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不完整的谷胱甘肽之谜:只是在猜测数字和数据吗?

The Incomplete Glutathione Puzzle: Just Guessing at Numbers and Figures?

作者信息

Deponte Marcel

机构信息

Department of Parasitology, Ruprecht-Karls University , Heidelberg, Germany .

出版信息

Antioxid Redox Signal. 2017 Nov 20;27(15):1130-1161. doi: 10.1089/ars.2017.7123. Epub 2017 Jul 19.

DOI:10.1089/ars.2017.7123
PMID:28540740
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5661824/
Abstract

SIGNIFICANCE

Glutathione metabolism is comparable to a jigsaw puzzle with too many pieces. It is supposed to comprise (i) the reduction of disulfides, hydroperoxides, sulfenic acids, and nitrosothiols, (ii) the detoxification of aldehydes, xenobiotics, and heavy metals, and (iii) the synthesis of eicosanoids, steroids, and iron-sulfur clusters. In addition, glutathione affects oxidative protein folding and redox signaling. Here, I try to provide an overview on the relevance of glutathione-dependent pathways with an emphasis on quantitative data. Recent Advances: Intracellular redox measurements reveal that the cytosol, the nucleus, and mitochondria contain very little glutathione disulfide and that oxidative challenges are rapidly counterbalanced. Genetic approaches suggest that iron metabolism is the centerpiece of the glutathione puzzle in yeast. Furthermore, recent biochemical studies provide novel insights on glutathione transport processes and uncoupling mechanisms.

CRITICAL ISSUES

Which parts of the glutathione puzzle are most relevant? Does this explain the high intracellular concentrations of reduced glutathione? How can iron-sulfur cluster biogenesis, oxidative protein folding, or redox signaling occur at high glutathione concentrations? Answers to these questions not only seem to depend on the organism, cell type, and subcellular compartment but also on different ideologies among researchers.

FUTURE DIRECTIONS

A rational approach to compare the relevance of glutathione-dependent pathways is to combine genetic and quantitative kinetic data. However, there are still many missing pieces and too little is known about the compartment-specific repertoire and concentration of numerous metabolites, substrates, enzymes, and transporters as well as rate constants and enzyme kinetic patterns. Gathering this information might require the development of novel tools but is crucial to address potential kinetic competitions and to decipher uncoupling mechanisms to solve the glutathione puzzle. Antioxid. Redox Signal. 27, 1130-1161.

摘要

意义

谷胱甘肽代谢就如同一个拼图,碎片过多。它应该包括:(i)二硫键、氢过氧化物、亚磺酸和亚硝基硫醇的还原;(ii)醛、外源性物质和重金属的解毒;(iii)类花生酸、类固醇和铁硫簇的合成。此外,谷胱甘肽还影响氧化蛋白折叠和氧化还原信号传导。在此,我试图提供一个关于谷胱甘肽依赖性途径相关性的概述,并重点关注定量数据。最新进展:细胞内氧化还原测量表明,细胞质、细胞核和线粒体中谷胱甘肽二硫化物含量极少,氧化应激能迅速得到平衡。遗传学方法表明,铁代谢是酵母中谷胱甘肽拼图的核心。此外,最近的生化研究为谷胱甘肽转运过程和解偶联机制提供了新的见解。

关键问题

谷胱甘肽拼图的哪些部分最为相关?这能解释还原型谷胱甘肽在细胞内的高浓度吗?在高谷胱甘肽浓度下,铁硫簇生物合成、氧化蛋白折叠或氧化还原信号传导是如何发生的?这些问题的答案似乎不仅取决于生物体、细胞类型和亚细胞区室,还取决于研究人员之间不同的观点。

未来方向

一种比较谷胱甘肽依赖性途径相关性的合理方法是结合遗传学和定量动力学数据。然而,仍然有许多缺失的部分,对于众多代谢物、底物、酶和转运蛋白的区室特异性组成和浓度以及速率常数和酶动力学模式了解甚少。收集这些信息可能需要开发新工具,但对于解决潜在的动力学竞争和解密解偶联机制以解开谷胱甘肽拼图至关重要。《抗氧化与氧化还原信号》27卷,1130 - 1161页 。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/ef5f04c58626/fig-8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/4632e0a78526/fig-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/1b7de6a7c497/fig-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/38d1011720dc/inl-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/50bfcc5d3926/fig-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/496e1062b4de/inl-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/33dd97381286/fig-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/8dd1232fe008/fig-5.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/4bdd7fd7c6d0/fig-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/ef5f04c58626/fig-8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/4632e0a78526/fig-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/1b7de6a7c497/fig-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/38d1011720dc/inl-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/50bfcc5d3926/fig-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/496e1062b4de/inl-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/33dd97381286/fig-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/8dd1232fe008/fig-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/cd9c18b8e7c0/fig-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/4bdd7fd7c6d0/fig-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d188/5661824/ef5f04c58626/fig-8.jpg

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