Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net

Jiyang Dong; Qianwen Peng; Lingli Deng; Chao Zhao; Zongwei Cai

doi:10.1016/j.xpro.2023.102159

Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net

Jiyang Dong, Qianwen Peng, Lingli Deng, Chao Zhao^*, Zongwei Cai^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

Abstract

Biomolecule regulation and communication between cells and organs show specific network and regional features and play an important role in disease progression. Here, we describe steps for in situ detection of biomolecules with detailed spatial distribution using imaging mass spectrometry (iMS). Using the information on inter-cells and inter-organs metabolic interactions provided by iMS, we detail the establishment of an iMS-dataset-sourced multiscale network strategy and present steps for exploring metabolic responses in environmental-exposure-induced disease model. For complete details on the use and execution of this protocol, please refer to Dong et al. (2022).¹

Original language	English
Article number	102159
Number of pages	16
Journal	STAR Protocols
Volume	4
Issue number	2
Early online date	13 Mar 2023
DOIs	https://doi.org/10.1016/j.xpro.2023.102159
Publication status	Published - 16 Jun 2023

Scopus Subject Areas

Neuroscience(all)
Biochemistry, Genetics and Molecular Biology(all)
Immunology and Microbiology(all)

User-Defined Keywords

Bioinformatics
Biotechnology and bioengineering
Computer sciences
Environmental sciences
Metabolism

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.xpro.2023.102159

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title = "Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net",

abstract = "Biomolecule regulation and communication between cells and organs show specific network and regional features and play an important role in disease progression. Here, we describe steps for in situ detection of biomolecules with detailed spatial distribution using imaging mass spectrometry (iMS). Using the information on inter-cells and inter-organs metabolic interactions provided by iMS, we detail the establishment of an iMS-dataset-sourced multiscale network strategy and present steps for exploring metabolic responses in environmental-exposure-induced disease model. For complete details on the use and execution of this protocol, please refer to Dong et al. (2022).1",

keywords = "Bioinformatics, Biotechnology and bioengineering, Computer sciences, Environmental sciences, Metabolism",

author = "Jiyang Dong and Qianwen Peng and Lingli Deng and Chao Zhao and Zongwei Cai",

note = "The work was supported by the National Key Research Program of China ( 2018YFA0901104 ), the National Natural Science Foundation of China ( 81871445 and 22176195 ), the Natural Science Foundation of Fujian Province , China ( 2022Y0003 ), the Natural Science Foundation of Guangdong Province , China ( 2021A1515010171 ), the Guangdong Province Zhu Jiang Talents Plan (2021QN02Y028), the Key Program of Fundamental Research in Shenzhen ( JCYJ20210324115811031), the Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression (ZDSYS20220606100606014), the Sustainable Development Program of Shenzhen (KCXFZ202002011008124 ), and Shenzhen Key Laboratory for Accurate Diagnosis and Treatment of Depression (2023). Copyright {\textcopyright} 2023 The Author(s). Published by Elsevier Inc. All rights reserved.",

year = "2023",

month = jun,

day = "16",

doi = "10.1016/j.xpro.2023.102159",

language = "English",

volume = "4",

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TY - JOUR

T1 - Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net

AU - Dong, Jiyang

AU - Peng, Qianwen

AU - Deng, Lingli

AU - Zhao, Chao

AU - Cai, Zongwei

N1 - The work was supported by the National Key Research Program of China ( 2018YFA0901104 ), the National Natural Science Foundation of China ( 81871445 and 22176195 ), the Natural Science Foundation of Fujian Province , China ( 2022Y0003 ), the Natural Science Foundation of Guangdong Province , China ( 2021A1515010171 ), the Guangdong Province Zhu Jiang Talents Plan (2021QN02Y028), the Key Program of Fundamental Research in Shenzhen ( JCYJ20210324115811031), the Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression (ZDSYS20220606100606014), the Sustainable Development Program of Shenzhen (KCXFZ202002011008124 ), and Shenzhen Key Laboratory for Accurate Diagnosis and Treatment of Depression (2023). Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.

PY - 2023/6/16

Y1 - 2023/6/16

N2 - Biomolecule regulation and communication between cells and organs show specific network and regional features and play an important role in disease progression. Here, we describe steps for in situ detection of biomolecules with detailed spatial distribution using imaging mass spectrometry (iMS). Using the information on inter-cells and inter-organs metabolic interactions provided by iMS, we detail the establishment of an iMS-dataset-sourced multiscale network strategy and present steps for exploring metabolic responses in environmental-exposure-induced disease model. For complete details on the use and execution of this protocol, please refer to Dong et al. (2022).1

AB - Biomolecule regulation and communication between cells and organs show specific network and regional features and play an important role in disease progression. Here, we describe steps for in situ detection of biomolecules with detailed spatial distribution using imaging mass spectrometry (iMS). Using the information on inter-cells and inter-organs metabolic interactions provided by iMS, we detail the establishment of an iMS-dataset-sourced multiscale network strategy and present steps for exploring metabolic responses in environmental-exposure-induced disease model. For complete details on the use and execution of this protocol, please refer to Dong et al. (2022).1

KW - Bioinformatics

KW - Biotechnology and bioengineering

KW - Computer sciences

KW - Environmental sciences

KW - Metabolism

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DO - 10.1016/j.xpro.2023.102159

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AN - SCOPUS:85150377614

SN - 2666-1667

VL - 4

JO - STAR Protocols

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ER -

Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net

Abstract

Scopus Subject Areas

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UN SDGs

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