Evidence map›Paper›PMID 38922492›Full record

ArticleApplied biochemistry and biotechnology2024

Integrating Experimental and Computational Analyses of Yeast Protein Profiles for Optimizing the Production of High-Quality Microbial Proteins.

Lu Liu, Weihe Rong, Xiang Du, Qianqian Yuan, Zhaoyu Xu, Chang Yu, Hongzhong Lu, Yanfei Wang, Yan Zhu, Zhijia Liu and 1 more

Abstract read
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In one paragraph

Article in Applied biochemistry and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Lu LiuFaculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, 650500, China.
Weihe RongTianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
Xiang DuFaculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, 650500, China.
Qianqian YuanTianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
Zhaoyu XuTianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
Chang YuTianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
Hongzhong LuState Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
Yanfei WangFaculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, 650500, China. wangyfkust@163.com.
Yan ZhuTianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
Zhijia LiuFaculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming, 650500, China.
Guokun WangTianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China. wanggk@tib.cas.cn.ORCID http://orcid.org/0000-0002-6151-3980

Funding

National Natural Science Foundation of China 32270085The Strategic Priority Research Program of the Chinese Academy of Sciences XDC0110303Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project TSBICIP-CXRC-041
6 · The paper itself

Abstract

Microbial proteins represent a promising solution to address the escalating global demand for protein, particularly in regions with limited arable land. Yeasts, such as Saccharomyces cerevisiae, are robust and safe protein-producing strains. However, the utilization of non-conventional yeast strains for microbial protein production has been hindered, partly due to a lack of comprehensive understanding of protein production traits. In this study, we conducted experimental analyses focusing on the growth, protein content, and amino acid composition of nine yeast strains, including one S. cerevisiae strain, three Yarrowia lipolytica strains, and five Pichia spp. strains. We identified that, though Y. lipolytica and Pichia spp. strains consumed glucose at a slower rate compared to S. cerevisiae, Pichia spp. strains showed a higher cellular protein content, and Y. lipolytica strains showed a higher glucose-to-biomass/protein yield and methionine content. We further applied computational approaches to explain that metabolism economy was the main underlying factor for the limited amount of scarce/carbon-inefficient amino acids (such as methionine) within yeast cell proteins. We additionally verified that the specialized metabolism was a key reason for the high methionine content in Y. lipolytica strains, and proposed Y. lipolytica strain as a potential producer of high-quality single-cell protein rich in scarce amino acids. Through experimental evaluation, we identified Pichia jadinii CICC 1258 as a potential strain for high-quality protein production under unfavorable pH/temperature conditions. Our work suggests a promising avenue for optimizing microbial protein production, identifying the factors influencing amino acid composition, and paving the way for the use of unconventional yeast strains to meet the growing protein demands.

Indexed as

Saccharomyces cerevisiaeYarrowiaAmino AcidsFungal ProteinsGlucosePichiaAmino AcidsFungal ProteinsGlucoseAmino acid compositionEssential amino acidMetabolic economyModelProtein content

Identifiers

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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.