Evidence map›Paper›PMID 33579268›Full record

ArticleMicrobial cell factories2021

Inducing secondary metabolite production of Aspergillus sydowii through microbial co-culture with Bacillus subtilis.

Yu Sun, Wen-Cai Liu, Xuan Shi, Hai-Zhou Zheng, Zhi-Hui Zheng, Xin-Hua Lu, Yan Xing, Kai Ji, Mei Liu, Yue-Sheng Dong

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
6.5field-weighted citation impact, top 3% of its field
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

28 citing papers in PubMed, 58 citations in OpenAlex.

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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

10 authors at 2 institutions in 2 countries.

Yu SunSchool of Bioengineering, Dalian University of Technology, DalianLiaoning, 116024, China.
Wen-Cai LiuShandong New Time Pharmaceutical Co., Ltd, Shandong, 255000, China.
Xuan ShiSchool of Bioengineering, Dalian University of Technology, DalianLiaoning, 116024, China.
Hai-Zhou ZhengNew Drug Research and Development Center, North China Pharmaceutical Group Corporation and National Microbial Medicine Engineering and Research Center, Shijiazhuang, 050015, Hebei, China.
Zhi-Hui ZhengNew Drug Research and Development Center, North China Pharmaceutical Group Corporation and National Microbial Medicine Engineering and Research Center, Shijiazhuang, 050015, Hebei, China.
Xin-Hua LuNew Drug Research and Development Center, North China Pharmaceutical Group Corporation and National Microbial Medicine Engineering and Research Center, Shijiazhuang, 050015, Hebei, China.
Yan XingSchool of Bioengineering, Dalian University of Technology, DalianLiaoning, 116024, China.
Kai JiCAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
Mei LiuCAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China. lium@im.ac.cn.
Yue-Sheng DongSchool of Bioengineering, Dalian University of Technology, DalianLiaoning, 116024, China. yshdong@dlut.edu.cn.ORCID http://orcid.org/0000-0001-5010-6426
Dalian University of Technology · CNChinese Academy of Sciences · CN

Funding

National Natural Science Foundation of China 31670052Natural Science Foundation of Liaoning Province 2019-ZD-0143
6 · The paper itself

Abstract

backgroundThe co-culture strategy which mimics natural ecology by constructing an artificial microbial community is a useful tool to activate the biosynthetic gene clusters to generate new metabolites. However, the conventional method to study the co-culture is to isolate and purify compounds separated by HPLC, which is inefficient and time-consuming. Furthermore, the overall changes in the metabolite profile cannot be well characterized.

resultsA new approach which integrates computational programs, MS-DIAL, MS-FINDER and web-based tools including GNPS and MetaboAnalyst, was developed to analyze and identify the metabolites of the co-culture of Aspergillus sydowii and Bacillus subtilis. A total of 25 newly biosynthesized metabolites were detected only in co-culture. The structures of the newly synthesized metabolites were elucidated, four of which were identified as novel compounds by the new approach. The accuracy of the new approach was confirmed by purification and NMR data analysis of 7 newly biosynthesized metabolites. The bioassay of newly synthesized metabolites showed that four of the compounds exhibited different degrees of PTP1b inhibitory activity, and compound N2 had the strongest inhibition activity with an IC

conclusionsCo-culture led to global changes of the metabolite profile and is an effective way to induce the biosynthesis of novel natural products. The new approach in this study is one of the effective and relatively accurate methods to characterize the changes of metabolite profiles and to identify novel compounds in co-culture systems.

Indexed as

Secondary MetabolismAspergillusBacillus subtilisCoculture TechniquesAspergillus sydowiiBacillus subtilisCo-cultureNatural products

Identifiers

PMID33579268
PMCPMC7881642
OpenAlexW3114611635

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.