Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics

Bad to the bone: B cell acute lymphoblastic leukemia cells mediate bone destruction

Skeletal morbidities continue to cause acute and long-term burdens for B-ALL patients underscoring the need to identify the mechanisms underlying these processes and to develop effective therapies. Our recent findings demonstrated that B-ALL cells isolated at patient diagnosis can cause bone destruction and have identified the receptor activator of nuclear factor κ-B (RANK-RANKL) ligand axis as a critical effector of these effects

Two Genetic Loci Regulate T Cell–Dependent Islet Inflammation and Drive Autoimmune Diabetes Pathogenesis

Insulin-dependent diabetes mellitus (IDDM) is a polygenic disease caused by progressive autoimmune infiltration (insulitis) of the pancreatic islets of Langerhan, culminating in the destruction of insulin-producing β cells. Genome scans of families with diabetes suggest that multiple loci make incremental contributions to disease susceptibility. However, only the IDDM1 locus is well characterized, at a molecular and functional level, as alleleic variants of the major histocompatibility complex (MHC) class II HLA-DQB1, DRB1, and DPB1 genes that mediate antigen presentation to T cells. In the nonobese diabetic (NOD) mouse model, the Idd1 locus was shown to be the orthologous MHC gene I-Ab. Inheritance of susceptibility alleles at IDDM1/Idd1 is insufficient for disease development in humans and NOD mice. However, the identities and functions of the remaining diabetes loci (Idd2–Idd19 in NOD mice) are largely undefined. A crucial limitation in previous genetic linkage studies of this disease has been reliance on a single complex phenotype—diabetes that displays low penetrance and is of limited utility for high-resolution genetic mapping. Using the NOD model, we have identified an early step in diabetes pathogenesis that behaves as a highly penetrant trait. We report that NOD-derived alleles at both the Idd5 and Idd13 loci regulate a T lymphocyte–dependent progression from a benign to a destructive stage of insulitis. Human chromosomal regions orthologous to the Idd5 and -13 intervals are also linked to diabetes risk, suggesting that conserved genes encoded at these loci are central regulators of disease pathogenesis. These data are the first to reveal a role for individual non-MHC Idd loci in a specific, critical step in diabetes pathogenesis—T cell recruitment to islet lesions driving destructive inflammation. Importantly, identification of intermediate phenotypes in complex disease pathogenesis provides the tools required to progress toward gene identification at these loci

gamma delta T Cells Are Essential Effectors of Type 1 Diabetes in the Nonobese Diabetic Mouse Model

γδ T cells, a lineage of innate-like lymphocytes, are distinguished from conventional αβ T cells in their antigen-recognition, cell activation requirements and effector functions. γδ T cells have been implicated in the pathology of several human autoimmune and inflammatory diseases and their corresponding mouse models, but their specific roles in these diseases have not been elucidated. We report that γδTCR(+) cells including both the CD27(−)CD44(hi) and CD27(+)CD44(lo) subsets infiltrate islets of pre-diabetic non-obese diabetic (NOD) mice. Moreover, NOD CD27(−)CD44(hi) and CD27(+)CD44(lo) γδ T cells were pre-programmed to secrete IL-17, or IFN-γ upon activation. Adoptive transfer of T1D to T and B lymphocyte-deficient NOD recipients was greatly potentiated when γδ T cells, and specifically the CD27(−) γδ T cell subset, were included compared to transfer of αβ T cells alone. Antibody-mediated blockade of IL-17 prevented T1D transfer in this setting. Moreover, introgression of genetic Tcrd deficiency onto the NOD background provided robust T1D protection, supporting a non-redundant, pathogenic role of γδ T cells in this model. The potent contributions of CD27(−) γδ T cells and IL-17 to islet inflammation and diabetes reported here suggest that these mechanisms may also underlie human T1D