Graph-based analysis of the metabolic exchanges between two co-resident intracellular symbionts, baumannia cicadellinicola and sulcia muelleri with their insect host, homalodisca coagulata

International audienceEndosymbiotic bacteria from different species can live inside cells of the same eukaryotic organism. Metabolic exchanges occur between host and bacteria but also between different endocytobionts. Since a complete genome annotation is available for both, we built the metabolic network of two endosymbiotic bacteria, Sulcia muelleri and Baumannia cicadellinicola, that live inside specific cells of the sharpshooter Homalodisca coagulata and studied the metabolic exchanges involving transfers of carbon atoms between the three. We automatically determined the set of metabolites potentially exogenously acquired (seeds) for both metabolic networks. We show that the number of seeds needed by both bacteria in the carbon metabolism is extremely reduced. Moreover, only three seeds are common to both metabolic networks, indicating that the complementarity of the two metabolisms is not only manifested in the metabolic capabilities of each bacterium, but also by their different use of the same environment. Furthermore, our results show that the carbon metabolism of S. muelleri may be completely independent of the metabolic network of B. cicadellinicola. On the contrary, the carbon metabolism of the latter appears dependent on the metabolism of S. muelleri, at least for two essential amino acids, threonine and lysine. Next, in order to define which subsets of seeds (precursor sets) are sufficient to produce the metabolites involved in a symbiotic function, we used a graph-based method, PITUFO, that we recently developed. Our results highly refine our knowledge about the complementarity between the metabolisms of the two bacteria and their host. We thus indicate seeds that appear obligatory in the synthesis of metabolites are involved in the symbiotic function. Our results suggest both B. cicadellinicola and S. muelleri may be completely independent of the metabolites provided by the co-resident endocytobiont to produce the carbon backbone of the metabolites provided to the symbiotic system (., thr and lys are only exploited by B. cicadellinicola to produce its proteins)

Énumération de sous-structures fonctionnelle dans des réseaux métaboliques complets : Histoires métaboliques, précurseurs et organisations chimiques

In this thesis, we presented three different methods for enumerating special subnetworks containedin a metabolic network: metabolic stories, minimal precursor sets and chemical organisations. Foreach of the three methods, we gave theoretical results, and for the two first ones, we further providedan illustration on how to apply them in order to study the metabolic behaviour of living organisms.Metabolic stories are defined as maximal directed acyclic graphs whose sets of sources and targets arerestricted to a subset of the nodes. The initial motivation of this definition was to analyse metabolomicsexperimental data, but the method was also explored in a different context. Metabolic precursor setsare minimal sets of nutrients that are able to produce metabolites of interest. We present threedifferent methods for enumerating minimal precursor sets and we illustrate the application in a studyof the metabolic exchanges in a symbiotic system. Chemical organisations are sets of metabolites thatare simultaneously closed and self-maintaining, which captures some stability feature in theDans cette thèse, nous avons présenté trois méthodes différentes pour l’énumération de sousréseauxparticuliers d’un réseau métabolique: les histoires métaboliques, les ensembles minimaux deprécurseurs et les organisations chimiques. Pour chacune de ces trois méthodes, nous avons présentédes résultats théoriques, et pour les deux premières, nous avons en outre fourni une illustration surcomment les appliquer afin d’étudier le comportement métabolique des organismes vivants. Les histoiresmétaboliques sont définies comme des graphes acycliques dirigés maximaux dont les ensemblesde sources et de cibles sont limités à un sous-ensemble des noeuds. La motivation initiale de cette définitionétait d’analyser des données expérimentales de métabolomique, mais la méthode a égalementété explorée dans un contexte différent. Les ensembles de précurseurs métaboliques sont des ensemblesminimaux de nutriments qui permettent de produire des métabolites d’intérêt. Nous présentons troisméthodes différentes pour l’énumération de tels ensembles minimaux de précurseurs, et nous illustronsleur application dans une étude des échanges métaboliques dans un système symbiotique. Les organisationschimiques sont des ensembles de métabolites qui à la fois sont fermés et s’auto-maintiennent,ce qui reflète des caractéristiques de stabilité dans le sens où aucun nouveau métabolite ne peut êtreproduit et qu’aucun des métabolites déjà présents dans le système ne peut disparaître

Structural and dynamical analysis of biological networks

Biological networks are currently being studied with approaches derived from the mathematical and physical sciences. Their structural analysis enables to highlight nodes with special properties that have sometimes been correlated with the biological importance of a gene or a protein. However, biological networks are dynamic both on the evolutionary time-scale, and on the much shorter time-scale of physiological processes. There is therefore no unique network for a given cellular process, but potentially many realizations, each with different properties as a consequence of regulatory mechanisms. Such realizations provide snapshots of a same network in different conditions, enabling the study of condition-dependent structural properties. True dynamical analysis can be obtained through detailed mathematical modeling techniques that are not easily scalable to full network models. © The Author 2012. Published by Oxford University Press. All rights reserved

Telling stories fast: Via linear-time delay pitch enumeration

This paper presents a linear-time delay algorithm for enumerating all directed acyclic subgraphs of a directed graph G(V,E) that have their sources and targets included in two subsets S and T of V, respectively. From these subgraphs, called pitches, the maximal ones, called stories, may be extracted in a dramatically more efficient way in relation to a previous story telling algorithm. The improvement may even increase if a pruning technique is further applied that avoids generating many pitches which have no chance to lead to a story. We experimentally demonstrate these statements by making use of a quite large dataset of real metabolic pathways and networks. © 2013 Springer-Verlag

Telling Stories Fast

International audienceThis paper presents a linear-time delay algorithm for enumerating all directed acyclic subgraphs of a directed graph G(V,E) that have their sources and targets included in two subsets S and T of V, respectively. From these subgraphs, called pitches, the maximal ones, called stories, may be extracted in a dramatically more efficient way in relation to a previous story telling algorithm. The improvement may even increase if a pruning technique is further applied that avoids generating many pitches which have no chance to lead to a story. We experimentally demonstrate these statements by making use of a quite large dataset of real metabolic pathways and networks

Enumerating precursor sets of target metabolites in a metabolic network

We present the first exact method based on the topology of a metabolic network to find minimal sets of metabolites (called precursors) sufficient to produce a set of target metabolites. In contrast with previous proposals, our model takes into account self-regenerating metabolites involved in cycles, which may be used to generate target metabolites from potential precursors. We analyse the complexity of the problem and we propose an algorithm to enumerate all minimal precursor sets for a set of target metabolites. The algorithm can be applied to identify a minimal medium necessary for a cell to ensure some metabolic functions. It can be used also to check inconsistencies caused by misannotations in a metabolic network. We present two illustrations of these applications. © 2008 Springer-Verlag Berlin Heidelberg

Telling stories: Enumerating maximal directed acyclic graphs with a constrained set of sources and targets.

International audienceWe present a constrained version of the problem of enumerating all maximal directed acyclic subgraphs (DAG) of a graph G. In this version, we enumerate maximal DAGs whose sources and targets belong to a predefined subset of the nodes. We call such DAGs stories. We first show how to compute one story in polynomial-time, and then describe two different algorithms to ''tell'' all possible stories

Telling metabolic stories to explore metabolomics data: a case study on the yeast response to cadmium exposure

Artículo de publicación ISIMotivation: The increasing availability of metabolomics data enables to better understand the metabolic processes involved in the immediate response of an organism to environmental changes and stress. The data usually come in the form of a list of metabolites whose concentrations significantly changed under some conditions, and are thus not easy to interpret without being able to precisely visualize how such metabolites are interconnected. Results: We present a method that enables to organize the data from any metabolomics experiment into metabolic stories. Each story corresponds to a possible scenario explaining the flow of matter between the metabolites of interest. These scenarios may then be ranked in different ways depending on which interpretation one wishes to emphasize for the causal link between two affected metabolites: enzyme activation, enzyme inhibition or domino effect on the concentration changes of substrates and products. Equally probable stories under any selected ranking scheme can be further grouped into a single anthology that summarizes, in a unique subnetwork, all equivalently plausible alternative stories. An anthology is simply a union of such stories. We detail an application of the method to the response of yeast to cadmium exposure. We use this system as a proof of concept for our method, and we show that we are able to find a story that reproduces very well the current knowledge about the yeast response to cadmium. We further show that this response is mostly based on enzyme activation. We also provide a framework for exploring the alternative pathways or side effects this local response is expected to have in the rest of the network. We discuss several interpretations for the changes we see, and we suggest hypotheses that could in principle be experimentally tested. Noticeably, our method requires simple input data and could be used in a wide variety of applications. Availability and implementation: The code for the method presented in this article is available at http://gobbolino.gforge.inria.fr.European Research Council under the European Community’s Seventh Framework Programme (FP7/2007- 2013)/ERC grant agreement no. (247073)10; the French project (ANR MIRI BLAN08-1335497); and the ANR funded LabEx ECOFECT. It was partially supported by the Plateforme Bioinformatique de Toulouse, ANR-BBSRC Systryp, the CIRIC-INRIA Chile line Natural Resources, the NWO-CLS MEMESA project and the ‘DISCO’ PRIN National Research Project