Evaluation of microbial diversity in the pilot-scale beer brewing process by culture-dependent and culture-independent method

When FLOW-FISH met FACS: Combining multiparametric, dynamic approaches for microbial single-cell research in the total environment

In environmental microbiology, the ability to assess, in a high-throughput way, single-cells within microbial communities is key to understand their heterogeneity. Fluorescence in situ hybridization (FISH) uses fluorescently labeled oligonucleotide probes to detect, identify, and quantify single cells of specific taxonomic groups. The combination of Flow Cytometry (FLOW) with FISH (FLOW-FISH) enables high-throughput quantification of complex whole cell populations, which when associated with fluorescence-activated cell sorting (FACS) enables sorting of target microorganisms. These sorted cells may be investigated in many ways, for instance opening new avenues for cytomics at a single-cell scale. In this review, an overview of FISH and FLOW methodologies is provided, addressing conventional methods, signal amplification approaches, common fluorophores for cell physiology parameters evaluation, and model variation techniques as well. The coupling of FLOW-FISH-FACS is explored in the context of different downstream applications of sorted cells. Current and emerging applications in environmental microbiology to outline the interactions and processes of complex microbial communities within soil, water, animal microbiota, polymicrobial biofilms, and food samples, are described.

Mixed-Culture Metagenomics of the Microbes Making Sour Beer

Mixed microbial cultures create sour beers but many brewers do not know which microbes comprise their cultures. The objective of this work was to use deep sequencing to identify microorganisms in sour beers brewed by spontaneous and non-spontaneous methods. Twenty samples were received from brewers, which were processed for microbiome analysis by next generation sequencing. For bacteria, primers were used to amplify the V3-V4 region of the 16S rRNA gene; fungal DNA detection was performed using primers to amplify the entire internal transcribed spacer region. The sequencing results were then used for taxonomy assignment, sample composition, and diversity analyses, as well as nucleotide BLAST searching. We identified 60 genera and 140 species of bacteria, of which the most prevalent were Lactobacillus acetotolerans, Pediococcus damnosus, and Ralstonia picketti/mannitolilytica. In fungal identification, 19 genera and 26 species were found, among which the most common yeasts were Brettanomyces bruxellensis and Saccharomyces cerevisiae. In some cases, genetic material from more than 60 microorganisms was found in a single sample. In conclusion, we were able to determine the microbiomes of various mixed cultures used to produce beer, providing useful information to better understand the sour beer fermentation process and brewing techniques.

A review of the analytical methods used for beer ingredient and finished product analysis and quality control

Beer is an incredibly complex beverage containing more than 3000 different compounds, including carbohydrates, proteins, ions, microbes, organic acids, and polyphenols, among others. Beer becomes even more complex during storage, for over time it may undergo chemical changes that negatively affect the flavor, aroma, and appearance. Thus, it can be expected that maintaining the quality of beer throughout its lifetime is a difficult task. Since it is such a popular drink throughout the world, being familiar with proper analytical techniques for beer evaluation is useful for researchers and brewers. These techniques include, but are not limited to, gas chromatography, liquid chromatography, matrix assisted laser desorption/ionization, capillary electrophoresis, mass spectrometry, ultraviolet-visible spectroscopy, and flame ionization detection. This review aims to summarize the various ingredients and components of beer, discuss how they affect the finished product, and present some of the analytical methods used for quality control and understanding the formation of chemicals in beer during the brewing process.

Current insights into fungal species diversity and perspective on naming the environmental DNA sequences of fungi

The global bio-diversity of fungi has been extensively investigated and their species number has been estimated. Notably, the development of molecular phylogeny has revealed an unexpected fungal diversity and utilisation of culture-independent approaches including high-throughput amplicon sequencing has dramatically increased number of fungal operational taxonomic units. A number of novel taxa including new divisions, classes, orders and new families have been established in last decade. Many cryptic species were identified by molecular phylogeny. Based on recently generated data from culture-dependent and -independent survey on same samples, the fungal species on the earth were estimated to be 12 (11.7-13.2) million compared to 2.2-3.8 million species recently estimated by a variety of the estimation techniques. Moreover, it has been speculated that the current use of high-throughput sequencing techniques would reveal an even higher diversity than our current estimation. Recently, the formal classification of environmental sequences and permission of DNA sequence data as fungal names' type were proposed but strongly objected by the mycologist community. Surveys on fungi in unusual niches have indicated that many previously regarded "unculturable fungi" could be cultured on certain substrates under specific conditions. Moreover, the high-throughput amplicon sequencing, shotgun metagenomics and a single-cell genomics could be a powerful means to detect novel taxa. Here, we propose to separate the fungal types into physical type based on specimen, genome DNA (gDNA) type based on complete genome sequence of culturable and uncluturable fungal specimen and digital type based on environmental DNA sequence data. The physical and gDNA type should have priority, while the digital type can be temporal supplementary before the physical type and gDNA type being available. The fungal name based on the "digital type" could be assigned as the "clade" name + species name. The "clade" name could be the name of genus, family or order, etc. which the sequence of digital type affiliates to. Facilitating future cultivation efforts should be encouraged. Also, with the advancement in knowledge of fungi inhabiting various environments mostly because of rapid development of new detection technologies, more information should be expected for fungal diversity on our planet.

Evaluation of method bias for determining bacterial populations in bacterial community analyses

Various methods are used for analyzing a bacterial community. We recently developed a method for quantifying each bacterium constituting the microbiota by combining a next-generation sequencing (NGS) analysis with a quantitative polymerase chain reaction (NGS-qPCR) assay. Our NGS-qPCR method is useful for analyzing a comprehensive bacterial community because it is enables the easy calculation of the amounts of each bacterium constituting the microbiota. However, it has not been confirmed whether the estimated bacterial community obtained using this NGS-qPCR method corresponds to the results obtained using conventional methods. Accordingly, we prepared model bacterial community samples and analyzed them by several methods (NGS-qPCR, species-specific qPCR, flow cytometry, total direct counting by epifluorescent microscopy [TDC], and plate count). The total bacterial cell densities determined by the PCR-based methods were largely consistent with those determined by the TDC method. There was a difference between the amounts of each bacterium analyzed by NGS-qPCR and species-specific qPCR, although the same trend was shown by both species-specific qPCR and NGS-qPCR. Our findings also demonstrated that there is a strong positive correlation between the cell densities of a specific bacterial group in craft beer samples determined by group-specific qPCR and NGS-qPCR, and there were no significant differences among quantification methods (we tested two bacterial groups: lactic acid bacteria and acetic acid bacteria). Thus, the NGS-qPCR method is a practical method for analyzing a comprehensive bacterial community based on a bacterial cell density.