Evidence map›Paper›PMID 32694129›Full record

ArticlemSystems2020

Temperature-Induced Annual Variation in Microbial Community Changes and Resulting Metabolome Shifts in a Controlled Fermentation System.

Shilei Wang, Wu Xiong, Yuqiao Wang, Yao Nie, Qun Wu, Yan Xu, Stefan Geisen

Abstract read
In one paragraph

Article in mSystems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
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  3. Unraveling flavor formation inFood chemistry: X · 2025
    Review
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  18. Article
  19. Eco-Evolutionary Dynamics in Microbial Communities from Spontaneous Fermented Foods.International journal of environmental research and public health · 2021
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shilei Wang *State Key Laboratory of Food Science and Technology, Synergetic Innovation Center of Food Safety and Nutrition, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, China.
Wu Xiong *Department of Biology, Utrecht University, Utrecht, The Netherlands.
Yuqiao WangState Key Laboratory of Food Science and Technology, Synergetic Innovation Center of Food Safety and Nutrition, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, China.
Yao NieState Key Laboratory of Food Science and Technology, Synergetic Innovation Center of Food Safety and Nutrition, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, China.
Qun WuState Key Laboratory of Food Science and Technology, Synergetic Innovation Center of Food Safety and Nutrition, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, China wuq@jiangnan.edu.cn yxu@jiangnan.edu.cn stefan.geisen@wur.nl.ORCID https://orcid.org/0000-0001-6756-196X
Yan XuState Key Laboratory of Food Science and Technology, Synergetic Innovation Center of Food Safety and Nutrition, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, China wuq@jiangnan.edu.cn yxu@jiangnan.edu.cn stefan.geisen@wur.nl.
Stefan GeisenLaboratory of Nematology, Wageningen University, Wageningen, The Netherlands wuq@jiangnan.edu.cn yxu@jiangnan.edu.cn stefan.geisen@wur.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We are rapidly increasing our understanding on the spatial distribution of microbial communities. However, microbial functioning, as well as temporal differences and mechanisms causing microbial community shifts, remains comparably little explored. Here, using Chinese liquor fermentation as a model system containing a low microbial diversity, we studied temporal changes in microbial community structure and functioning. For that, we used high-throughput sequencing to analyze the composition of bacteria and fungi and analyzed the microbially derived metabolome throughout the fermentation process in all four seasons in both 2018 and 2019. We show that microbial communities and the metabolome changed throughout the fermentation process in each of the four seasons, with metabolome diversity increasing throughout the fermentation process. Across seasons, bacterial and fungal communities as well as the metabolome driven by 10 indicator microorganisms and six metabolites varied even more. Daily average temperature in the external surroundings was the primary determinant of the observed temporal microbial community and metabolome changes. Collectively, our work reveals critical insights into patterns and processes determining temporal changes of microbial community composition and functioning. We highlight the importance of linking taxonomic to functional changes in microbial ecology to enable predictions of human-relevant applications.

Indexed as

fermentation systemmicrobiomeseasonal factorstemperature-induced

Identifiers

PMID32694129
PMCPMC7566281

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.