David S. Roos

Molecular tools for genetic dissection of the protozoan parasite Toxoplasma gondii.

Publisher Summary The genetic structure of Toxoplasma gondii is notable chiefly for being relatively conventional— similar to that of its mammalian host cells with respect to gene organization, codon usage, and nucleotide bias. These observations have led several investigators to examine the feasibility of molecular transformation in this parasite. This chapter outlines the use of several of the molecular genetic tools that have recently been developed for the T. gondii system. An introduction to parasite culture techniques is also provided. Recombinant molecules can be expressed either transiently or as stable transformants, as episomes or integrated into the parasite genome, and as single copy or multicopy transgenes. Stable integration can be produced by random nonhomologous recombination, single-site homologous recombination, or perfect gene replacement. Many of these outcomes can be selected specifically using appropriate vectors and transformation conditions. The extraordinarily high frequencies of stable transformation observed permit cloning by complementation, insertional mutagenesis/marker rescue, gene knock-outs, and allelic replacement. In combination with available classical and “cell-genetic” possibilities and physical and genetic mapping strategies, these tools provide a powerful arsenal for investigations into the biology of intracellular parasitism.

Tropical infectious diseases: metabolic maps and functions of the Plasmodium falciparum apicoplast.

Discovery of a relict chloroplast (the apicoplast) in malarial parasites presented new opportunities for drug development. The apicoplast – although no longer photosynthetic – is essential to parasites. Combining bioinformatics approaches with experimental validation in the laboratory, we have identified more than 500 proteins predicted to function in the apicoplast. By comparison with plant chloroplasts, we have reconstructed several anabolic pathways for the parasite plastid that are fundamentally different to the analogous pathways in the human host and are potentially good targets for drug development. Products of these pathways seem to be exported from the apicoplast and might be involved in host-cell invasion.

TriTrypDB: a functional genomic resource for the Trypanosomatidae

TriTrypDB (http://tritrypdb.org) is an integrated database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. TriTrypDB is a collaborative project, utilizing the GUS/WDK computational infrastructure developed by the Eukaryotic Pathogen Bioinformatics Resource Center (EuPathDB.org) to integrate genome annotation and analyses from GeneDB and elsewhere with a wide variety of functional genomics datasets made available by members of the global research community, often pre-publication. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ‘User Comments’ may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate.

Chemical genetics of Plasmodium falciparum

Malaria caused by Plasmodium falciparum is a disease that is responsible for 880,000 deaths per year worldwide. Vaccine development has proved difficult and resistance has emerged for most antimalarial drugs. To discover new antimalarial chemotypes, we have used a phenotypic forward chemical genetic approach to assay 309,474 chemicals. Here we disclose structures and biological activity of the entire library—many of which showed potent in vitro activity against drug-resistant P. falciparum strains—and detailed profiling of 172 representative candidates. A reverse chemical genetic study identified 19 new inhibitors of 4 validated drug targets and 15 novel binders among 61 malarial proteins. Phylochemogenetic profiling in several organisms revealed similarities between Toxoplasma gondii and mammalian cell lines and dissimilarities between P. falciparum and related protozoans. One exemplar compound displayed efficacy in a murine model. Our findings provide the scientific community with new starting points for malaria drug discovery.

PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing 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 genomic-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 (http://ToxoDB.org).

A review of the global burden, novel diagnostics, therapeutics, and vaccine targets for cryptosporidium

Cryptosporidium spp are well recognised as causes of diarrhoeal disease during waterborne epidemics and in immunocompromised hosts. Studies have also drawn attention to an underestimated global burden and suggest major gaps in optimum diagnosis, treatment, and immunisation. Cryptosporidiosis is increasingly identified as an important cause of morbidity and mortality worldwide. Studies in low-resource settings and high-income countries have confirmed the importance of cryptosporidium as a cause of diarrhoea and childhood malnutrition. Diagnostic tests for cryptosporidium infection are suboptimum, necessitating specialised tests that are often insensitive. Antigen-detection and PCR improve sensitivity, and multiplexed antigen detection and molecular assays are underused. Therapy has some effect in healthy hosts and no proven efficacy in patients with AIDS. Use of cryptosporidium genomes has helped to identify promising therapeutic targets, and drugs are in development, but methods to assess the efficacy in vitro and in animals are not well standardised. Partial immunity after exposure suggests the potential for successful vaccines, and several are in development; however, surrogates of protection are not well defined. Improved methods for propagation and genetic manipulation of the organism would be significant advances.

Genomic-scale prioritization of drug targets: the TDR Targets database

The increasing availability of genomic data for pathogens that cause tropical diseases has created new opportunities for drug discovery and development. However, if the potential of such data is to be fully exploited, the data must be effectively integrated and be easy to interrogate. Here, we discuss the development of the TDR Targets database (http://tdrtargets.org), which encompasses extensive genetic, biochemical and pharmacological data related to tropical disease pathogens, as well as computationally predicted druggability for potential targets and compound desirability information. By allowing the integration and weighting of this information, this database aims to facilitate the identification and prioritization of candidate drug targets for pathogens.

Creating a honey bee consensus gene set

BackgroundWe wished to produce a single reference gene set for honey bee (Apis mellifera). Our motivation was twofold. First, we wished to obtain an improved set of gene models with increased coverage of known genes, while maintaining gene model quality. Second, we wished to provide a single official gene list that the research community could further utilize for consistent and comparable analyses and functional annotation.ResultsWe created a consensus gene set for honey bee (Apis mellifera) using GLEAN, a new algorithm that uses latent class analysis to automatically combine disparate gene prediction evidence in the absence of known genes. The consensus gene models had increased representation of honey bee genes without sacrificing quality compared with any one of the input gene predictions. When compared with manually annotated gold standards, the consensus set of gene models was similar or superior in quality to each of the input sets.ConclusionMost eukaryotic genome projects produce multiple gene sets because of the variety of gene prediction programs. Each of the gene prediction programs has strengths and weaknesses, and so the multiplicity of gene sets offers users a more comprehensive collection of genes to use than is available from a single program. On the other hand, the availability of multiple gene sets is also a cause for uncertainty among users as regards which set they should use. GLEAN proved to be an effective method to combine gene lists into a single reference set.

Apicomplexan plastids as drug targets

Prokaryotic metabolic pathways in the relict plastid of apicomplexan parasites make this organelle a promising target for drug development. The parasiticidal activity of several herbicides and antibacterial antibiotics is suspected to be a result of their ability to inhibit key plastid activities.

Using OrthoMCL to assign proteins to OrthoMCL-DB groups or to cluster proteomes into new ortholog groups.

OrthoMCL is an algorithm for grouping proteins into ortholog groups based on their sequence similarity. OrthoMCL-DB is a public database that allows users to browse and view ortholog groups that were pre-computed using the OrthoMCL algorithm. Version 4 of this database contained 116,536 ortholog groups clustered from 1,270,853 proteins obtained from 88 eukaryotic genomes, 16 archaean genomes, and 34 bacterial genomes. Future versions of OrthoMCL-DB will include more proteomes as more genomes are sequenced. Here, we describe how you can group your proteins of interest into ortholog clusters using two different means provided by the OrthoMCL system. The OrthoMCL-DB Web site has a tool for uploading and grouping a set of protein sequences, typically representing a proteome. This method maps the uploaded proteins to existing groups in OrthoMCL-DB. Alternatively, if you have proteins from a set of genomes that need to be grouped, you can download, install, and run the stand-alone OrthoMCL software.