IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds.

The parasite species of genus Plasmodium causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, computational prediction of new Antimalarial compounds with novel targets in the proteome of Plasmodium sp. is a very important goal for the pharmaceutical industry. We can expect that the success of the pre-clinical assay depends on the conditions of assay per se, the chemical structure of the drug, the structure of the target protein to be targeted, as well as on factors governing the expression of this protein in the proteome such as genes (Deoxyribonucleic acid, DNA) sequence and/or chromosomes structure. However, there are no reports of computational models that consider all these factors simultaneously. Some of the difficulties for this kind of analysis are the dispersion of data in different datasets, the high heterogeneity of data, etc. In this work, we analyzed three databases ChEMBL (Chemical database of the European Molecular Biology Laboratory), UniProt (Universal Protein Resource), and NCBI-GDV (National Center for Biotechnology Information-Genome Data Viewer) to achieve this goal. The ChEMBL dataset contains outcomes for 17,758 unique assays of potential Antimalarial compounds including numeric descriptors (variables) for the structure of compounds as well as a huge amount of information about the conditions of assays. The NCBI-GDV and UniProt datasets include the sequence of genes, proteins, and their functions. In addition, we also created two partitions (cassayj = caj and cdataj = cdj) of categorical variables from theChEMBL dataset. These partitions contain variables that encode information about experimental conditions of preclinical assays (caj) or about the nature and quality of data (cdj). These categorical variables include information about 22 parameters of biological activity (ca0), 28 target proteins (ca1), and 9 organisms of assay (ca2), etc. We also created another partition of (cprotj = cpj) including categorical variables with biological information about the target proteins, genes, and chromosomes. These variables cover32 genes (cp0), 10 chromosomes (cp1), gene orientation (cp2), and 31 protein functions (cp3). We used a Perturbation-Theory Machine Learning Information Fusion (IFPTML) algorithm to map all this information (from three databases) into and train a predictive model. Shannon's entropy measure Shk (numerical variables) was used to quantify the information about the structure of drugs, protein sequences, gene sequences, and chromosomes in the same information scale. Perturbation Theory Operators (PTOs) with the form of Moving Average (MA) operators have been used to quantify perturbations (deviations) in the structural variables with respect to their expected values for different subsets (partitions) of categorical variables. We obtained three IFPTML models using General Discriminant Analysis (GDA), Classification Tree with Univariate Splits (CTUS), and Classification Tree with Linear Combinations (CTLC). The IFPTML-CTLC presented the better performance with Sensitivity Sn(%) = 83.6/85.1, and Specificity Sp(%) = 89.8/89.7 for training/validation sets, respectively. This model could become a useful tool for the optimization of preclinical assays of new Antimalarial compounds vs. different proteins in the proteome of Plasmodium.

Culture-free genome-wide locus sequence typing (GLST) provides new perspectives on Trypanosoma cruzi dispersal and infection complexity.

Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly from host/vector material but are often too complex and expensive for resource-poor settings where infectious diseases prevail. This study proposes a simple, cost-effective 'genome-wide locus sequence typing' (GLST) tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation at under 4 USD per sample. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/µl T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, TcV and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate TcI, TcIII, TcIV and TcV + TcVI and appear to distinguish multiclonal infections within TcI. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research.

Identity-by-descent with uncertainty characterises connectivity of Plasmodium falciparum populations on the Colombian-Pacific coast.

Characterising connectivity between geographically separated biological populations is a common goal in many fields. Recent approaches to understanding connectivity between malaria parasite populations, with implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). However, uncertainty around estimated relatedness has not been accounted for. IBD-based relatedness estimates with uncertainty were computed for pairs of monoclonal Plasmodium falciparum samples collected from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum is frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically but connected by frequent marine traffic. Fractions of highly-related sample pairs (whose classification using a threshold accounts for uncertainty) were greater within cities versus between. However, based on both highly-related fractions and on a threshold-free approach (Wasserstein distances between parasite populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura-Tumaco connectivity was consistent with transmission events involving parasites from five clonal components (groups of statistically indistinguishable parasites identified under a graph theoretic framework). To conclude, P. falciparum population connectivity on the Colombian-Pacific coast abides by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with opportunities for targeted intervention. Further investigations are required to test this hypothesis. For the first time in malaria epidemiology (and to our knowledge in ecological and epidemiological studies more generally), we account for uncertainty around estimated relatedness (an important consideration for studies that plan to use genotype versus whole genome sequence data to estimate IBD-based relatedness); we also use threshold-free methods to compare parasite populations and identify clonal components. Threshold-free methods are especially important in analyses of malaria parasites and other recombining organisms with mixed mating systems where thresholds do not have clear interpretation (e.g. due to clonal propagation) and thus undermine the cross-comparison of studies.

Aminoacyl tRNA synthetases as potential drug targets of the Panthera pathogen Babesia.

BACKGROUND: A century ago, pantheras were abundant across Asia. Illegal hunting and trading along with loss of habitat have resulted in the designation of Panthera as a genus of endangered species. In addition to the onslaught from humans, pantheras are also susceptible to outbreaks of several infectious diseases, including babesiosis. The latter is a hemoprotozoan disease whose causative agents are the eukaryotic parasites of the apicomplexan genus Babesia. Babesiosis affects a varied range of animals including humans (Homo sapiens), bovines (e.g. Bos taurus), pantheras (e.g. Panthera tigris, P. leo, P. pardus) and equines. Babesia spp. are transmitted by the tick vector Ixodes scapularis or ticks of domestic animals, namely Rhipicephalus (Boophilus) microplus and R. (B.) decoloratus. At the level of protein translation within these organisms, the conserved aminoacyl tRNA synthetase (aaRS) family offers an opportunity to identify the sequence and structural differences in the host (Panthera) and parasites (Babesia spp.) in order to exploit these for drug targeting Babesia spp. METHODS: Using computational tools we investigated the genomes of Babesia spp. and Panthera tigris so as to annotate their aaRSs. The sequences were analysed and their subcellular localizations were predicted using Target P1.1, SignalP 3.0, TMHMM v.2.0 and Deeploc 1.0 web servers. Structure-based analysis of the aaRSs from P. tigris and its protozoan pathogens Babesia spp. was performed using Phyre2 and chimera. RESULTS: We identified 33 (B. bovis), 34 (B. microti), 33 (B. bigemina) and 33 (P. tigris) aaRSs in these respective organisms. Poor sequence identity (~ 20-50%) between aaRSs from Babesia spp. and P. tigris was observed and this merits future experiments to validate new drug targets against Babesia spp. CONCLUSIONS: Overall this work provides a foundation for experimental investigation of druggable aaRSs from Babesia sp. in an effort to control Babesiosis in Panthera.

Technical and economic efficiency of methods for extracting genomic DNA from Meloidogyne javanica.

Plant parasitic nematodes reduce the production of agricultural crops. Species diagnosis is essential to predict losses, determine economic damage levels and develop integrated pest management programs. DNA extraction techniques need to be improved for precise and rapid molecular diagnosis of nematodes. The objective of the present study was to evaluate the efficiency of DNA extraction and amplification by PCR, cost and execution time by Chelex, Worm Lysis Buffer Method (WLB), Holterman Lysis Buffer Method (HLB) and FastDNA methods for nematodes of the Meloidogyne genus. The qualitative and quantitative efficiency of DNA extraction varied between methods. The band size of the amplified PCR product with WLB, Chelex and HLB methods was 590 bp. Extraction with the FastDNA is not recommended for DNA extraction from nematodes because it results in a low DNA concentration without bands in PCR amplification, besides presenting high cost. The efficiency of the WLB method to extracting DNA from Meloidogyne javanica was greater, ensuring a higher concentration and purity of the extracted material and guaranteeing lower costs and greater ease of PCR amplification.

Advances in the application of genetic manipulation methods to apicomplexan parasites.

Apicomplexan parasites such as Babesia, Theileria, Eimeria, Cryptosporidium and Toxoplasma greatly impact animal health globally, and improved, cost-effective measures to control them are urgently required. These parasites have complex multi-stage life cycles including obligate intracellular stages. Major gaps in our understanding of the biology of these relatively poorly characterised parasites and the diseases they cause severely limit options for designing novel control methods. Here we review potentially important shared aspects of the biology of these parasites, such as cell invasion, host cell modification, and asexual and sexual reproduction, and explore the potential of the application of relatively well-established or newly emerging genetic manipulation methods, such as classical transfection or gene editing, respectively, for closing important gaps in our knowledge of the function of specific genes and proteins, and the biology of these parasites. In addition, genetic manipulation methods impact the development of novel methods of control of the diseases caused by these economically important parasites. Transient and stable transfection methods, in conjunction with whole and deep genome sequencing, were initially instrumental in improving our understanding of the molecular biology of apicomplexan parasites and paved the way for the application of the more recently developed gene editing methods. The increasingly efficient and more recently developed gene editing methods, in particular those based on the CRISPR/Cas9 system and previous conceptually similar techniques, are already contributing to additional gene function discovery using reverse genetics and related approaches. However, gene editing methods are only possible due to the increasing availability of in vitro culture, transfection, and genome sequencing and analysis techniques. We envisage that rapid progress in the development of novel gene editing techniques applied to apicomplexan parasites of veterinary interest will ultimately lead to the development of novel and more efficient methods for disease control.

Genetic relatedness analysis reveals the cotransmission of genetically related Plasmodium falciparum parasites in Thiès, Senegal.

BACKGROUND: As public health interventions drive parasite populations to elimination, genetic epidemiology models that incorporate population genomics can be powerful tools for evaluating the effectiveness of continued intervention. However, current genetic epidemiology models may not accurately simulate the population genetic profile of parasite populations, particularly with regard to polygenomic (multi-strain) infections. Current epidemiology models simulate polygenomic infections via superinfection (multiple mosquito bites), despite growing evidence that cotransmission (a single mosquito bite) may contribute to polygenomic infections. METHODS: Here, we quantified the relatedness of strains within 31 polygenomic infections collected from patients in Thiès, Senegal using a hidden Markov model to measure the proportion of the genome that is inferred to be identical by descent. RESULTS: We found that polygenomic infections can be composed of highly related parasites and that superinfection models drastically underestimate the relatedness of strains within polygenomic infections. CONCLUSIONS: Our findings suggest that cotransmission is a major contributor to polygenomic infections in Thiès, Senegal. The incorporation of cotransmission into existing genetic epidemiology models may enhance our ability to characterize and predict changes in population structure associated with reduced transmission intensities and the emergence of important phenotypes like drug resistance that threaten to undermine malaria elimination activities.

An assessment on epitope prediction methods for protozoa genomes.

BACKGROUND: Epitope prediction using computational methods represents one of the most promising approaches to vaccine development. Reduction of time, cost, and the availability of completely sequenced genomes are key points and highly motivating regarding the use of reverse vaccinology. Parasites of genus Leishmania are widely spread and they are the etiologic agents of leishmaniasis. Currently, there is no efficient vaccine against this pathogen and the drug treatment is highly toxic. The lack of sufficiently large datasets of experimentally validated parasites epitopes represents a serious limitation, especially for trypanomatids genomes. In this work we highlight the predictive performances of several algorithms that were evaluated through the development of a MySQL database built with the purpose of: a) evaluating individual algorithms prediction performances and their combination for CD8+ T cell epitopes, B-cell epitopes and subcellular localization by means of AUC (Area Under Curve) performance and a threshold dependent method that employs a confusion matrix; b) integrating data from experimentally validated and in silico predicted epitopes; and c) integrating the subcellular localization predictions and experimental data. NetCTL, NetMHC, BepiPred, BCPred12, and AAP12 algorithms were used for in silico epitope prediction and WoLF PSORT, Sigcleave and TargetP for in silico subcellular localization prediction against trypanosomatid genomes. RESULTS: A database-driven epitope prediction method was developed with built-in functions that were capable of: a) removing experimental data redundancy; b) parsing algorithms predictions and storage experimental validated and predict data; and c) evaluating algorithm performances. Results show that a better performance is achieved when the combined prediction is considered. This is particularly true for B cell epitope predictors, where the combined prediction of AAP12 and BCPred12 reached an AUC value of 0.77. For T CD8+ epitope predictors, the combined prediction of NetCTL and NetMHC reached an AUC value of 0.64. Finally, regarding the subcellular localization prediction, the best performance is achieved when the combined prediction of Sigcleave, TargetP and WoLF PSORT is used. CONCLUSIONS: Our study indicates that the combination of B cells epitope predictors is the best tool for predicting epitopes on protozoan parasites proteins. Regarding subcellular localization, the best result was obtained when the three algorithms predictions were combined. The developed pipeline is available upon request to authors.

Malaria in India: the center for the study of complex malaria in India.

Malaria is a major public health problem in India and one which contributes significantly to the overall malaria burden in Southeast Asia. The National Vector Borne Disease Control Program of India reported ∼1.6 million cases and ∼1100 malaria deaths in 2009. Some experts argue that this is a serious underestimation and that the actual number of malaria cases per year is likely between 9 and 50 times greater, with an approximate 13-fold underestimation of malaria-related mortality. The difficulty in making these estimations is further exacerbated by (i) highly variable malaria eco-epidemiological profiles, (ii) the transmission and overlap of multiple Plasmodium species and Anopheles vectors, (iii) increasing antimalarial drug resistance and insecticide resistance, and (iv) the impact of climate change on each of these variables. Simply stated, the burden of malaria in India is complex. Here we describe plans for a Center for the Study of Complex Malaria in India (CSCMi), one of ten International Centers of Excellence in Malaria Research (ICEMRs) located in malarious regions of the world recently funded by the National Institute of Allergy and Infectious Diseases, National Institutes of Health. The CSCMi is a close partnership between Indian and United States scientists, and aims to address major gaps in our understanding of the complexity of malaria in India, including changing patterns of epidemiology, vector biology and control, drug resistance, and parasite genomics. We hope that such a multidisciplinary approach that integrates clinical and field studies with laboratory, molecular, and genomic methods will provide a powerful combination for malaria control and prevention in India.

RSpred, a set of Hidden Markov Models to detect and classify the RIFIN and STEVOR proteins of Plasmodium falciparum.

BACKGROUND: Many parasites use multicopy protein families to avoid their host's immune system through a strategy called antigenic variation. RIFIN and STEVOR proteins are variable surface antigens uniquely found in the malaria parasites Plasmodium falciparum and P. reichenowi. Although these two protein families are different, they have more similarity to each other than to any other proteins described to date. As a result, they have been grouped together in one Pfam domain. However, a recent study has described the sub-division of the RIFIN protein family into several functionally distinct groups. These sub-groups require phylogenetic analysis to sort out, which is not practical for large-scale projects, such as the sequencing of patient isolates and meta-genomic analysis. RESULTS: We have manually curated the rif and stevor gene repertoires of two Plasmodium falciparum genomes, isolates DD2 and HB3. We have identified 25% of mis-annotated and ~30 missing rif and stevor genes. Using these data sets, as well as sequences from the well curated reference genome (isolate 3D7) and field isolate data from Uniprot, we have developed a tool named RSpred. The tool, based on a set of hidden Markov models and an evaluation program, automatically identifies STEVOR and RIFIN sequences as well as the sub-groups: A-RIFIN, B-RIFIN, B1-RIFIN and B2-RIFIN. In addition to these groups, we distinguish a small subset of STEVOR proteins that we named STEVOR-like, as they either differ remarkably from typical STEVOR proteins or are too fragmented to reach a high enough score. When compared to Pfam and TIGRFAMs, RSpred proves to be a more robust and more sensitive method. We have applied RSpred to the proteomes of several P. falciparum strains, P. reichenowi, P. vivax, P. knowlesi and the rodent malaria species. All groups were found in the P. falciparum strains, and also in the P. reichenowi parasite, whereas none were predicted in the other species. CONCLUSIONS: We have generated a tool for the sorting of RIFIN and STEVOR proteins, large antigenic variant protein groups, into homogeneous sub-families. Assigning functions to such protein families requires their subdivision into meaningful groups such as we have shown for the RIFIN protein family. RSpred removes the need for complicated and time consuming phylogenetic analysis methods. It will benefit both research groups sequencing whole genomes as well as others working with field isolates. RSpred is freely accessible via http://www.ifm.liu.se/bioinfo/.

Post-genomics resources and tools for studying apicomplexan metabolism.

The phylum Apicomplexa comprises over 5000 species of obligate intracellular parasites, many responsible for diseases that significantly impact human health and economics. To aid drug development programs, global sequencing initiatives are generating increasing numbers of apicomplexan genomes. The challenge is how best to exploit these resources to identify effective therapeutic targets. Because of its important role in growth and maintenance, much interest has centred on metabolism. However, in the absence of detailed biochemical data, reconstructing the metabolic potential from a fully sequenced genome remains problematic. In this review current resources and tools facilitating the metabolic reconstruction for apicomplexans are examined. Furthermore, how these datasets can be utilized to explore the metabolic capabilities of apicomplexans are discussed and targets for therapeutic intervention are prioritized.

Plasmodium falciparum erythrocyte membrane protein 1 diversity in seven genomes--divide and conquer.

The var gene encoded hyper-variable Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) family mediates cytoadhesion of infected erythrocytes to human endothelium. Antibodies blocking cytoadhesion are important mediators of malaria immunity acquired by endemic populations. The development of a PfEMP1 based vaccine mimicking natural acquired immunity depends on a thorough understanding of the evolved PfEMP1 diversity, balancing antigenic variation against conserved receptor binding affinities. This study redefines and reclassifies the domains of PfEMP1 from seven genomes. Analysis of domains in 399 different PfEMP1 sequences allowed identification of several novel domain classes, and a high degree of PfEMP1 domain compositional order, including conserved domain cassettes not always associated with the established group A-E division of PfEMP1. A novel iterative homology block (HB) detection method was applied, allowing identification of 628 conserved minimal PfEMP1 building blocks, describing on average 83% of a PfEMP1 sequence. Using the HBs, similarities between domain classes were determined, and Duffy binding-like (DBL) domain subclasses were found in many cases to be hybrids of major domain classes. Related to this, a recombination hotspot was uncovered between DBL subdomains S2 and S3. The VarDom server is introduced, from which information on domain classes and homology blocks can be retrieved, and new sequences can be classified. Several conserved sequence elements were found, including: (1) residues conserved in all DBL domains predicted to interact and hold together the three DBL subdomains, (2) potential integrin binding sites in DBLα domains, (3) an acylation motif conserved in group A var genes suggesting N-terminal N-myristoylation, (4) PfEMP1 inter-domain regions proposed to be elastic disordered structures, and (5) several conserved predicted phosphorylation sites. Ideally, this comprehensive categorization of PfEMP1 will provide a platform for future studies on var/PfEMP1 expression and function.

New assembly, reannotation and analysis of the Entamoeba histolytica genome reveal new genomic features and protein content information.

BACKGROUND: In order to maintain genome information accurately and relevantly, original genome annotations need to be updated and evaluated regularly. Manual reannotation of genomes is important as it can significantly reduce the propagation of errors and consequently diminishes the time spent on mistaken research. For this reason, after five years from the initial submission of the Entamoeba histolytica draft genome publication, we have re-examined the original 23 Mb assembly and the annotation of the predicted genes. PRINCIPAL FINDINGS: The evaluation of the genomic sequence led to the identification of more than one hundred artifactual tandem duplications that were eliminated by re-assembling the genome. The reannotation was done using a combination of manual and automated genome analysis. The new 20 Mb assembly contains 1,496 scaffolds and 8,201 predicted genes, of which 60% are identical to the initial annotation and the remaining 40% underwent structural changes. Functional classification of 60% of the genes was modified based on recent sequence comparisons and new experimental data. We have assigned putative function to 3,788 proteins (46% of the predicted proteome) based on the annotation of predicted gene families, and have identified 58 protein families of five or more members that share no homology with known proteins and thus could be entamoeba specific. Genome analysis also revealed new features such as the presence of segmental duplications of up to 16 kb flanked by inverted repeats, and the tight association of some gene families with transposable elements. SIGNIFICANCE: This new genome annotation and analysis represents a more refined and accurate blueprint of the pathogen genome, and provides an upgraded tool as reference for the study of many important aspects of E. histolytica biology, such as genome evolution and pathogenesis.

The essentials of protein import in the degenerate mitochondrion of Entamoeba histolytica.

Several essential biochemical processes are situated in mitochondria. The metabolic transformation of mitochondria in distinct lineages of eukaryotes created proteomes ranging from thousands of proteins to what appear to be a much simpler scenario. In the case of Entamoeba histolytica, tiny mitochondria known as mitosomes have undergone extreme reduction. Only recently a single complete metabolic pathway of sulfate activation has been identified in these organelles. The E. histolytica mitosomes do not produce ATP needed for the sulfate activation pathway and for three molecular chaperones, Cpn60, Cpn10 and mtHsp70. The already characterized ADP/ATP carrier would thus be essential to provide cytosolic ATP for these processes, but how the equilibrium of inorganic phosphate could be maintained was unknown. Finally, how the mitosomal proteins are translocated to the mitosomes had remained unclear. We used a hidden Markov model (HMM) based search of the E. histolytica genome sequence to discover candidate (i) mitosomal phosphate carrier complementing the activity of the ADP/ATP carrier and (ii) membrane-located components of the protein import machinery that includes the outer membrane translocation channel Tom40 and membrane assembly protein Sam50. Using in vitro and in vivo systems we show that E. histolytica contains a minimalist set up of the core import components in order to accommodate a handful of mitosomal proteins. The anaerobic and parasitic lifestyle of E. histolytica has produced one of the simplest known mitochondrial compartments of all eukaryotes. Comparisons with mitochondria of another amoeba, Dictystelium discoideum, emphasize just how dramatic the reduction of the protein import apparatus was after the loss of archetypal mitochondrial functions in the mitosomes of E. histolytica.

Detection of new protein domains using co-occurrence: application to Plasmodium falciparum.

MOTIVATION: Hidden Markov models (HMMs) have proved to be a powerful tool for protein domain identification in newly sequenced organisms. However, numerous domains may be missed in highly divergent proteins. This is the case for Plasmodium falciparum proteins, the main causal agent of human malaria. RESULTS: We propose a method to improve the sensitivity of HMM domain detection by exploiting the tendency of the domains to appear preferentially with a few other favorite domains in a protein. When sequence information alone is not sufficient to warrant the presence of a particular domain, our method enables its detection on the basis of the presence of other Pfam or InterPro domains. Moreover, a shuffling procedure allows us to estimate the false discovery rate associated with the results. Applied to P. falciparum, our method identifies 585 new Pfam domains (versus the 3683 already known domains in the Pfam database) with an estimated error rate <20%. These new domains provide 387 new Gene Ontology (GO) annotations to the P. falciparum proteome. Analogous and congruent results are obtained when applying the method to related Plasmodium species (P. vivax and P. yoelii). AVAILABILITY: Supplementary Material and a database of the new domains and GO predictions achieved on Plasmodium proteins are available at http://www.lirmm.fr/~terrapon/codd/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assessment of the origins and spread of putative resistance-conferring mutations in Plasmodium vivax dihydropteroate synthase.

Infection with Plasmodium vivax is usually treated with chloroquine, but parasites are often exposed inadvertently to sulfadoxine-pyrimethamine. To infer patterns of selection and spread of resistant parasites in natural populations, we determined haplotypes of P. vivax dihydropteroate synthase ( dhps ) alleles that could confer resistance to sulfadoxine. We amplified the P. vivax pyrophosphokinase ( pppk )- dhps region and its flanking intergenic regions from 92 contemporary global isolates. Introns and exons of pppk-dhps were highly polymorphic, as were the flanking intergenic regions. Eighteen haplotypes were associated with wild-type alleles, but several different putatively sulfadoxine-resistant alleles have arisen in areas of intensive sulfadoxine-pyrimethamine use. Even when they encoded changes to the same amino acid, these mutant alleles were associated with multiple different haplotypes. Two main conclusions can be drawn from these data. First, dhps alleles resistant to sulfadoxine have arisen multiple times under drug pressure. Second, there has been convergent evolution of a variety of alleles that could confer resistance to sulfa drugs.

Assessment and improvement of the Plasmodium yoelii yoelii genome annotation through comparative analysis.

MOTIVATION: The sequencing of the Plasmodium yoelii genome, a model rodent malaria parasite, has greatly facilitated research for the development of new drug and vaccine candidates against malaria. Unfortunately, only preliminary gene models were annotated on the partially sequenced genome, mostly by in silico gene prediction, and there has been no major improvement of the annotation since 2002. RESULTS: Here we report on a systematic assessment of the accuracy of the genome annotation based on a detailed analysis of a comprehensive set of cDNA sequences and proteomics data. We found that the coverage of the current annotation tends to be biased toward genes expressed in the blood stages of the parasite life cycle. Based on our proteomic analysis, we estimate that about 15% of the liver stage proteome data we have generated is absent from the current annotation. Through comparative analysis we identified and manually curated a further 510 P. yoelii genes which have clear orthologs in the P. falciparum genome, but were not present or incorrectly annotated in the current annotation. This study suggests that improvements of the current P. yoelii genome annotation should focus on genes expressed in stages other than blood stages. Comparative analysis will be critically helpful for this re-annotation. The addition of newly annotated genes will facilitate the use of P. yoelii as a model system for studying human malaria. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Drugging the Plasmodium kinome: the benefits of academia-industry synergy.

Malaria remains a major killer in many parts of the world. Recently, the development of nonprofit organisations aimed at fighting this deadly scourge incited academic and industrial scientists to merge their expertise in drug-target validation and lead discovery. Expectations are clear: identification and characterisation of new molecules showing high efficacy, low toxicity and little propensity to induce resistance in the parasite. In this context, protein kinase inhibitors represent an attractive possibility. Here, we compare traditional target-based drug-discovery approaches with innovative exploratory paths (parallel screening, cell-based assays, integrated systems biology and allosteric inhibition) and discuss the benefits of acadaemia-industry cooperation. Early characterisation of distribution, metabolism, pharmacokinetic (DMPK) and toxicology parameters are considered as well.