Enumeration of minimal stoichiometric precursor sets in metabolic networks

Background: What an organism needs at least from its environment to produce a set of metabolites, e.g. target(s) of interest and/or biomass, has been called a minimal precursor set. Early approaches to enumerate all minimal precursor sets took into account only the topology of the metabolic network (topological precursor sets). Due to cycles and the stoichiometric values of the reactions, it is often not possible to produce the target(s) from a topological precursor set in the sense that there is no feasible flux. Although considering the stoichiometry makes the problem harder, it enables to obtain biologically reasonable precursor sets that we call stoichiometric. Recently a method to enumerate all minimal stoichiometric precursor sets was proposed in the literature. The relationship between topological and stoichiometric precursor sets had however not yet been studied. Results: Such relationship between topological and stoichiometric precursor sets is highlighted. We also present two algorithms that enumerate all minimal stoichiometric precursor sets. The first one is of theoretical interest only and is based on the above mentioned relationship. The second approach solves a series of mixed integer linear programming problems. We compared the computed minimal precursor sets to experimentally obtained growth media of several Escherichia coli strains using genome-scale metabolic networks. Conclusions: The results show that the second approach efficiently enumerates minimal precursor sets taking stoichiometry into account, and allows for broad in silico studies of strains or species interactions that may help to understand e.g. pathotype and niche-specific metabolic capabilities. sasita is written in Java, uses cplex as LP solver and can be downloaded together with all networks and input files used in this paper at http://www.sasita.gforge.inria.fr

A combinatorial algorithm for microbial consortia synthetic design

International audienceSynthetic biology has boomed since the early 2000s when it started being shown that it was possible to efficiently synthetize compounds of interest in a much more rapid and effective way by using other organisms than those naturally producing them. However, to thus engineer a single organism, often a microbe, to optimise one or a collection of metabolic tasks may lead to difficulties when attempting to obtain a production system that is efficient, or to avoid toxic effects for the recruited microorganism. The idea of using instead a microbial consortium has thus started being developed in the last decade. This was motivated by the fact that such consortia may perform more complicated functions than could single populations and be more robust to environmental fluctuations. Success is however not always guaranteed. In particular, establishing which consortium is best for the production of a given compound or set thereof remains a great challenge. This is the problem we address in this paper. We thus introduce an initial model and a method that enable to propose a consortium to synthetically produce compounds that are either exogenous to it, or are endogenous but where interaction among the species in the consortium could improve the production line. Synthetic biology has been defined by the European Commission as " the application of science, technology, and engineering to facilitate and accelerate the design, manufacture, and/or modification of genetic materials in living organisms to alter living or nonliving materials ". It is a field that has boomed since the early 2000s when in particular Jay Keasling showed that it was possible to efficiently synthetise a compound–artemisinic acid–which after a few more tricks then leads to an effective anti-malaria drug, artemisini

Concerted Action of Two Formins in Gliding Motility and Host Cell Invasion by Toxoplasma gondii

The invasive forms of apicomplexan parasites share a conserved form of gliding motility that powers parasite migration across biological barriers, host cell invasion and egress from infected cells. Previous studies have established that the duration and direction of gliding motility are determined by actin polymerization; however, regulators of actin dynamics in apicomplexans remain poorly characterized. In the absence of a complete ARP2/3 complex, the formin homology 2 domain containing proteins and the accessory protein profilin are presumed to orchestrate actin polymerization during host cell invasion. Here, we have undertaken the biochemical and functional characterization of two Toxoplasma gondii formins and established that they act in concert as actin nucleators during invasion. The importance of TgFRM1 for parasite motility has been assessed by conditional gene disruption. The contribution of each formin individually and jointly was revealed by an approach based upon the expression of dominant mutants with modified FH2 domains impaired in actin binding but still able to dimerize with their respective endogenous formin. These mutated FH2 domains were fused to the ligand-controlled destabilization domain (DD-FKBP) to achieve conditional expression. This strategy proved unique in identifying the non-redundant and critical roles of both formins in invasion. These findings provide new insights into how controlled actin polymerization drives the directional movement required for productive penetration of parasites into host cells

BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits

BACterial Hosts for production of Bioactive phenolics from bERRY fruits (BacHBerry) was a 3-year project funded by the Seventh Framework Programme (FP7) of the European Union that ran between November 2013 and October 2016. The overall aim of the project was to establish a sustainable and economically-feasible strategy for the production of novel high-value phenolic compounds isolated from berry fruits using bacterial platforms. The project aimed at covering all stages of the discovery and pre-commercialization process, including berry collection, screening and characterization of their bioactive components, identification and functional characterization of the corresponding biosynthetic pathways, and construction of Gram-positive bacterial cell factories producing phenolic compounds. Further activities included optimization of polyphenol extraction methods from bacterial cultures, scale-up of production by fermentation up to pilot scale, as well as societal and economic analyses of the processes. This review article summarizes some of the key findings obtained throughout the duration of the project

Data from: Cophylogeny Reconstruction via an Approximate Bayesian Computation

Despite an increasingly vast literature on cophylogenetic reconstructions for studying host-parasite associations, understanding the common evolutionary history of such systems remains a problem that is far from being solved. Most algorithms for host-parasite reconciliation use an event-based model, where the events include in general (a subset of) cospeciation, duplication, loss, and host switch. All known parsimonious event-based methods then assign a cost to each type of event in order to find a reconstruction of minimum cost. The main problem with this approach is that the cost of the events strongly influences the reconciliation obtained. Some earlier approaches attempt to avoid this problem by finding a Pareto set of solutions and hence by considering event costs under some minimisation constraints. To deal with this problem, we developed an algorithm, called \Coala, for estimating the frequency of the events based on an approximate Bayesian computation approach. The benefits of this method are twofold: (1) it provides more confidence in the set of costs to be used in a reconciliation, and (2) it allows estimation of the frequency of the events in cases where the dataset consists of trees with a large number of taxa. We evaluate our method on simulated and on biological datasets. We show that in both cases, for the same pair of host and parasite trees, different sets of frequencies for the events lead to equally probable solutions. Moreover, often these solutions differ greatly in terms of the number of inferred events. It appears crucial to take this into account before attempting any further biological interpretation of such reconciliations. More generally, we also show that the set of frequencies can vary widely depending on the input host and parasite trees. Indiscriminately applying a standard vector of costs may thus not be a good strategy