Revealing the dynamics and mechanisms of bacterial interactions in cheese production with metabolic modelling.

Cheese taste and flavour properties result from complex metabolic processes occurring in microbial communities. A deeper understanding of such mechanisms makes it possible to improve both industrial production processes and end-product quality through the design of microbial consortia. In this work, we caracterise the metabolism of a three-species community consisting of Lactococcus lactis, Lactobacillus plantarum and Propionibacterium freudenreichii during a seven-week cheese production process. Using genome-scale metabolic models and omics data integration, we modeled and calibrated individual dynamics using monoculture experiments, and coupled these models to capture the metabolism of the community. This model accurately predicts the dynamics of the community, enlightening the contribution of each microbial species to organoleptic compound production. Further metabolic exploration revealed additional possible interactions between the bacterial species. This work provides a methodological framework for the prediction of community-wide metabolism and highlights the added value of dynamic metabolic modeling for the comprehension of fermented food processes.

Many interspecific chromosomal introgressions are highly prevalent in Holarctic Saccharomyces uvarum strains found in human-related fermentations.

In the last two decades, the extensive genome sequencing of strains belonging to the Saccharomyces genus has revealed the complex reticulated evolution of this group. Among the various evolutionary mechanisms described, the introgression of large chromosomal regions resulting from interspecific hybridization has recently shed light on Saccharomyces uvarum species. In this work we provide the de novo assembled genomes of four S. uvarum strains presenting more than 712 kb of introgressed loci inherited from both Saccharomyces eubayanus and Saccharomyces kudriavzevii species. In order to study the prevalence of such introgressions in a large population, we designed multiplexed PCR markers able to survey the inheritance of eight chromosomal regions. Our data confirm that introgressions are widely disseminated in Holarctic S. uvarum populations and are more frequently found in strains isolated from human-related fermentations. According to the origin of the strains (nature or cider- or wine-related processes), some loci are over-represented, suggesting their positive selection by human activity. Except for one locus located on chromosome 7, the introgressions present a low level of heterozygozity similar to that observed for nine neutral markers (microsatellites). Finally, most of the loci tested showed an expected Mendelian segregation after meiosis and can recombine with their chromosomal counterpart in S. uvarum. Copyright © 2017 John Wiley & Sons, Ltd.

Pantograph: A template-based method for genome-scale metabolic model reconstruction.

Genome-scale metabolic models are a powerful tool to study the inner workings of biological systems and to guide applications. The advent of cheap sequencing has brought the opportunity to create metabolic maps of biotechnologically interesting organisms. While this drives the development of new methods and automatic tools, network reconstruction remains a time-consuming process where extensive manual curation is required. This curation introduces specific knowledge about the modeled organism, either explicitly in the form of molecular processes, or indirectly in the form of annotations of the model elements. Paradoxically, this knowledge is usually lost when reconstruction of a different organism is started. We introduce the Pantograph method for metabolic model reconstruction. This method combines a template reaction knowledge base, orthology mappings between two organisms, and experimental phenotypic evidence, to build a genome-scale metabolic model for a target organism. Our method infers implicit knowledge from annotations in the template, and rewrites these inferences to include them in the resulting model of the target organism. The generated model is well suited for manual curation. Scripts for evaluating the model with respect to experimental data are automatically generated, to aid curators in iterative improvement. We present an implementation of the Pantograph method, as a toolbox for genome-scale model reconstruction, curation and validation. This open source package can be obtained from: http://pathtastic.gforge.inria.fr.

Draft Genome Sequence of Rhodosporidium toruloides CECT1137, an Oleaginous Yeast of Biotechnological Interest.

We report the sequencing of the basidiomycetous yeast Rhodosporidium toruloides CECT1137. The current assembly comprises 62 scaffolds, for a total size of ca. 20.45 Mbp and a G+C content of ca. 61.9%. The genome annotation predicts 8,206 putative protein-coding genes.

A Gondwanan imprint on global diversity and domestication of wine and cider yeast Saccharomyces uvarum.

In addition to Saccharomyces cerevisiae, the cryotolerant yeast species S. uvarum is also used for wine and cider fermentation but nothing is known about its natural history. Here we use a population genomics approach to investigate its global phylogeography and domestication fingerprints using a collection of isolates obtained from fermented beverages and from natural environments on five continents. South American isolates contain more genetic diversity than that found in the Northern Hemisphere. Moreover, coalescence analyses suggest that a Patagonian sub-population gave rise to the Holarctic population through a recent bottleneck. Holarctic strains display multiple introgressions from other Saccharomyces species, those from S. eubayanus being prevalent in European strains associated with human-driven fermentations. These introgressions are absent in the large majority of wild strains and gene ontology analyses indicate that several gene categories relevant for wine fermentation are overrepresented. Such findings constitute a first indication of domestication in S. uvarum.

Knowledge-based generalization of metabolic models.

Genome-scale metabolic model reconstruction is a complicated process beginning with (semi-)automatic inference of the reactions participating in the organism's metabolism, followed by many iterations of network analysis and improvement. Despite advances in automatic model inference and analysis tools, reconstruction may still miss some reactions or add erroneous ones. Consequently, a human expert's analysis of the model will continue to play an important role in all the iterations of the reconstruction process. This analysis is hampered by the size of the genome-scale models (typically thousands of reactions), which makes it hard for a human to understand them. To aid human experts in curating and analyzing metabolic models, we have developed a method for knowledge-based generalization that provides a higher-level view of a metabolic model, masking its inessential details while presenting its essential structure. The method groups biochemical species in the model into semantically equivalent classes based on the ChEBI ontology, identifies reactions that become equivalent with respect to the generalized species, and factors those reactions into generalized reactions. Generalization allows curators to quickly identify divergences from the expected structure of the model, such as alternative paths or missing reactions, that are the priority targets for further curation. We have applied our method to genome-scale yeast metabolic models and shown that it improves understanding by helping to identify both specificities and potential errors.

QTL dissection of Lag phase in wine fermentation reveals a new translocation responsible for Saccharomyces cerevisiae adaptation to sulfite.

Quantitative genetics and QTL mapping are efficient strategies for deciphering the genetic polymorphisms that explain the phenotypic differences of individuals within the same species. Since a decade, this approach has been applied to eukaryotic microbes such as Saccharomyces cerevisiae in order to find natural genetic variations conferring adaptation of individuals to their environment. In this work, a QTL responsible for lag phase duration in the alcoholic fermentation of grape juice was dissected by reciprocal hemizygosity analysis. After invalidating the effect of some candidate genes, a chromosomal translocation affecting the lag phase was brought to light using de novo assembly of parental genomes. This newly described translocation (XV-t-XVI) involves the promoter region of ADH1 and the gene SSU1 and confers an increased expression of the sulfite pump during the first hours of alcoholic fermentation. This translocation constitutes another adaptation route of wine yeast to sulfites in addition to the translocation VIII-t-XVI previously described. A population survey of both translocation forms in a panel of domesticated yeast strains suggests that the translocation XV-t-XVI has been empirically selected by human activity.

A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica.

BACKGROUND: Yarrowia lipolytica is an oleaginous yeast which has emerged as an important microorganism for several biotechnological processes, such as the production of organic acids, lipases and proteases. It is also considered a good candidate for single-cell oil production. Although some of its metabolic pathways are well studied, its metabolic engineering is hindered by the lack of a genome-scale model that integrates the current knowledge about its metabolism. RESULTS: Combining in silico tools and expert manual curation, we have produced an accurate genome-scale metabolic model for Y. lipolytica. Using a scaffold derived from a functional metabolic model of the well-studied but phylogenetically distant yeast S. cerevisiae, we mapped conserved reactions, rewrote gene associations, added species-specific reactions and inserted specialized copies of scaffold reactions to account for species-specific expansion of protein families. We used physiological measures obtained under lab conditions to validate our predictions. CONCLUSIONS: Y. lipolytica iNL895 represents the first well-annotated metabolic model of an oleaginous yeast, providing a base for future metabolic improvement, and a starting point for the metabolic reconstruction of other species in the Yarrowia clade and other oleaginous yeasts.

Mining the semantics of genome super-blocks to infer ancestral architectures.

The study of evolutionary mechanisms is made more and more accurate by the increase in the number of fully sequenced genomes. One of the main problems is to reconstruct plausible ancestral genome architectures based on the comparison of contemporary genomes. Current methods have largely focused on finding complete architectures for ancestral genomes, and, due to the computational difficulty of the problem, stop after a small number of equivalent minimal solutions have been found. Recent results suggest, however, that the set of minimum complete architectures is very large and heterogeneous. In fact these solutions are collections of conserved blocks, freely rearranged. In this paper, we identify these conserved super-blocks, using a new method of analysis of ancestral architectures that reconciles both breakpoint and rearrangement analyses, as well as respects biological constraints. The resulting algorithms permit the first reliable reconstruction of plausible ancestral architectures for several non-WGD yeasts simultaneously, a problem hitherto intractable due to the extensive map reshuffling of these species. See online Supplementary Material at www.liebertonline.com.

Unusual composition of a yeast chromosome arm is associated with its delayed replication.

The 11.3-Mb genome of the yeast Lachancea (Saccharomyces) kluyveri displays an intriguing compositional heterogeneity: a region of approximately 1 Mb, covering almost the whole left arm of chromosome C (C-left), has an average GC content of 52.9%, which is significantly higher than the 40.4% global GC content of the rest of the genome. This region contains the MAT locus, which remains normal in composition. The excess of GC base pairs affects both coding and noncoding sequences, and thus is not due to selective pressure acting on protein sequences. It leads to a strong codon usage bias and alters the amino acid composition of the 457 proteins encoded on C-left that do not show obvious bias for functional categories, or the presence of paralogs or orthologs of essential genes of Saccharomyces cerevisiae. They share significant synteny conservation with other species of the Saccharomycetaceae, and phylogenetic analysis indicates that C-left originates from a Lachancea species. In contrast, there is a complete absence of transposable elements in C-left, whereas 18 elements per megabase are distributed across the rest of the genome. Comparative hybridization of synchronized cells using high-density genome arrays reveals that C-left is replicated later during S phase than the rest of the genome. Two possible primary causes of this major compositional heterogeneity are discussed: an ancient hybridization of two related species with very distinct GC composition, or an intrinsic mechanism, possibly associated with the loss of the silent cassettes from C-left that progressively increased the GC content and generated the delayed replication of this chromosomal arm.

Exploratory simulation of cell ageing using hierarchical models.

Thorough knowledge of the model organism S. cerevisiae has fueled efforts in developing theories of cell ageing since the 1950s. Models of these theories aim to provide insight into the general biological processes of ageing, as well as to have predictive power for guiding experimental studies such as cell rejuvenation. Current efforts in in silico modeling are frustrated by the lack of efficient simulation tools that admit precise mathematical models at both cell and population levels simultaneously. We developed a novel hierarchical simulation tool that allows dynamic creation of entities while rigorously preserving the mathematical semantics of the model. We used it to expand a single-cell model of protein damage segregation to a cell population model that explicitly tracks mother-daughter relations. Large-scale exploration of the resulting tree of simulations established that daughters of older mothers show a rejuvenation effect, consistent with experimental results. The combination of a single-cell model and a simulation platform permitting parallel composition and dynamic node creation has proved to be an efficient tool for in silico exploration of cell behavior.

A systematic nomenclature of chromosomal elements for hemiascomycete yeasts.

We present a compact, stable, unambiguous and extensible nomenclature for unique chromosomal elements from genomic DNA, developed to meet the increasing need created by the increasing number of yeast sequencing projects. Our proposal, adopted for use in the Génolevures project, is specifically designed to facilitate basic tasks in comparative genomics.