The deletion of Schizosaccharomyces pombe decreased the production of flavor-related metabolites during traditional Baijiu fermentation

Daqu and environmental microbiota regulate fatty acid biosynthesis via driving the core microbiota in soy sauce aroma type liquor fermentation

Fatty acids are considered as important compounds for the aroma and taste of Chinese liquor. Revealing the core microbiota related with fatty acid biosynthesis and how they are influenced are essential to control fatty acids in spontaneous Chinese liquor fermentation. Herein, we identified the core microbiota related with fatty acid biosynthesis based on their microbial abundance, abundance and expression level of genes related with fatty acid biosynthesis, using high-throughput amplicon sequencing, metagenomic and metatranscriptomic analysis, respectively. Acetilactobacillus, Kroppenstedtia, Saccharomyces, Paecilomyces and Pichia were identified as the core microbiota (the criteria for identifying core microbiota: average relative abundance ≥1 %, average abundance of related genes >400 fragments per kilobase of transcript per million fragments mapped [FPKM], and expression level of related genes >1000 FPKM) related with fatty acid biosynthesis. SourceTracker analysis showed that Daqu mainly provided Kroppenstedtia (34.01 %) and Acetilactobacillus (3.31 %). Ground mainly provided Pichia (47.47 %), Saccharomyces (16.17 %) and Paecilomyces (8.55 %). Structural equation model revealed that Daqu and environmental microbiota drove the core microbiota (P < 0.05), and the core microbiota drove the biosynthesis of fatty acids (P < 0.05). This work revealed the important role of Daqu and environmental microbiota in fatty acid biosynthesis in liquor fermentation. It would benefit controlling fatty acids in liquor fermentation, and improving the liquor quality.

Application of the fission yeast Schizosaccharomyces pombe in human nutrition

Fission yeast Schizosaccharomyces pombe (S. pombe) is renowned as a powerful genetic model for deciphering cellular and molecular biological phenomena, including cell division, chromosomal events, stress responses, and human carcinogenesis. Traditionally, Africans use S. pombe to ferment the beer called 'Pombe', which continues to be consumed in many parts of Africa. Although not as widely utilized as the baker's yeast Saccharomyces cerevisiae, S. pombe has secured several niches in the food industry for human nutrition because of its unique metabolism. This review will explore three specific facets of human nutrition where S. pombe has made a significant impact: namely, in wine fermentation, animal husbandry and neutraceutical supplementation coenzyme Q10 production. Discussions focus on the current gaps in these areas, and the potential research advances useful for addressing future challenges. Overall, gaining a better understanding of S. pombe metabolism will strengthen production in these areas and potentially spearhead novel future applications.

Fermentation Characteristics, Microbial Compositions, and Predicted Functional Profiles of Forage Oat Ensiled with Lactiplantibacillus plantarum or Lentilactobacillus buchneri

This study aimed to investigate the effects of lactic acid bacteria (LAB) inoculants on the fermentation quality, microbial compositions, and predicted functional profiles of forage oat. The forage oat was inoculated with distilled water, Lentilactobacillus buchneri (LB), and Lactiplantibacillus plantarum (LP) as the control (CON), LB and LP treatments, respectively, and the addition of Lentilactobacillus buchneri (LB) or Lactiplantibacillus plantarum (LP) resulted in 1 × 106 colony-forming units/g of fresh weight. After 30 days of fermentation, the lowest pH (4.23) and the lowest content of ammoniacal nitrogen (NH3-N) in dry matter (DM, 4.39%) were observed in the LP treatment. Interestingly, there was a significant (p < 0.05) difference in lactic acid (LA) concentration among the three treatments. The LP treatment had the highest lactate concentration (7.49% DM). At the same time, a markedly (p < 0.05) elevated acetic acid (AA) concentration (2.48% DM) was detected in the LB treatment. The Shannon and Chao1 indexes of bacterial and fungal communities in all the silage samples decreased compared to those in the fresh materials (FM). Proteobacteria was the dominant phylum in the FM group and shifted from Proteobacteria to Firmicutes after ensiling. Lactobacillus (64.87%) and Weissella (18.93%) were the predominant genera in the CON, whereas Lactobacillus dominated the fermentation process in the LB (94.65%) and LP (99.60%) treatments. For the fungal community structure, the major genus was Apiotrichum (21.65% and 60.66%) in the FM and CON groups after 30 days of fermentation. Apiotrichum was the most predominant in the LB and LP treatments, accounting for 52.54% and 34.47%, respectively. The genera Lactococcus, Pediococcus, and Weissella were negatively associated with the LA content. The genus Ustilago and Bulleromyces were positively associated with the LA content. These results suggest that the addition of LAB regulated the microbial community in oat silage, which influenced the ensiling products, and LP was more beneficial for decreasing the pH and NH3-N and increasing the LA concentration than LB in forage oat silage.

Fungal Interactions Strengthen the Diversity-Functioning Relationship of Solid-State Fermentation Systems

Traditional fermentation processes are driven by complex fungal microbiomes. However, the exact means by which fungal diversity affects fermentation remains unclear. In this study, we systematically investigated the diversity of a fungal community and its functions during the multibatch Baijiu fermentation process. Metabolomics analysis showed that the metabolic profiles of the Baijiu were enhanced with an increase in the fermentation time, as determined from the characteristic volatile flavors. High-throughput sequencing technology revealed that the major fungal species involved in sauce-flavor Baijiu fermentation are Pichia sp. (41.75%, average relative abundance), Saccharomyces sp. (13.07%), thermophilic species (9.16%), Monascus sp. (6.80%), Aspergillus sp. (4.69%), Schizosaccharomyces sp. (3.76%), Thermomyces sp. (3.74%), and Zygosaccharomyces sp. (1.41%). In addition, the fungal diversity increased as the number of fermentation batches increased. Moreover, the increased fungal diversity contributed to the modularity of the fungal communities, wherein Pichia sp., Torulaspora sp., and Saccharomyces sp. maintained the stability of the fungal community. In addition, metatranscriptomics sequencing technologies were used to reconstruct the key metabolic pathways during fermentation, and it was found that the increased microbial diversity significantly promoted glucose-mediated carbon metabolism. Finally, functional gene analysis showed that functional microorganisms, such as Zygosaccharomyces and Pichia, can enhance fermentation as a result of the high expression of pyruvate decarboxylase and propanol-preferring alcohol dehydrogenase during the metabolism of pyruvate. These results indicate that fungal biodiversity can be exploited to enhance fermentation-based processes via network interactions and metabolism during multiple-batch fermentation. IMPORTANCE Biodiversity and network interactions act simultaneously on the microbial community structure in the Baijiu fermentation process, thereby rendering the microbiome dynamics challenging to manage and predict. Understanding the complex fermentation community and its relationship to community functions is therefore important in the context of developing improved fermentation biotechnology systems. Our work demonstrates that multiple-batch fermentation steps increase microbial diversity and promote community stability. Crucially, the enhanced modularity in the microbial network increases the metabolism of flavor compounds and ethanol. This study highlights the power of biodiversity and network interactions in regulating the function of the microbiome in food fermentation ecosystems.

A Computational Toolbox to Investigate the Metabolic Potential and Resource Allocation in Fission Yeast

The fission yeast, Schizosaccharomyces pombe, is a popular eukaryal model organism for cell division and cell cycle studies. With this extensive knowledge of its cell and molecular biology, S. pombe also holds promise for use in metabolism research and industrial applications. However, unlike the baker's yeast, Saccharomyces cerevisiae, a major workhorse in these areas, cell physiology and metabolism of S. pombe remain less explored. One way to advance understanding of organism-specific metabolism is construction of computational models and their use for hypothesis testing. To this end, we leverage existing knowledge of S. cerevisiae to generate a manually curated high-quality reconstruction of S. pombe's metabolic network, including a proteome-constrained version of the model. Using these models, we gain insights into the energy demands for growth, as well as ribosome kinetics in S. pombe. Furthermore, we predict proteome composition and identify growth-limiting constraints that determine optimal metabolic strategies under different glucose availability regimes and reproduce experimentally determined metabolic profiles. Notably, we find similarities in metabolic and proteome predictions of S. pombe with S. cerevisiae, which indicate that similar cellular resource constraints operate to dictate metabolic organization. With these cases, we show, on the one hand, how these models provide an efficient means to transfer metabolic knowledge from a well-studied to a lesser-studied organism, and on the other, how they can successfully be used to explore the metabolic behavior and the role of resource allocation in driving different strategies in fission yeast. IMPORTANCE Our understanding of microbial metabolism relies mostly on the knowledge we have obtained from a limited number of model organisms, and the diversity of metabolism beyond the handful of model species thus remains largely unexplored in mechanistic terms. Computational modeling of metabolic networks offers an attractive platform to bridge the knowledge gap and gain new insights into physiology of lesser-studied organisms. Here we showcase an example of successful knowledge transfer from the budding yeast Saccharomyces cerevisiae to a popular model organism in molecular and cell biology, fission yeast Schizosaccharomyces pombe, using computational models.

Insights into the ecology of Schizosaccharomyces species in natural and artificial habitats

The fission yeast genus Schizosaccharomyces contains important model organisms for biological research. In particular, S. pombe is a widely used model eukaryote. So far little is known about the natural and artificial habitats of species in this genus. Finding out where S. pombe and other fission yeast species occur and how they live in their habitats can promote better understanding of their biology. Here we investigate in which substrates S. pombe, S. octosporus, S. osmophilus and S. japonicus are present. To this end about 2100 samples consisting of soil, tree sap fluxes, fresh fruit, dried fruit, honey, cacao beans, molasses and other substrates were analyzed. Effective isolation methods that allow efficient isolation of the above mentioned species were developed. Based on the frequency of isolating different fission yeast species in various substrates and on extensive literature survey, conclusions are drawn on their ecology. The results suggest that the primary habitat of S. pombe and S. octosporus is honeybee honey. Both species were also frequently detected on certain dried fruit like raisins, mango or pineapple to which they could be brought by the honey bees during ripening or during drying. While S. pombe was regularly isolated from grape mash and from fermented raw cacao beans S. octosporus was never isolated from fresh fruit. The main habitat of S. osmophilus seems to be solitary bee beebread. It was rarely isolated from raisins. S. japonicus was mainly found in forest substrates although it occurs on fruit and in fruit fermentations, too.