Linear plasmids in Klebsiella and other Enterobacteriaceae.

Linear plasmids are extrachromosomal DNA elements that have been found in a small number of bacterial species. To date, the only linear plasmids described in the family Enterobacteriaceae belong to Salmonella, first found in Salmonella enterica Typhi. Here, we describe a collection of 12 isolates of the Klebsiella pneumoniae species complex in which we identified linear plasmids. Screening of assembly graphs assembled from public read sets identified linear plasmid structures in a further 13 K. pneumoniae species complex genomes. We used these 25 linear plasmid sequences to query all bacterial genome assemblies in the National Center for Biotechnology Information database, and discovered an additional 61 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

Distinct evolutionary dynamics of horizontal gene transfer in drug resistant and virulent clones of Klebsiella pneumoniae

Klebsiella pneumoniae has emerged as an important cause of two distinct public health threats: multi-drug resistant (MDR) healthcare-associated infections and drug susceptible community-acquired invasive infections. These pathotypes are generally associated with two distinct subsets of K. pneumoniae lineages or ‘clones’ that are distinguished by the presence of acquired resistance genes and several key virulence loci. Genomic evolutionary analyses of the most notorious MDR and invasive community-associated (‘hypervirulent’) clones indicate differences in terms of chromosomal recombination dynamics and capsule polysaccharide diversity, but it remains unclear if these differences represent generalised trends. Here we leverage a collection of >2200 K. pneumoniae genomes to identify 28 common clones (n ≥ 10 genomes each), and perform the first genomic evolutionary comparison. Eight MDR and 6 hypervirulent clones were identified on the basis of acquired resistance and virulence gene prevalence. Chromosomal recombination, surface polysaccharide locus diversity, pan-genome, plasmid and phage dynamics were characterised and compared. The data showed that MDR clones were highly diverse, with frequent chromosomal recombination generating extensive surface polysaccharide locus diversity. Additional pan-genome diversity was driven by frequent acquisition/loss of both plasmids and phage. In contrast, chromosomal recombination was rare in the hypervirulent clones, which also showed a significant reduction in pan-genome diversity, largely driven by a reduction in plasmid diversity. Hence the data indicate that hypervirulent clones may be subject to some sort of constraint for horizontal gene transfer that does not apply to the MDR clones. Our findings are relevant for understanding the risk of emergence of individual K. pneumoniae strains carrying both virulence and acquired resistance genes, which have been increasingly reported and cause highly virulent infections that are extremely difficult to treat. Specifically, our data indicate that MDR clones pose the greatest risk, because they are more likely to acquire virulence genes than hypervirulent clones are to acquire resistance genes

Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort

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 individuals with matched gut microbial shotgun metagenomes, dietary information and health records up to 16 years post-sampling, 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 <5.0×10 -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 examples of the intricate relationship between humans and their gut microbial communities, and highlight important health implications

Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort

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 individuals 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

TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Abstract Background A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57–74, 2012; Nat 507:462–70, 2014; Nat 507:455–61, 2014; Nat 518:317–30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. Results We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563–5, 2007; Nat Protoc 5:323–34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. Conclusions TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at: http://trawler.erc.monash.edu.au

3D-cardiomics: A spatial transcriptional atlas of the mammalian heart.

Understanding the spatial gene expression and regulation in the heart is key to uncovering its developmental and physiological processes, during homeostasis and disease. Numerous techniques exist to gain gene expression and regulation information in organs such as the heart, but few utilize intuitive true-to-life three-dimensional representations to analyze and visualise results. Here we combined transcriptomics with 3D-modelling to interrogate spatial gene expression in the mammalian heart. For this, we microdissected and sequenced transcriptome-wide 18 anatomical sections of the adult mouse heart. Our study has unveiled known and novel genes that display complex spatial expression in the heart sub-compartments. We have also created 3D-cardiomics, an interface for spatial transcriptome analysis and visualization that allows the easy exploration of these data in a 3D model of the heart. 3D-cardiomics is accessible from http://3d-cardiomics.erc.monash.edu/

Additional file 2: of TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Table S2. Details of motif occurrence comparison between web-based motif discovery software. The highest scoring motifs discovered in DREME, MEME, RSAT peak-motifs, and TrawlerWeb and their corresponding occurrences are illustrated here. For the highest scoring motif, the number of motif occurrences were expressed as a percentage of the total number of input sequences. *MEME-ChIP pre-processes submitted sequences longer than 100 by trimming them evenly from both ends to get the centered 100 bp sequence and discards trimmed sequences containing only Ns from repeat masking. **MEME motif discovery automatically limits the run to a randomly sampled 600 sequences to reduce run time. (XLSX 576 kb

Additional file 1: of TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Table S1. Details of the assessment of TrawlerWeb. Detailed table of Fig. 1b showing, for each ChIP experiment, the ability of individual programs to uncover the correct binding site in yeast. For each individual ChIP experiment, the success or failure of 8 different algorithms including TrawlerWeb is shown. The results from the 6 algorithms (Coverage, AlignACE, Kellis, mdscan, MEME, and MEME-c) were extracted from Harbison et al. 2004 [38]. The matching motifs found by TrawlerWeb are identical to that found by Trawler_standalone (detailed previously in Ettwiller et al. 2007 [5]). The results from RSAT were performed by this study, where the matching motifs found by RSAT were described in the last column. (XLSX 190 kb

Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19

Severe COVID-19 is characterised by immunopathology and epithelial injury. Proteomic studies have identified circulating proteins that are biomarkers of severe COVID-19, but cannot distinguish correlation from causation. To address this, we performed Mendelian randomisation (MR) to identify proteins that mediate severe COVID-19. Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. We identified significant MR results for five proteins: FAS, TNFRSF10A, CCL2, EPHB4 and LGALS9. Further evaluation of these candidates using sensitivity analyses and colocalization testing provided strong evidence to implicate the apoptosis-associated cytokine receptor FAS as a causal mediator of severe COVID-19. This effect was specific to severe disease. Using RNA-seq data from 4,778 individuals, we demonstrate that the pQTL at the FAS locus results from genetically influenced alternate splicing causing skipping of exon 6. We show that the risk allele for very severe COVID-19 increases the proportion of transcripts lacking exon 6, and thereby increases soluble FAS. Soluble FAS acts as a decoy receptor for FAS-ligand, inhibiting apoptosis induced through membrane-bound FAS. In summary, we demonstrate a novel genetic mechanism that contributes to risk of severe of COVID-19, highlighting a pathway that may be a promising therapeutic target