Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications
IntroductionCastor bean or ricin-induced intoxication or terror events have threatened public security and social safety. Potential resources or materials include beans, raw extraction products, crude toxins, and purified ricin. The traceability of the origins of castor beans is thus essential for f...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2022.1083901/full |
| _version_ | 1798006063030599680 |
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| author | Luyuan Qin Junshan Han Chuang Wang Chuang Wang Bin Xu Deyun Tan Song He Lei Guo Xiaochen Bo Jianwei Xie |
| author_facet | Luyuan Qin Junshan Han Chuang Wang Chuang Wang Bin Xu Deyun Tan Song He Lei Guo Xiaochen Bo Jianwei Xie |
| author_sort | Luyuan Qin |
| collection | DOAJ |
| description | IntroductionCastor bean or ricin-induced intoxication or terror events have threatened public security and social safety. Potential resources or materials include beans, raw extraction products, crude toxins, and purified ricin. The traceability of the origins of castor beans is thus essential for forensic and anti-terror investigations. As a new imaging technique with label-free, rapid, and high throughput features, matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) has been gradually stressed in plant research. However, sample preparation approaches for plant tissues still face severe challenges, especially for some lipid-rich, water-rich, or fragile tissues. Proper tissue washing procedures would be pivotal, but little information is known until now.MethodsFor castor beans containing plenty of lipids that were fragile when handled, we developed a comprehensive tissue pretreatment protocol. Eight washing procedures aimed at removing lipids were discussed in detail. We then constructed a robust MALDI-MSI method to enhance the detection sensitivity of RCBs in castor beans.Results and DiscussionA modified six-step washing procedure was chosen as the most critical parameter regarding the MSI visualization of peptides. The method was further applied to visualize and quantify the defense peptides, Ricinus communis biomarkers (RCBs) in castor bean tissue sections from nine different geographic sources from China, Pakistan, and Ethiopia. Multivariate statistical models, including deep learning network, revealed a valuable classification clue concerning nationality and altitude. |
| first_indexed | 2024-04-11T12:48:59Z |
| format | Article |
| id | doaj.art-d9e484d60c434cd7b047b6104f4a7192 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-04-11T12:48:59Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-d9e484d60c434cd7b047b6104f4a71922022-12-22T04:23:16ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2022-12-011310.3389/fpls.2022.10839011083901Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applicationsLuyuan Qin0Junshan Han1Chuang Wang2Chuang Wang3Bin Xu4Deyun Tan5Song He6Lei Guo7Xiaochen Bo8Jianwei Xie9State Key Laboratory of Toxicology and Medical Countermeasures, Institute of Pharmacology and Toxicology, Academy of Military Medical Sciences, Beijing, ChinaDepartment of Bioinformatics, Institute of Health Service and Transfusion Medicine, Beijing, ChinaState Key Laboratory of Toxicology and Medical Countermeasures, Institute of Pharmacology and Toxicology, Academy of Military Medical Sciences, Beijing, ChinaMinistry of Education Key Laboratory of Ethnic Medicine, College of Pharmacy, Minzu University of China, Beijing, ChinaState Key Laboratory of Toxicology and Medical Countermeasures, Institute of Pharmacology and Toxicology, Academy of Military Medical Sciences, Beijing, ChinaInstitute of Cash Crop Research, Zibo Academy of Agricultural Sciences, Zibo, ChinaDepartment of Bioinformatics, Institute of Health Service and Transfusion Medicine, Beijing, ChinaState Key Laboratory of Toxicology and Medical Countermeasures, Institute of Pharmacology and Toxicology, Academy of Military Medical Sciences, Beijing, ChinaDepartment of Bioinformatics, Institute of Health Service and Transfusion Medicine, Beijing, ChinaState Key Laboratory of Toxicology and Medical Countermeasures, Institute of Pharmacology and Toxicology, Academy of Military Medical Sciences, Beijing, ChinaIntroductionCastor bean or ricin-induced intoxication or terror events have threatened public security and social safety. Potential resources or materials include beans, raw extraction products, crude toxins, and purified ricin. The traceability of the origins of castor beans is thus essential for forensic and anti-terror investigations. As a new imaging technique with label-free, rapid, and high throughput features, matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) has been gradually stressed in plant research. However, sample preparation approaches for plant tissues still face severe challenges, especially for some lipid-rich, water-rich, or fragile tissues. Proper tissue washing procedures would be pivotal, but little information is known until now.MethodsFor castor beans containing plenty of lipids that were fragile when handled, we developed a comprehensive tissue pretreatment protocol. Eight washing procedures aimed at removing lipids were discussed in detail. We then constructed a robust MALDI-MSI method to enhance the detection sensitivity of RCBs in castor beans.Results and DiscussionA modified six-step washing procedure was chosen as the most critical parameter regarding the MSI visualization of peptides. The method was further applied to visualize and quantify the defense peptides, Ricinus communis biomarkers (RCBs) in castor bean tissue sections from nine different geographic sources from China, Pakistan, and Ethiopia. Multivariate statistical models, including deep learning network, revealed a valuable classification clue concerning nationality and altitude.https://www.frontiersin.org/articles/10.3389/fpls.2022.1083901/fullcastor beansMALDI-MSItissue washingpeptide attribution markersgeographical origin |
| spellingShingle | Luyuan Qin Junshan Han Chuang Wang Chuang Wang Bin Xu Deyun Tan Song He Lei Guo Xiaochen Bo Jianwei Xie Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications Frontiers in Plant Science castor beans MALDI-MSI tissue washing peptide attribution markers geographical origin |
| title | Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications |
| title_full | Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications |
| title_fullStr | Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications |
| title_full_unstemmed | Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications |
| title_short | Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications |
| title_sort | key defatting tissue pretreatment protocol for enhanced maldi ms imaging of peptide biomarkers visualization in the castor beans and their attribution applications |
| topic | castor beans MALDI-MSI tissue washing peptide attribution markers geographical origin |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2022.1083901/full |
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