Dynamic study of yeast species and Saccharomyces cerevisiae strains during the spontaneous fermentations of Muscat blanc in Jingyang, China
College of Enology, Northwest A & F University, Yangling 712100, Shaanxi, China. Food Microbiology
(Impact Factor: 3.33).
04/2013; 33(2):172-7. DOI: 10.1016/j.fm.2012.09.014
The evolution of yeast species and Saccharomyces cerevisiae genotypes during spontaneous fermentations of Muscat blanc planted in 1957 in Jingyang region of China was followed in this study. Using a combination of colony morphology on Wallerstein Nutrient (WLN) medium, sequence analysis of the 26S rDNA D1/D2 domain and 5.8S-ITS-RFLP analysis, a total of 686 isolates were identified at the species level. The six species identified were S. cerevisiae, Hanseniaspora uvarum, Hanseniaspora opuntiae, Issatchenkia terricola, Pichia kudriavzevii (Issatchenkia orientalis) and Trichosporon coremiiforme. This is the first report of T. coremiiforme as an inhabitant of grape must. Three new colony morphologies on WLN medium and one new 5.8S-ITS-RFLP profile are described. Species of non-Saccharomyces, predominantly H. opuntiae, were found in early stages of fermentation. Subsequently, S. cerevisiae prevailed followed by large numbers of P. kudriavzevii that dominated at the end of fermentations. Six native genotypes of S. cerevisiae were determined by interdelta sequence analysis. Genotypes III and IV were predominant. As a first step in exploring untapped yeast resources of the region, this study is important for monitoring the yeast ecology in native fermentations and screening indigenous yeasts that will produce wines with regional characteristics.
Available from: Braulio Esteve-Zarzoso
- "Wine fermentation is an ecologically complex process, and it is widely accepted that the yeast population changes as the fermentation proceeds (Fleet, 2008; Wang and Liu, 2013). Yeast species play important roles in the wine-making processes: transforming sugar to ethanol, producing specific secondary metabolites, and finally, contributing to wine flavor characteristics. "
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ABSTRACT: Various molecular approaches have been applied as culture-independent techniques to monitor wine fermentations over the last decade. Among them, those based on RNA detection have been widely used for yeast cell detection, assuming that RNA only exists in live cells. Fluorescence in situ hybridization (FISH) targeting intracellular rRNA is considered a promising technique for the investigation of wine ecology. For the present study, we applied the FISH technique in combination with epifluorescence microscopy and flow cytometry to directly quantify populations of Saccharomyces cerevisiae, Hanseniaspora uvarum, and Starmerella bacillaris during alcoholic fermentations. A new specific probe that hybridizes with eight species of Hanseniaspora genus and a second probe specific for Starm. bacillaris were designed, and the conditions for their application to pure cultures, mixed cultures, and wine samples were optimized. Single and mixed fermentations were performed with natural, concentrated must at two different temperatures, 15°C and 25°C. The population dynamics revealed that the Sacch. cerevisiae population increased to 10(7)-10(8)cells/ml during all fermentations, whereas H. uvarum and Starm. bacillaris tended to increase in single fermentations but remained at levels similar to their inoculations at 10(6)cells/ml in mixed fermentations. Temperature mainly affected the fermentation duration (slower at the lower temperature) but did not affect the population sizes of the different species. The use of these probes in natural wine fermentations has been validated.
International Journal of Food Microbiology 08/2014; 191C:1-9. DOI:10.1016/j.ijfoodmicro.2014.08.014 · 3.08 Impact Factor
Available from: Yue Sun
- "Yeast growth was analyzed by enumeration of viable cells using the classical plate count method. Aliquots of 0.1 ml from serially diluted samples were spread on WLN agar (Pallmann et al. 2001) in triplicate, supplemented with 100 mg l −1 chloramphenicol (Wang and Liu 2013) to inhibit bacterial growth. Colonies were counted, recorded and sorted into different phenotypes after incubation at 28 °C for 5 days. "
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ABSTRACT: Mixed inoculation of Saccharomyces cerevisiae strains is used in winemaking for achieving high sensory quality of the wine. However, information on the diversity and population of yeasts during inoculated fermentation is very limited. In this study, we evaluated the effect of mixed inocula with different inoculation timing on the yeast commu-nity during fermentations of Cabernet Sauvignon. Grape must was inoculated with pure cultures of S. cerevisiae RC212 or S. cerevisiae R312, and simultaneous and sequential inocula-tion of both strains. Wallersterin Laboratory Nutrient (WLN) medium and sequence of the 26S rDNA D1/D2 domain were used to compare the diversity of yeast species. Five species, including Candida diversa, Hanseniaspora opuntiae, H. uvarum, Issatchenkia orientalis and I. terricola, were identified in the grape must, with Issatchenkia sp. being predominant (67.5 %). Three to four species were involved in each fermentation treatment. The fermentations by mixed inocula presented more yeast species than by pure inocula. Interdelta sequence typing was used to identify S. cerevisiae strains. Ten genotypes were identified among 322 isolated S. cerevisiae strains. Their distribution varied among different stages of fermentations and different inoculation treatments. The inoculated strains were not predominant, while indige-nous genotypes I, III, and V showed strong competitiveness during fermentation. In general, this study provided informa-tion on the change of population structure and genetic diversity of yeasts in fermentations inoculated with pure and mixed S. cerevisiae strains.
Annals of Microbiology 08/2014; 65(2). DOI:10.1007/s13213-014-0934-8 · 0.99 Impact Factor
- "opuntiae and H. uvarum) could not be distinguished one from each other by ITS-RFLP using the three endonucleases chosen (Table 2). Wang and Liu (2013) solved this problem by employing endonucleases MboII and DdeI. In the present study, MS was sufficient to designate the correct species by protein profiling. "
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ABSTRACT: Yeast identification using traditional methods which employ morphological, physiological, and biochemical characteristics can be considered a hard task as it requires experienced microbiologists and a rigorous control in culture conditions that could implicate in different outcomes. Considering clinical or industrial applications, the fast and accurate identification of microorganisms is a crescent demand. Hence, molecular biology approaches has been extensively used and, more recently, protein profiling using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has proved to be an even more efficient tool for taxonomic purposes. Nonetheless, concerning to mass spectrometry, data available for the differentiation of yeast species for industrial purpose is limited and reference databases commercially available comprise almost exclusively clinical microorganisms. In this context, studies focusing on environmental isolates are required to extend the existing databases. The development of a supplementary database and the assessment of a commercial database for taxonomic identifications of environmental yeast are the aims of this study. We challenge MALDI-TOF MS to create protein profiles for 845 yeast strains isolated from grape must and 67.7 % of the strains were successfully identified according to previously available manufacturer database. The remaining 32.3 % strains were not identified due to the absence of a reference spectrum. After matching the correct taxon for these strains by using molecular biology approaches, the spectra concerning the missing species were added in a supplementary database. This new library was able to accurately predict unidentified species at first instance by MALDI-TOF MS, proving it is a powerful tool for the identification of environmental yeasts.
Applied Microbiology and Biotechnology 04/2014; 98(12). DOI:10.1007/s00253-014-5686-7 · 3.34 Impact Factor
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