16 research outputs found
Improving RNA-Seq Precision with MapAl
With currently available RNA-Seq pipelines, expression estimates for most genes are very noisy. We here introduce MapAl, a tool for RNA-Seq expression profiling that builds on the established programs Bowtie and Cufflinks. In the post-processing of RNA-Seq reads, it incorporates gene models already at the stage of read alignment, increasing the number of reliably measured known transcripts consistently by 50%. Adding genes identified de novo then allows a reliable assessment of double the total number of transcripts compared to other available pipelines. This substantial improvement is of general relevance: Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not
Status Report on the Development of Research Campaigns
Research campaigns were conceived as a means to focus EMSL research on specific scientific questions. Campaign will help fulfill the Environmental Molecular Sciences Laboratory (EMSL) strategic vision to develop and integrate, for use by the scientific community, world leading capabilities that transform understanding in the environmental molecular sciences and accelerate discoveries relevant to the Department of Energy’s (DOE’s) missions. Campaigns are multi-institutional multi-disciplinary projects with scope beyond those of normal EMSL user projects. The goal of research campaigns is to have EMSL scientists and users team on the projects in the effort to accelerate progress and increase impact in specific scientific areas by focusing user research, EMSL resources, and expertise in those areas. This report will give a history and update on the progress of those campaigns
Oncostatin M drives intestinal inflammation and predicts response to tumor necrosis factor–neutralizing therapy in patients with inflammatory bowel disease
Inflammatory bowel diseases (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), are complex chronic inflammatory conditions of the gastrointestinal tract that are driven by perturbed cytokine pathways. Anti-tumor necrosis factor-α (TNF) antibodies are mainstay therapies for IBD. However, up to 40% of patients are nonresponsive to anti-TNF agents, which makes the identification of alternative therapeutic targets a priority. Here we show that, relative to healthy controls, inflamed intestinal tissues from patients with IBD express high amounts of the cytokine oncostatin M (OSM) and its receptor (OSMR), which correlate closely with histopathological disease severity. The OSMR is expressed in nonhematopoietic, nonepithelial intestinal stromal cells, which respond to OSM by producing various proinflammatory molecules, including interleukin (IL)-6, the leukocyte adhesion factor ICAM1, and chemokines that attract neutrophils, monocytes, and T cells. In an animal model of anti-TNF-resistant intestinal inflammation, genetic deletion or pharmacological blockade of OSM significantly attenuates colitis. Furthermore, according to an analysis of more than 200 patients with IBD, including two cohorts from phase 3 clinical trials of infliximab and golimumab, high pretreatment expression of OSM is strongly associated with failure of anti-TNF therapy. OSM is thus a potential biomarker and therapeutic target for IBD, and has particular relevance for anti-TNF-resistant patients
Biological Interactions and Dynamics Science Theme Advisory Panel (BID-STAP)
This report contains the charge to the panel, the panel's discussions and panel recommendations
CO2 exposure at pressure impacts metabolism and stress responses in the model sulfate-reducing bacterium Desulfovibrio vulgaris strain Hildenborough
Geologic carbon dioxide (CO2) sequestration drives physical and geochemical changes in deep subsurface environments that impact indigenous microbial activities. The combined effects of pressurized CO2 on a model sulfate-reducing microorganism, Desulfovibrio vulgaris, have been assessed using a suite of genomic and kinetic measurements. Novel high-pressure NMR time-series measurements using 13C-lactate were used to track D. vulgaris metabolism. We identified cessation of respiration at CO2 pressures of 10 bar, 25 bar, 50 bar, and 80 bar. Concurrent experiments using N2 as the pressurizing phase had no negative effect on microbial respiration, as inferred from reduction of sulfate to sulfide. Complementary pressurized batch incubations and fluorescence microscopy measurements supported NMR observations, and indicated that non-respiring cells were mostly viable at 50 bar CO2 for at least four hours, and at 80 bar CO2 for two hours. The fraction of dead cells increased rapidly after four hours at 80 bar CO2. Transcriptomic (RNA-Seq) measurements on mRNA transcripts from CO2-incubated biomass indicated that cells up-regulated the production of certain amino acids (leucine, isoleucine) following CO2 exposure at elevated pressures, likely as part of a general stress response. Evidence for other poorly understood stress responses were also identified within RNA-Seq data, suggesting that while pressurized CO2 severely limits the growth and respiration of D. vulgaris cells, biomass retains intact cell membranes at pressures up to 80 bar CO2. Together, these data show that geologic sequestration of CO2 may have significant impacts on rates of sulfate reduction in many deep subsurface environments where this metabolism is a key respiratory process
Recommended from our members
Biological Interactions and Dynamics Science Theme Advisory Panel (BID-STAP)
This report contains the charge to the panel, the panel's discussions and panel recommendations
Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling
Motivation: Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not. With the compilation of large-scale RNA-Seq datasets with technical replicate samples, however, we can now, for the first time, perform a systematic analysis of the precision of expression level estimates from massively parallel sequencing technology. This then allows considerations for its improvement by computational or experimental means