Citation: Xiaoli Zhong, Liangsheng Chen, Hao Xu, Tianhang Jiang, Zhengyi Hua, Fancheng Tan, Xiaoya Mao, Ziquan Fan, Zhiwei Li, Jun Zeng, Shu-Hai Lin. Development of a comprehensive computational pipeline for cardiolipin atlas in an intermittent fasting model[J]. Chinese Chemical Letters, ;2025, 36(12): 111027. doi: 10.1016/j.cclet.2025.111027 shu

Development of a comprehensive computational pipeline for cardiolipin atlas in an intermittent fasting model

Xiaoli Zhong ^{a, 1} ,
Liangsheng Chen ^{a, 1} ,
Hao Xu ^{a, b} ,
Tianhang Jiang ^a ,
Zhengyi Hua ^a ,
Fancheng Tan ^a ,
Xiaoya Mao ^c ,
Ziquan Fan ^d ,
Zhiwei Li ^e ,
Jun Zeng ^{f, g, *,} ,
Shu-Hai Lin ^{a, b, *,}

a.
State Key Laboratory of Cellular Stress Biology, Xiang'an Hospital, School of Life Sciences, XMU-HBN skin biomedical research center, Xiamen University, Xiamen 361102, China
b.
National Institute for Data Science in Health and Medicine, School of Medicine, Xiamen University, Xiamen 361102, China
c.
School of Pharmaceutical Sciences, Xiamen University, Xiamen 361102, China
d.
Thermo Fisher Scientific, Shanghai 201206, China
e.
HBN Research Institute and Biological Laboratory, Shenzhen Hujia Technology Co., Ltd., Shenzhen 518000, China
f.
College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, China
g.
Research Unit Analytical BioGeoChemistry, Helmholtz Munich, Neuherberg 85764, Germany

junzeng@jmu.edu.cn

shuhai@xmu.edu.cn

Received Date: 14 October 2024
Revised Date: 21 February 2025
Accepted Date: 2 March 2025
Available Online: 3 March 2025

Figures(4)

Cardiolipins (CLs), the mitochondria-specific class of phospholipids, are crucial to energy metabolism, cristae structure, and cell apoptosis. CLs present significant challenges in lipidomics analysis due to their structural diversity with up to four fatty acyl side chains. In this study, we developed CLAN (CardioLipin ANalysis), a comprehensive computational pipeline designed to improve the accuracy and coverage of cardiolipin identification. CLAN integrates three innovative modules: A cardiolipin identification module that utilizes specific fragmentation rules for precise characterization of CLs and their acyl side chains; a false positives detection module that employs retention time (RT) criteria to reduce false positives; and a prediction module that constructs regression models to identify CLs lacking authentic MS/MS spectra. CLAN achieved better identification accuracy and the highest recall rate for potential CL identification compared to the existing lipid identification tools. Furthermore, we applied CLAN program to an intermittent fasting mouse model, delineating tissue-specific CL alterations across 10 tissues. Every-other-day fasting (EODF) can partially counteract the disruption of the CL atlas across multiple tissues caused by high-fat-high-sugar diet feeding, providing novel insights into mitochondrial lipid metabolism under dietary interventions. Taken together, this work not only advances CL identification methodology but also underscores CLAN's potential in comprehensive analysis of CL atlas in the EODF animal model. CLAN is freely accessible on GitHub.
- Cardiolipin identification,
- Mass spectrometry,
- Computational pipeline,
- Cardiolipin atlas,
- Intermittent fasting
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