Evidence map›Paper›PMID 28703874›Full record

ArticleMicrobial biotechnology2017

The functional potential and active populations of the pit mud microbiome for the production of Chinese strong-flavour liquor.

Yong Tao, Xiang Wang, Xiangzhen Li, Na Wei, Hong Jin, Zhancheng Xu, Qinglan Tang, Xiaoyu Zhu

Open access · goldAbstract read
In one paragraph

Article in Microbial biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
9.3field-weighted citation impact, top 2% 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

32 citing papers in PubMed, 99 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

8 authors at 5 institutions in 1 country.

Yong TaoKey Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences & Environmental Microbiology Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Sichuan, 610041, China.
Xiang WangKey Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences & Environmental Microbiology Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Sichuan, 610041, China.
Xiangzhen LiKey Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences & Environmental Microbiology Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Sichuan, 610041, China.
Na WeiKey Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences & Environmental Microbiology Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Sichuan, 610041, China.
Hong JinChengdu Medical College, Chengdu, 610083, China.
Zhancheng XuThe National-recognized Enterprise Technology Center, Sichuan Jiannanchun Group Co. Ltd., Mianzhu, Sichuan, 618200, China.
Qinglan TangThe National-recognized Enterprise Technology Center, Sichuan Jiannanchun Group Co. Ltd., Mianzhu, Sichuan, 618200, China.
Xiaoyu ZhuKey Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences & Environmental Microbiology Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Sichuan, 610041, China.
Chinese Academy of Sciences · CNChengdu Institute of Biology · CNChengdu Medical College · CNFirst Automotive Works (China) · CNSichuan Research Center of New Materials · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The popular distilled Chinese strong-flavour liquor (CSFL) is produced by solid fermentation in the ground pit. Microbes inhabiting in the pit mud (PM) on the walls of the fermentation pit are responsible for the production of caproic acid (CA) that determines the quality of CSFL to a large degree. However, little is known about the active microbial populations and metabolic potential of the PM microbiome. Here, we investigated the overall metabolic features of the PM microbiome and its active microbial components by combining metagenomics and MiSeq-sequencing analyses of the 16S rRNA genes from DNA and RNA (cDNA). Results showed that prokaryotes were predominant populations in the PM microbiome, accounting for 95.3% of total metagenomic reads, while eukaryotic abundance was only 1.8%. The dominant prokaryotic phyla were Firmicutes, Euryarchaeota, Bacteroidetes, Actinobacteria and Proteobacteria, accounting for 48.0%, 19.0%, 13.5%, 2.5% and 2.1% of total metagenomic reads respectively. Most genes encoding putative metabolic pathways responsible for the putative CA production via chain elongation pathway were detected. This indicated that the PM microbiome owned functional potential for synthesizing CA from ethanol or lactate. Some key genes encoding enzymes involved in hydrogenotrophic and acetoclastic methanogenesis pathways were detected in the PM metagenome, suggesting the possible occurrence of interspecies hydrogen transfer between CA-producing bacteria and methanogens. The 16S rDNA and 16S rRNA profiles showed that the Clostridial cluster IV, Lactobacillus, Caloramator, Clostridium, Sedimentibacter, Bacteroides and Porphyromonas were active populations in situ, in which Clostridial cluster IV and Clostridium were likely involved in the CA production. This study improved our understandings on the active populations and metabolic pathways of the PM microbiome involved in the CA synthesis in the CSFL fermentation.

Indexed as

MicrobiotaAlcoholic BeveragesAluminum SilicatesBacteriaCaproatesChinaClayFermentationFlavoring AgentsAluminum SilicatesCaproatesClayFlavoring Agentshexanoic acid

Identifiers

PMID28703874
PMCPMC5658580
OpenAlexW2734486416

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.