Control of seed dormancy in Arabidopsis by a cis-acting noncoding antisense transcript.

Seed dormancy is one of the most crucial process transitions in a plant's life cycle. Its timing is tightly controlled by the expression level of the Delay of Germination 1 gene (DOG1). DOG1 is the major quantitative trait locus for seed dormancy in Arabidopsis and has been shown to control dormancy in many other plant species. This is reflected by the evolutionary conservation of the functional short alternatively polyadenylated form of the DOG1 mRNA. Notably, the 3' region of DOG1, including the last exon that is not included in this transcript isoform, shows a high level of conservation at the DNA level, but the encoded polypeptide is poorly conserved. Here, we demonstrate that this region of DOG1 contains a promoter for the transcription of a noncoding antisense RNA, asDOG1, that is 5' capped, polyadenylated, and relatively stable. This promoter is autonomous and asDOG1 has an expression profile that is different from known DOG1 transcripts. Using several approaches we show that asDOG1 strongly suppresses DOG1 expression during seed maturation in cis, but is unable to do so in trans Therefore, the negative regulation of seed dormancy by asDOG1 in cis results in allele-specific suppression of DOG1 expression and promotes germination. Given the evolutionary conservation of the asDOG1 promoter, we propose that this cis-constrained noncoding RNA-mediated mechanism limiting the duration of seed dormancy functions across the Brassicaceae.

An Apoptotic and Endosymbiotic Explanation of the Warburg and the Inverse Warburg Hypotheses.

Otto Warburg, a Nobel prize winner, observed that cancer cells typically "switch" from aerobic to anaerobic respiration. He hypothesized that mitochondrial damage induces neoplastic transformation. In contrast, pathological aging is observed mainly in neuron cells in neurodegenerative diseases. Oxidative respiration is particularly active in neurons. There is inverse comorbidity between cancer and neurodegenerative diseases. This led to the creation of the "inverse Warburg hypothesis", according to which excessive mitochondrial activity induces pathological aging. The findings of our studies suggest that both the Warburg effect and the "inverse Warburg hypothesis" can be elucidated by the activation or suppression of apoptosis through oxidative respiration. The key outcome of our phylogenetic studies was the discovery that apoptosis and apoptosis-like cell death evolved due to an evolutionary "arms race" conducted between "prey" protomitochondrion and "predator" primitive eukaryotes. The ancestral protomitochondrial machinery produces and releases toxic mitochondrial proteins. Extant apoptotic factors evolved from these toxins. Our experiments indicate that the mitochondrial machinery is directly involved in adaptation to aerobic conditions. Additionally, our hypothesis is supported by the fact that different apoptotic factors are directly involved in respiration.

Seed Dormancy in Arabidopsis Is Controlled by Alternative Polyadenylation of DOG1.

DOG1 (Delay of Germination 1) is a key regulator of seed dormancy in Arabidopsis (Arabidopsis thaliana) and other plants. Interestingly, the C terminus of DOG1 is either absent or not conserved in many plant species. Here, we show that in Arabidopsis, DOG1 transcript is subject to alternative polyadenylation. In line with this, mutants in RNA 3' processing complex display weakened seed dormancy in parallel with defects in DOG1 proximal polyadenylation site selection, suggesting that the short DOG1 transcript is functional. This is corroborated by the finding that the proximally polyadenylated short DOG1 mRNA is translated in vivo and complements the dog1 mutant. In summary, our findings indicate that the short DOG1 protein isoform produced from the proximally polyadenylated DOG1 mRNA is a key player in the establishment of seed dormancy in Arabidopsis and characterizes a set of mutants in RNA 3' processing complex required for production of proximally polyadenylated functional DOG1 transcript.

Apoptosis: its origin, history, maintenance and the medical implications for cancer and aging.

Programmed cell death is a basic cellular mechanism. Apoptotic-like programmed cell death (called apoptosis in animals) occurs in both unicellular and multicellular eukaryotes, and some apoptotic mechanisms are observed in bacteria. Endosymbiosis between mitochondria and eukaryotic cells took place early in the eukaryotic evolution, and some of the apoptotic-like mechanisms of mitochondria that were retained after this event now serve as parts of the eukaryotic apoptotic machinery. Apoptotic mechanisms have several functions in unicellular organisms: they include kin-selected altruistic suicide that controls population size, sharing common goods, and responding to viral infection. Apoptotic factors also have non-apoptotic functions. Apoptosis is involved in the cellular aging of eukaryotes, including humans. In addition, apoptosis is a key part of the innate tumor-suppression mechanism. Several anticancer drugs induce apoptosis, because apoptotic mechanisms are inactivated during oncogenesis. Because of the ancient history of apoptosis, I hypothesize that there is a deep relationship between mitochondrial metabolism, its role in aerobic versus anaerobic respiration, and the connection between apoptosis and cancer. Whereas normal cells rely primarily on oxidative mitochondrial respiration, most cancer cells use anaerobic metabolism. According to the Warburg hypothesis, the remodeling of the metabolism is one of the processes that leads to cancer. Recent studies indicate that anaerobic, non-mitochondrial respiration is particularly active in embryonic cells, stem cells, and aggressive stem-like cancer cells. Mitochondrial respiration is particularly active during the pathological aging of human cells in neurodegenerative diseases. According to the reversed Warburg hypothesis formulated by Demetrius, pathological aging is induced by mitochondrial respiration. Here, I advance the hypothesis that the stimulation of mitochondrial metabolism leads to pathological aging.

Dominance from the perspective of gene-gene and gene-chemical interactions.

In this study, we used genetic interaction (GI) and gene-chemical interaction (GCI) data to compare mutations with different dominance phenotypes. Our analysis focused primarily on Saccharomyces cerevisiae, where haploinsufficient genes (HI; genes with dominant loss-of-function mutations) were found to be participating in gene expression processes, namely, the translation and regulation of gene transcription. Non-ribosomal HI genes (mainly regulators of gene transcription) were found to have more GIs and GCIs than haplosufficient (HS) genes. Several properties seem to lead to the enrichment of interactions, most notably, the following: importance, pleiotropy, gene expression level and gene expression variation. Importantly, after these properties were appropriately considered in the analysis, the correlation between dominance and GI/GCI degrees was still observed. Strikingly, for the GCIs of heterozygous strains, haploinsufficiency was the only property significantly correlated with the number of GCIs. We found ribosomal HI genes to be depleted in GIs/GCIs. This finding can be explained by their high variation in gene expression under different genetic backgrounds and environmental conditions. We observed the same distributions of GIs among non-ribosomal HI, ribosomal HI and HS genes in three other species: Schizosaccharomyces pombe, Drosophila melanogaster and Homo sapiens. One potentially interesting exception was the lack of significant differences in the degree of GIs between non-ribosomal HI and HS genes in Schizosaccharomyces pombe.

Loss-of-function mutations are main drivers of adaptations during short-term evolution.

We noticed that during short-term experimental evolution and carcinogenesis, mutations causing gene inactivation (i.e., nonsense mutations or frameshifts) are frequent. Our meta-analysis of 65 experiments using modified dN/dS statistics indicated that nonsense mutations are adaptive in different experimental conditions and we empirically confirmed this prediction. Using yeast S. cerevisiae as a model we show that fixed or highly frequent gene loss-of-function mutations are almost exclusively adaptive in the majority of experiments.

The evolutionary rate of antibacterial drug targets.

BACKGROUND: One of the major issues in the fight against infectious diseases is the notable increase in multiple drug resistance in pathogenic species. For that reason, newly acquired high-throughput data on virulent microbial agents attract the attention of many researchers seeking potential new drug targets. Many approaches have been used to evaluate proteins from infectious pathogens, including, but not limited to, similarity analysis, reverse docking, statistical 3D structure analysis, machine learning, topological properties of interaction networks or a combination of the aforementioned methods. From a biological perspective, most essential proteins (knockout lethal for bacteria) or highly conserved proteins (broad spectrum activity) are potential drug targets. Ribosomal proteins comprise such an example. Many of them are well-known drug targets in bacteria. It is intuitive that we should learn from nature how to design good drugs. Firstly, known antibiotics are mainly originating from natural products of microorganisms targeting other microorganisms. Secondly, paleontological data suggests that antibiotics have been used by microorganisms for million years. Thus, we have hypothesized that good drug targets are evolutionary constrained and are subject of evolutionary selection. This means that mutations in such proteins are deleterious and removed by selection, which makes them less susceptible to random development of resistance. Analysis of the speed of evolution seems to be good approach to test this hypothesis. RESULTS: In this study we show that pN/pS ratio of genes coding for known drug targets is significantly lower than the genome average and also lower than that for essential genes identified by experimental methods. Similar results are observed in the case of dN/dS analysis. Both analyzes suggest that drug targets tend to evolve slowly and that the rate of evolution is a better predictor of drugability than essentiality. CONCLUSIONS: Evolutionary rate can be used to score and find potential drug targets. The results presented here may become a useful addition to a repertoire of drug target prediction methods. As a proof of concept, we analyzed GO enrichment among the slowest evolving genes. These may become the starting point in the search for antibiotics with a novel mechanism.

A kinetic model of the evolution of a protein interaction network.

BACKGROUND: Known protein interaction networks have very particular properties. Old proteins tend to have more interactions than new ones. One of the best statistical representatives of this property is the node degree distribution (distribution of proteins having a given number of interactions). It has previously been shown that this distribution is very close to the sum of two distinct exponential components. In this paper, we asked: What are the possible mechanisms of evolution for such types of networks? To answer this question, we tested a kinetic model for simplified evolution of a protein interactome. Our proposed model considers the emergence of new genes and interactions and the loss of old ones. We assumed that there are generally two coexisting classes of proteins. Proteins constituting the first class are essential only for ecological adaptations and are easily lost when ecological conditions change. Proteins of the second class are essential for basic life processes and, hence, are always effectively protected against deletion. All proteins can transit between the above classes in both directions. We also assumed that the phenomenon of gene duplication is always related to ecological adaptation and that a new copy of a duplicated gene is not essential. According to this model, all proteins gain new interactions with a rate that preferentially increases with the number of interactions (the rich get richer). Proteins can also gain interactions because of duplication. Proteins lose their interactions both with and without the loss of partner genes. RESULTS: The proposed model reproduces the main properties of protein-protein interaction networks very well. The connectivity of the oldest part of the interaction network is densest, and the node degree distribution follows the sum of two shifted power-law functions, which is a theoretical generalization of the previous finding. The above distribution covers the wide range of values of node degrees very well, much better than a power law or generalized power law supplemented with an exponential cut-off. The presented model also relates the total number of interactome links to the total number of interacting proteins. The theoretical results were for the interactomes of A. thaliana, B. taurus, C. elegans, D. melanogaster, E. coli, H. pylori, H. sapiens, M. musculus, R. norvegicus and S. cerevisiae. CONCLUSIONS: Using these approaches, the kinetic parameters could be estimated. Finally, the model revealed the evolutionary kinetics of proteome formation, the phenomenon of protein differentiation and the process of gaining new interactions.

Detection of positive selection acting on protein surfaces at the whole-genome scale in the human malaria parasite Plasmodium falciparum.

The host-parasite evolutionary arms race is a fundamental process with medical implications. During this process, the host develops parasite resistance, and the parasite develops host immune evasion strategies. Thus, this process accelerates relevant protein evolution. This study test hypothesizes that proteins subject to sequence evolution structural constraints play a crucial role and that these constraints hinder the modification of such proteins in this process. These hypotheses were tested using Plasmodium falciparum model and evaluated protein structures predicted for the entire proteome by the AlphaFold method. Based on dN/dS test results and P. falciparum and P. reichenowi comparisons, the presented approach identified proteins subject to purifying selection acting on the whole sequence and buried residues (dN < dS) and positive selection on nonburied residues. Of the 26 proteins, some known antigens (ring-exported protein 3, RAP protein, erythrocyte binding antigen-140, and protein P47) targeted by the host immune system are promising vaccine candidates. The set also contained 11 enzymes, including FIKK kinase, which modifies host proteins. This set was compared with genes for which the dN/dS test suggested that positive selection acts on the whole gene (i.e., dN > dS). The present study found that such genes encode enzymes and antigenic vaccine candidates less frequently than genes for which evolution is not subject to selection constraints and positive selection acts on only exposed residues. The analysis was repeated comparing P. falciparum with P. alderi, which is more distantly related. The study discusses the potential implications of the presented methodology for rational vaccine design and the parasitology and evolutionary biology fields.

Apoptotic Factors Are Evolutionarily Conserved Since Mitochondrial Domestication.

The mechanisms initiating apoptotic programmed cell death in diverse eukaryotes are very similar. Basically, the mitochondrial permeability transition activates apoptotic proteases, DNases, and flavoproteins such as apoptosis-inducing factors (AIFs). According to the hypothesis of the endosymbiotic origin of apoptosis, these mechanisms evolved during mitochondrial domestication. Various phylogenetic analyses, including ours, have suggested that apoptotic factors were eubacterial protomitochondrial toxins used for killing protoeukaryotic hosts. Here, we tested whether the function of yeast Saccharomyces cerevisiae apoptotic proteases (metacaspases Mca1 and Nma111), DNase Nuc1, and flavoprotein Ndi1 can be substituted with orthologs from remotely related eukaryotes such as plants, protists, and eubacteria. We found that orthologs of remotely related eukaryotic and even eubacterial proteins can initiate apoptosis in yeast when triggered by chemical stresses. This observation suggests that apoptotic mechanisms have been maintained since mitochondrial domestication, which occurred approximately 1,800 Mya. Additionally, it supports the hypothesis that some of these apoptotic factors could be modified eubacterial toxins.

Three members of the 6-cys protein family of Plasmodium play a role in gamete fertility.

The process of fertilization is critically dependent on the mutual recognition of gametes and in Plasmodium, the male gamete surface protein P48/45 is vital to this process. This protein belongs to a family of 10 structurally related proteins, the so called 6-cys family. To identify the role of additional members of this family in Plasmodium fertilisation, we performed genetic and functional analysis on the five members of the 6-cys family that are transcribed during the gametocyte stage of P. berghei. This analysis revealed that in addition to P48/45, two members (P230 and P47) also play an essential role in the process of parasite fertilization. Mating studies between parasites lacking P230, P48/45 or P47 demonstrate that P230, like P48/45, is a male fertility factor, consistent with the previous demonstration of a protein complex containing both P48/45 and P230. In contrast, disruption of P47 results in a strong reduction of female fertility, while males remain unaffected. Further analysis revealed that gametes of mutants lacking expression of p48/45 or p230 or p47 are unable to either recognise or attach to each other. Disruption of the paralog of p230, p230p, also specifically expressed in gametocytes, had no observable effect on fertilization. These results indicate that the P. berghei 6-cys family contains a number of proteins that are either male or female specific ligands that play an important role in gamete recognition and/or attachment. The implications of low levels of fertilisation that exist even in the absence of these proteins, indicating alternative pathways of fertilisation, as well as positive selection acting on these proteins, are discussed in the context of targeting these proteins as transmission blocking vaccine candidates.

Novel application of the MSSCP method in biodiversity studies.

Analysis of 16S rRNA sequence diversity is widely performed for characterizing the biodiversity of microbial samples. The number of determined sequences has a considerable impact on complete results. Although the cost of mass sequencing is decreasing, it is often still too high for individual projects. We applied the multi-temperature single-strand conformational polymorphism (MSSCP) method to decrease the number of analysed sequences. This was a novel application of this method. As a control, the same sample was analysed using random sequencing. In this paper, we adapted the MSSCP technique for screening of unique sequences of the 16S rRNA gene library and bacterial strains isolated from biofilms growing on the walls of an ancient gold mine in Poland and determined whether the results obtained by both methods differed and whether random sequencing could be replaced by MSSCP. Although it was biased towards the detection of rare sequences in the samples, the qualitative results of MSSCP were not different than those of random sequencing. Unambiguous discrimination of unique clones and strains creates an opportunity to effectively estimate the biodiversity of natural communities, especially in populations which are numerous but species poor.

Genetic interaction network has a very limited impact on the evolutionary trajectories in continuous culture-grown populations of yeast.

BACKGROUND: The impact of genetic interaction networks on evolution is a fundamental issue. Previous studies have demonstrated that the topology of the network is determined by the properties of the cellular machinery. Functionally related genes frequently interact with one another, and they establish modules, e.g., modules of protein complexes and biochemical pathways. In this study, we experimentally tested the hypothesis that compensatory evolutionary modifications, such as mutations and transcriptional changes, occur frequently in genes from perturbed modules of interacting genes. RESULTS: Using Saccharomyces cerevisiae haploid deletion mutants as a model, we investigated two modules lacking COG7 or NUP133, which are evolutionarily conserved genes with many interactions. We performed laboratory evolution experiments with these strains in two genetic backgrounds (with or without additional deletion of MSH2), subjecting them to continuous culture in a non-limiting minimal medium. Next, the evolved yeast populations were characterized through whole-genome sequencing and transcriptome analyses. No obvious compensatory changes resulting from inactivation of genes already included in modules were identified. The supposedly compensatory inactivation of genes in the evolved strains was only rarely observed to be in accordance with the established fitness effect of the genetic interaction network. In fact, a substantial majority of the gene inactivations were predicted to be neutral in the experimental conditions used to determine the interaction network. Similarly, transcriptome changes during continuous culture mostly signified adaptation to growth conditions rather than compensation of the absence of the COG7, NUP133 or MSH2 genes. However, we noticed that for genes whose inactivation was deleterious an upregulation of transcription was more common than downregulation. CONCLUSIONS: Our findings demonstrate that the genetic interactions and the modular structure of the network described by others have very limited effects on the evolutionary trajectory following gene deletion of module elements in our experimental conditions and has no significant impact on short-term compensatory evolution. However, we observed likely compensatory evolution in functionally related (albeit non-interacting) genes.

Symbiotic Origin of Apoptosis.

The progress of evolutionary biology has revealed that symbiosis played a basic role in the evolution of complex eukaryotic organisms, including humans. Mitochondria are actually simplified endosymbiotic bacteria currently playing the role of cellular organelles. Mitochondrial domestication occurred at the very beginning of eukaryotic evolution. Mitochondria have two different basic functions: they produce energy using oxidative respiration, and they initiate different forms of apoptotic programmed/regulated cell death. Apoptotic programmed cell death may have different cytological forms. Mechanisms of apoptotic programmed cell death exist even in the unicellular organisms, and they play a basic role in the development of complex multicellular organisms, such as fungi, green plants, and animals. Multicellularity was independently established many times among eukaryotes. There are indications that apoptotic programmed cell death is a trait required for the establishment of multicellularity. Regulated cell death is initiated by many different parallel biochemical pathways. It is generally accepted that apoptosis evolved during mitochondrial domestication. However, there are different hypothetical models of the origin of apoptosis. The phylogenetic studies of my group indicate that apoptosis probably evolved during an evolutionary arms race between host ancestral eukaryotic predators and ancestral prey mitochondria (named protomitochondria). Protomitochondrial prey produced many different toxins as a defense against predators. From these toxins evolved extant apoptotic factors. There are indications that aerobic respiration and apoptosis co-evolved and are functionally linked in extant organisms. Perturbations of apoptosis and oxidative respiration are frequently observed during neoplastic transition. Our group showed that perturbations of apoptosis in yeasts also cause perturbations of oxidative respiration.

Slow Adaptive Response of Budding Yeast Cells to Stable Conditions of Continuous Culture Can Occur without Genome Modifications.

Continuous cultures assure the invariability of environmental conditions and the metabolic state of cultured microorganisms, whereas batch-cultured cells undergo constant changes in nutrients availability. For that reason, continuous culture is sometimes employed in the whole transcriptome, whole proteome, or whole metabolome studies. However, the typical method for establishing uniform growth of a cell population, i.e., by limited chemostat, results in the enrichment of the cell population gene pool with mutations adaptive for starvation conditions. These adaptive changes can skew the results of large-scale studies. It is commonly assumed that these adaptations reflect changes in the genome, and this assumption has been confirmed experimentally in rare cases. Here we show that in a population of budding yeast cells grown for over 200 generations in continuous culture in non-limiting minimal medium and therefore not subject to selection pressure, remodeling of transcriptome occurs, but not as a result of the accumulation of adaptive mutations. The observed changes indicate a shift in the metabolic balance towards catabolism, a decrease in ribosome biogenesis, a decrease in general stress alertness, reorganization of the cell wall, and transactions occurring at the cell periphery. These adaptive changes signify the acquisition of a new lifestyle in a stable nonstressful environment. The absence of underlying adaptive mutations suggests these changes may be regulated by another mechanism.

The High Throughput Sequence Annotation Service (HT-SAS) - the shortcut from sequence to true Medline words.

BACKGROUND: Advances in high-throughput technologies available to modern biology have created an increasing flood of experimentally determined facts. Ordering, managing and describing these raw results is the first step which allows facts to become knowledge. Currently there are limited ways to automatically annotate such data, especially utilizing information deposited in published literature. RESULTS: To aid researchers in describing results from high-throughput experiments we developed HT-SAS, a web service for automatic annotation of proteins using general English words. For each protein a poll of Medline abstracts connected to homologous proteins is gathered using the UniProt-Medline link. Overrepresented words are detected using binomial statistics approximation. We tested our automatic approach with a protein test set from SGD to determine the accuracy and usefulness of our approach. We also applied the automatic annotation service to improve annotations of proteins from Plasmodium bergei expressed exclusively during the blood stage. CONCLUSION: Using HT-SAS we created new, or enriched already established annotations for over 20% of proteins from Plasmodium bergei expressed in the blood stage, deposited in PlasmoDB. Our tests show this approach to information extraction provides highly specific keywords, often also when the number of abstracts is limited. Our service should be useful for manual curators, as a complement to manually curated information sources and for researchers working with protein datasets, especially from poorly characterized organisms.

e-LiSe--an online tool for finding needles in the '(Medline) haystack'.

UNLABELLED: Using literature databases one can find not only known and true relations between processes but also less studied, non-obvious associations. The main problem with discovering such type of relevant biological information is 'selection'. The ability to distinguish between a true correlation (e.g. between different types of biological processes) and random chance that this correlation is statistically significant is crucial for any bio-medical research, literature mining being no exception. This problem is especially visible when searching for information which has not been studied and described in many publications. Therefore, a novel bio-linguistic statistical method is required, capable of 'selecting' true correlations, even when they are low-frequency associations. In this article, we present such statistical approach based on Z-score and implemented in a web-based application 'e-LiSe'. AVAILABILITY: The software is available at http://miron.ibb.waw.pl/elise/

Acquisition of cell polarity during cell cycle and oral replacement in Tetrahymena.

The aim of this study was to search for a mechanism responsible for the acquisition of cell polarity in a ciliate Tetrahymena. Homologs of the mammalian genes coding for CDC42-GSK3beta- MARK/PAR1-MAPs proteins were found in the Tetrahymena genome (Eisen et al., 2006, and this study). These proteins belong to a pathway which controls assembly and disassembly of microtubule bundles and cell polarity in neural cells. In Tetrahymena, there are two types of morphogenesis: divisional and oral replacement (OR). In divisional morphogenesis, an elongation of longitudinal microtubule bundles (LMs) takes place during cell division. In contrast, in OR type morphogenesis, which occurs in starved non-dividing cells, a polar retraction of LMs occurs. In T. pyriformis, the frequency of developmental switch to OR morphogenesis increases in the presence of wortmannin, an inhibitor of the CDC42-GSK3beta-MARK pathway. In contrast, wortmannin when applied to dividing cells does not affect divisional morphogenesis. Using immunostaining with the antibody against mammalian mitotic phosphoproteins (MPM-2) we show that these proteins co-localize with the LMs and are distributed along the anterior-posterior gradient. In addition, we show that during OR type morphogenesis, the fate of LMs correlates with the anterior-posterior gradient of instability of the cortical structures. We used the conditional mouth-less mutant of T. thermophila (Tiedtke et al., 1988) to test if the presence of the oral apparatus is required for the maintenance of cell polarity. We discuss our results in relation to the hypothesis of GSK3-beta-MARK pathway involvement in the acquisition of cell polarity in Tetrahymena.

Systematic association of genes to phenotypes by genome and literature mining.

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene-phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases.

Host-parasite interactions and ecology of the malaria parasite-a bioinformatics approach.

Malaria remains one of the highest mortality infectious diseases. Malaria is caused by parasites from the genus Plasmodium. Most deaths are caused by infections involving Plasmodium falciparum, which has a complex life cycle. Malaria parasites are extremely well adapted for interactions with their host and their host's immune system and are able to suppress the human immune system, erase immunological memory and rapidly alter exposed antigens. Owing to this rapid evolution, parasites develop drug resistance and express novel forms of antigenic proteins that are not recognized by the host immune system. There is an emerging need for novel interventions, including novel drugs and vaccines. Designing novel therapies requires knowledge about host-parasite interactions, which is still limited. However, significant progress has recently been achieved in this field through the application of bioinformatics analysis of parasite genome sequences. In this review, we describe the main achievements in 'malarial' bioinformatics and provide examples of successful applications of protein sequence analysis. These examples include the prediction of protein functions based on homology and the prediction of protein surface localization via domain and motif analysis. Additionally, we describe PlasmoDB, a database that stores accumulated experimental data. This tool allows data mining of the stored information and will play an important role in the development of malaria science. Finally, we illustrate the application of bioinformatics in the development of population genetics research on malaria parasites, an approach referred to as reverse ecology.