梨果实代谢组学研究进展

doi:10.16420/j.issn.0513-353x.2023-0699

摘要/Abstract

摘要：

目前梨代谢组学的研究主要集中在果实生育期代谢图谱差异表达分析、不同品种果实代谢物差异分析及表征、采后贮藏保鲜及加工过程代谢物动态变化和影响果实品质相关代谢产物积累因素分析等。近年来，代谢组学结合转录组学、蛋白质组学等数据集联合分析，建立多维数据集之间的相关性，在识别重要性状的关键基因、阐明果实品质形成机制和揭示未知代谢物代谢途径等方面展现出巨大潜力。本文中主要介绍了代谢组学检测技术和数据分析现状，代谢组学技术及多组学技术在梨果实上的研究进展，并展望了多种新兴代谢组学技术以及多组学联合研究在梨果实中的应用前景，以期为梨品种改良和品质提升提供参考。

关键词: 梨, 代谢物, 代谢组学, 多组学

Abstract:

Presently，the research of metabolomics in pears and other Rosaceae fruits focuse on the differential expression of metabolic maps throughout the growth period of the fruit，the analysis and characterization of metabolites in different cultivars of pear fruits，the dynamic changes in metabolism during postharvest storage and processing，and the analysis of factors affecting the accumulation of metabolic products related to fruit quality. In recent years，metabolomics has been combined with transcriptomics datasets，proteomics datasets，and others to jointly analyse and establish the correlation between multi-dimensional datasets，showing potential in identifying key genes for important traits，elucidating the mechanism of fruit quality formation，and revealing the metabolic pathways of unknown metabolites. This article mainly introduces the current state of metabolomics technologies and metabolite identification，the research progress of metabolomics technology and multi-omics technology in pear fruit，and the application prospects of various emerging metabolomics technologies and multi-omics correlation research in pear fruit，in order to provide a reference for the improvement of pear variety and quality.

Key words: pear, metabolite, metabolomics, multi-omics

李文远, 林梦桦, 李亚辉, 于全琦, 梁颖, 张志勇. 梨果实代谢组学研究进展[J]. 园艺学报, 2024, 51(7): 1595-1609.

LI Wenyuan, LIN Menghua, LI Yahui, YU Quanqi, LIANG Ying, ZHANG Zhiyong. Advances in Metabolomics of Pear Fruit[J]. Acta Horticulturae Sinica, 2024, 51(7): 1595-1609.

图/表 2

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技术 Technique	重现性 Reproducibility	灵敏度 Sensitivity	样品制备 Sample preparation	代谢物覆盖范围和鉴定 Metabolite identification	参考文献 Reference
LC-MS	高 High	高 High	制备复杂，需要色谱分离 Complex preparation and require chromatographic separation	覆盖范围广泛，缺少商业标准库，鉴定较困难 Wide range of coverage，lack of a commercial standards base，more difficult to identify	Ma & Qi，2021； Yan et al.，2022
GC-MS	高 High	高 High	制备复杂，部分需要衍生化 Complex preparation，some require derivatisation	适合热稳定和挥发性代谢物鉴定 Suitable for heat stabilisation and volatile metabolite identification	Ma & Qi，2021； Monti et al.，2016
NMR	较高 Higher	低 Low	制备简单 Simple preparation	覆盖范围有限，精确定性Limited coverage，precise characterisation	Li et al.，2022a
MALDI-MSI	较高 Higher	高 High	制备复杂，需要冷冻切片处理以及基质喷涂 Complex preparation，requires frozen section processing and substrate spraying	覆盖范围广泛，缺少商业标准库，鉴定较困难 Wide range of coverage，lack of a commercial standards base，more difficult to identify	Segers et al.，2019；Shen et al.，2022
TOF-MS	高 High	高 High	制备简单 Simple preparation	覆盖范围广，鉴定困难，尤其是非靶向代谢组 Wide coverage and identification difficulties， especially for non-targeted metabolomes	Alvarez & Naldrett，2021
GC-IMS	高 High	高 High	制备简单 Simple preparation	适合热稳定和挥发性代谢物，鉴定相对容易 Suitable for heat-stable and volatile metabolites， relatively easy to identify	Ma et al.，2022；Song et al.，2023

技术 Technique	重现性 Reproducibility	灵敏度 Sensitivity	样品制备 Sample preparation	代谢物覆盖范围和鉴定 Metabolite identification	参考文献 Reference
LC-MS	高 High	高 High	制备复杂，需要色谱分离 Complex preparation and require chromatographic separation	覆盖范围广泛，缺少商业标准库，鉴定较困难 Wide range of coverage，lack of a commercial standards base，more difficult to identify	Ma & Qi，2021； Yan et al.，2022
GC-MS	高 High	高 High	制备复杂，部分需要衍生化 Complex preparation，some require derivatisation	适合热稳定和挥发性代谢物鉴定 Suitable for heat stabilisation and volatile metabolite identification	Ma & Qi，2021； Monti et al.，2016
NMR	较高 Higher	低 Low	制备简单 Simple preparation	覆盖范围有限，精确定性Limited coverage，precise characterisation	Li et al.，2022a
MALDI-MSI	较高 Higher	高 High	制备复杂，需要冷冻切片处理以及基质喷涂 Complex preparation，requires frozen section processing and substrate spraying	覆盖范围广泛，缺少商业标准库，鉴定较困难 Wide range of coverage，lack of a commercial standards base，more difficult to identify	Segers et al.，2019；Shen et al.，2022
TOF-MS	高 High	高 High	制备简单 Simple preparation	覆盖范围广，鉴定困难，尤其是非靶向代谢组 Wide coverage and identification difficulties， especially for non-targeted metabolomes	Alvarez & Naldrett，2021
GC-IMS	高 High	高 High	制备简单 Simple preparation	适合热稳定和挥发性代谢物，鉴定相对容易 Suitable for heat-stable and volatile metabolites， relatively easy to identify	Ma et al.，2022；Song et al.，2023

数据库 Database	简介 Introduction	化合物数量 Compound number	应用实例 Example	参考文献 Reference
HMDB	人类代谢组数据库，其中内源代谢物占81%，食品、药物、植物等外源代谢物占19% Human metabolome database，with 81% endogenous metabolites and 19% exogenous metabolites from food，drugs，plants，etc	114 100	草莓 Strawberry	Antunes et al.，2019
METLIN	最大的代谢物串联质谱数据库，包括脂类、类固醇、碳水化合物及微生物代谢组、外源性药物、毒物等 Largest metabolite tandem mass spectrometry database，including lipids，steroids，carbohydrates and microbial metabolomes，exogenous drugs，poisons，etc	> 850 000	柑橘，草莓 Citrus， strawberry	Antunes et al.， 2019；Kim et al.， 2021
mzCloud	标准品采集，高分辨/高准确度质谱数据库，应用于生命科学、代谢组学、药物研究、毒理学、食品工业等 Standard collection，high-resolution/high-accuracy mass spectrometry database for applications in life sciences，metabolomics，pharmaceutical research，toxicology，food industry，etc	19 211	木薯 Cassava	Chaowongdee et al.，2023
GNPS	天然产物质谱数据库，整合了第三方数据库及全球多个科研团队提供的代谢物质谱谱图数据 Natural product mass spectrometry database，integrating metabolite mass spectrometry data from third-party databases and multiple research teams around the world	18 163	苹果 Apple	Bilbrey et al.， 2021
MassBank	通用数据库，质谱数据来自多个实验室，包括多种离子化方式、高分辨质谱、低分辨质谱得到的数据 Common database with mass spectrometry data from multiple laboratories，including data from multiple ionisation modes，high-resolution mass spectrometry and low-resolution mass spectrometry	14 788	柑橘 Citrus	Tan et al.，2019
KEGG	整合了基因组、化学和系统功能信息的数据库 Databases integrating genomic，chemical and systemic functional information	—	梨，猕猴桃 Pear，kiwifruit	Yu et al.，2020；Gong et al.，2022

数据库 Database	简介 Introduction	化合物数量 Compound number	应用实例 Example	参考文献 Reference
HMDB	人类代谢组数据库，其中内源代谢物占81%，食品、药物、植物等外源代谢物占19% Human metabolome database，with 81% endogenous metabolites and 19% exogenous metabolites from food，drugs，plants，etc	114 100	草莓 Strawberry	Antunes et al.，2019
METLIN	最大的代谢物串联质谱数据库，包括脂类、类固醇、碳水化合物及微生物代谢组、外源性药物、毒物等 Largest metabolite tandem mass spectrometry database，including lipids，steroids，carbohydrates and microbial metabolomes，exogenous drugs，poisons，etc	> 850 000	柑橘，草莓 Citrus， strawberry	Antunes et al.， 2019；Kim et al.， 2021
mzCloud	标准品采集，高分辨/高准确度质谱数据库，应用于生命科学、代谢组学、药物研究、毒理学、食品工业等 Standard collection，high-resolution/high-accuracy mass spectrometry database for applications in life sciences，metabolomics，pharmaceutical research，toxicology，food industry，etc	19 211	木薯 Cassava	Chaowongdee et al.，2023
GNPS	天然产物质谱数据库，整合了第三方数据库及全球多个科研团队提供的代谢物质谱谱图数据 Natural product mass spectrometry database，integrating metabolite mass spectrometry data from third-party databases and multiple research teams around the world	18 163	苹果 Apple	Bilbrey et al.， 2021
MassBank	通用数据库，质谱数据来自多个实验室，包括多种离子化方式、高分辨质谱、低分辨质谱得到的数据 Common database with mass spectrometry data from multiple laboratories，including data from multiple ionisation modes，high-resolution mass spectrometry and low-resolution mass spectrometry	14 788	柑橘 Citrus	Tan et al.，2019
KEGG	整合了基因组、化学和系统功能信息的数据库 Databases integrating genomic，chemical and systemic functional information	—	梨，猕猴桃 Pear，kiwifruit	Yu et al.，2020；Gong et al.，2022