Biotyping Saccharomyces cerevisiae strains using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)

Identification of yeasts in fermented foods and beverages using MALDI-TOF MS

Yeasts are an important group of microorganisms and contribute to the fermentation of a broad range of foods and beverages spontaneously or as a starter culture. Rapid and reliable microbial species identification is essential to evaluate biodiversity in fermented foods and beverages. Nowadays, high-throughput omics technologies and bioinformatics tools produce large-scale molecular-level data in many fields. These omics technologies generate data at different expression levels and are used to identify microorganisms. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a powerful analytical technique in proteomic technology. It is a tool used to analyze the peptides or proteins of microorganisms for identification. MALDI-TOF MS has been used for the taxonomic identification of microorganisms as a fast, high-throughput, and cost-effective method. This review briefly discussed the application of MALDI-TOF MS in identifying yeasts in fermented foods and beverages.

Application of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for the Rapid Identification of Yeast Species From Polar Regions

Protein profiling based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has proved to be a powerful tool for yeast identification. However, it is rarely used in the identification of yeast isolates from polar regions, which may be due to the limited data available for the differentiation of polar yeast species. The present study constructed a supplementary database of MALDI-TOF MS, including 33 yeast species from the Arctic and Antarctica. These yeast species were used to assess the accuracy and practicality of MALDI-TOF MS-based identification compared to the ribosomal DNA [internal transcribed spacer (ITS) and large subunit (LSU) gene regions] sequencing identification. Their dendrogram based on main spectra profiles (MSPs) in the supplementary database was somewhat consistent with their phylogenetic tree. The accuracy of MALDI-TOF MS identification was also compared by the ethanol-formic acid extraction method and the on-plate extraction method. In addition, peptide markers of some yeast species (e.g., Glaciozyma, Phenoliferia, Mrakia, and Vishniacozyma) were identified. It is concluded that the MALDI-TOF MS method can differentiate some closely related yeast species from polar regions, thus is suitable for the identification of polar yeasts.

Predictive Potential of MALDI-TOF Analyses for Wine and Brewing Yeast

The potential of MALDI-TOF profiling for predicting potential applications of yeast strains in the beverage sector was assessed. A panel of 59 commercial yeasts (47 wine and 12 brewing yeasts) was used to validate the concept whereby 2 culture media (YPD agar and YPD broth), as well as two mass ranges m/z 500–4000 and m/z 2000–20,000, were evaluated for the best fit. Three machine learning-based algorithms, PCA, MDS, and UMAP, in addition to a hierarchical clustering method, were employed. Profiles derived from broth cultures yielded more peaks, but these were less well-defined compared with those from agar cultures. Hierarchical clustering more clearly resolved different species and gave a broad overview of potential strain utility, but more nuanced insights were provided by MDS and UMAP analyses. PCA-based displays were less informative. The potential of MALDI-TOF proteomics in predicting the utility of yeast strains of commercial benefit is supported in this study, provided appropriate approaches are used for data generation and analysis.

Application of MALDI-TOF analysis to reveal diversity and dynamics of winemaking yeast species in wild-fermented, organically produced, New Zealand Pinot Noir wine

Rapid yeast identification is of particular importance in monitoring wine fermentation and assessing strain application in winemaking. We used MALDI-TOF MS analysis supported by 26 S rRNA gene sequence analysis and Saccharomyces-specific PCR testing to differentiate reference and field strains recovered from organic wine production facilities in Waipara, New Zealand, in which Pinot Noir wine was produced by spontaneous fermentations in the vineyard and in the winery. Strains were isolated from each of four key stages of each ferment to evaluate changes in taxonomic diversity. MALDI-TOF MS analysis was confirmed as an excellent yeast identification method, with even closely related Saccharomyces species readily distinguished. A total of 13 indigenous species belonging to eight genera were identified from Pinot Noir ferments, with taxonomic diversity generally reducing as fermentation progressed. However, differences between the taxa recovered were observed between the vineyard and winery ferments, despite the grapes used being from the same batch. Furthermore, some consistent proteomic differences between strains of S. cerevisiae, Hanseniasporum uvarum, Candida californica, Pichia membranifaciens and Starmerella bacillaris correlated with the different fermentation systems used. The high speed, low cost, taxonomic resolution and ability to characterise subtle changes in phenotype that may result from variations in environmental conditions makes MALDI-TOF analysis an attractive tool for further and wider applications in the wine industry. Such applications may include monitoring wine fermentation to actively support the consistency of high-quality wine products, and potentially for the development of such products too.

Population Dynamics and Yeast Diversity in Early Winemaking Stages without Sulfites Revealed by Three Complementary Approaches

Nowadays, the use of sulfur dioxide (SO2) during the winemaking process is a controversial societal issue. In order to reduce its use, various alternatives are emerging, in particular bioprotection by adding yeasts, with different impacts on yeast microbiota in early winemaking stages. In this study, quantitative-PCR and metabarcoding high-throughput sequencing (HTS) were combined with MALDI-TOF-MS to monitor yeast population dynamic and diversity in the early stages of red winemaking process without sulfites and with bioprotection by Torulaspora delbrueckii and Metschnikowia pulcherrima addition. By using standard procedures for yeast protein extraction and a laboratory-specific database of wine yeasts, identification at species level of 95% of the isolates was successfully achieved by MALDI-TOF-MS, thus confirming that it is a promising method for wine yeast identification. The different approaches confirmed the implantation and the niche occupation of bioprotection leading to the decrease of fungal communities (HTS) and Hanseniaspora uvarum cultivable population (MALDI-TOF MS). Yeast and fungi diversity was impacted by stage of maceration and, to a lesser extent, by bioprotection and SO2, resulting in a modification of the nature and abundance of the operational taxonomic units (OTUs) diversity.

Occurrence of Yeasts in White-Brined Cheeses: Methodologies for Identification, Spoilage Potential and Good Manufacturing Practices

Yeasts are generally recognized as contaminants in the production of white-brined cheeses, such as Feta and Feta-type cheeses. The most predominant yeasts species are Debaryomyces hansenii, Geotrichum candidum, Kluyveromyces marxianus, Kluyveromyces lactis, Rhodotorula mucilaginosa, and Trichosporon spp. Although their spoilage potential varies at both species and strain levels, yeasts will, in case of excessive growth, present a microbiological hazard, effecting cheese quality. To evaluate the hazard and trace routes of contamination, the exact taxonomic classification of yeasts is required. Today, identification of dairy yeasts is mainly based on DNA sequencing, various genotyping techniques, and, to some extent, advanced phenotypic identification technologies. Even though these technologies are state of the art at the scientific level, they are only hardly implemented at the industrial level. Quality defects, caused by yeasts in white-brined cheese, are mainly linked to enzymatic activities and metabolism of fermentable carbohydrates, leading to production of metabolites (CO2, fatty acids, volatile compounds, amino acids, sulfur compounds, etc.) and resulting in off-flavors, texture softening, discoloration, and swelling of cheese packages. The proliferation of spoilage yeast depends on maturation and storage conditions at each specific dairy, product characteristics, nutrients availability, and interactions with the co-existing microorganisms. To prevent and control yeast contamination, different strategies based on the principles of HACCP and Good Manufacturing Practice (GMP) have been introduced in white-brined cheese production. These strategies include milk pasteurization, refrigeration, hygienic sanitation, air filtration, as well as aseptic and modified atmosphere packaging. Though a lot of research has been dedicated to yeasts in dairy products, the role of yeast contaminants, specifically in white-brined cheeses, is still insufficiently understood. This review aims to summarize the current knowledge on the identification of contaminant yeasts in white-brined cheeses, their occurrence and spoilage potential related to different varieties of white-brined cheeses, their interactions with other microorganisms, as well as guidelines used by dairies to prevent cheese contamination.

Mass Spectrometry: A Rosetta Stone to Learn How Fungi Interact and Talk

Fungi are a highly diverse group of heterotrophic organisms that play an important role in diverse ecological interactions, many of which are chemically mediated. Fungi have a very versatile metabolism, which allows them to synthesize a large number of still little-known chemical compounds, such as soluble compounds that are secreted into the medium and volatile compounds that are chemical mediators over short and long distances. Mass spectrometry (MS) is currently playing a dominant role in mycological studies, mainly due to its inherent sensitivity and rapid identification capabilities of different metabolites. Furthermore, MS has also been used as a reliable and accurate tool for fungi identification (i.e., biotyping). Here, we introduce the readers about fungal specialized metabolites, their role in ecological interactions and provide an overview on the MS-based techniques used in fungal studies. We particularly present the importance of sampling techniques, strategies to reduce false-positive identification and new MS-based analytical strategies that can be used in mycological studies, further expanding the use of MS in broader applications. Therefore, we foresee a bright future for mass spectrometry-based research in the field of mycology.

Toward a rapid method for the study of biodiversity in cold environments: the characterization of psychrophilic yeasts by MALDI-TOF mass spectrometry

To investigate the potential of matrix-assisted laser desorption ionization mass spectrometry (MALDI-TOF/MS) as a platform to support biodiversity and phylogenetic studies of psychrophilic yeasts in cold environments, the technique was employed to rapidly characterize and distinguish three psychrophilic yeasts (Rhodotorula mucilaginosa, Naganishia vishniacii, and Dioszegia cryoxerica) from three mesophilic counterparts (Saccharomyces cerevisiae Cry Havoc, S. cerevisiae California V Ale, and S. pastorianus). A detailed workflow for providing reproducible mass spectral fingerprints of low molecular weight protein/peptide features specific to the organisms studied is presented. The potential of this approach as a tool in the study of biodiversity, systematics, and phylogeny of psychrophilic microorganisms is highlighted.

Cell-Free Identification of S. cerevisiae Strains by Analysis of Supernatant Using LC-MS

Current literature shows a gap for methods which can identify yeast sub-species (strains or serovars) in samples where there are no viable cells remaining. Presented here is a technique for the analysis of yeast supernatant, including solid phase extraction, data-dependent acquisition liquid chromatography/mass spectrometry (LC-MS), and two chemometric methods to identify and classify yeast strains. Five strains of Saccharomyces cerevisiae were successfully identified in various stages of growth. In addition, peptide/protein identification was performed, without the need for additional data acquisition. Graphical Abstract ᅟ.

MALDI-TOF MS typing enables the classification of brewing yeasts of the genus Saccharomyces to major beer styles

Brewing yeasts of the genus Saccharomyces are either available from yeast distributor centers or from breweries employing their own “in-house strains”. During the last years, the classification and characterization of yeasts of the genus Saccharomyces was achieved by using biochemical and DNA-based methods. The current lack of fast, cost-effective and simple methods to classify brewing yeasts to a beer type, may be closed by Matrix Assisted Laser Desorption/Ionization–Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) upon establishment of a database based on sub-proteome spectra from reference strains of brewing yeasts. In this study an extendable “brewing yeast” spectra database was established including 52 brewing yeast strains of the most important types of bottom- and top-fermenting strains as well as beer-spoiling S. cerevisiae var. diastaticus strains. 1560 single spectra, prepared with a standardized sample preparation method, were finally compared against the established database and investigated by bioinformatic analyses for similarities and distinctions. A 100% separation between bottom-, top-fermenting and S. cerevisiae var. diastaticus strains was achieved. Differentiation between Alt and Kölsch strains was not achieved because of the high similarity of their protein patterns. Whereas the Ale strains show a high degree of dissimilarity with regard to their sub-proteome. These results were supported by MDS and DAPC analysis of all recorded spectra. Within five clusters of beer types that were distinguished, and the wheat beer (WB) cluster has a clear separation from other groups. With the establishment of this MALDI-TOF MS spectra database proof of concept is provided of the discriminatory power of this technique to classify brewing yeasts into different major beer types in a rapid, easy way, and focus brewing trails accordingly. It can be extended to yeasts for specialty beer types and other applications including wine making or baking.

Sugar cane spirit (cachaça): Effects of mixed inoculum of yeasts on the sensory and chemical characteristics

The main goal of this study was to produce cachaça using a mixed inoculum of Saccharomyces cerevisiae and Meyerozyma caribbica and characterize the produced beverage using HPLC, GC-FID, GC-MS and sensorial analysis. Additionally, the use of MALDI-TOF as a tool to characterize and monitor pure and mixed inocula fermenting sugar cane juice was also evaluated. Vat fermentations were carried out for three consecutive batches using autoclaved 16°Brix sugar cane juice fermented by a mixed inoculum of M. caribbica 10⁷ cells/mL and S. cerevisiae 10⁸ cells/mL. The cachaça produced by the mixed culture of M. caribbica and S. cerevisiae showed the highest concentration of volatile compounds associated with good sensory descriptors such as ethyl hexanoate (114.11μg/L), 2-phenylethyl acetate (2.77μg/L), a-terpineol (0.45μg/L), b-citronellol (2.47μg/L), and geraniol (0.24μg/L). This beverage consequently showed greater acceptance in the sensorial analysis for taste and aroma, especially by younger panelists. The feasibility of MALDI-TOF use under studied conditions was demonstrated by the comparison of the results obtained from yeast cultivation in YPD broth, YPD agar and sugar cane juice, showing that there was no interference of sugar cane juice in protein profile. The results obtained from MALDI-TOF analysis showed that the protein extraction directly from sugar cane juice under fermentation, without the traditional plating step, allowed the distinction between mixed and pure inocula even under different M. caribbica populations and Brix degrees.

MALDI-TOF MS based identification of food-borne yeast isolates

In this study, food-borne yeast isolates (n=96), comprising at least 33 species, were identified using MALDI-TOF MS and conventional methods (API ID 32 C and Phoenix Yeast ID). Discrepancies of both methods were resolved by sequencing the ITS1-5.8S-rRNA-ITS2 region. For ten isolates, mainly classified to Rhodotorula and Trichosporon species, no clear final species identification was possible. 62 isolates were correctly identified to species level using either MALDI-TOF MS or conventional tests. 15 isolates were misidentified when applying conventional assays. In contrary, no species misidentifications were observed after MALDI-TOF MS based classification. In return, 16 isolates were not identifiable after matching their protein fingerprints against MALDI Biotyper 4.0.0.1 library. MALDI TOF MS in-house database update clearly improved the identification. In conclusion, the presented data suggest that MALDI-TOF MS is an appropriate platform for reliable classification and identification of food-borne yeast isolates.

Evaluation of MALDI-TOF mass spectrometry for identification of environmental yeasts and development of supplementary database

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.