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.

Proteomics LIMS: A caBIG project, year 1.

protLIMS is a web-based proteomics laboratory information management system. In February, we released version 1 of protLIMS, completed to the year one goal: The web-interface provides for recording of the biological material, protein mixture preparation, 2D-PAGE, gel image files and spot and plug mapping. Associated files may be uploaded and retrieved through the web-interface to the file system. In year two, protLIMS will be extended to accommodate mass spectrometric analyses and protein identification.

Bayesian decomposition: analyzing microarray data within a biological context.

The detection and correct identification of cancer, especially at an early stage, are vitally important for patient survival and quality of life. Since signaling pathways play critical roles in cancer development and metastasis, methods that reliably assess the activity of these pathways are critical to understand cancer and the response to therapy. Bayesian Decomposition (BD) identifies signatures of expression that can be linked directly to signaling pathway activity, allowing the changes in mRNA levels to be used as downstream indicators of pathway activity. Here, we demonstrate this ability by identifying the downstream expression signal associated with the mating response in Saccharomyces cerevisiae and showing that this signal disappears in deletion mutants of genes critical to the MAPK signaling cascade used to trigger the response. We also show the use of BD in the context of supervised learning, by analyzing the Mus musculus tissue-specific data set provided by Project Normal. The algorithm correctly removes routine metabolic processes, allowing tissue-specific signatures of expression to be identified. Gene ontology is used to interpret these signatures. Since a number of modern therapeutics specifically target signaling proteins, it is important to be able to identify changes in signaling pathways in order to use microarray data to interpret cancer response. By removing routine metabolic signatures and linking specific signatures to signaling pathway activity, BD makes it possible to link changes in microarray results to signaling pathways.

miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and may downregulate the high affinity cationic amino acid transporter CAT-1.

These studies show that miR-122, a 22-nucleotide microRNA, is derived from a liver-specific noncoding polyadenylated RNA transcribed from the gene hcr. The exact sequence of miR-122 as well as the adjacent secondary structure within the hcr mRNA are conserved from mammalian species back to fish. Levels of miR-122 in the mouse liver increase to half maximal values around day 17 of embryogenesis, and reach near maximal levels of 50,000 copies per average cell before birth. Lewis et al. (2003) predicted the cationic amino acid transporter (CAT-1 or SLC7A1) as a miR-122 target. CAT-1 protein and its mRNA are expressed in all mammalian tissues but with lower levels in adult liver. Furthermore, during mouse liver development CAT-1 mRNA decreases in an almost inverse correlation with miR-122. Eight potential miR-122 target sites were predicted within the human CAT-1 mRNA, with six in the 3'-untranslated region. Using a reporter construct it was found that just three of the predicted sites, linked in a 400-nucleotide sequence from human CAT-1, acted with synergy and were sufficient to strongly inhibit protein synthesis and reduce mRNA levels. In summary, these studies followed the accumulation during development of miR-122 from its mRNA precursor, hcr, through to identification of what may be a specific mRNA target, CAT-1.

ASAP: automated sequence annotation pipeline for web-based updating of sequence information with a local dynamic database.

The automated sequence annotation pipeline (ASAP) is designed to ease routine investigation of new functional annotations on unknown sequences, such as expressed sequence tags (ESTs), through querying of web-accessible resources and maintenance of a local database. The system allows easy use of the output from one search as the input for a new search, as well as the filtering of results. The database is used to store formats and parameters and information for parsing data from web sites. The database permits easy updating of format information should a site modify the format of a query or of a returned web page.