Evidence map›Paper›PMID 32303548›Full record

ArticleApplied and environmental microbiology2020

A Bottom-Up Approach To Develop a Synthetic Microbial Community Model: Application for Efficient Reduced-Salt Broad Bean Paste Fermentation.

Yun Jia, Cheng-Tuo Niu, Zhen-Ming Lu, Xiao-Juan Zhang, Li-Juan Chai, Jin-Song Shi, Zheng-Hong Xu, Qi Li

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

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0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

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  18. Applied and environmental microbiology · 2024
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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

8 authors.

Yun JiaSchool of Biotechnology, Jiangnan University, Wuxi, People's Republic of China.
Cheng-Tuo NiuSchool of Biotechnology, Jiangnan University, Wuxi, People's Republic of China.
Zhen-Ming LuSchool of Biotechnology, Jiangnan University, Wuxi, People's Republic of China zmlu@jiangnan.edu.cn liqi@jiangnan.edu.cn.
Xiao-Juan ZhangNational Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi, People's Republic of China.
Li-Juan ChaiNational Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi, People's Republic of China.
Jin-Song ShiSchool of Pharmaceutical Science, Jiangnan University, Wuxi, People's Republic of China.
Zheng-Hong XuSchool of Biotechnology, Jiangnan University, Wuxi, People's Republic of China.
Qi LiSchool of Biotechnology, Jiangnan University, Wuxi, People's Republic of China zmlu@jiangnan.edu.cn liqi@jiangnan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans have used high salinity for the production of bean-based fermented foods over thousands of years. Although high salinity can inhibit the growth of harmful microbes and select functional microbiota in an open environment, it also affects fermentation efficiency of bean-based fermented foods and has a negative impact on people's health. Therefore, it is imperative to develop novel defined starter cultures for reduced-salt fermentation in a sterile environment. Here, we explored the microbial assembly and function in the fermentation of traditional Chinese broad bean paste with 12% salinity. The results revealed that the salinity and microbial interactions together drove the dynamic of community and pointed out that five dominant genera (

Indexed as

FermentationSalinityBacterial Physiological PhenomenaFood MicrobiologyFungiMicrobiotaModels, BiologicalVicia fabaChinese broad bean pastecommunity driving forcemicrobial community structuremicrobial functionsreconstruction of synthetic microbial community

Identifiers

PMID32303548
PMCPMC7267206

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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.