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Shi Q, Yu X, Sun S, Wu W, Shi W, Yu Q. Diverse thermal desorption combined with self-aspirating corona discharge ionization for direct mass spectrometry analysis of complex samples. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:2071-2076. [PMID: 38505988 DOI: 10.1039/d4ay00200h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
The thermal desorption (TD) technique is widely employed in modern mass spectrometry to facilitate the detection of non-volatile analytes. In this study, we developed a compact TD device based on a small resistance wire and coupled it with a self-aspirating corona discharge ionization (CDI) source to conduct direct MS analysis of various liquid and solid samples. Due to its small size and low heat capacity, the temperature of the TD module can be flexibly and rapidly modulated by controlling the power sequence. Multiple heating modes, including pulse heating (PH), isothermal heating, and step heating (SH), are realized and characterized, and then applied for the detection of different real samples. In particular, the PH mode is suitable for the simultaneous detection of multiple components in samples with relatively simple matrices, while the SH mode is capable of component separation. In addition, the sensitivity and quantitative capability of the TD-CDI system for DEP solutions were tested, showing acceptable stability with a relative standard deviation of about 6.7% and a detection limit of 0.088 ng. Overall, the developed TD-CDI system provides a simple, convenient, and versatile tool for direct mass spectrometry analysis of real samples.
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Affiliation(s)
- Qinhao Shi
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Xiaohua Yu
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Shuang Sun
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Weilong Wu
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Wenyan Shi
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Quan Yu
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
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Liu P, Chen Q, Zhang L, Ren C, Shi B, Zhang J, Wang S, Chen Z, Wang Q, Xie H, Huang Q, Tang H. Rapid quantification of 50 fatty acids in small amounts of biological samples for population molecular phenotyping. BIOPHYSICS REPORTS 2023; 9:299-308. [PMID: 38524698 PMCID: PMC10960574 DOI: 10.52601/bpr.2023.230042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 12/15/2023] [Indexed: 03/26/2024] Open
Abstract
Efficient quantification of fatty-acid (FA) composition (fatty-acidome) in biological samples is crucial for understanding physiology and pathophysiology in large population cohorts. Here, we report a rapid GC-FID/MS method for simultaneous quantification of all FAs in numerous biological matrices. Within eight minutes, this method enabled simultaneous quantification of 50 FAs as fatty-acid methyl esters (FAMEs) in femtomole levels following the efficient transformation of FAs in all lipids including FFAs, cholesterol-esters, glycerides, phospholipids and sphingolipids. The method showed satisfactory inter-day and intra-day precision, stability and linearity (R2 > 0.994) within a concentration range of 2-3 orders of magnitude. FAs were then quantified in typical multiple biological matrices including human biofluids (urine, plasma) and cells, animal intestinal content and tissue samples. We also established a quantitative structure-retention relationship (QSRR) for analytes to accurately predict their retention time and aid their reliable identification. We further developed a novel no-additive retention index (NARI) with endogenous FAMEs reducing inter-batch variations to 15 seconds; such NARI performed better than the alkanes-based classical RI, making meta-analysis possible for data obtained from different batches and platforms. Collectively, this provides an inexpensive high-throughput analytical system for quantitative phenotyping of all FAs in 8-minutes multiple biological matrices in large cohort studies of pathophysiological effects.
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Affiliation(s)
- Pinghui Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Qinsheng Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Lianglong Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Chengcheng Ren
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Biru Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jingxian Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Shuaiyao Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Ziliang Chen
- Wuhan Laboratory for Shanghai Metabolome Institute (SMI) Ltd, Wuhan 430000, China
| | - Qi Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Hui Xie
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Qingxia Huang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
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