Single-cell transcriptomics identifies an effectorness gradient shaping the response of CD4 T cells to cytokines.

Naïve CD4 T cells coordinate the immune response by acquiring an effector phenotype in response to cytokines. However, the cytokine responses in memory T cells remain largely understudied. Here we use quantitative proteomics, bulk RNA-seq, and single-cell RNA-seq of over 40,000 human naïve and memory CD4 T cells to show that responses to cytokines differ substantially between these cell types.

Chromatin activity at GWAS loci identifies T cell states driving complex immune diseases.

Immune-disease-associated variants are enriched in active chromatin regions of T cells and macrophages. However, whether these variants function in specific cell states is unknown. Here we stimulated T cells and macrophages in the presence of 13 cytokines and profiled active and open chromatin regions.

A computational framework for complex disease stratification from multiple large-scale datasets.

Background: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states.

ASPASIA: A toolkit for evaluating the effects of biological interventions on SBML model behaviour.

A calibrated computational model reflects behaviours that are expected or observed in a complex system, providing a baseline upon which sensitivity analysis techniques can be used to analyse pathways that may impact model responses. However, calibration of a model where a behaviour depends on an intervention introduced after a defined time point is difficult, as model responses may be dependent on the conditions at the time the intervention is applied. We present ASPASIA (Automated Simulation Parameter Alteration and SensItivity Analysis), a cross-platform, open-source Java toolkit that addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language (SBML).

Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

Objectives: To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation.

Methods: Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms.

Empowering industrial research with shared biomedical vocabularies.

The life science industries (including pharmaceuticals, agrochemicals and consumer goods) are exploring new business models for research and development that focus on external partnerships. In parallel, there is a desire to make better use of data obtained from sources such as human clinical samples to inform and support early research programmes. Success in both areas depends upon the successful integration of heterogeneous data from multiple providers and scientific domains, something that is already a major challenge within the industry.

Minimum information about a bioactive entity (MIABE).

Bioactive molecules such as drugs, pesticides and food additives are produced in large numbers by many commercial and academic groups around the world. Enormous quantities of data are generated on the biological properties and quality of these molecules. Access to such data - both on licensed and commercially available compounds, and also on those that fail during development - is crucial for understanding how improved molecules could be developed.

Cloning and pharmacological characterisation of the guinea pig 5-ht5A receptor.

The guinea pig 5-hydroxytryptamine(5A) (gp5-ht(5A)) receptor was cloned from guinea pig brain using degenerate polymerase chain reaction (PCR) and shows 88%, 85% and 84% amino acid sequence identity versus the human, rat and mouse 5-ht(5A) receptors, respectively. The receptor was transiently expressed in human embryonic kidney (HEK) 293 cells. [(3)H]-Lysergic acid diethylamide (LSD) bound saturably to gp5-ht(5A)/HEK293 membranes with a K(d) of 2.

Selective expression of regulators of G-protein signaling (RGS) in the human central nervous system.

The human tissue distribution of the nineteen known human regulators of G-protein signaling (RGS) is described. Measurement of RGS mRNA levels in human brain and in nine peripheral tissues revealed striking tissue preferences in gene expression. Five RGS members were identified with enriched expression in brain.