as well as corresponding pathological clinical isolates. Genome analysis identified 3 groups; non-NRCS-A isolates, NRCS-A isolates, and a group of proto NRCS-A - isolates closely related to NRCS-A but not associated with neonatal infection. All bloodstream isolates belonged to the NRCS-A group and were indistinguishable from strains carried on the skin or in the gut. NRCS-A isolates showed increased tolerance to chlorhexidine and antibiotics relative to the other S. capitis as well as enhanced ability to grow at higher pH values. Analysis of 138 pangenomes of the clades identified characteristic nsr and tarJ genes in the NRCS-A and proto groups with a CRISPR-cas system only seen in NRCS-A isolates which also showed enrichment of genes for metal acquisition and transport. We found evidence for transmission of S. capitis NRCS-A within NICU, with related isolates shared between babies and multiple acquisitions by some babies. Our data show NRCS-A strains commonly colonise uninfected babies in NICU representing a potential reservoir for potential infection. This work provides more evidence that adaptation to survive in the gut and on skin facilitates spread of NRCS-A, and that metal acquisition and tolerance may be important to the biology of NRCS-A. Understanding how NRCS-A survives in NICUs can help develop infection control procedures against this clone.

genomics↗

bioRxiv2022

Genomic Surveillance of SARS CoV2 in COVID-19 vaccinated healthcare workers in Lebanon.

The emergence of SARS-CoV-2 variants including the Delta and Omicron along with waning of vaccine-induced immunity over time contributed to increased rates of breakthrough infection specifically among healthcare workers (HCWs). SARS-CoV-2 genomic surveillance is an important tool for timely detection and characterization of circulating variants as well as monitoring the emergence of new strains. Our study is the first national SARS-CoV-2 genomic surveillance among HCWs in Lebanon. We collected 250 samples from five hospitals across Lebanon between December 2021 and January 2022. We extracted viral RNA and performed whole genome sequencing using the Illumina NextSeq 500 platform. A total of 133 (57.1%) samples belonging to the Omicron (BA.1.1) sub-lineage were identified, as well as 44 (18.9%) samples belonging to the BA.1 sub-lineage, 28 (12%) belonging to the BA.2 sub-lineage, and only 15 (6.6%) samples belonging to the Delta variant sub-lineage B.1.617.2. These results show that Lebanon followed the global trend in terms of circulating SARS-CoV-2 variants with Delta rapidly replaced by the Omicron variant. This study underscores the importance of continuous genomic surveillance programs in Lebanon for the timely detection and characterization of circulating variants. The latter is critical to guide public health policy making and to timely implement public health interventions.

genomics↗

bioRxiv2022

LoRTIS Software Suite: Transposon mutant analysis using long-read sequencing

To date transposon insertion sequencing (TIS) methodologies have used short-read nucleotide sequencing technology. However, short-read sequences are unlikely to be matched correctly within repeated genomic regions which are longer than the sequence read. This drawback may be overcome using long-read sequencing technology. We have developed a suite of new analysis tools, the "LoRTIS software suite" (LoRTIS-SS), that produce transposon insertion site mapping data for a reference genome using long-read nucleotide sequence data. Long-read nucleotide sequence data can be applied to TIS, this enables the unique mapping of transposon insertion sites within long genomic repeated sequences. Here we present long-read TIS analysis software, LoRTIS-SS, which uses the Snakemake framework to manage the workflow. A docker image is provided, complete with dependencies and ten scripts are included for experiment specific data processing before or after use of the main workflow. The workflow uses long-read nucleotide sequence data such as those generated by the MinION sequencer (Oxford Nanopore Technologies). The unique mapping properties of long-read sequence data were exemplified by reference to the ribosomal RNA genes of Escherichia coli strain BW25113, of which there are 7 copies of [~]4.9 kbases in length that are at least 99% similar. Of reads that matched within rRNA genes, approximately half matched uniquely. The software workflow outputs data compatible with the established Bio-TraDIS analysis toolkit allowing for existing workflows to be easily upgraded to support long-read sequencing.

bioinformatics↗

bioRxiv2021

Tatajuba - Exploring the distribution of homopolymer tracts

Length variation of homopolymeric tracts, which induces phase variation, is known to regulate gene expression leading to phenotypic variation in a wide range of bacterial species. There is no specialised bioinformatics software which can, at scale, exhaustively explore and describe these features from sequencing data. Identifying these is non-trivial as sequencing and bioinformatics methods are prone to introducing artefacts when presented with homopolymeric tracts due to the decreased base diversity. We present tatajuba, which can automatically identify potential homopolymeric tracts and their putative phenotypic impact, allowing for rapid investigation. We use it to detect all tracts in two separate datasets, one of Campylobacter jejuni and one of three Bordetella species, and to highlight those tracts that are polymorphic across samples. With this we confirm homopolymer tract variation with phenotypic impact found in previous studies and additionally find many more with potential variability. The software is written in C and is available under the open source license GNU GPL version 3 from https://github.com/quadram-institute-bioscience/tatajuba.

bioinformatics↗

bioRxiv2021

Linking carbohydrate structure with function in the human gut microbiome using hybrid metagenome assemblies

BackgroundComplex carbohydrates that escape digestion in the small intestine, are broken down in the large intestine by enzymes encoded by the gut microbiome. This is a symbiotic relationship between particular microbes and the host, resulting in metabolic products that influence host gut health and are exploited by other microbes. However, the role of carbohydrate structure in directing microbiota community composition and the succession of carbohydrate-degrading microbes is not fully understood. Here we take the approach of combining data from long and short read sequencing allowing recovery of large numbers of high quality genomes, from which we can predict carbohydrate degrading functions, and impact of carbohydrate on microbial communities. ResultsIn this study we evaluate species-level compositional variation within a single microbiome in response to six structurally distinct carbohydrates in a controlled model gut using hybrid metagenome assemblies. We identified 509 high-quality metagenome-assembled genomes (MAGs) belonging to ten bacterial classes and 28 bacterial families. We found dynamic variations in the microbiome amongst carbohydrate treatments, and over time. Using these data, the MAGs were characterised as primary (0h to 6h) and secondary degraders (12h to 24h). Annotating the MAGs with the Carbohydrate Active Enzyme (CAZyme) database we are able to identify species which are enriched through time and have the potential to actively degrade carbohydrate substrates. ConclusionsRecent advances in sequencing technology allowed us to identify significant unexplored diversity amongst starch degrading species in the human gut microbiota including CAZyme profiles and complete MAGs. We have identified changes in microbial community composition in response to structurally distinct carbohydrate substrates, which can be directly related to the CAZyme complement of the enriched MAGs. Through this approach, we have identified a number of species which have not previously been implicated in starch degradation, but which have the potential to play an important role.

microbiology↗

bioRxiv2021

Invasive atypical non-typhoidal Salmonella in The Gambia

BackgroundInvasive non-typhoidal Salmonella (iNTS) disease continues to be a significant public health problem in sub-Saharan Africa. Common clinical misdiagnosis, antimicrobial resistance, high case fatality and lack of a vaccine make iNTS a priority for global health research. Using whole genome sequence analysis of 164 invasive Salmonella isolates obtained through population-based surveillance between 2008 and 2016, we conducted genomic analysis of the serovars causing invasive Salmonella diseases in rural Gambia. ResultsThe incidence of iNTS varied over time. The proportion of atypical serovars causing disease increased over time from 40% to 65% compared to the typical serovars Enteritidis and Typhimurium decreasing from 30% to 12%. Overall iNTS case fatality was 10% with 10% fatality in cases of atypical iNTS. Genetic virulence factors were identified in 14/70 (20%) typical serovars and 45/68 (66%) of the atypical serovars and were associated with: invasion, proliferation and/or translocation (Clade A); and host colonization and immune modulation (Clade G). Among Enteritidis isolates, 33/40 were resistant to [≥]4 the antimicrobials tested, except for ciprofloxacin, to which all isolates were susceptible. Resistance was low in Typhimurium isolates, however, all16 isolates were resistant to gentamicin. ConclusionThe increase in incidence and proportion of iNTS disease caused by atypical serovars is concerning. The increased proportion of atypical serovars and the high associated case fatality may be related to acquisition of specific genetic virulence factors. These factors may provide a selective advantage to the atypical serovars. Investigations should be conducted elsewhere in Africa to identify potential changes in the distribution iNTS serovars and the extent of these virulence elements.

genomics↗

bioRxiv2020

Long-read-sequenced reference genomes of the seven major lineages of enterotoxigenic Escherichia coli (ETEC) circulating in modern time

BackgroundEnterotoxigenic Escherichia coli (ETEC) is an enteric pathogen responsible for the majority of diarrheal cases worldwide. ETEC infections are estimated to cause 80,000 fatalities per year, with the highest rates of burden, ca 75 million cases per year, amongst children under five years of age in resource-poor countries. It is also the leading cause of diarrhoea in travellers. Previous large-scale sequencing studies have found seven major ETEC lineages currently in circulation worldwide. ResultsWe used PacBio long-read sequencing combined with Illumina sequencing to create high-quality complete reference genomes for each of the major lineages with manually curated chromosomes and plasmids. The plasmids carrying ETEC virulence genes were compared to other available long-read sequenced ETEC strains using blastn. The ETEC reference strains harbour between two and five plasmids, including virulence, antibiotic resistance and phage-plasmids. The virulence plasmids carrying the colonisation factors are highly conserved as shown by comparison with plasmids with other ETEC strains and confirm that the plasmids and chromosomes of ETEC are both crucial for ETEC virulence and success as pathogens. ConclusionWe confirm that the major ETEC lineages all harbour conserved plasmids that have been associated with their respective background genomes for decades. The in-depth analysis of gene content, synteny and correct annotations of plasmids will elucidate other plasmids with and without virulence factors in related bacterial species. These reference genomes allow for fast and accurate comparison between different ETEC strains, and these data will form the foundation of ETEC genomics research for years to come.

genomics↗

bioRxiv2020

A global resource for genomic predictions of antimicrobial resistance and surveillance of Salmonella Typhi at Pathogenwatch

BackgroundMicrobial whole-genome sequencing (WGS) is now increasingly used to inform public health investigations of infectious disease. This approach has transformed our understanding of the global population structure of Salmonella enterica serovar Typhi (S. Typhi), the causative agent of typhoid fever. WGS has been particularly informative for understanding the global spread of multi-drug resistant (MDR) typhoid. As WGS capacity becomes more decentralised, there is a growing opportunity for collaboration and sharing of surveillance data within and between countries to inform disease control policies. This requires freely available, community driven tools that reduce the barriers to access genomic data for public health surveillance and that deliver genomic data on a global scale. MethodsHere we present the Pathogenwatch (https://pathogen.watch/styphi) scheme for S. Typhi, a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data to identify high-risk clones at a population level. Data are delivered in single genome reports or in collections of genomes combined with geographic and other data using trees, maps and tables. ResultsWe show that the clustering of S. Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are largely concordant with phenotypic drug susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from over 4,300 public genomes available in the application. ConclusionsPathogenwatch democratises genomic epidemiology of S. Typhi by providing an intuitive entry point for the analysis of WGS and linked epidemiological data, enabling international public health monitoring of the emergence and spread of high risk clones.

genomics↗

bioRxiv2020

CoronaHiT: large scale multiplexing of SARS-CoV-2 genomes using Nanopore sequencing

The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 96 samples at a time. There is a need, however, for a flexible, platform agnostic, method that can provide multiple throughput options depending on changing requirements as the pandemic peaks and troughs. Here we present CoronaHiT, a method capable of multiplexing up to 96 small genomes on a single MinION flowcell or >384 genomes on Illumina NextSeq, using transposase mediated addition of adapters and PCR based addition of barcodes to ARTIC PCR products. We demonstrate the method by sequencing 95 and 59 SARS-CoV-2 genomes for routine and rapid outbreak response runs, respectively, on Nanopore and Illumina platforms and compare to the standard ARTIC LoCost nanopore method. Of the 154 samples sequenced using the three approaches, genomes with [≥] 90% coverage (GISAID criteria) were generated for 64.3% of samples for ARTIC LoCost, 71.4% for CoronaHiT-ONT, and 76.6% for CoronaHiT-Illumina and have almost identical clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 96 SARS-CoV-2 genomes per MinION flowcell and that Illumina sequencing can be performed on the same libraries, which will allow significantly higher throughput. CoronaHiT provides increased coverage for higher Ct samples, thereby increasing the number of high quality genomes that pass the GISAID QC threshold. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.

genomics↗

bioRxiv2020

Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

Spoligotyping of Mycobacterium tuberculosis provides a subspecies classification of this major human pathogen. Spoligotypes can be predicted from short read genome sequencing data; however, no methods exist for long read sequence data such as from Nanopore or PacBio. We present a novel software package Galru, which can rapidly detect the spoligotype of a Mycobacterium tuberculosis sample from as little as a single uncorrected long read. It allows for near real-time spoligotyping from long read data as it is being sequenced, giving rapid sample typing. We compare it to the existing state of the art software and find it performs identically to the results obtained from short read sequencing data. Galru is freely available from https://github.com/quadram-institute-bioscience/galru under the GPLv3 open source licence.

bioinformatics↗

bioRxiv2019

Taxonomic resolution of the ribosomal RNA operon in bacteria: Implications for its use with long read sequencing

Long-read sequencing technologies enable capture of the full-length of ribosomal RNA operons in a single read. Bacterial cells usually have multiple copies of this ribosomal operon; sequence variation within a species of bacterium can exceed variation between species. For uncultured organisms this may affect the overall taxonomic resolution, to genus level, of the full-length ribosomal operon.

bioinformatics↗

bioRxiv2019

AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments

BackgroundBacteria have evolved over billions of years to survive in a wide range of environments. Currently, there is an incomplete understanding of the genetic basis for mechanisms underpinning survival in stressful conditions, such as the presence of anti-microbials. Transposon mutagenesis has been proven to be a powerful tool to identify genes and networks which are involved in survival and fitness under a given condition by simultaneously assaying the fitness of millions of mutants, thereby relating genotype to phenotype and contributing to an understanding of bacterial cell biology. A recent refinement of this approach allows the roles of essential genes in conditional stress survival to be inferred by altering their expression. These advancements combined with the rapidly falling costs of sequencing now allows comparisons between multiple experiments to identify commonalities in stress responses to different conditions. This capacity however poses a new challenge for analysis of multiple data sets in conjunction.\n\nResultsTo address this analysis need, we have developed AlbaTraDIS; a software application for rapid large-scale comparative analysis of TraDIS experiments that predicts the impact of transposon insertions on nearby genes. AlbaTraDIS can identify genes which are up or down regulated, or inactivated, between multiple conditions, producing a filtered list of genes for further experimental validation as well as several accompanying data visualisations. We demonstrate the utility of our new approach by applying it to identify genes used by Escherichia coli to survive in a wide range of different concentrations of the biocide Triclosan. AlbaTraDIS automatically identified all well characterised Triclosan resistance genes, including the primary target, fabI. A number of new loci were also implicated in Triclosan resistance and the predicted phenotypes for a selection of these were validated experimentally and results showed high consistency with predictions.\n\nConclusionsAlbaTraDIS provides a simple and rapid method to analyse multiple transposon mutagenesis data sets allowing this technology to be used at large scale. To our knowledge this is the only tool currently available that can perform these tasks. AlbaTraDIS is written in Python 3 and is available under the open source licence GNU GPL 3 from https://github.com/quadram-institute-bioscience/albatradis.

bioinformatics↗

bioRxiv2019

Socru: Typing of genome level order and orientation in bacteria

SummaryGenome rearrangements occur in bacteria between repeat sequences and impact growth and gene expression. Homologous recombination can occur between ribosomal operons, which are found in multiple copies in many bacteria. Inversion between indirect repeats and excision/translocation between direct repeats enable structural genome rearrangement. To identify what these rearrangements are by sequencing, reads of several thousand bases are required to span the ribosomal operons. With long read sequencing aiding the routine generation of complete bacterial assemblies, we have developed socru, a typing method for the order and orientation of genome fragments between ribosomal operons, defined against species-specific baselines. It allows for a single identifier to convey the order and orientation of genome level structure and 434 of the most common bacterial species are supported. Additionally, socru can be used to identify large scale misassemblies. Availability and implementationSocru is written in Python 3, runs on Linux and OSX systems and is available under the open source license GNU GPL 3 from https://github.com/quadram-institute-bioscience/socru. Contactgemma.langridge@quadram.ac.uk

bioinformatics↗