The microbiota — the collection of microorganisms that live within and on all mammals — provides crucial signals for the development and function of the immune system. Increased availability of technologies that profile microbial communities is facilitating the entry of many immunologists into the evolving field of host-microbiota studies. The microbial communities, their metabolites and components are not only necessary for immune homeostasis, they also influence the susceptibility of the host to many immune-mediated diseases and disorders. In this Review, we discuss technological and computational approaches for investigating the microbiome, as well as recent advances in our understanding of host immunity and microbial mutualism with a focus on specific microbial metabolites, bacterial components and the immune system.
Dysregulated immune responses to gut microbes are central to inflammatory bowel disease (IBD), and gut microbial activity can fuel chronic inflammation. Examining how IBD-directed therapies influence gut microbiomes may identify microbial community features integral to mitigating disease and maintaining health. However, IBD patients often receive multiple treatments during disease flares, confounding such analyses. Preclinical models of IBD with well-defined disease courses and opportunities for controlled treatment exposures provide a valuable solution. Here, we surveyed the gut microbiome of the T-bet−/− Rag2−/− mouse model of colitis during active disease and treatment-induced remission. Microbial features modified among these conditions included altered potential for carbohydrate and energy metabolism and bacterial pathogenesis, specifically cell motility and signal transduction pathways. We also observed an increased capacity for xenobiotics metabolism, including benzoate degradation, a pathway linking host adrenergic stress with enhanced bacterial virulence, and found decreased levels of fecal dopamine in active colitis. When transferred to gnotobiotic mice, gut microbiomes from mice with active disease versus treatment-induced remission elicited varying degrees of colitis. Thus, our study provides insight into specific microbial clades and pathways associated with health, active disease and treatment interventions in a mouse model of colitis.
It is now possible to perform whole-genome shotgun sequencing as well as capture of specific genomic regions for extinct organisms. However, targeted resequencing of large parts of nuclear genomes has yet to be demonstrated for ancient DNA. Here we show that hybridization capture on microarrays can successfully recover more than a megabase of target regions from Neandertal DNA even in the presence of~99.8% microbial DNA. Using this approach, we have sequenced~14,000 protein-coding positions inferred to have changed on the human lineage since the last common ancestor shared with chimpanzees. By generating the sequence of one Neandertal and 50 present-day humans at these positions, we have identified 88 amino acid substitutions that have become fixed in humans since our divergence from the Neandertals.
DNA methylation stabilizes developmentally programmed gene expression states. Aberrant methylation is associated with disease progression and is a common feature of cancer genomes. Presently, few methods enable quantitative, largescale, single-base resolution mapping of DNA methylation states in desired regions of a complex mammalian genome. Here, we present an approach that combines array-based hybrid selection and massively parallel bisulfite sequencing to profile DNA methylation in genomic regions spanning hundreds of thousands of bases. This single molecule strategy enables methylation variable positions to be quantitatively examined with high sampling precision. Using bisulfite capture, we assessed methylation patterns across 324 randomly selected CpG islands (CGI) representing more than 25,000 CpG sites. A single lane of Illumina sequencing permitted methylation states to be definitively called for >90% of target sties. The accuracy of the hybrid-selection approach was verified using conventional bisulfite capillary sequencing of cloned PCR products amplified from a subset of the selected regions. This confirmed that even partially methylated states could be successfully called. A comparison of human primary and cancer cells revealed multiple differentially methylated regions. More than 25% of islands showed complex methylation patterns either with partial methylation states defining the entire CGI or with contrasting methylation states appearing in specific regional blocks within the island. We observed that transitions in methylation state often correlate with genomic landmarks, including transcriptional start sites and intron-exon junctions. Methylation, along with specific histone marks, was enriched in exonic regions, suggesting that chromatin states can foreshadow the content of mature mRNAs.
Next-generation sequencers have sufficient power to analyze simultaneously DNAs from many different specimens, a practice known as multiplexing. Such schemes rely on the ability to associate each sequence read with the specimen from which it was derived. The current practice of appending molecular barcodes prior to pooling is practical for parallel analysis of up to many dozen samples. Here, we report a strategy that permits simultaneous analysis of tens of thousands of specimens. Our approach relies on the use of combinatorial pooling strategies in which pools rather than individual specimens are assigned barcodes. Thus, the identity of each specimen is encoded within the pooling pattern rather than by its association with a particular sequence tag. Decoding the pattern allows the sequence of an original specimen to be inferred with high confidence. We verified the ability of our encoding and decoding strategies to accurately report the sequence of individual samples within a large number of mixed specimens in two ways. First, we simulated data both from a clone library and from a human population in which a sequence variant associated with cystic fibrosis was present. Second, we actually pooled, sequenced, and decoded identities within two sets of 40,000 bacterial clones comprising approximately 20,000 different artificial microRNAs targeting Arabidopsis or human genes. We achieved greater than 97% accuracy in these trials. The strategies reported here can be applied to a wide variety of biological problems, including the determination of genotypic variation within large populations of individuals.[Supplemental material is available online at www.genome.org.]There are many biological applications wherein the sequence of a small region must be determined from many independent specimens and wherein the link between the specimen and the sequence must be preserved. Examples might include studies of variation within specific regions from a large population, looking for correlations between variants and phenotype in areas that might have been narrowed by prior linkage analysis, or even medical diagnostics. We were faced with the practical matter of determining clone identity and quality in a very large collection of arrayed clones derived from a pooled oligonucleotide mixture. Use of next-generation sequencing technologies (NGST) for interrogating sequence for any of these tasks is hampered if libraries must be constructed independently from each sample or if different barcodes must be applied to each specimen prior to sequencing, particularly if specimen numbers run into many thousands.To circumvent such limitations, we have developed a novel multiplexing framework in which the identity of individual specimens is not encoded directly by an appended barcode sequence. Instead, specimen identities are encoded by positional information created by an optimized series of pooling schema. In this manner, more than 100,000 different samples can be analyzed using only a few hundred barcodes (e.g., 384). Results Conceptual fr...
Complementary techniques that deepen information content and minimize reagent costs are required to realize the full potential of massively parallel sequencing. Here, we describe a resequencing approach that directs focus to genomic regions of high interest by combining hybridization-based purification of multi-megabase regions with sequencing on the Illumina Genome Analyzer (GA). The capture matrix is created by a microarray on which probes can be programmed as desired to target any non-repeat portion of the genome, while the method requires only a basic familiarity with microarray hybridization. We present a detailed protocol suitable for 1-2 µg of input genomic DNA and highlight key design tips in which high specificity (>65% of reads stem from enriched exons) and high sensitivity (98% targeted base pair coverage) can be achieved. We have successfully applied this to the enrichment of coding regions, in both human and mouse, ranging from 0.5 to 4 Mb in length. From genomic DNA library production to basecalled sequences, this procedure takes approximately 9-10 d inclusive of array captures and one Illumina flow cell run.
Next-generation sequencing technologies generate vast catalogs of short RNA sequences from which to mine microRNAs. However, such data must be vetted to appropriately categorize microRNA precursors and interpret their evolution. A recent study annotated hundreds of microRNAs in three Drosophila species on the basis of singleton reads of heterogeneous length1. Our multi-million read datasets indicated that most of these were not substrates of RNAse III cleavage, and comprised many mRNA degradation fragments. We instead identified a distinct and smaller set of novel microRNAs supported by confident cloning signatures, including a high proportion of evolutionarily nascent mirtrons. Our data support a much lower rate in the emergence of lineage-specific microRNAs than previously inferred1, with a net flux of ~1 microRNA/million years of Drosophilid evolution.
Hosts and their microbes have established a sophisticated communication system over many millennia. Within mammalian hosts, this dynamic cross-talk is essential for maintaining intestinal homeostasis. In a genetically susceptible host, dysbiosis of the gut microbiome and dysregulated immune responses are central to the development of inflammatory bowel disease (IBD). Previous surveys of stool from the T-bet −/− Rag2 −/− IBD mouse model revealed microbial features that discriminate between health and disease states. Enterobacteriaceae expansion and increased gene abundances for benzoate degradation, two-component systems, and bacterial motility proteins pointed to the potential involvement of a catecholamine-mediated bacterial signaling axis in colitis pathogenesis. Enterobacteriaceae sense and respond to microbiota-generated signals and host-derived catecholamines through the two-component quorum-sensing Escherichia coli regulators B and C (QseBC) system. On signal detection, QseC activates a cascade to induce virulence gene expression. Although a single pathogen has not been identified as a causative agent in IBD, adherent-invasive Escherichia coli (AIEC) have been implicated. Flagellar expression is necessary for the IBD-associated AIEC strain LF82 to establish colonization. Thus, we hypothesized that qseC inactivation could reduce LF82's virulence, and found that an absence of qseC leads to down-regulated flagellar expression and motility in vitro and reduced colonization in vivo. We extend these findings on the potential of QseC-based IBD therapeutics to three preclinical IBD models, wherein we observe that QseC blockade can effectively modulate colitogenic microbiotas to reduce intestinal inflammation. Collectively, our data support a role for QseC-mediated bacterial signaling in IBD pathogenesis and indicate that QseC inhibition may be a useful microbiota-targeted approach for disease management.colitis | Escherichia coli | QseC | antivirulence | gut microbiome
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