Christian Blouin

GenGIS: A geospatial information system for genomic data

The increasing availability of genetic sequence data associated with explicit geographic and ecological information is offering new opportunities to study the processes that shape biodiversity. The generation and testing of hypotheses using these data sets requires effective tools for mathematical and visual analysis that can integrate digital maps, ecological data, and large genetic, genomic, or metagenomic data sets. GenGIS is a free and open-source software package that supports the integration of digital map data with genetic sequences and environmental information from multiple sample sites. Essential bioinformatic and statistical tools are integrated into the software, allowing the user a wide range of analysis options for their sequence data. Data visualizations are combined with the cartographic display to yield a clear view of the relationship between geography and genomic diversity, with a particular focus on the hierarchical clustering of sites based on their similarity or phylogenetic proximity. Here we outline the features of GenGIS and demonstrate its application to georeferenced microbial metagenomic, HIV-1, and human mitochondrial DNA data sets.

SPR Distance Computation for Unrooted Trees

The subtree prune and regraft distance (dSPR) between phylogenetic trees is important both as a general means of comparing phylogenetic tree topologies as well as a measure of lateral gene transfer (LGT). Although there has been extensive study on the computation of dSPR and similar metrics between rooted trees, much less is known about SPR distances for unrooted trees, which often arise in practice when the root is unresolved. We show that unrooted SPR distance computation is NP-Hard and verify which techniques from related work can and cannot be applied. We then present an efficient heuristic algorithm for this problem and benchmark it on a variety of synthetic datasets. Our algorithm computes the exact SPR distance between unrooted tree, and the heuristic element is only with respect to the algorithms computation time. Our method is a heuristic version of a fixed parameter tractability (FPT) approach and our experiments indicate that the running time behaves similar to FPT algorithms. For real data sets, our algorithm was able to quickly compute dSPR for the majority of trees that were part of a study of LGT in 144 prokaryotic genomes. Our analysis of its performance, especially with respect to searching and reduction rules, is applicable to computing many related distance measures.

Improved Helix and Kink Characterization in Membrane Proteins Allows Evaluation of Kink Sequence Predictors

Although the α-helical secondary structure of proteins is well-defined, the exact causes and structures of helical kinks are not. This is especially important for transmembrane (TM) helices of integral membrane proteins, many of which contain kinks providing functional diversity despite predominantly helical structure. We have developed a Monte Carlo method based algorithm, MC-HELAN, to determine helical axes alongside positions and angles of helical kinks. Analysis of all nonredundant high-resolution α-helical membrane protein structures (842 TM helices from 205 polypeptide chains) revealed kinks in 64% of TM helices, demonstrating that a significantly greater proportion of TM helices are kinked than those indicated by previous analyses. The residue proline is over-represented by a factor >5 if it is two or three residues C-terminal to a bend. Prolines also cause kinks with larger kink angles than other residues. However, only 33% of TM kinks are in proximity to a proline. Machine learning techniques were used to test for sequence-based predictors of kinks. Although kinks are somewhat predicted by sequence, kink formation appears to be driven predominantly by other factors. This study provides an improved view of the prevalence and architecture of kinks in helical membrane proteins and highlights the fundamental inaccuracy of the typical topological depiction of helical membrane proteins as series of ideal helices.

Insertions and the emergence of novel protein structure: a structure-based phylogenetic study of insertions

BackgroundIn protein evolution, the mechanism of the emergence of novel protein domain is still an open question. The incremental growth of protein variable regions, which was produced by stochastic insertions, has the potential to generate large and complex sub-structures. In this study, a deterministic methodology is proposed to reconstruct phylogenies from protein structures, and to infer insertion events in protein evolution. The analysis was performed on a broad range of SCOP domain families.ResultsPhylogenies were reconstructed from protein 3D structural data. The phylogenetic trees were used to infer ancestral structures with a consensus method. From these ancestral reconstructions, 42.7% of the observed insertions are nested insertions, which locate in previous insert regions. The average size of inserts tends to increase with the insert rank or total number of insertions in the variable regions. We found that the structures of some nested inserts show complex or even domain-like fold patterns with helices, strands and loops. Furthermore, a basal level of structural innovation was found in inserts which displayed a significant structural similarity exclusively to themselves. The β-Lactamase/D-ala carboxypeptidase domain family is provided as an example to illustrate the inference of insertion events, and how the incremental growth of a variable region is capable to generate novel structural patterns.ConclusionUsing 3D data, we proposed a method to reconstruct phylogenies. We applied the method to reconstruct the sequences of insertion events leading to the emergence of potentially novel structural elements within existing protein domains. The results suggest that structural innovation is possible via the stochastic process of insertions and rapid evolution within variable regions where inserts tend to be nested. We also demonstrate that the structure-based phylogeny enables the study of new questions relating to the evolution of protein domain and biological function.

Estimation of rates-across-sites distributions in phylogenetic substitution models

Previous work has shown that it is often essential to account for the variation in rates at different sites in phylogenetic models in order to avoid phylogenetic artifacts such as long branch attraction. In most current models, the gamma distribution is used for the rates-across-sites distributions and is implemented as an equal-probability discrete gamma. In this article, we introduce discrete distribution estimates with large numbers of equally spaced rate categories allowing us to investigate the appropriateness of the gamma model. With large numbers of rate categories, these discrete estimates are flexible enough to approximate the shape of almost any distribution. Likelihood ratio statistical tests and a nonparametric bootstrap confidence-bound estimation procedure based on the discrete estimates are presented that can be used to test the fit of a parametric family. We applied the methodology to several different protein data sets, and found that although the gamma model often provides a good parametric model for this type of data, rate estimates from an equal-probability discrete gamma model with a small number of categories will tend to underestimate the largest rates. In cases when the gamma model assumption is in doubt, rate estimates coming from the discrete rate distribution estimate with a large number of rate categories provide a robust alternative to gamma estimates. An alternative implementation of the gamma distribution is proposed that, for equal numbers of rate categories, is computationally more efficient during optimization than the standard gamma implementation and can provide more accurate estimates of site rates.

Inhibition of Escherichia coli glucosamine-6 phosphate synthase by reactive intermediate analogues - The role of the 2-amino function in catalysis

Glucosamine-6-phosphate synthase (GlmS) catalyzes the formation of d-glucosamine 6-phosphate fromd-fructose 6-phosphate using l-glutamine as the ammonia source. Because N-acetylglucosamine is an essential building block of both bacterial cell walls and fungal cell wall chitin, the enzyme is a potential target for antibacterial and antifungal agents. The most potent carbohydrate-based inhibitor of GlmS reported to date is 2-amino-2-deoxy-d-glucitol 6-phosphate, an analogue of the putative cis-enolamine intermediate formed during catalysis. The interaction of a series of structurally related cis-enolamine intermediate analogues with GlmS is described. Although arabinose oxime 5-phosphate is identified as a good competitive inhibitor of GlmS with an inhibition constant equal to 1.2 (±0.3) mm, the presence of the amino function at the 2-position is shown to be important for potent inhibition. Comparison of the binding affinities of 2-deoxy-d-glucitol 6-phosphate and 2-amino-2-deoxy-d-glucitol 6-phosphate indicates that the amino function contributes −4.1 (±0.1) kcal/mol to the free energy of inhibitor binding. Similarly, comparison of the binding affinities of 2-deoxy-d-glucose 6-phosphate andd-glucosamine 6-phosphate indicates that the amino function contributes −3.0 (±0.1) kcal/mol to the free energy of product binding. Interactions between GlmS and the 2-amino function of its ligands contribute to the uniform binding of the product and thecis-enolamine intermediate as evidenced by the similar contribution of the amino group to the free energy of binding ofd-glucosamine 6-phosphate and 2-amino-2-deoxy-d-glucitol 6-phosphate, respectively.

Rapid evolution in conformational space: A study of loop regions in a ubiquitous GTP binding domain

The rapidly evolving subsets of a protein are often evident in multiple sequence alignments as poorly defined, gap‐containing regions. We investigated the 3D context of these regions observed in 28 protein structures containing a GTP‐binding domain assumed to be homologous to the transforming factor p21‐RAS. The phylogenetic depth of this data set is such that it is possible to observe lineages sharing a common protein core that diverged early in the eukaryotic cell history. The sequence variability among these homolog proteins is directly linked to the structural variability of surface loops. We demonstrate that these regions are self‐contained and thus mostly free of the evolutionary constraints imposed by the conserved core of the domain. These intraloop interactions have the property to create stem‐like structures. Interestingly, these stem‐like structures can be observed in loops of varying size, up to the size of small protein domains. We propose a model under which the diversity of protein topologies observed in these loops can be the product of a stochastic sampling of sequence and conformational space in a near‐neutral fashion, while the proximity of the functional features of the domain core allows novel beneficial traits to be fixed. Our comparative observations, limited here to the proteins containing the RAS‐like GTP‐binding domain, suggest that a stochastic process of insertion/deletion analogous to “budding” of loops is a likely mechanism of structural innovation. Such a framework could be experimentally exploited to investigate the folding of increasingly complex model inserts.

Resolving the Individual Components of a pH-Induced Conformational Change

This communication introduces a simple method to determine the pKs of microscopic ionizations from complex titration curves. We used this approach to study the alkaline transition (pH-dependent ligand exchange) of mitochondrial cytochrome c. The linearization of titration curves permitted resolution of two to three limiting microscopic ionizations. By combining these data with studies of the temperature dependence of ligand-exchange equilibria, we found evidence that the alkaline transition comprises two chemically distinct processes: the deprotonation of the alternative ligands and the break of the iron-methionine ligation bond. We also noted that, in the horse and untrimethylated S. cerevisiae iso-1 cytochromes c, the permissible deprotonation of the epsilon-amino group of Lys(72) allows formation of an alkaline isomer at lower pH, with lesser stability, which leads to hysteresis in the titration curves. The linearization of the titration curves for different cytochromes c thus brings insight on the microscopic contributions to conformational stability.

Intein-mediated cyclization of bacterial acyl carrier protein stabilizes its folded conformation but does not abolish function.

Bacterial acyl carrier protein (ACP) is essential for the synthesis of fatty acids and serves as the major acyl donor for the formation of phospholipids and other lipid products. Acyl-ACP encloses attached fatty acyl groups in a hydrophobic pocket within a four-helix bundle, but must at least partially unfold to present the acyl chain to the active sites of its multiple enzyme partners. To further examine the constraints of ACP structure and function, we have constructed a cyclic version of Vibrio harveyi ACP, using split-intein technology to covalently join its closely apposed N and C termini. Cyclization stabilized ACP in a folded helical conformation as indicated by gel electrophoresis, circular dichroism, fluorescence, and mass spectrometry. Molecular dynamics simulations also indicated overall decreased polypeptide chain mobility in cyclic ACP, although no major conformational rearrangements over a 10-ns period were noted. In vivo complementation assays revealed that cyclic ACP can functionally replace the linear wild-type protein and support growth of an Escherichia coli ACP-null mutant strain. Cyclization of a folding-deficient ACP mutant (F50A) both restored its ability to adopt a folded conformation and enhanced complementation of growth. Our results thus suggest that ACP must be able to adopt a folded conformation for biological activity, and that its function does not require complete unfolding of the protein.

libcov: A C++ bioinformatic library to manipulate protein structures, sequence alignments and phylogeny

BackgroundAn increasing number of bioinformatics methods are considering the phylogenetic relationships between biological sequences. Implementing new methodologies using the maximum likelihood phylogenetic framework can be a time consuming task.ResultsThe bioinformatics library libcov is a collection of C++ classes that provides a high and low-level interface to maximum likelihood phylogenetics, sequence analysis and a data structure for structural biological methods. libcov can be used to compute likelihoods, search tree topologies, estimate site rates, cluster sequences, manipulate tree structures and compare phylogenies for a broad selection of applications.ConclusionUsing this library, it is possible to rapidly prototype applications that use the sophistication of phylogenetic likelihoods without getting involved in a major software engineering project. libcov is thus a potentially valuable building block to develop in-house methodologies in the field of protein phylogenetics.