Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Oct 31;9(2):e0071821.
doi: 10.1128/Spectrum.00718-21. Epub 2021 Sep 22.

Deciphering Succession and Assembly Patterns of Microbial Communities in a Two-Stage Solid-State Fermentation System

Affiliations

Deciphering Succession and Assembly Patterns of Microbial Communities in a Two-Stage Solid-State Fermentation System

Dengjin Shen et al. Microbiol Spectr. .

Abstract

Although the importance of microbiota in the natural environment and in industrial production has been widely recognized, little is known about the formation and succession patterns of the microbial community, particularly secondary succession after disturbance. Here, we choose the Xiaoqu liquor brewing process as an experimental model in which sorghum grains were first aerobically saccharified and then anaerobically fermented after being stirred and acidified to explore multistage community succession patterns. We analyzed microbial composition, physicochemical factors, and metabolites of brewing grains inoculated with two different starters, pure starter and traditional starter, respectively. Two groups showed similar succession patterns where the saccharification microbiota was mainly derived from starters, while environmental microorganisms, mainly Lactobacillaceae and Saccharomyces, dominated the fermentation microbiota regardless of the original saccharification community composition. Species replacement shaped the bacterial community, while species replacement and loss both contributed to fungal community succession in both groups. Grain acidification and hypoxia led to the succession of bacterial and fungal communities during fermentation, respectively. Despite inoculation with starters containing different microorganisms, similar microbial communities during the fermentation stage of the two groups exhibited similar metabolite composition. However, higher abundance of Rhizopus in the saccharification of the pure starter group led to more alcohols, while higher abundance of Monascus and Saccharomycopsis in the traditional starter group promoted acid and ester metabolism. These results revealed the microbial succession patterns of two-stage liquor brewing and its influence on flavor metabolism, which could be used to regulate the microbial community in food fermentation to further promote the modernization of the fermented food industry. IMPORTANCE Revealing formation and assembly mechanisms of microbiota can help us to understand and further regulate its roles in the ecosystems. The Xiaoqu liquor brewing system is a tractable microbial ecosystem with low complexity. This two-stage microbial ecosystem can be used as an experimental model to analyze the multistage temporal succession pattern of microbial communities. Our results demonstrated the dynamic composition and succession pattern of a microbial community in the two-stage liquor brewing system. The results also revealed the microbial origins determining community composition, the ecological processes dominating microbial community succession patterns, the determinants affecting microbial community successions, and the effect of microbial community changes on metabolite synthesis. Overall, our study not only provides an insight into multistage succession patterns of microbial communities in liquor brewing systems but also provides reference for optimizing the quality of fermented products, which will be helpful to understand the succession patterns of microbial communities in other natural ecosystems.

Keywords: Xiaoqu liquor; community assembly; community succession; nestedness; turnover.

PubMed Disclaimer

Figures

FIG 1
FIG 1
Schematic of the brewing process and sampling procedures of Chinese Xiaoqu light-flavor liquor. Starter powder, brewing grains, and fresh liquor were sampled in triplicate from pure starter (PS) batch and traditional starter (TS) batch. Grain samples were named by the combined information of the starter batch (P for PS batch, T for TS batch), brewing stage (SAC for saccharification stage, FER for fermentation stage), and sampling time points. Time units for saccharification and fermentation are indicated by “h” (hours) and “d” (days), respectively.
FIG 2
FIG 2
Dynamic changes of moisture (A), temperature (B), reducing sugar (C), acidity (D), pH (E), and ethanol (F) during the brewing process. The data are presented as means ± standard deviation (SD) (n = 3). A t test was conducted, with significant differences at three levels (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001).
FIG 3
FIG 3
Compositions and sources of the microbial community during the brewing process. (A) Bacterial community composition of the PS batch. (B) Bacterial community composition of the TS batch. (C) Fungal community composition of the PS batch. (D) Fungal community composition of the TS batch. Only the top 11 genera with the highest abundance are shown in the bar plots. (E) Relative abundance of bacteria from different sources. (F) Relative abundance of fungi from different sources.
FIG 4
FIG 4
Multistage community succession patterns during the brewing process. Jaccard distance matrix of the bacterial community in the PS batch (A) and TS batch (B) and that of the fungal community in the PS batch (C) and TS batch (D). Jaccard distance is partitioned into the component of turnover (species replacement) and nestedness (species loss). Lighter colors represent pairwise samples with less shared ASVs. βjac is the total Jaccard dissimilarity. βjtu is the turnover component of Jaccard dissimilarity. βjne is the nestedness component of Jaccard dissimilarity.
FIG 5
FIG 5
Ecological processes that generate the community succession patterns and corresponding determinants during the brewing process. (A) βNTI results of the bacterial community. (B) βNTI results of the fungal community. (C) RCbray results of the fungal community; βNTI > 2, variable selection; βNTI < −2, homogeneous selection; |βNTI| < 2, stochastic process; RCbray > 0.95, dispersal limitation; RCbray < −0.95, homogenizing dispersal; |RCbray| < 0.95, drift. βNTI is calculated within, but not between, each sampling time point. RCbray is calculated only when pairwise βNTI is insignificant (|βNTI| < 2). A linear regression model indicates that log-transformed reducing sugar (D), pH (E), and temperature (F) are correlated with a deterministic process during the saccharification stage, while log-transformed acidity (G) and temperature (H) are correlated with a deterministic process in the postfermentation stage.
FIG 6
FIG 6
(A) Heat map of relative abundance of metabolites in each stage. Redundancy analysis (RDA) of dominant microbes (red) at genus levels and flavor compounds (blue) in the PS group (B) and the TS group (C). Only relative abundances of microbes above 0.1% were considered to the dominant microbes. Flavor compounds were Z-score transformed.

Similar articles

Cited by

References

    1. Lozupone CA, Knight R. 2007. Global patterns in bacterial diversity. Proc Natl Acad Sci USA 104:11436–11440. doi:10.1073/pnas.0611525104. - DOI - PMC - PubMed
    1. Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, Prill RJ, Tripathi A, Gibbons SM, Ackermann G, Navas-Molina JA, Janssen S, Kopylova E, Vazquez-Baeza Y, Gonzalez A, Morton JT, Mirarab S, Zech Xu Z, Jiang L, Haroon MF, Kanbar J, Zhu Q, Jin Song S, Kosciolek T, Bokulich NA, Lefler J, Brislawn CJ, Humphrey G, Owens SM, Hampton-Marcell J, Berg-Lyons D, McKenzie V, Fierer N, Fuhrman JA, Clauset A, Stevens RL, Shade A, Pollard KS, Goodwin KD, Jansson JK, Gilbert JA, Knight R, Earth Microbiome Project Consortium. 2017. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551:457–463. doi:10.1038/nature24621. - DOI - PMC - PubMed
    1. Langenheder S, Lindstrom ES. 2019. Factors influencing aquatic and terrestrial bacterial community assembly. Environ Microbiol Rep 11:306–315. doi:10.1111/1758-2229.12731. - DOI - PubMed
    1. Costello EK, Stagaman K, Dethlefsen L, Bohannan BJ, Relman DA. 2012. The application of ecological theory toward an understanding of the human microbiome. Science 336:1255–1262. doi:10.1126/science.1224203. - DOI - PMC - PubMed
    1. Ferrenberg S, O’Neill SP, Knelman JE, Todd B, Duggan S, Bradley D, Robinson T, Schmidt SK, Townsend AR, Williams MW, Cleveland CC, Melbourne BA, Jiang L, Nemergut DR. 2013. Changes in assembly processes in soil bacterial communities following a wildfire disturbance. ISME J 7:1102–1111. doi:10.1038/ismej.2013.11. - DOI - PMC - PubMed

Publication types

Substances

LinkOut - more resources