ToxoDB (http://ToxoDB.org) is a genome and functional genomic database for the protozoan parasite Toxoplasma gondii. It incorporates the sequence and annotation of the T. gondii ME49 strain, as well as genome sequences for the GT1, VEG and RH (Chr Ia, Chr Ib) strains. Sequence information is integrated with various other genomic-scale data, including community annotation, ESTs, gene expression and proteomics data. ToxoDB has matured significantly since its initial release. Here we outline the numerous updates with respect to the data and increased functionality available on the website.

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequen-cing consortium. This resource incorporates the recently completed P. falciparum genome sequence and annotation, as well as draft sequence and annotation emerging from other Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for intra-and inter-species comparisons. Sequence information is integrated with other geno-mic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects and proteomics studies. The relational schema used to build PlasmoDB, GUS (Genomics Unified Schema) employs a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically-based, queries of the database. A stand-alone version of the database is also available on CD-ROM (P. falciparum GenePlot), facilitating access to the data in situations where internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to facilitate utilization of the vast quantities of genomic-scale data produced by the global malaria research community. The software used to develop PlasmoDB has been used to create a second Apicomplexan parasite genome database, ToxoDB

No abstract

We introduce a method for analyzing small interfering RNA (siRNA) genetic screens based entirely on off-target effects. Using a screen for members of the Wnt pathway, we demonstrate that this method identifies known pathway components, some of which are not present in the screening library. This technique can be applied to siRNA screen results retroactively to confirm positives and identify genes missed using conventional methods for on-target gene selection.

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates finished and draft genome sequence data and annotation emerging from Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for cross-species comparisons. Sequence information is also integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects. The relational schemas used to build PlasmoDB [Genomics Unified Schema (GUS) and RNA Abundance Database (RAD)] employ a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically based queries of the database. A version of the database is also available on CD-ROM (Plasmodium GenePlot), facilitating access to the data in situations where Internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to enhance utilization of the vast quantities of data emerging from genome-scale projects by the global malaria research community.

Genome-scale small interfering RNA (siRNA) screens have become an increasingly popular approach to new target identification and pathway elucidation. However, the large data sets generated from siRNA screens have demonstrated high false-positive rates and the requirement for extensive experimental triage to distinguish true hits. A number of groups have independently reported the presence of siRNAs with identical seed sequences among their top screening hits. Based on these observations, we have developed a comprehensive technique for detecting and visualizing seed-based off-target effects in siRNA screening data. This is accomplished by analyzing the behavior of siRNAs that share identical seed sequences, which we refer to as common seed analysis (CSA). By applying these techniques to primary screening data of the Wnt pathway, we identify 158 distinct seed sequences that have a statistically significant effect on the assay. The promiscuous seed sequences identified in this manner can then be discounted in the analysis of follow-up experiments using single siRNAs. The ability to detect off-target effects when sufficient numbers of siRNAs share a common seed has significant implications for the design of siRNA screening experiments, data analysis, hit selection, and library design.

BackgroundMicroarrays are invaluable tools for genome interrogation, SNP detection, and expression analysis, among other applications. Such broad capabilities would be of value to many pathogen research communities, although the development and use of genome-scale microarrays is often a costly undertaking. Therefore, effective methods for reducing unnecessary probes while maintaining or expanding functionality would be relevant to many investigators.ResultsTaking advantage of available genome sequences and annotation for Toxoplasma gondii (a pathogenic parasite responsible for illness in immunocompromised individuals) and Plasmodium falciparum (a related parasite responsible for severe human malaria), we designed a single oligonucleotide microarray capable of supporting a wide range of applications at relatively low cost, including genome-wide expression profiling for Toxoplasma, and single-nucleotide polymorphism (SNP)-based genotyping of both T. gondii and P. falciparum. Expression profiling of the three clonotypic lineages dominating T. gondii populations in North America and Europe provides a first comprehensive view of the parasite transcriptome, revealing that ~49% of all annotated genes are expressed in parasite tachyzoites (the acutely lytic stage responsible for pathogenesis) and 26% of genes are differentially expressed among strains. A novel design utilizing few probes provided high confidence genotyping, used here to resolve recombination points in the clonal progeny of sexual crosses. Recent sequencing of additional T. gondii isolates identifies >620 K new SNPs, including ~11 K that intersect with expression profiling probes, yielding additional markers for genotyping studies, and further validating the utility of a combined expression profiling/genotyping array design. Additional applications facilitating SNP and transcript discovery, alternative statistical methods for quantifying gene expression, etc. are also pursued at pilot scale to inform future array designs.ConclusionsIn addition to providing an initial global view of the T. gondii transcriptome across major lineages and permitting detailed resolution of recombination points in a historical sexual cross, the multifunctional nature of this array also allowed opportunities to exploit probes for purposes beyond their intended use, enhancing analyses. This array is in widespread use by the T. gondii research community, and several aspects of the design strategy are likely to be useful for other pathogens.

RNA interference (RNAi) is a post‐transcriptional gene silencing process mediated by short, interfering RNA molecules (siRNAs) targeting complementary mRNA. siRNAs prevent protein expression and create an opportunity to use RNAi for drug target identification, validation, and therapeutics for treating human diseases. Successful application requires efficient delivery approaches, a hurdle which can be overcome through packaging siRNA inside lipid nanoparticles (LNPs). To evaluate biological activities of LNPs, we developed innovative assays and microscopy techniques to monitor tissue biodistribution, cell internalization, endosomal escape, and gene silencing. In combination with fluorescent markers, we visualized Cy5‐labeled siRNA encapsulated in LNPs and quantified kinetics of cell uptake and endosomal escape in various cells. Some LNPs displayed defects in cell uptake whereas other internalized into endosomes and distributed rapidly to the cytosol. Use of endocytosis inhibitors reveal clathrin and non‐clathrin coated pits participate, in part, in internalization in hepatocytes. Multiplexed, image‐based assays were employed to evaluate potential cellular toxicities and bioinformatics tools were developed to visualize multiparameter HCS data and mine phenotypic signatures.