Whole Genome Sequencing of Field Isolates Reveals a Common Duplication of the Duffy Binding Protein Gene in Malagasy Plasmodium vivax Strains

Background

Plasmodium vivax is the most prevalent human malaria parasite, causing serious public health problems in malaria-endemic countries. Until recently the Duffy-negative blood group phenotype was considered to confer resistance to vivax malaria for most African ethnicities. We and others have reported that P. vivax strains in African countries from Madagascar to Mauritania display capacity to cause clinical vivax malaria in Duffy-negative people. New insights must now explain Duffy-independent P. vivax invasion of human erythrocytes.

Methods/Principal Findings

Through recent whole genome sequencing we obtained ≥70× coverage of the P. vivax genome from five field-isolates, resulting in ≥93% of the Sal I reference sequenced at coverage greater than 20×. Combined with sequences from one additional Malagasy field isolate and from five monkey-adapted strains, we describe here identification of DNA sequence rearrangements in the P. vivax genome, including discovery of a duplication of the P. vivax Duffy binding protein (PvDBP) gene. A survey of Malagasy patients infected with P. vivax showed that the PvDBP duplication was present in numerous locations in Madagascar and found in over 50% of infected patients evaluated. Extended geographic surveys showed that the PvDBP duplication was detected frequently in vivax patients living in East Africa and in some residents of non-African P. vivax-endemic countries. Additionally, the PvDBP duplication was observed in travelers seeking treatment of vivax malaria upon returning home. PvDBP duplication prevalence was highest in west-central Madagascar sites where the highest frequencies of P. vivax-infected, Duffy-negative people were reported.

Conclusions/Significance

The highly conserved nature of the sequence involved in the PvDBP duplication suggests that it has occurred in a recent evolutionary time frame. These data suggest that PvDBP, a merozoite surface protein involved in red cell adhesion is rapidly evolving, possibly in response to constraints imposed by erythrocyte Duffy negativity in some human populations.     

Nanomoulding of Functional Materials,a Versatile Complementary Pattern Replication Method to Nanoimprinting

We describe a nanomoulding technique which allows low-cost nanoscale patterning of functional materials, materials stacks and full devices. Nanomoulding combined with layer transfer enables the replication of arbitrary surface patterns from a master structure onto the functional material. Nanomoulding can be performed on any nanoimprinting setup and can be applied to a wide range of materials and deposition processes. In particular we demonstrate the fabrication of patterned transparent zinc oxide electrodes for light trapping applications in solar cells.     

An information-theoretic classification of amino acids for the assessment of interfaces in protein–protein docking

Docking represents a versatile and powerful method to predict the geometry of protein–protein complexes. However, despite significant methodical advances, the identification of good docking solutions among a large number of false solutions still remains a difficult task. We have previously demonstrated that the formalism of mutual information (MI) from information theory can be adapted to protein docking, and we have now extended this approach to enhance its robustness and applicability. A large dataset consisting of 22,934 docking decoys derived from 203 different protein–protein complexes was used for an MI-based optimization of reduced amino acid alphabets representing the protein–protein interfaces. This optimization relied on a clustering analysis that allows one to estimate the mutual information of whole amino acid alphabets by considering all structural features simultaneously, rather than by treating them individually. This clustering approach is fast and can be applied in a similar fashion to the generation of reduced alphabets for other biological problems like fold recognition, sequence data mining, or secondary structure prediction. The reduced alphabets derived from the present work were converted into a scoring function for the evaluation of docking solutions, which is available for public use via the web service score-MI: http://score-MI.biochem.uni-erlangen.de     

Is hyper-hardness more chemically relevant than expected?

In this work, the third derivative of the energy with respect to the number of electrons, the so-called hyper-hardness, is investigated to assess whether this quantity has a chemical meaning. To achieve this goal a new working expression for hyper-hardness is developed and analyzed. It transpired from this analysis that hyper-hardness, just like hardness, can measure the reactivity or the stability of electron systems. Interestingly, positive values of hyper-hardness point to quite stable species such as noble gases and molecules. On the other hand, radicals almost always display large negative values of hyper-hardness.     

Citrulline enhances myofibrillar constituents expression of skeletal muscle and induces a switch in muscle energy metabolism in malnourished aged rats

Citrulline (Cit) actions on muscle metabolism remain unclear. Those latter were investigated using a proteomic approach on Tibialis muscles from male Sprague‐Dawley rats. At 23 months of age, rats were either fed ad libitum (AL group) or subjected to dietary restriction for 12 weeks. At the end of the restriction period, one group of rats was euthanized (R group) and two groups were refed for one week with a standard diet supplemented with nonessential amino acids group or Cit (CIT group). Results of the proteomic approach were validated using targeted Western blot analysis and assessment of gene expression of the related genes. Maximal activities of the key enzymes involved in mitochondrial functioning were also determined. Cit supplementation results in a significant increase in the protein expression of the main myofibrillar constituents and of a few enzymes involved in glycogenolysis and glycolysis (CIT vs. AL and R, p < 0.05). Conversely, the expression of oxidative enzymes from Krebs cycle and mitochondrial respiratory chain was significantly decreased (CIT vs. AL, p < 0.05). However, maximal activities of key enzymes of mitochondrial metabolism were not significantly affected, except for complex 1 which presented an increased activity (CIT vs. AL and R, p < 0.05). In conclusion, Cit supplementation increases expression of the main myofibrillar proteins and seems to induce a switch in muscle energy metabolism, from aerobia toward anaerobia.     

Approximate Bayesian Computation

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

This is a “Topic Page” article for PLOS Computational Biology.

     

High performance analysis of the cyanobacterial metabolism via liquid chromatography coupled to a LTQ-Orbitrap mass spectrometer: evidence that glucose reprograms the whole carbon metabolism and triggers oxidative stress

Cyanobacteria are environmentally important photosynthetic microorganisms attracting a growing attention in various areas of basic and applied researches. To better understand their metabolism, we presently report on the development of a robust and simple protocol for facile extraction and high throughput analysis of the metabolites of the widely-used strain Synechocystis PCC6803 through liquid chromatography coupled to high resolution mass spectrometry (LC/MS). Our analytical method was developed and tested with 102 reference compounds representative of the chemical diversity of polar cell metabolites, and Synechocystis cell extracts spiked with 37 reference compounds. These samples were analyzed with two chromatographic systems, each coupled to a LTQ-Orbitrap mass spectrometer: a liquid chromatographic system equipped with a pentafluorophenylpropyl column (the PFPP-LC/MS system), and an ultra-high performance liquid chromatographic system with a C₁₈-reversed phase column (the C₁₈-UHPLC/MS system). We showed that the PFPP-LC/MS method performs better than the C₁₈-UHPLC/MS method in terms of retention, separation and detection of metabolites. Consequently, we applied the PFPP-LC/MS method to analyze the metabolome of Synechocystis growing under various conditions of light and glucose, which strongly influence cell growth. We found that glucose increases glucose storage (synthesis of glycogen-like polysaccharide) and catabolism (oxidative pentose phosphate pathway and glycolysis), while it decreases the Calvin–Benson cycle that consumes photosynthetic electrons for CO₂ assimilation. Depending on light and glucose availabilities, this global metabolic reprogramming can generate an oxidative stress, likely through the recombination of the glucose-spared electrons with the photosynthetic oxygen thereby producing toxic reactive oxygen species.     

The Impact of Gene Duplication,Insertion, Deletion,Lateral Gene Transfer and Sequencing Error on Orthology Inference: A Simulation Study

The identification of orthologous genes, a prerequisite for numerous analyses in comparative and functional genomics, is commonly performed computationally from protein sequences. Several previous studies have compared the accuracy of orthology inference methods, but simulated data has not typically been considered in cross-method assessment studies. Yet, while dependent on model assumptions, simulation-based benchmarking offers unique advantages: contrary to empirical data, all aspects of simulated data are known with certainty. Furthermore, the flexibility of simulation makes it possible to investigate performance factors in isolation of one another.Here, we use simulated data to dissect the performance of six methods for orthology inference available as standalone software packages (Inparanoid, OMA, OrthoInspector, OrthoMCL, QuartetS, SPIMAP) as well as two generic approaches (bidirectional best hit and reciprocal smallest distance). We investigate the impact of various evolutionary forces (gene duplication, insertion, deletion, and lateral gene transfer) and technological artefacts (ambiguous sequences) on orthology inference. We show that while gene duplication/loss and insertion/deletion are well handled by most methods (albeit for different trade-offs of precision and recall), lateral gene transfer disrupts all methods. As for ambiguous sequences, which might result from poor sequencing, assembly, or genome annotation, we show that they affect alignment score-based orthology methods more strongly than their distance-based counterparts.     

Evolutionary History of the Plant Pathogenic Bacterium Xanthomonas axonopodis

Deciphering mechanisms shaping bacterial diversity should help to build tools to predict the emergence of infectious diseases. Xanthomonads are plant pathogenic bacteria found worldwide. Xanthomonas axonopodis is a genetically heterogeneous species clustering, into six groups, strains that are collectively pathogenic on a large number of plants. However, each strain displays a narrow host range. We address the question of the nature of the evolutionary processes – geographical and ecological speciation – that shaped this diversity. We assembled a large collection of X. axonopodis strains that were isolated over a long period, over continents, and from various hosts. Based on the sequence analysis of seven housekeeping genes, we found that recombination occurred as frequently as point mutation in the evolutionary history of X. axonopodis. However, the impact of recombination was about three times greater than the impact of mutation on the diversity observed in the whole dataset. We then reconstructed the clonal genealogy of the strains using coalescent and genealogy approaches and we studied the diversification of the pathogen using a model of divergence with migration. The suggested scenario involves a first step of generalist diversification that spanned over the last 25 000 years. A second step of ecology-driven specialization occurred during the past two centuries. Eventually, secondary contacts between host-specialized strains probably occurred as a result of agricultural development and intensification, allowing genetic exchanges of virulence-associated genes. These transfers may have favored the emergence of novel pathotypes. Finally, we argue that the largest ecological entity within X. axonopodis is the pathovar.