Modeling the Mechanism of Action of a DGAT1 Inhibitor Using a Causal Reasoning Platform

Triglyceride accumulation is associated with obesity and type 2 diabetes. Genetic disruption of diacylglycerol acyltransferase 1 (DGAT1), which catalyzes the final reaction of triglyceride synthesis, confers dramatic resistance to high-fat diet induced obesity. Hence, DGAT1 is considered a potential therapeutic target for treating obesity and related metabolic disorders. However, the molecular events shaping the mechanism of action of DGAT1 pharmacological inhibition have not been fully explored yet. Here, we investigate the metabolic molecular mechanisms induced in response to pharmacological inhibition of DGAT1 using a recently developed computational systems biology approach, the Causal Reasoning Engine (CRE). The CRE algorithm utilizes microarray transcriptomic data and causal statements derived from the biomedical literature to infer upstream molecular events driving these transcriptional changes. The inferred upstream events (also called hypotheses) are aggregated into biological models using a set of analytical tools that allow for evaluation and integration of the hypotheses in context of their supporting evidence. In comparison to gene ontology enrichment analysis which pointed to high-level changes in metabolic processes, the CRE results provide detailed molecular hypotheses to explain the measured transcriptional changes. CRE analysis of gene expression changes in high fat habituated rats treated with a potent and selective DGAT1 inhibitor demonstrate that the majority of transcriptomic changes support a metabolic network indicative of reversal of high fat diet effects that includes a number of molecular hypotheses such as PPARG, HNF4A and SREBPs. Finally, the CRE-generated molecular hypotheses from DGAT1 inhibitor treated rats were found to capture the major molecular characteristics of DGAT1 deficient mice, supporting a phenotype of decreased lipid and increased insulin sensitivity

Nodeomics: Pathogen Detection in Vertebrate Lymph Nodes Using Meta-Transcriptomics

The ongoing emergence of human infections originating from wildlife highlights the need for better knowledge of the microbial community in wildlife species where traditional diagnostic approaches are limited. Here we evaluate the microbial biota in healthy mule deer (Odocoileus hemionus) by analyses of lymph node meta-transcriptomes. cDNA libraries from five individuals and two pools of samples were prepared from retropharyngeal lymph node RNA enriched for polyadenylated RNA and sequenced using Roche-454 Life Sciences technology. Protein-coding and 16S ribosomal RNA (rRNA) sequences were taxonomically profiled using protein and rRNA specific databases. Representatives of all bacterial phyla were detected in the seven libraries based on protein-coding transcripts indicating that viable microbiota were present in lymph nodes. Residents of skin and rumen, and those ubiquitous in mule deer habitat dominated classifiable bacterial species. Based on detection of both rRNA and protein-coding transcripts, we identified two new proteobacterial species; a Helicobacter closely related to Helicobacter cetorum in the Helicobacter pylori/Helicobacter acinonychis complex and an Acinetobacter related to Acinetobacter schindleri. Among viruses, a novel gamma retrovirus and other members of the Poxviridae and Retroviridae were identified. We additionally evaluated bacterial diversity by amplicon sequencing the hypervariable V6 region of 16S rRNA and demonstrate that overall taxonomic diversity is higher with the meta-transcriptomic approach. These data provide the most complete picture to date of the microbial diversity within a wildlife host. Our research advances the use of meta-transcriptomics to study microbiota in wildlife tissues, which will facilitate detection of novel organisms with pathogenic potential to human and animals

Gut Microbial Gene Expression in Mother-Fed and Formula-Fed Piglets

Effects of diet on the structure and function of gut microbial communities in newborn infants are poorly understood. High-resolution molecular studies are needed to definitively ascertain whether gut microbial communities are distinct in milk-fed and formula-fed infants.Pyrosequencing-based whole transcriptome shotgun sequencing (RNA-seq) was used to evaluate community wide gut microbial gene expression in 21 day old neonatal piglets fed either with sow's milk (mother fed, MF; n = 4) or with artificial formula (formula fed, FF; n = 4). Microbial DNA and RNA were harvested from cecal contents for each animal. cDNA libraries and 16S rDNA amplicons were sequenced on the Roche 454 GS-FLX Titanium system. Communities were similar at the level of phylum but were dissimilar at the level of genus; Prevotella was the dominant genus within MF samples and Bacteroides was most abundant within FF samples. Screened cDNA sequences were assigned functional annotations by the MG-RAST annotation pipeline and based upon best-BLASTX-hits to the NCBI COG database. Patterns of gene expression were very similar in MF and FF animals. All samples were enriched with transcripts encoding enzymes for carbohydrate and protein metabolism, as well as proteins involved in stress response, binding to host epithelium, and lipopolysaccharide metabolism. Carbohydrate utilization transcripts were generally similar in both groups. The abundance of enzymes involved in several pathways related to amino acid metabolism (e.g., arginine metabolism) and oxidative stress response differed in MF and FF animals.Abundant transcripts identified in this study likely contribute to a core microbial metatranscriptome in the distal intestine. Although microbial community gene expression was generally similar in the cecal contents of MF and FF neonatal piglets, several differentially abundant gene clusters were identified. Further investigations of gut microbial gene expression will contribute to a better understanding of normal and abnormal enteric microbiology in animals and humans

Measurement of the mass difference m(D-s(+))-m(D+) at CDF II

We present a measurement of the mass difference m(D-s(+))-m(D+), where both the D-s(+) and D+ are reconstructed in the phipi(+) decay channel. This measurement uses 11.6 pb(-1) of data collected by CDF II using the new displaced-track trigger. The mass difference is found to be m(D-s(+))-m(D+)=99.41+/-0.38(stat)+/-0.21(syst) MeV/c(2)

Limits to reproduction and seed size-number trade-offs that shape forest dominance and future recovery

International audienceThe relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential

Limits to reproduction and seed size-number tradeoffs that shape forest dominance and future recovery

The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential