Evidence map›Paper›PMID 39152233›Full record

ArticleCommunications chemistry2024

Activity-based metaproteomics driven discovery and enzymological characterization of potential α-galactosidases in the mouse gut microbiome.

Jianbing Jiang, Diana Czuchry, Yanxia Ru, Huipai Peng, Junfeng Shen, Teng Wang, Wenjuan Zhao, Weihua Chen, Sen-Fang Sui, Yaowang Li and 1 more

Abstract read
In one paragraph

Article in Communications chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

11 authors.

Jianbing Jiang *Institute for Inheritance-Based Innovation of Chinese Medicine, School of Pharmacy, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518055, China.ORCID http://orcid.org/0000-0003-4792-8140
Diana Czuchry *Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Yanxia Ru *School of Life Sciences, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China.
Huipai Peng *Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Junfeng ShenKey Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Teng WangKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.
Wenjuan ZhaoKey Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Weihua ChenKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.ORCID http://orcid.org/0000-0003-2168-6147
Sen-Fang SuiSchool of Life Sciences, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China.ORCID http://orcid.org/0000-0001-5253-2592
Yaowang LiSchool of Life Sciences, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China. liyw@sustech.edu.cn.ORCID http://orcid.org/0000-0003-2006-5971
Nan LiKey Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. nan.li@siat.ac.cn.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32271501Natural Science Foundation of Guangdong Province (Guangdong Natural Science Foundation) 2018A030310035Shenzhen Science and Technology Innovation Commission JCYJ20180302145723601
6 · The paper itself

Abstract

The gut microbiota offers an extensive resource of enzymes, but many remain uncharacterized. To distinguish the activities of similar annotated proteins and mine the potentially applicable ones in the microbiome, we applied an effective Activity-Based Metaproteomics (ABMP) strategy using a specific activity-based probe (ABP) to screen the entire gut microbiome for directly discovering active enzymes and their potential applications, not for exploring host-microbiome interactions. By using an activity-based cyclophellitol aziridine probe specific to α-galactosidases (AGAL), we successfully identified and characterized several gut microbiota enzymes possessing AGAL activities. Cryo-electron microscopy analysis of a newly characterized enzyme (AGLA5) revealed the covalent binding conformations between the AGAL5 active site and the cyclophellitol aziridine ABP, which could provide insights into the enzyme's catalytic mechanism. The four newly characterized AGALs have diverse potential activities, including raffinose family oligosaccharides (RFOs) hydrolysis and enzymatic blood group transformation. Collectively, we present a ABMP platform that facilitates gut microbiota AGALs discovery, biochemical activity annotations and potential industrial or biopharmaceutical applications.

Identifiers

PMID39152233
PMCPMC11329505

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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.