Orbi-SIMS 介导的致病组织代谢组学分析达到细胞分辨率

IF 6.1 Q1 CHEMISTRY, MULTIDISCIPLINARY Chemistry methods : new approaches to solving problems in chemistry Pub Date : 2024-07-12 DOI:10.1002/cmtd.202400008
Christine Kern, Astrid Scherer, Laura Gambs, Dr. Mariia Yuneva, Prof. Dr. Henning Walczak, Dr. Gianmaria Liccardi, Julia Saggau, Dr. Peter Kreuzaler, Prof. Dr. Marcus Rohnke
{"title":"Orbi-SIMS 介导的致病组织代谢组学分析达到细胞分辨率","authors":"Christine Kern,&nbsp;Astrid Scherer,&nbsp;Laura Gambs,&nbsp;Dr. Mariia Yuneva,&nbsp;Prof. Dr. Henning Walczak,&nbsp;Dr. Gianmaria Liccardi,&nbsp;Julia Saggau,&nbsp;Dr. Peter Kreuzaler,&nbsp;Prof. Dr. Marcus Rohnke","doi":"10.1002/cmtd.202400008","DOIUrl":null,"url":null,"abstract":"<p>Tumors have a complex metabolism that differs from most metabolic processes in healthy tissues. It is highly dynamic and driven by the tumor cells themselves, as well as by the non-transformed stromal infiltrates and immune components. Each of these cell populations has a distinct metabolism that depends on both their cellular state and the availability of nutrients. Consequently, to fully understand the individual metabolic states of all tumor-forming cells, correlative mass spectrometric imaging (MSI) up to cellular resolution with minimal metabolite shift needs to be achieved. By using a secondary ion mass spectrometer (SIMS) equipped with an Orbitrap mass analyzer, we present a workflow to image primary murine tumor tissues up to cellular resolution and correlate these ion images with post acquisition immunofluorescence or histological staining. In a murine breast cancer model, we could identify metabolic profiles that clearly distinguish tumor tissue from stromal cells and immune infiltrates. We demonstrate the robustness of the classification by applying the same profiles to an independent murine model of lung cancer, which is accurately segmented by histological traits. Our pipeline allows metabolic segmentation with simultaneous cell identification, which in the future will enable the design of subpopulation-targeted metabolic interventions for therapeutic purposes.</p>","PeriodicalId":72562,"journal":{"name":"Chemistry methods : new approaches to solving problems in chemistry","volume":"4 7-8","pages":""},"PeriodicalIF":6.1000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cmtd.202400008","citationCount":"0","resultStr":"{\"title\":\"Orbi-SIMS Mediated Metabolomics Analysis of Pathogenic Tissue up to Cellular Resolution\",\"authors\":\"Christine Kern,&nbsp;Astrid Scherer,&nbsp;Laura Gambs,&nbsp;Dr. Mariia Yuneva,&nbsp;Prof. Dr. Henning Walczak,&nbsp;Dr. Gianmaria Liccardi,&nbsp;Julia Saggau,&nbsp;Dr. Peter Kreuzaler,&nbsp;Prof. Dr. Marcus Rohnke\",\"doi\":\"10.1002/cmtd.202400008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Tumors have a complex metabolism that differs from most metabolic processes in healthy tissues. It is highly dynamic and driven by the tumor cells themselves, as well as by the non-transformed stromal infiltrates and immune components. Each of these cell populations has a distinct metabolism that depends on both their cellular state and the availability of nutrients. Consequently, to fully understand the individual metabolic states of all tumor-forming cells, correlative mass spectrometric imaging (MSI) up to cellular resolution with minimal metabolite shift needs to be achieved. By using a secondary ion mass spectrometer (SIMS) equipped with an Orbitrap mass analyzer, we present a workflow to image primary murine tumor tissues up to cellular resolution and correlate these ion images with post acquisition immunofluorescence or histological staining. In a murine breast cancer model, we could identify metabolic profiles that clearly distinguish tumor tissue from stromal cells and immune infiltrates. We demonstrate the robustness of the classification by applying the same profiles to an independent murine model of lung cancer, which is accurately segmented by histological traits. Our pipeline allows metabolic segmentation with simultaneous cell identification, which in the future will enable the design of subpopulation-targeted metabolic interventions for therapeutic purposes.</p>\",\"PeriodicalId\":72562,\"journal\":{\"name\":\"Chemistry methods : new approaches to solving problems in chemistry\",\"volume\":\"4 7-8\",\"pages\":\"\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2024-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cmtd.202400008\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chemistry methods : new approaches to solving problems in chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cmtd.202400008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemistry methods : new approaches to solving problems in chemistry","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cmtd.202400008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

肿瘤的新陈代谢十分复杂,与健康组织的大多数新陈代谢过程不同。它是高度动态的,由肿瘤细胞本身以及未转化的基质浸润和免疫成分驱动。这些细胞群中的每一个都有独特的新陈代谢,这取决于它们的细胞状态和营养物质的可用性。因此,要全面了解所有肿瘤形成细胞的个体代谢状态,就必须实现相关的质谱成像(MSI),达到细胞分辨率,并尽量减少代谢物的转移。通过使用配备 Orbitrap 质量分析仪的二次离子质谱仪 (SIMS),我们提出了一种工作流程,对原代小鼠肿瘤组织进行细胞分辨率成像,并将这些离子图像与采集后的免疫荧光或组织学染色进行关联。在小鼠乳腺癌模型中,我们可以识别出能清晰区分肿瘤组织与基质细胞和免疫浸润的代谢特征。我们将相同的图谱应用于一个独立的小鼠肺癌模型,证明了分类的稳健性,该模型可根据组织学特征进行准确分割。我们的管道可在进行代谢细分的同时识别细胞,这在未来将有助于设计以治疗为目的的亚群靶向代谢干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Orbi-SIMS Mediated Metabolomics Analysis of Pathogenic Tissue up to Cellular Resolution

Tumors have a complex metabolism that differs from most metabolic processes in healthy tissues. It is highly dynamic and driven by the tumor cells themselves, as well as by the non-transformed stromal infiltrates and immune components. Each of these cell populations has a distinct metabolism that depends on both their cellular state and the availability of nutrients. Consequently, to fully understand the individual metabolic states of all tumor-forming cells, correlative mass spectrometric imaging (MSI) up to cellular resolution with minimal metabolite shift needs to be achieved. By using a secondary ion mass spectrometer (SIMS) equipped with an Orbitrap mass analyzer, we present a workflow to image primary murine tumor tissues up to cellular resolution and correlate these ion images with post acquisition immunofluorescence or histological staining. In a murine breast cancer model, we could identify metabolic profiles that clearly distinguish tumor tissue from stromal cells and immune infiltrates. We demonstrate the robustness of the classification by applying the same profiles to an independent murine model of lung cancer, which is accurately segmented by histological traits. Our pipeline allows metabolic segmentation with simultaneous cell identification, which in the future will enable the design of subpopulation-targeted metabolic interventions for therapeutic purposes.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.30
自引率
0.00%
发文量
0
期刊最新文献
Cover Picture: Analysis of Macromolecular Size Distributions in Concentrated Solutions (Chem. Methods 12/2024) Towards Precision Biocatalysis – Leveraging Inline NMR for Autonomous Experimentation in Flow Reactors In situ X-Ray Powder Diffraction Investigation on the Development of Zeolite-Templated Carbons in FAU Zeolite Analysis of Macromolecular Size Distributions in Concentrated Solutions Cover Picture: Video Documented Upscaled Synthesis of Salts of the Parent Carbaborate Ion [CB11H12]−, its Undecafluorinated Form [CHB11F11]− and Useful Starting Materials for its Introduction (Chem. Methods 11/2024)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1