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从色谱图到分析物到代谢物。如何从海量的质谱植物代谢组学网络资源中为特定目的选择合适的资源。

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics.

机构信息

Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.

出版信息

Gigascience. 2017 Jul 1;6(7):1-20. doi: 10.1093/gigascience/gix037.

DOI:10.1093/gigascience/gix037
PMID:28520864
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5499862/
Abstract

The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome.

摘要

目前代谢组学面临的重大挑战是将代谢组的覆盖范围从细胞代谢物的一小部分扩展到转录组学和蛋白质组学等其他后基因组技术的覆盖范围。在植物中,构成代谢组的化学物质的多样性使这个问题更加严重,植物王国中的代谢物数量通常被认为超过 200000 种。在这篇综述中,我们专注于可以利用的网络资源,以提高分析物,最终是代谢物的鉴定和定量。有各种各样的可用软件不仅有助于这一点,而且还在峰对齐的相关领域;然而,对于初学者来说,选择要使用的程序是一项艰巨的任务。出于这个原因,我们提供了软件的优缺点概述,以及关于有效利用其基本功能所需编程技能水平的评论。此外,随着下一代测序的出现,可用的基因组和转录组序列的洪流为代谢物鉴定开辟了更多有价值的资源。综上所述,我们认为,只有通过持续共享信息,例如在文章中描述的数据库中存储的信息,我们才有可能在提高我们对植物代谢组的覆盖范围方面取得重大进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a150/5499862/73d70dcb285d/gix037fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a150/5499862/73d70dcb285d/gix037fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a150/5499862/73d70dcb285d/gix037fig1.jpg

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