Functional proteomics reveals that Slr0237 is a SigE-regulated glycogen debranching enzyme pivotal for glycogen breakdown

IF 3.4 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Proteomics Pub Date : 2024-04-05 DOI:10.1002/pmic.202300222
Ye Liu, Haitao Ge, Dandan Lu
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引用次数: 0

Abstract

The group 2 σ factor for RNA polymerase SigE plays important role in regulating central carbon metabolism in cyanobacteria. However, the regulation of SigE for these pathways at a proteome level remains unknown. Using a sigE-deficient strain (ΔsigE) of Synechocystis sp. PCC 6803 and quantitative proteomics, we found that SigE depletion induces differential protein expression for sugar catabolic pathways including glycolysis, oxidative pentose phosphate (OPP) pathway, and glycogen catabolism. Two glycogen debranching enzyme homologues Slr1857 and Slr0237 are found differentially expressed in ΔsigE. Glycogen determination indicated that Δslr0237 accumulated glycogen under photomixotrophic condition but was unable to utilize these reserves in the dark, whereas Δslr1857 accumulates and utilizes glycogen in a similar way as the WT strain does in the same condition. These results suggest that Slr0237 plays the major role as the glycogen debranching enzyme in Synechocystis.

功能蛋白质组学发现,Slr0237 是一种受 SigE 调控的糖原去支链酶,对糖原分解至关重要
RNA 聚合酶 SigE 的第 2 组 σ 因子在调控蓝藻的中心碳代谢方面发挥着重要作用。然而,SigE 在蛋白质组水平上对这些途径的调控仍然未知。利用 Synechocystis sp. PCC 6803 的 SigE 缺失菌株(ΔsigE)和定量蛋白质组学研究,我们发现 SigE 缺失会诱导糖分解途径(包括糖酵解、磷酸戊糖氧化(OPP)途径和糖原分解)的不同蛋白质表达。在ΔsigE中发现两种糖原分解酶同源物Slr1857和Slr0237有差异表达。糖原测定结果表明,Δslr0237 在光复营养条件下积累糖原,但在黑暗条件下无法利用这些储备,而Δslr1857 在相同条件下积累和利用糖原的方式与 WT 菌株相似。这些结果表明,Slr0237 在 Synechocystis 中扮演着糖原去支链酶的主要角色。
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来源期刊
Proteomics
Proteomics 生物-生化研究方法
CiteScore
6.30
自引率
5.90%
发文量
193
审稿时长
3 months
期刊介绍: PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.
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