Ontology development for biological systems: immunology.

UNLABELLED: We recently implemented improvements to the representation of immunology content of the biological process branch of the Gene Ontology (GO). The aims of the revision were to provide a comprehensive representation of immunological processes and to improve the organization of immunology related terms in the GO to match current concepts in the field of immunology. With these improvements, the GO will better reflect current understanding in the field of immunology and thus prove to be a more valuable resource for knowledge representation in gene annotation and analysis in the areas of immunology related to genomics and bioinformatics. AVAILABILITY: http://www.geneontology.org.

MIFlowCyt: the minimum information about a Flow Cytometry Experiment.

A fundamental tenet of scientific research is that published results are open to independent validation and refutation. Minimum data standards aid data providers, users, and publishers by providing a specification of what is required to unambiguously interpret experimental findings. Here, we present the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard, stating the minimum information required to report flow cytometry (FCM) experiments. We brought together a cross-disciplinary international collaborative group of bioinformaticians, computational statisticians, software developers, instrument manufacturers, and clinical and basic research scientists to develop the standard. The standard was subsequently vetted by the International Society for Advancement of Cytometry (ISAC) Data Standards Task Force, Standards Committee, membership, and Council. The MIFlowCyt standard includes recommendations about descriptions of the specimens and reagents included in the FCM experiment, the configuration of the instrument used to perform the assays, and the data processing approaches used to interpret the primary output data. MIFlowCyt has been adopted as a standard by ISAC, representing the FCM scientific community including scientists as well as software and hardware manufacturers. Adoptionof MIFlowCyt by the scientific and publishing communities will facilitate third-party understanding and reuse of FCM data.

Components of the antigen processing and presentation pathway revealed by gene expression microarray analysis following B cell antigen receptor (BCR) stimulation.

BACKGROUND: Activation of naïve B lymphocytes by extracellular ligands, e.g. antigen, lipopolysaccharide (LPS) and CD40 ligand, induces a combination of common and ligand-specific phenotypic changes through complex signal transduction pathways. For example, although all three of these ligands induce proliferation, only stimulation through the B cell antigen receptor (BCR) induces apoptosis in resting splenic B cells. In order to define the common and unique biological responses to ligand stimulation, we compared the gene expression changes induced in normal primary B cells by a panel of ligands using cDNA microarrays and a statistical approach, CLASSIFI (Cluster Assignment for Biological Inference), which identifies significant co-clustering of genes with similar Gene Ontology annotation. RESULTS: CLASSIFI analysis revealed an overrepresentation of genes involved in ion and vesicle transport, including multiple components of the proton pump, in the BCR-specific gene cluster, suggesting that activation of antigen processing and presentation pathways is a major biological response to antigen receptor stimulation. Proton pump components that were not included in the initial microarray data set were also upregulated in response to BCR stimulation in follow up experiments. MHC Class II expression was found to be maintained specifically in response to BCR stimulation. Furthermore, ligand-specific internalization of the BCR, a first step in B cell antigen processing and presentation, was demonstrated. CONCLUSION: These observations provide experimental validation of the computational approach implemented in CLASSIFI, demonstrating that CLASSIFI-based gene expression cluster analysis is an effective data mining tool to identify biological processes that correlate with the experimental conditional variables. Furthermore, this analysis has identified at least thirty-eight candidate components of the B cell antigen processing and presentation pathway and sets the stage for future studies focused on a better understanding of the components involved in and unique to B cell antigen processing and presentation.

Activation of the Syk tyrosine kinase is insufficient for downstream signal transduction in B lymphocytes.

BACKGROUND: Immature B lymphocytes and certain B cell lymphomas undergo apoptotic cell death following activation of the B cell antigen receptor (BCR) signal transduction pathway. Several biochemical changes occur in response to BCR engagement, including activation of the Syk tyrosine kinase. Although Syk activation appears to be necessary for some downstream biochemical and cellular responses, the signaling events that precede Syk activation remain ill defined. In addition, the requirements for complete activation of the Syk-dependent signaling step remain to be elucidated. RESULTS: A mutant form of Syk carrying a combination of a K395A substitution in the kinase domain and substitutions of three phenylalanines (3F) for the three C-terminal tyrosines was expressed in a murine B cell lymphoma cell line, BCL1.3B3 to interfere with normal Syk regulation as a means to examine the Syk activation step in BCR signaling. Introduction of this kinase-inactive mutant led to the constitutive activation of the endogenous wildtype Syk enzyme in the absence of receptor engagement through a 'dominant-positive' effect. Under these conditions, Syk kinase activation occurred in the absence of phosphorylation on Syk tyrosine residues. Although Syk appears to be required for BCR-induced apoptosis in several systems, no increase in spontaneous cell death was observed in these cells. Surprisingly, although the endogenous Syk kinase was enzymatically active, no enhancement in the phosphorylation of cytoplasmic proteins, including phospholipase Cgamma2 (PLCgamma2), a direct Syk target, was observed. CONCLUSION: These data indicate that activation of Syk kinase enzymatic activity is insufficient for Syk-dependent signal transduction. This observation suggests that other events are required for efficient signaling. We speculate that localization of the active enzyme to a receptor complex specifically assembled for signal transduction may be the missing event.

Systematic relationships among Lutzomyia sand flies (Diptera: Psychodidae) of Peru and Colombia based on the analysis of 12S and 28S ribosomal DNA sequences.

Lutzomyia spp. are New World phlebotomine sand flies, many of which are involved in the transmission of human diseases, such as leishmaniases and bartonellosis. The systematic classification of the approximately 400 species in the genus has been based on morphological characters, but the relationships within the genus are still very much in question. We have inferred phylogenies of 32 species of phlebotomine sand flies belonging to seven sub-genera and two species groups, by using fragments of the mitochondrial small subunit (12SrRNA) and of the nuclear large subunit (28SrRNA) ribosomal gene sequences. The subgenus Helcocyrtomyia and the Verrucarum species group, prominent representatives of the Peruvian sand fly fauna, were represented by 11 and 7 species, respectively. Although based on a limited number of taxa, the resulting phylogenies, based on 837 characters, provide an initial phylogenetic backbone for the progressive reconstruction of infrageneric relationships within Lutzomyia.

Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data.

BACKGROUND: Advances in multiparameter flow cytometry (FCM) now allow for the independent detection of larger numbers of fluorochromes on individual cells, generating data with increasingly higher dimensionality. The increased complexity of these data has made it difficult to identify cell populations from high-dimensional FCM data using traditional manual gating strategies based on single-color or two-color displays. METHODS: To address this challenge, we developed a novel program, FLOCK (FLOw Clustering without K), that uses a density-based clustering approach to algorithmically identify biologically relevant cell populations from multiple samples in an unbiased fashion, thereby eliminating operator-dependent variability. RESULTS: FLOCK was used to objectively identify seventeen distinct B-cell subsets in a human peripheral blood sample and to identify and quantify novel plasmablast subsets responding transiently to tetanus and other vaccinations in peripheral blood. FLOCK has been implemented in the publically available Immunology Database and Analysis Portal-ImmPort (http://www.immport.org)-for open use by the immunology research community. CONCLUSIONS: FLOCK is able to identify cell subsets in experiments that use multiparameter FCM through an objective, automated computational approach. The use of algorithms like FLOCK for FCM data analysis obviates the need for subjective and labor-intensive manual gating to identify and quantify cell subsets. Novel populations identified by these computational approaches can serve as hypotheses for further experimental study.