Evidence map›Paper›PMID 41676019›Full record

ReviewQuantitative biology (Beijing, China)2024

Constructing efficient bacterial cell factories to enable one-carbon utilization based on quantitative biology: A review.

Yazhen Song, Chenxi Feng, Difei Zhou, Zengxin Ma, Lian He, Cong Zhang, Guihong Yu, Yan Zhao, Song Yang, Xinhui Xing

Abstract readReview
In one paragraph

Review in Quantitative biology (Beijing, China), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Yazhen SongSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Chenxi FengSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Difei ZhouSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Zengxin MaSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Lian HeDepartment of Chemical Engineering University of Washington Seattle Washington USA.
Cong ZhangSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Guihong YuSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Yan ZhaoSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Song YangSchool of Life Sciences Shandong Province Key Laboratory of Applied Mycology, and Qingdao International Center on Microbes Utilizing Biogas Qingdao Agricultural University Qingdao China.
Xinhui XingKey Laboratory of Industrial Biocatalysis Ministry of Education Department of Chemical Engineering Tsinghua University Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing methylotrophic cell factories that can efficiently catalyze organic one-carbon (C1) feedstocks derived from electrocatalytic reduction of carbon dioxide into bio-based chemicals and biofuels is of strategic significance for building a carbon-neutral, sustainable economic and industrial system. With the rapid advancement of RNA sequencing technology and mass spectrometer analysis, researchers have used these quantitative microbiology methods extensively, especially isotope-based metabolic flux analysis, to study the metabolic processes initiating from C1 feedstocks in natural C1-utilizing bacteria and synthetic C1 bacteria. This paper reviews the use of advanced quantitative analysis in recent years to understand the metabolic network and basic principles in the metabolism of natural C1-utilizing bacteria grown on methane, methanol, or formate. The acquired knowledge serves as a guide to rewire the central methylotrophic metabolism of natural C1-utilizing bacteria to improve the carbon conversion efficiency, and to engineer non-C1-utilizing bacteria into synthetic strains that can use C1 feedstocks as the sole carbon and energy source. These progresses ultimately enhance the design and construction of highly efficient C1-based cell factories to synthesize diverse high value-added products. The integration of quantitative biology and synthetic biology will advance the iterative cycle of understand-design-build-testing-learning to enhance C1-based biomanufacturing in the future.

Indexed as

13C‐metabolic flux analysismethylotrophic cell factoriesone‐carbon feedstockquantitative biology

Identifiers

PMID41676019
PMCPMC12806228

What OpenQuestion holds

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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.