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:The meninges are densely innervated by nociceptive sensory neurons that mediate pain and headache. How pain and neuro-immune interactions impact meningeal host defenses is unclear. Bacterial meningitis causes life-threatening infections of the meninges and central nervous system (CNS), affecting over one million people a year. Here we find that Nav1.8+ neuron signaling to immune cells in the meninges via the neuropeptide calcitonin gene-related peptide (CGRP) exacerbates bacterial meningitis. Nociceptor ablation reduced meningeal and brain invasion by two bacterial pathogens: Streptococcus pneumoniae and Streptococcus agalactiae. S. pneumoniae activated nociceptors via Pneumolysin to release CGRP, which acts through its receptor RAMP1 on meningeal macrophages to inhibit chemokine expression, neutrophil recruitment and antimicrobial defenses. Macrophage-specific RAMP1 deficiency or blockade of RAMP1 signaling enhanced immune responses and bacterial clearance in meninges and brain. Therefore, targeting a neuro-immune axis in the meninges can enhance host defenses and may be a potential treatment for bacterial meningitis.
Project description:During an intracellular bacterial infection, the host cell and the infecting pathogen interact through a progressive series of events that may result in many distinct outcomes. To understand the specific strategies our immune system employs to manage attack by diverse pathogens, we sought to identify the unique and the core host and pathogen interactions that occur during infection: We compared in molecular detail the pathways induced across infection by seven diverse bacterial species that constitute many of the main human pathogens: Staphylococcus aureus, Listeria monocytogenes, Enterococcus faecalis, Group B Streptococcus, Yersinia pseudotuberculosis, Shigella flexneri and Salmonella enterica. We infected primary human macrophages with each species and used scRNA-Seq to generate a comprehensive dataset of gene expression profiles during bacterial infection. Examining the expression profiles of the infected macrophages across the pathogens, we discovered different modules of infection representing different states through which the infection progresses. The early module captures intra-cellular activity such as lysosome and degranulation, followed by type I IFN signaling, from which results in a cell death module, with a last mode of inflammatory response through response to IL-1. Comparing these modules across the pathogens, we found that their dynamics differ, with some modules active in all species and others which are present in some, but not all pathogens. Our work defines the hallmarks of host-pathogen interactions by identifying recurring properties of infection that can provide insight into diagnostics and therapeutic timing.
Project description:Six bacterial genomes, Geobacter metallireducens GS-15, Chromohalobacter salexigens, Vibrio breoganii 1C-10, Bacillus cereus ATCC 10987, Campylobacter jejuni subsp. jejuni 81-176 and Campylobacter jejuni NCTC 11168, all of which had previously been sequenced using other platforms were re-sequenced using single-molecule, real-time (SMRT) sequencing specifically to analyze their methylomes. In every case a number of new N6-methyladenine (m6A) and N4-methylcytosine (m4C) methylation patterns were discovered and the DNA methyltransferases (MTases) responsible for those methylation patterns were assigned. In 15 cases it was possible to match MTase genes with MTase recognition sequences without further sub-cloning. Two Type I restriction systems required sub-cloning to differentiate their recognition sequences, while four MTases genes that were not expressed in the native organism were sub-cloned to test for viability and recognition sequences. No attempt was made to detect 5-methylcytosine (m5C) recognition motifs from the SMRT sequencing data because this modification produces weaker signals using current methods. However, all predicted m6A and m4C MTases were detected unambiguously. This study shows that the addition of SMRT sequencing to traditional sequencing approaches gives a wealth of useful functional information about a genome showing not only which MTase genes are active, but also revealing their recognition sequences. Examination of the methylomes of six different strains of bacteria using kinetic data from single-molecule, real-time (SMRT) sequencing on the PacBio RS.
Project description:Purpose: We investigate the evolutionary footprints of a bacteria-plasmid association consisting of Escherichia coli K-12 MG1655 and plasmid RP4 undergoing a long-term sub-MIC antibiotic stress. Methods: Bacterial mRNA profiles of evolved RP4-carrying strains (E:H:p) and ancestral RP4-carrying strains (A:H:p) were generated by deep sequencing on an Illumina Hiseq platform. The sequence reads that passed quality filters were analyzed by Burrows–Wheeler Aligner (BWA), followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 15 million sequence reads of E:H:p and 12 million sequence reads of A:H:p to the E. coli MG1655 genome (GCF_000801205.1) and differential expressed genes were identified with TopHat workflow. RNA-seq data showed that approximately 15% of the transcripts showed differential expression between the E:H:p and A:H:p strains, with a fold change ≥1 and p value <0.005. Altered expression of 26 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Data analysis with bowtie and TopHat workflows provided complementary insights in transcriptome profiling. Conclusions: Our study showed the coevolved bacteria-plasmid pairs has colonization traits superior to the wild-type parent strain. Antibiotic stress was necessary for bacterial evolution and evolved strains mostly employed transcriptional modifications to reduce plasmid-related cost in evolutionary adaptations. Several genes related to chromosome-encoded efflux pumps were transcriptionally upregulated, while most plasmid-harboring genes were downregulated based on RNA gene sequencing. These transcriptional modifications endowed evolved strains with resistant phenotype modifications, including the enhanced bacterial growth and biofilm formation.