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<p>The impact of brewing materials on the spatial distribution of eukaryotic microbiota in pit muds (PMs) of Luzhou-flavor liquor was investigated using high-throughput sequencing of 18&#xa0;S rDNA amplicons to compare the differences in eukaryotic microbiota composition between PMs derived from three grains and five grains. Our findings revealed contrasting trends in the spatial distribution of microbiota structure between the two types of PMs, with the Chao1 index of eukaryotic microbiota in three-grain PMs being higher than that of five-grain PMs. Significant differences in relative abundance were observed among the various samples, including <i>Brettanomyces custersianus</i>, <i>Debaryomyces</i> sp., <i>Pichia fementans</i>, <i>Pichia</i> sp., <i>Naganishia</i> sp., <i>Saccharomyces selenospora</i>, <i>Saccharomyces cerevisiae</i>, and <i>Saccharomycopsis fibuligera</i> in yeast, and <i>Aspergillus fumatus</i>, <i>Aspergillus</i> sp., and <i>Penicillium chrysogenum</i> in mold. Linear discriminant analysis based on 14 dominant operational taxonomic units accurately classified all samples, indicating that our discriminant model can be utilized for quality control of microbiota in PMs. These results provide a foundation for precisely regulating the spatial distribution of fungal community structure and quality control by adjusting the composition of brewing raw materials.</p>

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Different brewing materials change the vertical distribution pattern of eukaryotic communities in Luzhou-flavor liquor pit muds

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月11日

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  • Mingyu Zhang,
  • Jinjin Li,
  • Yuanyuan Zhang,
  • Kaixin Wang,
  • Wenxuan Hou,
  • Chenxu Wang

摘要

The impact of brewing materials on the spatial distribution of eukaryotic microbiota in pit muds (PMs) of Luzhou-flavor liquor was investigated using high-throughput sequencing of 18 S rDNA amplicons to compare the differences in eukaryotic microbiota composition between PMs derived from three grains and five grains. Our findings revealed contrasting trends in the spatial distribution of microbiota structure between the two types of PMs, with the Chao1 index of eukaryotic microbiota in three-grain PMs being higher than that of five-grain PMs. Significant differences in relative abundance were observed among the various samples, including Brettanomyces custersianus, Debaryomyces sp., Pichia fementans, Pichia sp., Naganishia sp., Saccharomyces selenospora, Saccharomyces cerevisiae, and Saccharomycopsis fibuligera in yeast, and Aspergillus fumatus, Aspergillus sp., and Penicillium chrysogenum in mold. Linear discriminant analysis based on 14 dominant operational taxonomic units accurately classified all samples, indicating that our discriminant model can be utilized for quality control of microbiota in PMs. These results provide a foundation for precisely regulating the spatial distribution of fungal community structure and quality control by adjusting the composition of brewing raw materials.