Phenotypic and genotypic diversity of wine yeasts used for acidic musts

The aim of this study was to examine the physiological and genetic stability of the industrial wine yeasts Saccharomyces cerevisiae and Saccharomyces bayanus var. uvarum under acidic stress during fermentation. The yeasts were sub-cultured in aerobic or fermentative conditions in media with or without l-malic acid. Changes in the biochemical profiles, karyotypes, and mitochondrial DNA profiles were assessed after minimum 50 generations. All yeast segregates showed a tendency to increase the range of compounds used as sole carbon sources. The wild strains and their segregates were aneuploidal or diploidal. One of the four strains of S. cerevisiae did not reveal any changes in the electrophoretic profiles of chromosomal and mitochondrial DNA, irrespective of culture conditions. The extent of genomic changes in the other yeasts was strain-dependent. In the karyotypes of the segregates, the loss of up to 2 and the appearance up to 3 bands was noted. The changes in their mtDNA patterns were much broader, reaching 5 missing and 10 additional bands. The only exception was S. bayanus var. uvarum Y.00779, characterized by significantly greater genome plasticity only under fermentative stress. Changes in karyotypes and mtDNA profiles prove that fermentative stress is the main driving force of the adaptive evolution of the yeasts. l-malic acid does not influence the extent of genomic changes and the resistance of wine yeasts exhibiting increased demalication activity to acidic stress is rather related to their ability to decompose this acid. The phenotypic changes in segregates, which were found even in yeasts that did not reveal deviations in their DNA profiles, show that phenotypic characterization may be misleading in wine yeast identification. Because of yeast gross genomic diversity, karyotyping even though it does not seem to be a good discriminative tool, can be useful in determining the stability of wine yeasts. Restriction analysis of mitochondrial DNA appears to be a more sensitive method allowing for an early detection of genotypic changes in yeasts. Thus, if both of these methods are applied, it is possible to conduct the quick routine assessment of wine yeast stability in pure culture collections depositing industrial strains

Balancing user interaction and control in BNSL

Editors: Legrand, P., Corsini, M.-M., Hao, J.-K., Monmarché, N., Lutton, E., Schoenauer, M. (Eds.)International audienceIn this paper we present a study based on an evolutionary framework to explore what would be a reasonable compromise between interaction and automated optimisation in finding possible solutions for a complex problem, namely the learning of Bayesian network structures, an NP-hard problem where user knowledge can be crucial to distinguish among solutions of equal fitness but very different physical meaning. Even though several classes of complex problems can be effectively tackled with Evolutionary Computation, most possess qualities that are difficult to directly encode in the fitness function or in the individual's genotype description. Expert knowledge can sometimes be used to integrate the missing information, but new challenges arise when searching for the best way to access it: full human interaction can lead to the well-known problem of user-fatigue, while a completely automated evolutionary process can miss important contributions by the expert. For our study, we developed a GUI-based prototype application that lets an expert user guide the evolution of a network by alternating between fully-interactive and completely automatic steps. Preliminary user tests were able to show that despite still requiring some improvements with regards to its efficiency, the proposed approach indeed achieves its goal of delivering satisfying results for an expert user