Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

The organization and mining of malaria genomic and post-genomic data is highly motivated by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should therefore be as reliable and versatile as possible. In this context, we examined five aspects of the organization and mining of malaria genomic and post-genomic data: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Progresses toward a grid-enabled chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa

Phylogenetic framework for coevolutionary studies: A compass for exploring jungles of tangled trees

Phylogenetics is used to detect past evolutionary events, from how species originated to how their ecological interactions with other species arose, which can mirror cophylogenetic patterns. Cophylogenetic reconstructions uncover past ecological relationships between taxa through inferred coevolutionary events on trees, for example, codivergence, duplication, host-switching, and loss. These events can be detected by cophylogenetic analyses based on nodes and the length and branching pattern of the phylogenetic trees of symbiotic associations, for example, host-parasite. In the past 2 decades, algorithms have been developed for cophylogetenic analyses and implemented in different software, for example, statistical congruence index and event-based methods. Based on the combination of these approaches, it is possible to integrate temporal information into cophylogenetical inference, such as estimates of lineage divergence times between 2 taxa, for example, hosts and parasites. Additionally, the advances in phylogenetic biogeography applying methods based on parametric process models and combined Bayesian approaches, can be useful for interpreting coevolutionary histories in a scenario of biogeographical area connectivity through time. This article briefly reviews the basics of parasitology and provides an overview of software packages in cophylogenetic methods. Thus, the objective here is to present a phylogenetic framework for coevolutionary studies, with special emphasis on groups of parasitic organisms. Researchers wishing to undertake phylogeny-based coevolutionary studies can use this review as a "compass" when "walking" through jungles of tangled phylogenetic trees.Facultad de Ciencias Naturales y Muse

Phylogenetic framework for coevolutionary studies: A compass for exploring jungles of tangled trees

Phylogenetics is used to detect past evolutionary events, from how species originated to how their ecological interactions with other species arose, which can mirror cophylogenetic patterns. Cophylogenetic reconstructions uncover past ecological relationships between taxa through inferred coevolutionary events on trees, for example, codivergence, duplication, host-switching, and loss. These events can be detected by cophylogenetic analyses based on nodes and the length and branching pattern of the phylogenetic trees of symbiotic associations, for example, host-parasite. In the past 2 decades, algorithms have been developed for cophylogetenic analyses and implemented in different software, for example, statistical congruence index and event-based methods. Based on the combination of these approaches, it is possible to integrate temporal information into cophylogenetical inference, such as estimates of lineage divergence times between 2 taxa, for example, hosts and parasites. Additionally, the advances in phylogenetic biogeography applying methods based on parametric process models and combined Bayesian approaches, can be useful for interpreting coevolutionary histories in a scenario of biogeographical area connectivity through time. This article briefly reviews the basics of parasitology and provides an overview of software packages in cophylogenetic methods. Thus, the objective here is to present a phylogenetic framework for coevolutionary studies, with special emphasis on groups of parasitic organisms. Researchers wishing to undertake phylogeny-based coevolutionary studies can use this review as a "compass" when "walking" through jungles of tangled phylogenetic trees.Facultad de Ciencias Naturales y Muse

Plasmodium vivax-like genome sequences shed new insights into Plasmodium vivax biology and evolution

Although Plasmodium vivax is responsible for the majority of malaria infections outside Africa, little is known about its evolution and pathway to humans. Its closest genetic relative, P. vivax-like, was discovered in African great apes and is hypothesized to have given rise to P. vivax in humans. To unravel the evolutionary history and adaptation of P. vivax to different host environments, we generated using long- and short-read sequence technologies 2 new P. vivax-like reference genomes and 9 additional P. vivax-like genotypes. Analyses show that the genomes of P. vivax and P. vivax-like are highly similar and colinear within the core regions. Phylogenetic analyses clearly show that P. vivax-like parasites form a genetically distinct clade from P. vivax. Concerning the relative divergence dating, we show that the evolution of P. vivax in humans did not occur at the same time as the other agents of human malaria, thus suggesting that the transfer of Plasmodium parasites to humans happened several times independently over the history of the Homo genus. We further identify several key genes that exhibit signatures of positive selection exclusively in the human P. vivax parasites. Two of these genes have been identified to also be under positive selection in the other main human malaria agent, P. falciparum, thus suggesting their key role in the evolution of the ability of these parasites to infect humans or their anthropophilic vectors. Finally, we demonstrate that some gene families important for red blood cell (RBC) invasion (a key step of the life cycle of these parasites) have undergone lineage-specific evolution in the human parasite (e.g., reticulocyte-binding proteins [RBPs])

PACo: A Novel Procrustes Application to Cophylogenetic Analysis

We present Procrustean Approach to Cophylogeny (PACo), a novel statistical tool to test for congruence between phylogenetic trees, or between phylogenetic distance matrices of associated taxa. Unlike previous tests, PACo evaluates the dependence of one phylogeny upon the other. This makes it especially appropriate to test the classical coevolutionary model that assumes that parasites that spend part of their life in or on their hosts track the phylogeny of their hosts. The new method does not require fully resolved phylogenies and allows for multiple host-parasite associations. PACo produces a Procrustes superimposition plot enabling a graphical assessment of the fit of the parasite phylogeny onto the host phylogeny and a goodness-of-fit statistic, whose significance is established by randomization of the host-parasite association data. The contribution of each individual host-parasite association to the global fit is measured by means of jackknife estimation of their respective squared residuals and confidence intervals associated to each host-parasite link. We carried out different simulations to evaluate the performance of PACo in terms of Type I and Type II errors with respect to two similar published tests. In most instances, PACo performed at least as well as the other tests and showed higher overall statistical power. In addition, the jackknife estimation of squared residuals enabled more elaborate validations about the nature of individual links than the ParaFitLink1 test of the program ParaFit. In order to demonstrate how it can be used in real biological situations, we applied PACo to two published studies using a script written in the public-domain statistical software R

An integrative approach assesses the intraspecific variations of Procamallanus (Spirocamallanus) inopinatus, a common parasite in Neotropical freshwater fishes, and the phylogenetic patterns of Camallanidae

Integrative taxonomy was used to evaluate two component populations of Procamallanus (Spirocamallanus) inopinatus in Brazil and the phylogeny Camallanidae. Parasite populations were collected in the characiform Anostomoides passionis from River Xingu (Amazon basin) and Megaleporinus elongatus from River Miranda (Paraguay basin). Morphology was analysed using light and scanning electron microscopy (SEM). Genetic characterization was based on partial sequences of the 18S and 28S rDNA, and COI mtDNA. Phylogenies were based on 18S and COI due to data availability. Generalized Mixed Yule Coalescent (GMYC), Poisson Tree Process (PTP) and BEAST were used for species delimitation and validation. SEM revealed for the first time the presence of minute denticles and pore-like structures surrounding the oral opening, phasmids in females and confirmed other important morphological aspects. Statistical comparison between the two-component populations indicated morphometric variations, especially among males. The different component population of P. (S.) inopinatus showed variable morphometry, but uniform morphology and were validated as conspecific by the GMYC, PTP and BEAST. Some camallanid sequences in GenBank have incorrect taxonomic labelling. Host, environment and geographic aspects seem to be related to some lineages within Camallanidae; however, their real phylogenetic meanings are still unclear.Fil: Ailan Choke, Lorena Gisela. Universidad Nacional de Salta. Facultad de Ciencias Naturales. Instituto para el Estudio de la Biodiversidad de Invertebrados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta; ArgentinaFil: Tavares, Luiz E. R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Luque, José L.. Universidade Federal do Rio de Janeiro; BrasilFil: Pereira, Felipe B.. Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas; Brasi

Cophylogenetic analysis of dated trees

Parasites and the associations they form with their hosts is an important area of research due to the associated health risks which parasites pose to the human population. The associations parasites form with their hosts are responsible for a number of the worst emerging diseases impacting global health today, including Ebola, HIV, and malaria. Macro-scale coevolutionary research aims to analyse these associations to provide further insights into these deadly diseases. This approach, first considered by Fahrenholz in 1913, has been applied to hundreds of coevolutionary systems and remains the most robust means to infer the underlying relationships which form between coevolving species. While reconciling the coevolutionary relationships between a pair of evolutionary systems is NP-Hard, it has been shown that if dating information exists there is a polynomial solution. These solutions however are computationally expensive, and are quickly becoming infeasible due to the rapid growth of phylogenetic data. If the rate of growth continues in line with the last three decades, the current means for analysing dated systems will become computationally infeasible. Within this thesis a collection of algorithms are introduced which aim to address this problem. This includes the introduction of the most efficient solution for analysing dated coevolutionary systems optimally, along with two linear time heuristics which may be applied where traditional algorithms are no longer feasible, while still offering a high degree of accuracy 91%. Finally, this work integrates these incremental results into a single model which is able to handle widespread parasitism, the case where parasites infect multiple hosts. This proposed model reconciles two competing theories of widespread parasitism, while also providing an accuracy improvement of 21%, one of the largest single improvements provided in this field to date. As such, the set of algorithms introduced within this thesis offers another step toward a unified coevolutionary analysis framework, consistent with Fahrenholz original coevolutionary analysis model

Return to Beringia: Parasites Reveal Cryptic Biogeographic History of North American Pikas

Traditional concepts of the Bering Land Bridge as a zone of predominantly eastward expansion from Eurasia and a staging area for subsequent colonization of lower latitudes in North America led to early inferences regarding biogeographic histories of North American faunas, many of which remain untested. Here we apply a host–parasite comparative phylogeographical (HPCP) approach to evaluate one such history, by testing competing biogeographic hypotheses for five lineages of host-specific parasites shared by the collared pika (Ochotona collaris) and American pika (Ochotona princeps) of North America. We determine whether the southern host species (O. princeps) was descended from a northern ancestor or vice versa. Three parasite phylogenies revealed patterns consistent with the hypothesis of a southern origin, which is corroborated by four additional parasite lineages restricted to O. princeps. This finding reverses the traditional narrative for the origins of North American pikas and highlights the role of dispersal from temperate North America into Beringia in structuring northern diversity considerably prior to the Holocene. By evaluating multiple parasite lineages simultaneously, the study demonstrates the power of HPCP for resolving complex biogeographic histories that are not revealed by characteristics of the host alone

AxPcoords & parallel AxParafit: statistical co-phylogenetic analyses on thousands of taxa

Background Current tools for Co-phylogenetic analyses are not able to cope with the continuous accumulation of phylogenetic data. The sophisticated statistical test for host-parasite co-phylogenetic analyses implemented in Parafit does not allow it to handle large datasets in reasonable times. The Parafit and DistPCoA programs are the by far most compute-intensive components of the Parafit analysis pipeline. We present AxParafit and AxPcoords (Ax stands for Accelerated) which are highly optimized versions of Parafit and DistPCoA respectively. Results Both programs have been entirely re-written in C. Via optimization of the algorithm and the C code as well as integration of highly tuned BLAS and LAPACK methods AxParafit runs 5–61 times faster than Parafit with a lower memory footprint (up to 35% reduction) while the performance benefit increases with growing dataset size. The MPI-based parallel implementation of AxParafit shows good scalability on up to 128 processors, even on medium-sized datasets. The parallel analysis with AxParafit on 128 CPUs for a medium-sized dataset with an 512 by 512 association matrix is more than 1,200/128 times faster per processor than the sequential Parafit run. AxPcoords is 8–26 times faster than DistPCoA and numerically stable on large datasets. We outline the substantial benefits of using parallel AxParafit by example of a large-scale empirical study on smut fungi and their host plants. To the best of our knowledge, this study represents the largest co-phylogenetic analysis to date. Conclusion The highly efficient AxPcoords and AxParafit programs allow for large-scale co-phylogenetic analyses on several thousands of taxa for the first time. In addition, AxParafit and AxPcoords have been integrated into the easy-to-use CopyCat tool