Patricia Thébault

An Introduction to Metabolic Networks and Their Structural Analysis

There has been a renewed interest for metabolism in the computational biology community, leading to an avalanche of papers coming from methodological network analysis as well as experimental and theoretical biology. This paper is meant to serve as an initial guide for both the biologists interested in formal approaches and the mathematicians or computer scientists wishing to inject more realism into their models. The paper is focused on the structural aspects of metabolism only. The literature is vast enough already, and the thread through it difficult to follow even for the more experienced worker in the field. We explain methods for acquiring data and reconstructing metabolic networks, and review the various models that have been used for their structural analysis. Several concepts such as modularity are introduced, as are the controversies that have beset the field these past few years, for instance, on whether metabolic networks are small-world or scale-free, and on which model better explains the evolution of metabolism. Clarifying the work that has been done also helps in identifying open questions and in proposing relevant future directions in the field, which we do along the paper and in the conclusion.

Emergence of Atypical Mycoplasma agalactiae Strains Harboring a New Prophage and Associated with an Alpine Wild Ungulate Mortality Episode

ABSTRACT The bacterium Mycoplasma agalactiae is responsible for contagious agalactia (CA) in small domestic ruminants, a syndrome listed by the World Organization for Animal Health and responsible for severe damage to the dairy industry. Recently, we frequently isolated this pathogen from lung lesions of ibexes during a mortality episode in the French Alps. This situation was unusual in terms of host specificity and tissue tropism, raising the question of M. agalactiae emergence in wildlife. To address this issue, the ibex isolates were characterized using a combination of approaches that included antigenic profiles, molecular typing, optical mapping, and whole-genome sequencing. Genome analyses showed the presence of a new, large prophage containing 35 coding sequences (CDS) that was detected in most but not all ibex strains and has a homolog in Mycoplasma conjunctivae, a species causing keratoconjunctivitis in wild ungulates. This and the presence in all strains of large integrated conjugative elements suggested highly dynamic genomes. Nevertheless, M. agalactiae strains circulating in the ibex population were shown to be highly related, most likely originating from a single parental clone that has also spread to another wild ungulate species of the same geographical area, the chamois. These strains clearly differ from strains described in Europe so far, including those found nearby, before CA eradication a few years ago. While M. agalactiae pathogenicity in ibexes remains unclear, our data showed the emergence of atypical strains in Alpine wild ungulates, raising the question of a role for the wild fauna as a potential reservoir of pathogenic mycoplasmas.

Evolutionary History of Contagious Bovine Pleuropneumonia Using Next Generation Sequencing of Mycoplasma mycoides Subsp. mycoides “Small Colony”

Mycoplasma mycoides subsp. mycoides “Small Colony” (MmmSC) is responsible for contagious bovine pleuropneumonia (CBPP) in bovidae, a notifiable disease to the World Organization for Animal Health (OIE). Although its origin is not documented, the disease was known in Europe in 1773. It reached nearly world-wide distribution in the 19th century through the cattle trade and was eradicated from most continents by stamping-out policies. During the 20th century it persisted in Africa, and it reappeared sporadically in Southern Europe. Yet, classical epidemiology studies failed to explain the re-occurrence of the disease in Europe in the 1990s. The objectives of this study were to obtain a precise phylogeny of this pathogen, reconstruct its evolutionary history, estimate the date of its emergence, and determine the origin of the most recent European outbreaks. A large-scale genomic approach based on next-generation sequencing technologies was applied to construct a robust phylogeny of this extremely monomorphic pathogen by using 20 representative strains of various geographical origins. Sixty two polymorphic genes of the MmmSC core genome were selected, representing 83601 bp in total and resulting in 139 SNPs within the 20 strains. A robust phylogeny was obtained that identified a lineage specific to European strains; African strains were scattered in various branches. Bayesian analysis allowed dating the most recent common ancestor for MmmSC around 1700. The strains circulating in Sub-Saharan Africa today, however, were shown to descend from a strain that existed around 1810. MmmSC emerged recently, about 300 years ago, and was most probably exported from Europe to other continents, including Africa, during the 19th century. Its diversity is now greater in Africa, where CBPP is enzootic, than in Europe, where outbreaks occurred sporadically until 1999 and where CBPP may now be considered eradicated unless MmmSC remains undetected.

A novel substitution matrix fitted to the compositional bias in Mollicutes improves the prediction of homologous relationships

BackgroundSubstitution matrices are key parameters for the alignment of two protein sequences, and consequently for most comparative genomics studies. The composition of biological sequences can vary importantly between species and groups of species, and classical matrices such as those in the BLOSUM series fail to accurately estimate alignment scores and statistical significance with sequences sharing marked compositional biases.ResultsWe present a general and simple methodology to build matrices that are especially fitted to the compositional bias of proteins. Our approach is inspired from the one used to build the BLOSUM matrices and is based on learning substitution and amino acid frequencies on real sequences with the corresponding compositional bias. We applied it to the large scale comparison of Mollicute AT-rich genomes. The new matrix, MOLLI60, was used to predict pairwise orthology relationships, as well as homolog families among 24 Mollicute genomes. We show that this new matrix enables to better discriminate between true and false orthologs and improves the clustering of homologous proteins, with respect to the use of the classical matrix BLOSUM62.ConclusionsWe show in this paper that well-fitted matrices can improve the predictions of orthologous and homologous relationships among proteins with a similar compositional bias. With the ever-increasing number of sequenced genomes, our approach could prove valuable in numerous comparative studies focusing on atypical genomes.

Flux Analysis of the Trypanosoma brucei Glycolysis Based on a Multiobjective-Criteria Bioinformatic Approach

Trypanosoma brucei is a protozoan parasite of major of interest in discovering new genes for drug targets. This parasite alternates its life cycle between the mammal host(s) (bloodstream form) and the insect vector (procyclic form), with two divergent glucose metabolism amenable to in vitro culture. While the metabolic network of the bloodstream forms has been well characterized, the flux distribution between the different branches of the glucose metabolic network in the procyclic form has not been addressed so far. We present a computational analysis (called Metaboflux) that exploits the metabolic topology of the procyclic form, and allows the incorporation of multipurpose experimental data to increase the biological relevance of the model. The alternatives resulting from the structural complexity of networks are formulated as an optimization problem solved by a metaheuristic where experimental data are modeled in a multiobjective function. Our results show that the current metabolic model is in agreement with experimental data and confirms the observed high metabolic flexibility of glucose metabolism. In addition, Metaboflux offers a rational explanation for the high flexibility in the ratio between final products from glucose metabolism, thsat is, flux redistribution through the malic enzyme steps.

Draft Genome Sequences of Mycoplasma alkalescens, Mycoplasma arginini, and Mycoplasma bovigenitalium, Three Species with Equivocal Pathogenic Status for Cattle

ABSTRACT We report here the draft genome sequences of Mycoplasma alkalescens, Mycoplasma arginini, and Mycoplasma bovigenitalium. These three species are regularly isolated from bovine clinical specimens, although their role in disease is unclear.

Draft Genome Sequences of Mycoplasma auris and Mycoplasma yeatsii, Two Species of the Ear Canal of Caprinae.

ABSTRACT We report here the draft genome sequences of Mycoplasma auris and Mycoplasma yeatsii, two species commonly isolated from the external ear canal of Caprinae.

Systrip: A Visual Environment for the Investigation of Time-series Data in the Context of Metabolic Networks

Technological advances in biology lead to a profusion of quantitative data, raising analytical challenges. Visual analytics is particularly well suited to address these difficulties. It helps to interactively move through the different levels of analysis and to simultaneously investigate data with different point of views. It is especially the case when dealing with biological networks that can contain hundreds of elements. In these studies biologists generally follow the same analytic process which consists in first getting an overview of the data before focussing on a few relevant subnetworks. In this article we present, Systrip, a visual environment for the analysis of time-series data in the context of biological networks. In particular we focus on the study of metabolism. Systrip gathers bioinformatics and graph theoretical algorithms that can be assembled in different ways to help biologists in their visual mining process. This framework had been used to analyse various real biological data. In this article we describe how it helped in understanding drug effects on the metabolism of the parasite of the tsetse fly causing sleeping sickness.

rNAV 2.0: a visualization tool for bacterial sRNA-mediated regulatory networks mining

BackgroundBacterial sRNA-mediated regulatory networks has been introduced as a powerful way to analyze the fast rewiring capabilities of a bacteria in response to changing environmental conditions. The identification of mRNA targets of bacterial sRNAs is essential to investigate their functional activities. However, this step remains challenging with the lack of knowledge of the topological and biological constraints behind the formation of sRNA-mRNA duplexes. Even with the most sophisticated bioinformatics target prediction tools, the large proportion of false predictions may be prohibitive for further analyses. To deal with this issue, sRNA target analyses can be carried out from the resulting gene lists given by RNA-SEQ experiments when available. However, the number of resulting target candidates may be still huge and cannot be easily interpreted by domain experts who need to confront various biological features to prioritize the target candidates. Therefore, novel strategies have to be carried out to improve the specificity of computational prediction results, before proposing new candidates for an expensive experimental validation stage.ResultTo address this issue, we propose a new visualization tool rNAV 2.0, for detecting and filtering bacterial sRNA targets for regulatory networks. rNAV is designed to cope with a variety of biological constraints, including the gene annotations, the conserved regions of interaction or specific patterns of regulation. Depending on the application, these constraints can be variously combined to analyze the target candidates, prioritized for instance by a known conserved interaction region, or because of a common function.ConclusionThe standalone application implements a set of known algorithms and interaction techniques, and applies them to the new problem of identifying reasonable sRNA target candidates.

Complete Genome Sequence of Mycoplasma putrefaciens Strain 9231, One of the Agents of Contagious Agalactia in Goats

ABSTRACT Mycoplasma putrefaciens is one of the etiologic agents of contagious agalactia in goats. We report herein the complete genome sequence of Mycoplasma putrefaciens strain 9231.