Project description:Background Trombidid mites have a unique lifecycle in which only the larval stage is ectoparasitic. In the superfamily Trombiculoidea (“chiggers”), the larvae feed preferentially on vertebrates, including humans. Species in the genus Leptotrombidium are vectors of a potentially fatal bacterial infection, scrub typhus, which affects 1 million people annually. Moreover, chiggers can cause pruritic dermatitis (trombiculiasis) in humans and domesticated animals. In the Trombidioidea (velvet mites), the larvae feed on other arthropods and are potential biological control agents for agricultural pests. Here, we present the first trombidid mites genomes, obtained both for a chigger, Leptotrombidium deliense, and for a velvet mite, Dinothrombium tinctorium. Results Sequencing was performed on the Illumina MiSeq platform. A 180 Mb draft assembly for D. tinctorium was generated from two paired-end and one mate-pair library using a single adult specimen. For L. deliense, a lower-coverage draft assembly (117 Mb) was obtained using pooled, engorged larvae with a single paired-end library. Remarkably, both genomes exhibited evidence of ancient lateral gene transfer from soil-derived bacteria or fungi. The transferred genes confer functions that are rare in animals, including terpene and carotenoid synthesis. Thirty-seven allergenic protein families were predicted in the L. deliense genome, of which nine were unique. Preliminary proteomic analyses identified several of these putative allergens in larvae. Conclusions Trombidid mite genomes appear to be more dynamic than those of other acariform mites. A priority for future research is to determine the biological function of terpene synthesis in this taxon and its potential for exploitation in disease control. Project was jointly supervised by Stuart Armstrong and Ben Makepeace.
Project description:<p>Traveler's diarrhea (TD) is caused by enterotoxigenic Escherichia coli (ETEC), other pathogenic gram-negative pathogens, norovirus and some parasites. Nevertheless, standard diagnostic methods fail to identify pathogens in more than 30% of TD patients, so it is predicted that new pathogens or groups of pathogens may be causative agents of disease. A comprehensive metagenomic study of the fecal microbiomes from 23 TD patients and seven healthy travelers was performed, all of which tested negative for the known etiologic agents of TD in standard tests. Metagenomic reads were assembled and the resulting contigs were subjected to semi-manual binning to assemble independent genomes from metagenomic pools. Taxonomic and functional annotations were conducted to assist identification of putative pathogens. We extracted 560 draft genomes, 320 of which were complete enough to be enough characterized as cellular genomes and 160 of which were bacteriophage genomes. We made predictions of the etiology of disease in individual subjects based on the properties and features of the recovered cellular genomes. Three subtypes of samples were observed. First were four patients with low diversity metagenomes that were predominated by one or more pathogenic E. coli strains. Annotation allowed prediction of pathogenic type in most cases. Second, five patients were co-infected with E. coli and other members of the Enterobacteriaceae, including antibiotic resistant Enterobacter, Klebsiella, and Citrobacter. Finally, several samples contained genomes that represented dark matter. In one of these samples we identified a TM7 genome that phylogenetically clustered with a strain isolated from wastewater and carries genes encoding potential virulence factors. We also observed a very high proportion of bacteriophage reads in some samples. The relative abundance of phage was significantly higher in healthy travelers when compared to TD patients. Our results highlight that assembly-based analysis revealed that diarrhea is often polymicrobial and includes members of the Enterobacteriaceae not normally associated with TD and have implicated a new member of the TM7 phylum as a potential player in diarrheal disease. </p>
Project description:Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated techniques depend heavily on sequence context and often underestimate the complexity of the proteome. We developed REPARATION (RibosomeE Profiling Assisted (Re-)AnnotaTION), a de novo algorithm that takes advantage of experimental evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation. Ribo-seq next generation sequencing technique that provides a genome-wide snapshot of the position translating ribosome along an mRNA at the time of the experiment. REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds to screen for spurious ORFs based on a growth curve model. We applied REPARATION to three annotated bacterial species to obtain a more comprehensive mapping of their translation landscape in support of experimental data. In all cases, we identified hundreds of novel ORFs including variants of previously annotated and novel small ORFs (<71 codons). Our predictions were supported by matching mass spectrometry (MS) proteomics data and sequence conservation analysis. REPARATION is unique in that it makes use of experimental Ribo-seq data to perform de novo ORF delineation in bacterial genomes, and thus can identify putative coding ORFs irrespective of the sequence context of the reading frame.
Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>
Project description:Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated techniques depend heavily on sequence context and often underestimate the complexity of the proteome. We developed REPARATION (RibosomeE Profiling Assisted (Re-)AnnotaTION), a de novo algorithm that takes advantage of experimental evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation. Ribo-seq next generation sequencing technique that provides a genome-wide snapshot of the position translating ribosome along an mRNA at the time of the experiment. REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds to screen for spurious ORFs based on a growth curve model. We applied REPARATION to three annotated bacterial species to obtain a more comprehensive mapping of their translation landscape in support of experimental data. In all cases, we identified hundreds of novel ORFs including variants of previously annotated and novel small ORFs (<71 codons). Our predictions were supported by matching mass spectrometry (MS) proteomics data and sequence conservation analysis. REPARATION is unique in that it makes use of experimental Ribo-seq data to perform de novo ORF delineation in bacterial genomes, and thus can identify putative coding ORFs irrespective of the sequence context of the reading frame.
Project description:Peripheral blood was collected from human patients infected with influenza A virus only or in addition with bacterial pathogens and at different days after hospital admission. For comparison, blood from healthy controls was collected. Gene expression differences were detected in influenza and bacterial infections compared to healthy controls, and at various days post infection.
Project description:Plant pathogens can cause serious diseases that impact global agriculture1. Understanding how the plant immune system naturally restricts pathogen infection holds a key to sustainable disease control in modern agricultural practices. However, despite extensive studies into the molecular and genetic basis of plant defense against pathogens since the 1950s2,3, one of the most fundamental questions in plant pathology remains unanswered: how resistant plants halt pathogen growth during immune activation. In the case of bacterial infections, a major bottleneck is an inability to determine the global bacterial transcriptome and metabolic responses in planta. Here, we developed an innovative pipeline that allows for in planta high-resolution bacterial transcriptome analysis with RNA-Seq, using the model plant Arabidopsis thaliana and the foliar bacterial pathogen Pseudomonas syringae. We examined a total of 27 combinations of plant immunity and bacterial virulence mutants to gain an unprecedented insight into the bacterial transcriptomic responses during plant immunity. We were able to identify specific bacterial transcriptomic signatures that are linked to bacterial inhibition during two major forms of plant immunity: pattern-triggered immunity and effector-triggered immunity. Among them, regulation of a P. syringae sigma factor gene, involved in iron regulation and an unknown process(es), was found to play a causative role in bacterial restriction during plant immunity. This study unlocked the enigmatic mechanisms of bacterial growth inhibition during plant immunity; results have broad basic and practical implications for future study of plant diseases.