VIP DB--a viral protein domain usage and distribution database.

During the viral infection and replication processes, viral proteins are highly regulated and may interact with host proteins. However, the functions and interaction partners of many viral proteins have yet to be explored. Here, we compiled a VIral Protein domain DataBase (VIP DB) to associate viral proteins with putative functions and interaction partners. We systematically assign domains and infer the functions of proteins and their protein interaction partners from their domain annotations. A total of 2,322 unique domains that were identified from 2,404 viruses are used as a starting point to correlate GO classification, KEGG metabolic pathway annotation and domain-domain interactions. Of the unique domains, 42.7% have GO records, 39.6% have at least one domain-domain interaction record and 26.3% can also be found in either mammals or plants. This database provides a resource to help virologists identify potential roles for viral protein. All of the information is available at http://vipdb.cgu.edu.tw.

DSAP: deep-sequencing small RNA analysis pipeline.

DSAP is an automated multiple-task web service designed to provide a total solution to analyzing deep-sequencing small RNA datasets generated by next-generation sequencing technology. DSAP uses a tab-delimited file as an input format, which holds the unique sequence reads (tags) and their corresponding number of copies generated by the Solexa sequencing platform. The input data will go through four analysis steps in DSAP: (i) cleanup: removal of adaptors and poly-A/T/C/G/N nucleotides; (ii) clustering: grouping of cleaned sequence tags into unique sequence clusters; (iii) non-coding RNA (ncRNA) matching: sequence homology mapping against a transcribed sequence library from the ncRNA database Rfam (http://rfam.sanger.ac.uk/); and (iv) known miRNA matching: detection of known miRNAs in miRBase (http://www.mirbase.org/) based on sequence homology. The expression levels corresponding to matched ncRNAs and miRNAs are summarized in multi-color clickable bar charts linked to external databases. DSAP is also capable of displaying miRNA expression levels from different jobs using a log(2)-scaled color matrix. Furthermore, a cross-species comparative function is also provided to show the distribution of identified miRNAs in different species as deposited in miRBase. DSAP is available at http://dsap.cgu.edu.tw.

Identification of microRNA in the protist Trichomonas vaginalis.

MicroRNAs (miRNAs) are a class of small noncoding RNAs that have important regulatory roles in multicellular organisms. However, miRNA has never been identified experimentally in protist. Direct cloning of 438 expressed miRNA tags by microRNA serial analysis of gene expression from the parasitic protist Trichomonas vaginalis identified nine candidate miRNAs. Bioinformatics analysis of the corresponding genomic region revealed that these miRNA candidates contain a classical stem-loop-stem structure of pre-microRNAs. Analysis of the 20 nt long mature tva-miR-001 showed that it is an intergenic miRNA located at the scaffold DS113596. Tva-miR-001 was differentially expressed in the trophozoite, pseudocyst and amoeboid stages. Based on the experimental results of the present study, we provided solid evidence that protist possesses a miRNA regulating network comparable with multicellular organisms for the first time.

A proteome reference map of Trichomonas vaginalis.

Trichomoniasis caused by Trichomonas vaginalis is the most common sexual transmitted infection in the world. The 170-MB genome of this protozoan contains 60,000 genes, the largest number of genes ever identified in protozoan. High-throughput expression sequenced tag analysis showed that at least 4,000 genes were expressed in the trophozoite stage. In the present study, we use two-dimensional electrophoresis combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry analysis to profile, identify, and characterize proteins expressed in the trophozoite stage of T. vaginalis. A total of 247 spots representing 164 different proteins were identified. The identified proteins with known sequence or motif/domain homologies were further classified into groups according to their biological functions. Among them, proteins related to carbohydrate metabolism represented the most abundant category in the T. vaginalis proteome. This study presented the most extensive proteomic analysis of T. vaginalis to date and provided a reference proteome database for future comparative proteomic studies.