ORCID Profile
0000-0001-6288-9958
Current Organisation
Baker IDI Heart and Diabetes Institute
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Publisher: Wiley
Date: 30-08-2012
DOI: 10.1111/J.1462-2920.2012.02852.X
Abstract: Plants are increasingly considered as secondary reservoirs for commensal and pathogenic Escherichia coli strains, but the ecological and functional factors involved in this association are not clear. To address this question, we undertook a comparative approach combining phenotypic and phylogenetic analyses of E. coli isolates from crops and mammalian hosts. Phenotypic profiling revealed significant differences according to the source of isolation. Notably, isolates from plants displayed higher biofilm and extracellular matrix production and higher frequency of utilization of sucrose and the aromatic compound p-hydroxyphenylacetic acid. However, when compared with mammalian-associated strains, they reached lower growth yields on many C-sources commonly used by E. coli. Strikingly, we observed a strong association between phenotypes and E. coli phylogenetic groups. Strains belonging to phylogroup B1 were more likely to harbour traits indicative of a higher ability to colonize plants, whereas phylogroup A and B2 isolates displayed phenotypes linked to an animal-associated lifestyle. This work provides clear indications that E. coli phylogroups are specifically affected by niche-specific selective pressures, and provides an explanation on why E. coli population structures vary in natural environments, implying that different lineages in E. coli have substantially different transmission ecology.
Publisher: Cold Spring Harbor Laboratory
Date: 11-11-2021
DOI: 10.1101/2021.11.10.21266163
Abstract: To examine the previously unknown long-term association between gut microbiome composition and incident type 2 diabetes in a representative population cohort. We collected fecal s les of 5 572 Finns (mean age 48.7 years, 54.1% women) in 2002 who were followed up for incident type 2 diabetes until Dec 31 st , 2017. The s les were sequenced using shotgun metagenomics. We examined associations between gut microbiome compositions and incident diabetes using multivariable-adjusted Cox regression models. We first used the Eastern Finland sub-population to obtain initial findings and validated these in the Western Finland sub-population. Altogether 432 cases of incident diabetes occurred over the median follow-up of 15.8 years. We detected 4 species and 2 clusters consistently associated with incident diabetes in the validation models. These 4 species were Clostridium citroniae (HR, 1.21 95% CI, 1.04-1.42), C. bolteae (HR, 1.20 95% CI, 1.04-1.39), Tyzzerella nexilis (HR, 1.17 95% CI, 1.01-1.36), and Ruminococcus gnavus (HR = 1.17 95% CI, 1.01-1.36). The positively associated clusters, cluster 1 (HR, 1.18 95% CI, 1.02-1.38) and cluster 5 (HR, 1.18 95% CI, 1.02-1.36), mostly consisted of these same species. We observed robust species-level taxonomic features predictive of incident type 2 diabetes over a long-term follow-up. These findings build on and extend previous mainly cross-sectional evidence and further support links between dietary habits, metabolic diseases, and type 2 diabetes that are modulated by the gut microbiome. The gut microbiome could potentially be used to improve risk prediction and to uncover novel therapeutic targets for diabetes.
Publisher: Proceedings of the National Academy of Sciences
Date: 07-2013
Abstract: Genome-wide association studies have the potential to identify causal genetic factors underlying important phenotypes but have rarely been performed in bacteria. We present an association mapping method that takes into account the clonal population structure of bacteria and is applicable to both core and accessory genome variation. C ylobacter is a common cause of human gastroenteritis as a consequence of its proliferation in multiple farm animal species and its transmission via contaminated meat and poultry. We applied our association mapping method to identify the factors responsible for adaptation to cattle and chickens among 192 C ylobacter isolates from these and other host sources. Phylogenetic analysis implied frequent host switching but also showed that some lineages were strongly associated with particular hosts. A seven-gene region with a host association signal was found. Genes in this region were almost universally present in cattle but were frequently absent in isolates from chickens and wild birds. Three of the seven genes encoded vitamin B 5 biosynthesis. We found that isolates from cattle were better able to grow in vitamin B 5 -depleted media and propose that this difference may be an adaptation to host diet.
Publisher: Springer Science and Business Media LLC
Date: 2012
Publisher: Microbiology Society
Date: 07-2019
Abstract: Reference and type strains of well-known bacteria have been a cornerstone of microbiology research for decades. The sharing of well-characterized isolates among laboratories has run in parallel with research efforts and enhanced the reproducibility of experiments, leading to a wealth of knowledge about trait variation in different species and the underlying genetics. C ylobacter jejuni strain NCTC 11168, deposited at the National Collection of Type Cultures in 1977, has been adopted widely as a reference strain by researchers worldwide and was the first C ylobacter for which the complete genome was published (in 2000). In this study, we collected 23 C . jejuni NCTC 11168 reference isolates from laboratories across the UK and compared variation in simple laboratory phenotypes with genetic variation in sequenced genomes. Putatively identical isolates, identified previously to have aberrant phenotypes, varied by up to 281 SNPs (in 15 genes) compared to the most recent reference strain. Isolates also display considerable phenotype variation in motility, morphology, growth at 37 °C, invasion of chicken and human cell lines, and susceptibility to icillin. This study provides evidence of ongoing evolutionary change among C. jejuni isolates as they are cultured in different laboratories and highlights the need for careful consideration of genetic variation within laboratory reference strains. This article contains data hosted by Microreact .
Publisher: eLife Sciences Publications, Ltd
Date: 03-02-2022
Publisher: Cold Spring Harbor Laboratory
Date: 03-09-2021
Abstract: The number of publicly available microbiome s les is continually growing. As data set size increases, bottlenecks arise in standard analytical pipelines. Faith's phylogenetic ersity (Faith's PD) is a highly utilized phylogenetic alpha ersity metric that has thus far failed to effectively scale to trees with millions of vertices. Stacked Faith's phylogenetic ersity (SFPhD) enables calculation of this widely adopted ersity metric at a much larger scale by implementing a computationally efficient algorithm. The algorithm reduces the amount of computational resources required, resulting in more accessible software with a reduced carbon footprint, as compared to previous approaches. The new algorithm produces identical results to the previous method. We further demonstrate that the phylogenetic aspect of Faith's PD provides increased power in detecting ersity differences between younger and older populations in the FINRISK study's metagenomic data.
Publisher: Cold Spring Harbor Laboratory
Date: 13-09-2020
DOI: 10.1101/2020.09.12.20193045
Abstract: Co-evolution between humans and the microbial communities colonizing them has resulted in an intimate assembly of thousands of microbial species mutualistically living on and in their body and impacting multiple aspects of host physiology and health. Several studies examining whether human genetic variation can affect gut microbiota suggest a complex combination of environmental and host factors. Here, we leverage a single large-scale population-based cohort of 5,959 genotyped in iduals with matched gut microbial shotgun metagenomes, dietary information and health records up to 16 years post-s ling, to characterize human genetic variations associated with microbial abundances, and predict possible causal links with various diseases using Mendelian randomization (MR). Genome-wide association study (GWAS) identified 583 independent SNP-taxon associations at genome-wide significance ( p .0×10 -8 ), which included notable strong associations with LCT ( p =5.02×10 -35 ), ABO ( p =1.1×10 -12 ), and MED13L ( p =1.84×10 -12 ). A combination of genetics and dietary habits was shown to strongly shape the abundances of certain key bacterial members of the gut microbiota, and explain their genetic association. Genetic effects from the LCT locus on Bifidobacterium and three other associated taxa significantly differed according to dairy intake. Variation in mucin-degrading Faecalicatena lactaris abundances were associated with ABO , highlighting a preferential utilization of secreted A/B/AB-antigens as energy source in the gut, irrespectively of fibre intake. Enterococcus faecalis levels showed a robust association with a variant in MED13L , with putative links to colorectal cancer. Finally, we identified putative causal relationships between gut microbes and complex diseases using MR, with a predicted effect of Morganella on major depressive disorder that was consistent with observational incident disease analysis. Overall, we present striking ex les of the intricate relationship between humans and their gut microbial communities, and highlight important health implications.
Publisher: Wiley
Date: 31-12-2014
DOI: 10.1111/MEC.13001
Abstract: Environmental pollution often accompanies the expansion and urbanization of human populations where sewage and wastewaters commonly have an impact on the marine environments. Here, we explored the potential for faecal bacterial pathogens, of anthropic origin, to spread to marine wildlife in coastal areas. The common zoonotic bacterium C ylobacter was isolated from grey seals (Halichoerus grypus), an important sentinel species for environmental pollution, and compared to isolates from wild birds, agricultural sources and clinical s les to characterize possible transmission routes. C ylobacter jejuni was present in half of all grey seal pups s led (24/50 dead and 46/90 live pups) in the breeding colony on the Isle of May (Scotland), where it was frequently associated with histological evidence of disease. Returning yearling animals (19/19) were negative for C. jejuni suggesting clearance of infection while away from the localized colony infection source. The genomes of 90 isolates from seals were sequenced and characterized using a whole-genome multilocus sequence typing (MLST) approach and compared to 192 published genomes from multiple sources using population genetic approaches and a probabilistic genetic attribution model to infer the source of infection from MLST data. The strong genotype-host association has enabled the application of source attribution models in epidemiological studies of human c ylobacteriosis, and here assignment analyses consistently grouped seal isolates with those from human clinical s les. These findings are consistent with either a common infection source or direct transmission of human c ylobacter to grey seals, raising concerns about the spread of human pathogens to wildlife marine sentinel species in coastal areas.
Publisher: Cold Spring Harbor Laboratory
Date: 18-04-2019
DOI: 10.1101/591701
Abstract: Reference and type strains of well-known bacteria have been a cornerstone of microbiology research for decades. The sharing of well-characterised isolates among laboratories has parallelised research efforts and enhanced the reproducibility of experiments, leading to a wealth of knowledge about trait variation in different species and the underlying genetics. C ylobacter jejuni strain NCTC 11168, deposited at the National Collection of Type Cultures in 1977, has been adopted widely as a reference strain by researchers worldwide and was the first C ylobacter for which the complete genome was published (in 2000). In this study, we collected 23 C. jejuni NCTC 11168 reference isolates from laboratories across the UK and compared variation in simple laboratory phenotypes with genetic variation in sequenced genomes. Putatively identical isolates identified previously to have aberrant phenotypes varied by up to 281 SNPs (in 15 genes) compared to the most recent reference strain. Isolates also display considerable phenotype variation in motility, morphology, growth at 37°C, invasion of chicken and human cell lines and susceptibility to icillin. This study provides evidence of ongoing evolutionary change among C. jejuni isolates as they are cultured in different laboratories and highlights the need for careful consideration of genetic variation within laboratory reference strains. In this paper, we comment on the changing role of laboratory reference strains. While the model organism allows basic comparison within and among laboratories, it is important to remember the effect even small differences in isolate genomes can have on the validity and reproducibility of experimental work. We quantify differences in 23 reference C ylobacter genomes and compare them with observable differences in common laboratory phenotypes. Short read data are archived on the NCBI SRA associated with BioProject accession PRJNA517467 ( ioproject/PRJNA517467 ). All assembled genomes are also available on FigShare (doi: 10.6084/m9.figshare.7849268). Phylogeny visualised on microreact: roject/NCTC11168 . Short read data are archived on the NCBI SRA repository, associated with BioProject accession PRJNA517467 ( ioproject/PRJNA517467 Table S1 ). The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.
Publisher: Cold Spring Harbor Laboratory
Date: 17-06-2021
DOI: 10.1101/2021.06.17.447897
Abstract: Streptococcus suis is a leading cause of bacterial meningitis in SE Asia, with frequent zoonotic transfer to humans associated with close contact with pigs. A small number of invasive lineages are responsible for endemic infection in the swine industry causing considerable global economic losses. A lack of surveillance and a rising trend in clinical treatment failure has raised concerns of growing antimicrobial resistance (AMR) among invasive S. suis . The source-sink dynamics between healthy and disease isolates is poorly understood and, in this study, we s le and sequence a collection of isolates predominantly from healthy pigs in Chiang Mai province, Northern Thailand. Pangenome comparisons with a selection of invasive serotype 2 isolates identified increased genetic ersity and more frequent AMR carriage in isolates from healthy pigs. Multiple antimicrobial resistance genes were identified conferring resistance to aminoglycosides, lincosamides, tetracycline and macrolides. All isolates were non-susceptinle to three or more different antimicrobial classes, and 75% of non-serotype 2 isolates were non-susceptible to 6 or more classes (compared to 37.5% of serotype 2 isolates). Antimicrobial resistance genes were found on integrative and conjugative elements (ICE) previously observed in other species, suggesting mobile gene pool which can be accessed by invasive disease isolates. The zoonotic pathogen Streptococcus suis causes respiratory disease in pigs and is among the most common causative agents of human clinical bacterial meningitis in SE Asia. We collected isolates from farmed healthy pigs in Northern Thailand, representing a source population from which invasive isolates have recently emerged – linked to the pork production industry. Pangenome characterisation of the isolates revealed a reservoir of genetic ersity and antimicrobial resistance suggesting that One Health approaches may be beneficial in tackling the increase in antimicrobial resistance.
Publisher: Public Library of Science (PLoS)
Date: 10-08-2020
Publisher: American Society for Microbiology
Date: 26-04-2022
DOI: 10.1128/MSYSTEMS.00167-22
Abstract: Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene licon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution.
Publisher: Public Library of Science (PLoS)
Date: 27-03-2014
Publisher: Cold Spring Harbor Laboratory
Date: 05-08-2023
DOI: 10.1101/2023.07.30.23293396
Abstract: Multi-omics has opened new avenues for non-invasive risk profiling and early detection of complex diseases. Both polygenic risk scores (PRSs) and the human microbiome have shown promise in improving risk assessment of various common diseases. Here, in a prospective population-based cohort (FINRISK 2002 n=5,676) with ∼18 years of e-health record follow-up, we assess the incremental and combined value of PRSs and gut metagenomic sequencing as compared to conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer’s disease (AD) and prostate cancer. We found that PRSs improved predictive capacity over conventional risk factors for all diseases (ΔC-indices between 0.010 – 0.027). In sex-stratified analyses, gut metagenomics improved predictive capacity over baseline age for CAD, T2D and prostate cancer however, improvement over all conventional risk factors was only observed for T2D (ΔC-index 0.004) and prostate cancer (ΔC-index 0.005). Integrated risk models of PRSs, gut metagenomic scores and conventional risk factors achieved the highest predictive performance for all diseases studied as compared to models based on conventional risk factors alone. We make our integrated risk models available for the wider research community. This study demonstrates that integrated PRS and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.
Publisher: Springer Science and Business Media LLC
Date: 02-2022
DOI: 10.1038/S41588-021-00991-Z
Abstract: Human genetic variation affects the gut microbiota through a complex combination of environmental and host factors. Here we characterize genetic variations associated with microbial abundances in a single large-scale population-based cohort of 5,959 genotyped in iduals with matched gut microbial metagenomes, and dietary and health records (prevalent and follow-up). We identified 567 independent SNP-taxon associations. Variants at the LCT locus associated with Bifidobacterium and other taxa, but they differed according to dairy intake. Furthermore, levels of Faecalicatena lactaris associated with ABO, and suggested preferential utilization of secreted blood antigens as energy source in the gut. Enterococcus faecalis levels associated with variants in the MED13L locus, which has been linked to colorectal cancer. Mendelian randomization analysis indicated a potential causal effect of Morganella on major depressive disorder, consistent with observational incident disease analysis. Overall, we identify and characterize the intricate nature of host-microbiota interactions and their association with disease.
Publisher: Springer Science and Business Media LLC
Date: 11-05-2021
DOI: 10.1038/S41467-021-22962-Y
Abstract: The collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland ( n = 7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status.
Publisher: Cold Spring Harbor Laboratory
Date: 24-08-2021
DOI: 10.1101/2021.08.24.457495
Abstract: Horizontal gene transfer (HGT) can allow traits that have evolved in one bacterial species to transfer to another. This has potential to rapidly promote new adaptive trajectories such as zoonotic transfer or antimicrobial resistance. However, for this to occur requires gaps to align in barriers to recombination within a given time frame. Chief among these barriers is the physical separation of species with distinct ecologies in separate niches. Within the genus C ylobacter there are species with ergent ecologies, from rarely isolated single host specialists to multi-host generalist species that are among the most common global causes of human bacterial gastroenteritis. Here, by characterising these contrasting ecologies, we can quantify HGT among sympatric and allopatric species in natural populations. Analysing recipient and donor population ancestry among genomes from 30 C ylobacter species we show that cohabitation in the same host can lead to a 6-fold increase in HGT between species. This accounts for up to 30% of all SNPs within a given species and identifies highly recombinogenic genes with functions including host adaptation and antimicrobial resistance. As described in some animal and plant species, ecological factors are a major evolutionary force for speciation in bacteria and changes to the host landscape can promote partial convergence of distinct species through HGT.
Publisher: Microbiology Society
Date: 03-11-2022
Abstract: Streptococcus suis is a leading cause of bacterial meningitis in South-East Asia, with frequent zoonotic transfer to humans associated with close contact with pigs. A small number of invasive lineages are responsible for endemic infection in the swine industry, causing considerable global economic losses. A lack of surveillance and a rising trend in clinical treatment failure has raised concerns of growing antimicrobial resistance (AMR) among invasive S. suis . Gene flow between healthy and disease isolates is poorly understood and, in this study, we s le and sequence a collection of isolates predominantly from healthy pigs in Chiang Mai province, Northern Thailand. Pangenome characterization identified extensive genetic ersity and frequent AMR carriage in isolates from healthy pigs. Multiple AMR genes were identified, conferring resistance to aminoglycosides, lincosamides, tetracycline and macrolides. All isolates were non-susceptible to three or more different antimicrobial classes, and 75 % of non-serotype 2 isolates were non-susceptible to six or more classes (compared to 37.5 % of serotype 2 isolates). AMR genes were found on integrative and conjugative elements previously observed in other species, suggesting a mobile gene pool that can be accessed by invasive disease isolates. This article contains data hosted by Microreact .
Publisher: Cold Spring Harbor Laboratory
Date: 05-06-2018
DOI: 10.1101/332544
Abstract: Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP method for identifying and estimating the relative abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our method facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.
Publisher: Cold Spring Harbor Laboratory
Date: 22-05-2021
DOI: 10.1101/2021.05.21.445058
Abstract: Varying technologies and experimental approaches used in microbiome studies often lead to irreproducible results due to unwanted technical variations. Such variations, often unaccounted for and of unknown source, may interfere with true biological signals, resulting in misleading biological conclusions. In this work, we aim to characterize the major sources of technical variations in microbiome data and demonstrate how a state-of-the art approach can minimize their impact on downstream analyses. We analyzed 184 pig faecal metagenomes encompassing 21 specific combinations of deliberately introduced factors of technical and biological variations. We identify several known experimental factors, specifically storage conditions and freeze-thaw cycles, as a likely major source of unwanted variation in metagenomes. We also observed that these unwanted technical variations do not affect taxa uniformly, with freezing s les affecting taxa of class Bacteroidia the most, for ex le. Additionally, we benchmarked the performance of a novel batch correcting tool used in this study, RUV-III-NB ( imfuxing/ruvIIInb/ ), to other popular batch correction methods, including ComBat, ComBat-seq, RUVg, and RUVs. While RUV-III-NB performed consistently robustly across our sensitivity and specificity metrics, most other methods did not remove unwanted variations optimally, with RUVg even overcorrecting and removing some of the true biological signals from the s les. Our analyses suggests that a careful consideration of possible technical confounders is critical in the experimental design of microbiome studies to ensure accurate biological reading of microbial taxa of interest, and that the inclusion of technical replicates is necessary to efficiently remove unwanted variations computationally.
Publisher: Cold Spring Harbor Laboratory
Date: 23-07-2019
DOI: 10.1101/712166
Abstract: Assessing the taxonomic composition of metagenomic s les 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 s le 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 ersity 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 in idual microbiome studies, and for comparison and meta-analysis of microbiome datasets.
Publisher: F1000 Research Ltd
Date: 30-01-2020
DOI: 10.12688/WELLCOMEOPENRES.15639.1
Abstract: Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.
Publisher: Informa UK Limited
Date: 2021
Publisher: F1000 Research Ltd
Date: 08-10-2021
DOI: 10.12688/WELLCOMEOPENRES.15639.2
Abstract: Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.
Publisher: Cold Spring Harbor Laboratory
Date: 06-04-2021
DOI: 10.1101/2021.04.04.438427
Abstract: We introduce Operational Genomic Unit (OGU), a metagenome analysis strategy that directly exploits sequence alignment hits to in idual reference genomes as the minimum unit for assessing the ersity of microbial communities and their relevance to environmental factors. This approach is independent from taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldomly applied to shotgun metagenomics despite being prevalent in 16S rRNA gene licon studies. As demonstrated in one synthetic and two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome datasets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene licon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project dataset, and more accurate prediction of human age by the gut microbiomes in the Finnish population. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate OGU adoption in future metagenomics studies. Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene licon sequencing for decoding the composition and structure of microbial communities. However, current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution compared to 16S rRNA licon sequence variant analysis. To solve these challenges, we introduce Operational Genomic Units (OGUs), which are the in idual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition while (ii) permitting use of phylogeny-aware tools. Our analysis of real-world datasets shows several advantages over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGU as standard practice in metagenomic studies.
Publisher: No publisher found
Date: 2013
DOI: 10.5061/DRYAD.28N35
Publisher: Springer Science and Business Media LLC
Date: 22-03-2021
DOI: 10.1038/S41467-021-22238-5
Abstract: A Correction to this paper has been published: 0.1038/s41467-021-22238-5
Publisher: American Society for Microbiology
Date: 02-2015
DOI: 10.1128/AEM.00546-15
Abstract: C ylobacter jejuni is a highly erse species of bacteria commonly associated with infectious intestinal disease of humans and zoonotic carriage in poultry, cattle, pigs, and other animals. The species contains a large number of distinct clonal complexes that vary from host generalist lineages commonly found in poultry, livestock, and human disease cases to host-adapted specialized lineages primarily associated with livestock or poultry. Here, we present novel data on the ST403 clonal complex of C. jejuni , a lineage that has not been reported in avian hosts. Our data show that the lineage exhibits a distinctive pattern of intralineage recombination that is accompanied by the presence of lineage-specific restriction-modification systems. Furthermore, we show that the ST403 complex has undergone gene decay at a number of loci. Our data provide a putative link between the lack of association with avian hosts of C. jejuni ST403 and both gene gain and gene loss through nonsense mutations in coding sequences of genes, resulting in pseudogene formation.
Publisher: Cold Spring Harbor Laboratory
Date: 23-03-2022
DOI: 10.1101/2022.03.22.22272736
Abstract: The gut-lung axis is generally recognized, but there are few large studies of the gut microbiome and incident respiratory disease in adults. To investigate the associations between gut microbiome and respiratory disease and to construct predictive models from baseline gut microbiome profiles for incident asthma or chronic obstructive pulmonary disease (COPD). Shallow metagenomic sequencing was performed for stool s les from a prospective, population-based cohort (FINRISK02 N=7,115 adults) with linked national administrative health register derived classifications for incident asthma and COPD up to 15 years after baseline. Generalised linear models and Cox regressions were utilised to assess associations of microbial taxa and ersity with disease occurrence. Predictive models were constructed using machine learning with extreme gradient boosting. Models considered taxa abundances in idually and in combination with other risk factors, including sex, age, body mass index and smoking status. A total of 695 and 392 significant microbial associations at different taxonomic levels were found with incident asthma and COPD, respectively. Gradient boosting decision trees of baseline gut microbiome predicted incident asthma and COPD with mean area under the curves of 0.608 and 0.780, respectively. For both incident asthma and COPD, the baseline gut microbiome had C-indices of 0.623 for asthma and 0.817 for COPD, which were more predictive than other conventional risk factors. The integration of gut microbiome and conventional risk factors further improved prediction capacities. Subgroup analyses indicated gut microbiome was significantly associated with incident COPD in both current smokers and non-smokers, as well as in in iduals who reported never smoking. The gut microbiome is a significant risk factor for incident asthma and incident COPD and is largely independent of conventional risk factors.
Publisher: Wiley
Date: 25-04-2014
DOI: 10.1111/MEC.12742
Publisher: S. Karger AG
Date: 26-09-2008
DOI: 10.1159/000159193
Abstract: i Background: /i Quorum sensing (QS) is a process by which bacteria communicate with diffusible chemical signaling molecules called autoinducers (AIs). The autoinducer-2 signal (AI-2) produced by the LuxS protein mediates interspecies communication among Gram-positive and Gram-negative bacteria. In this study, we report that luxS-dependent QS is involved in the formation of i Streptococcus mutans /i biofilms. i Methods: /i An i S. mutans /i luxS mutant was constructed, and the differences in growth and biofilm formation were compared between the wild-type strain and the mutant strain. To quantificationally analyze the kinetic biofilm formation of the mutant strain, an assay of BioFilm Ring Test® was applied. i Results: /i There is a small increase in the growth of the luxS mutant strain after the stationary phase, compared with the parent strain. However during the exponential period, there were no significant differences. Using the BioFilm Ring Test®, it was demonstrated that this luxS mutation was able to accelerate biofilm formation on a polystyrene surface during the mid-exponential growth phase. With 1% glucose treatment, even greater differences were observed between the mutant strain and its parental strain. i Conclusion: /i These data suggest that a luxS-dependent signal may play an important role in the biofilm formation of i S. mutans. /i
Publisher: Wiley
Date: 04-2018
DOI: 10.1111/MEC.14546
Publisher: Elsevier BV
Date: 04-2015
DOI: 10.1016/J.CIMID.2015.02.003
Abstract: In order to compare the prevalence of C ylobacter coli and C ylobacter jejuni during the processing of broilers at slaughterhouse a total of 848 s les were analyzed during 2012 in southern Spain. Four hundred and seventy six s les were collected from cloaca, carcass surfaces and quartered carcasses. Moreover, 372 environmental swabs from equipment and scalding water were collected. Minimum inhibitory concentration (MIC) to ciprofloxacin, erythromycin, streptomycin, tetracycline and gentamicin was determined for isolates from chicken meat. The general prevalence of C ylobacter was 68.8% (40.2% of C. coli and 28.5% of C. jejuni). The relative prevalence of C. coli increased from loading dock area (41.5%) to packing area (64.6%). In contrast, the relative prevalence of C. jejuni decreased from 58.5% to 35.4%. These differences between species from initial to final area were significant (p=0.02). The highest antimicrobial resistance for C. jejuni and C. coli was detected to tetracycline (100%) and ciprofloxacin (100%), respectively. C ylobacter coli showed an antimicrobial resistance significantly higher than C. jejuni to streptomycin (p=0.002) and erythromycin (p<0.0001).
Publisher: Springer Science and Business Media LLC
Date: 03-02-2021
DOI: 10.1038/S41467-021-20988-W
Abstract: Chickens are the most common birds on Earth and colibacillosis is among the most common diseases affecting them. This major threat to animal welfare and safe sustainable food production is difficult to combat because the etiological agent, avian pathogenic Escherichia coli (APEC), emerges from ubiquitous commensal gut bacteria, with no single virulence gene present in all disease-causing isolates. Here, we address the underlying evolutionary mechanisms of extraintestinal spread and systemic infection in poultry. Combining population scale comparative genomics and pangenome-wide association studies, we compare E. coli from commensal carriage and systemic infections. We identify phylogroup-specific and species-wide genetic elements that are enriched in APEC, including pathogenicity-associated variation in 143 genes that have erse functions, including genes involved in metabolism, lipopolysaccharide synthesis, heat shock response, antimicrobial resistance and toxicity. We find that horizontal gene transfer spreads pathogenicity elements, allowing ergent clones to cause infection. Finally, a Random Forest model prediction of disease status (carriage vs. disease) identifies pathogenic strains in the emergent ST-117 poultry-associated lineage with 73% accuracy, demonstrating the potential for early identification of emergent APEC in healthy flocks.
Publisher: Cold Spring Harbor Laboratory
Date: 05-2020
DOI: 10.1101/2020.04.26.20075689
Abstract: C ylobacter is the leading bacterial cause of gastroenteritis worldwide and its incidence is especially high in low- and middle-income countries (LMIC). Disease epidemiology in LMICs is different compared to high income countries like the USA or in Europe. Children in LMICs commonly have repeated and chronic infections even in the absence of symptoms, which can lead to deficits in early childhood development. In this study, we sequenced and characterized C. jejuni (n=62) from a longitudinal cohort study of children under the age of 5 with and without diarrheal symptoms, and contextualized them within a global C. jejuni genome collection. Epidemiological differences in disease presentation were reflected in the genomes, specifically by the absence of some of the most common global disease-causing lineages. As in many other countries, poultry-associated strains were a major source of human infection but almost half of local disease cases (15 of 31) were attributable to genotypes that are rare outside of Peru. Asymptomatic infection was not limited to a single (or few) human adapted lineages but resulted from phylogenetically ergent strains suggesting an important role for host factors in the cryptic epidemiology of c ylobacteriosis in LMICs. C ylobacter is the leading bacterial cause of gastroenteritis worldwide and despite high incidence in low- and middle-income countries (LMICs), where infection can be fatal, culture based isolation is rare and the genotypes responsible for disease have not broadly been identified. The epidemiology of disease is different to that in high income countries, where sporadic infection associated with contaminated food consumption typically leads to acute gastroenteritis. In some LMICs infection is endemic among children and common asymptomatic carriage is associated with malnutrition, attenuated growth in early childhood, and poor cognitive and physical development. Here, we sequenced the genomes of isolates s led from children in the Peruvian Amazon to investigate genotypes associated with varying disease severity and the source of infection. Among the common globally circulating genotypes and local genotypes rarely seen before, no single lineage was responsible for symptomatic or asymptomatic infection – suggesting an important role for host factors. However, consistent with other countries, poultry-associated strains were a major source of infection. This genomic surveillance approach, that integrates microbial ecology with population based studies in humans and animals, has considerable potential for describing cryptic epidemiology in LMICs and will inform work to improve infant health worldwide.
Publisher: eLife Sciences Publications, Ltd
Date: 22-02-2022
DOI: 10.7554/ELIFE.73552
Abstract: Horizontal gene transfer (HGT) can allow traits that have evolved in one bacterial species to transfer to another. This has potential to rapidly promote new adaptive trajectories such as zoonotic transfer or antimicrobial resistance. However, for this to occur requires gaps to align in barriers to recombination within a given time frame. Chief among these barriers is the physical separation of species with distinct ecologies in separate niches. Within the genus C ylobacter, there are species with ergent ecologies, from rarely isolated single-host specialists to multihost generalist species that are among the most common global causes of human bacterial gastroenteritis. Here, by characterizing these contrasting ecologies, we can quantify HGT among sympatric and allopatric species in natural populations. Analyzing recipient and donor population ancestry among genomes from 30 C ylobacter species, we show that cohabitation in the same host can lead to a six-fold increase in HGT between species. This accounts for up to 30% of all SNPs within a given species and identifies highly recombinogenic genes with functions including host adaptation and antimicrobial resistance. As described in some animal and plant species, ecological factors are a major evolutionary force for speciation in bacteria and changes to the host landscape can promote partial convergence of distinct species through HGT.
Publisher: Cold Spring Harbor Laboratory
Date: 09-03-2021
DOI: 10.1101/2021.03.08.434372
Abstract: Bioinformatic research relies on large-scale computational infrastructures which have a non-zero carbon footprint. So far, no study has quantified the environmental costs of bioinformatic tools and commonly run analyses. In this study, we estimate the bioinformatic carbon footprint (in kilograms of CO 2 equivalent units, kgCO 2 e) using the freely available Green Algorithms calculator ( www.green-algorithms.org ). We assess (i) bioinformatic approaches in genome-wide association studies (GWAS), RNA sequencing, genome assembly, metagenomics, phylogenetics and molecular simulations, as well as (ii) computation strategies, such as parallelisation, CPU (central processing unit) vs GPU (graphics processing unit), cloud vs. local computing infrastructure and geography. In particular, for GWAS, we found that biobank-scale analyses emitted substantial kgCO 2 e and simple software upgrades could make GWAS greener, e.g. upgrading from BOLT-LMM v1 to v2.3 reduced carbon footprint by 73%. Switching from the average data centre to a more efficient data centres can reduce carbon footprint by ~34%. Memory over-allocation can be a substantial contributor to an algorithm’s carbon footprint. The use of faster processors or greater parallelisation reduces run time but can lead to, sometimes substantially, greater carbon footprint. Finally, we provide guidance on how researchers can reduce power consumption and minimise kgCO 2 e. Overall, this work elucidates the carbon footprint of common analyses in bioinformatics and provides solutions which empower a move toward greener research.
Location: Spain
No related grants have been discovered for Guillaume Méric.