Evidence map›Paper›PMID 39987219›Full record

ArticleBiotechnology for biofuels and bioproducts2025

Combining transcriptomic and metabolomic insights into carbohydrate utilization by Ruminiclostridium papyrosolvens DSM2782.

Mengcheng You, Zhenxing Ren, Letian Ye, Qiuyun Zhao, Ziyi Liu, Houhui Song, Chenggang Xu

Abstract read
In one paragraph

Article in Biotechnology for biofuels and bioproducts, 2025. 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.

  1. Article
  2. Review
  3. 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.

Mengcheng You *Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics & Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang Agriculture and Forestry University, Hangzhou, 311300, Zhejiang Province, China.
Zhenxing Ren *Institute of Applied Chemistry, Shanxi University, Taiyuan, 030006, Shanxi Province, China.
Letian YeLaboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics & Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang Agriculture and Forestry University, Hangzhou, 311300, Zhejiang Province, China.
Qiuyun ZhaoLaboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics & Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang Agriculture and Forestry University, Hangzhou, 311300, Zhejiang Province, China.
Ziyi LiuLaboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics & Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang Agriculture and Forestry University, Hangzhou, 311300, Zhejiang Province, China.
Houhui SongLaboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics & Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang Agriculture and Forestry University, Hangzhou, 311300, Zhejiang Province, China. songhh@zafu.edu.cn.
Chenggang XuLaboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics & Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology & College of Veterinary Medicine of Zhejiang Agriculture and Forestry University, Hangzhou, 311300, Zhejiang Province, China. xucg@zafu.edu.cn.

Funding

National Natural Science Foundation of China 32070045National Natural Science Foundation of China 32170053Natural Science Foundation of Zhejiang Province Z24C010001Science Development Foundation of Zhejiang A&F University 2022LFR065
6 · The paper itself

Abstract

backgroundLignocellulose is the most abundant renewable bioresource on earth, and its biodegradation and utilization would contribute to the sustainable development of the global environment. Ruminiclostridium papyrosolvens, an anaerobic, mesophilic, and cellulolytic bacterium, produces an enzymatic complex known as the cellulosome. As one of the most highly evolved species among Ruminiclostridium-type species, R. papyrosolvens is particularly relevant for understanding how cellulolytic clostridia modulate their biomass degradation mechanisms in response to diverse carbon sources.

resultsOur study investigates the transcriptional responses of Ruminiclostridium papyrosolvens to different carbon sources to understand its lignocellulose utilization. Using RNA-seq, we analyzed gene expression under glucose, cellobiose, xylan, cellulose, and corn stover, identifying distinct metabolic preferences and regulatory responses. We found significant gene expression changes under corn stover compared to other carbon sources, with enrichment in ABC transporters and cell growth pathways. CAZyme gene expression was regulated by TCSs, affecting sugar transporter systems. Metabolic profiling showed R. papyrosolvens produced more complex metabolites during corn stover fermentation, revealing its adaptability to various carbon sources and implications for metabolic engineering.

conclusionThis study not only uncovers the intricate response mechanisms of R. papyrosolvens to lignocellulose and its hydrolysates, but it also outlines the strategy for using R. papyrosolvens as a cellulolytic chassis in genetic engineering.

Indexed as

ABC transportersCAZymesMetabolomeRuminiclostridium papyrosolvensTranscriptomeTwo-component systems

Identifiers

PMID39987219
PMCPMC11847368

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.