IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-34824-2.html
   My bibliography  Save this article

Spatially resolved proteomics via tissue expansion

Author

Listed:
  • Lu Li

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Cuiji Sun

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake Institute for Advanced Study)

  • Yaoting Sun

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Zhen Dong

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Runxin Wu

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Xiaoting Sun

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake Institute for Advanced Study)

  • Hanbin Zhang

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake Institute for Advanced Study)

  • Wenhao Jiang

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Yan Zhou

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Xufeng Cen

    (Zhejiang University School of Medicine)

  • Shang Cai

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Hongguang Xia

    (Zhejiang University School of Medicine
    The First Affiliated Hospital, Zhejiang University School of Medicine
    Zhejiang University Medical Center)

  • Yi Zhu

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Tiannan Guo

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake University
    Westlake Institute for Advanced Study)

  • Kiryl D. Piatkevich

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake Institute for Advanced Study)

Abstract

Spatially resolved proteomics is an emerging approach for mapping proteome heterogeneity of biological samples, however, it remains technically challenging due to the complexity of the tissue microsampling techniques and mass spectrometry analysis of nanoscale specimen volumes. Here, we describe a spatially resolved proteomics method based on the combination of tissue expansion with mass spectrometry-based proteomics, which we call Expansion Proteomics (ProteomEx). ProteomEx enables quantitative profiling of the spatial variability of the proteome in mammalian tissues at ~160 µm lateral resolution, equivalent to the tissue volume of 0.61 nL, using manual microsampling without the need for custom or special equipment. We validated and demonstrated the utility of ProteomEx for streamlined large-scale proteomics profiling of biological tissues including brain, liver, and breast cancer. We further applied ProteomEx for identifying proteins associated with Alzheimer’s disease in a mouse model by comparative proteomic analysis of brain subregions.

Suggested Citation

  • Lu Li & Cuiji Sun & Yaoting Sun & Zhen Dong & Runxin Wu & Xiaoting Sun & Hanbin Zhang & Wenhao Jiang & Yan Zhou & Xufeng Cen & Shang Cai & Hongguang Xia & Yi Zhu & Tiannan Guo & Kiryl D. Piatkevich, 2022. "Spatially resolved proteomics via tissue expansion," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34824-2
    DOI: 10.1038/s41467-022-34824-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-34824-2
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-022-34824-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ruedi Aebersold & Matthias Mann, 2016. "Mass-spectrometric exploration of proteome structure and function," Nature, Nature, vol. 537(7620), pages 347-355, September.
    2. Paul D. Piehowski & Ying Zhu & Lisa M. Bramer & Kelly G. Stratton & Rui Zhao & Daniel J. Orton & Ronald J. Moore & Jia Yuan & Hugh D. Mitchell & Yuqian Gao & Bobbie-Jo M. Webb-Robertson & Sudhansu K. , 2020. "Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-μm spatial resolution," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simon Davis & Connor Scott & Janina Oetjen & Philip D. Charles & Benedikt M. Kessler & Olaf Ansorge & Roman Fischer, 2023. "Deep topographic proteomics of a human brain tumour," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Simon Davis & Connor Scott & Janina Oetjen & Philip D. Charles & Benedikt M. Kessler & Olaf Ansorge & Roman Fischer, 2023. "Deep topographic proteomics of a human brain tumour," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Yunhao Bai & Bokai Zhu & John-Paul Oliveria & Bryan J. Cannon & Dorien Feyaerts & Marc Bosse & Kausalia Vijayaragavan & Noah F. Greenwald & Darci Phillips & Christian M. Schürch & Samuel M. Naik & Edw, 2023. "Expanded vacuum-stable gels for multiplexed high-resolution spatial histopathology," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    3. Sofani Tafesse Gebreyesus & Asad Ali Siyal & Reta Birhanu Kitata & Eric Sheng-Wen Chen & Bayarmaa Enkhbayar & Takashi Angata & Kuo-I Lin & Yu-Ju Chen & Hsiung-Lin Tu, 2022. "Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    4. Hao Hu & Wei Hu & An-Di Guo & Linhui Zhai & Song Ma & Hui-Jun Nie & Bin-Shan Zhou & Tianxian Liu & Xinglong Jia & Xing Liu & Xuebiao Yao & Minjia Tan & Xiao-Hua Chen, 2024. "Spatiotemporal and direct capturing global substrates of lysine-modifying enzymes in living cells," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Yuwan Chen & Wen Zhou & Yufei Xia & Weijie Zhang & Qun Zhao & Xinwei Li & Hang Gao & Zhen Liang & Guanghui Ma & Kaiguang Yang & Lihua Zhang & Yukui Zhang, 2023. "Targeted cross-linker delivery for the in situ mapping of protein conformations and interactions in mitochondria," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    6. Martin Mehnert & Rodolfo Ciuffa & Fabian Frommelt & Federico Uliana & Audrey Drogen & Kilian Ruminski & Matthias Gstaiger & Ruedi Aebersold, 2020. "Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes," Nature Communications, Nature, vol. 11(1), pages 1-18, December.
    7. Daniela Klaproth-Andrade & Johannes Hingerl & Yanik Bruns & Nicholas H. Smith & Jakob Träuble & Mathias Wilhelm & Julien Gagneur, 2024. "Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    8. Erik Hartman & Aaron M. Scott & Christofer Karlsson & Tirthankar Mohanty & Suvi T. Vaara & Adam Linder & Lars Malmström & Johan Malmström, 2023. "Interpreting biologically informed neural networks for enhanced proteomic biomarker discovery and pathway analysis," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    9. Fushi Wang & Chunxiao Zhao & Pinlong Zhao & Fanfan Chen & Dan Qiao & Jiandong Feng, 2023. "MoS2 nanopore identifies single amino acids with sub-1 Dalton resolution," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    10. Jongmin Woo & Sarah M. Williams & Lye Meng Markillie & Song Feng & Chia-Feng Tsai & Victor Aguilera-Vazquez & Ryan L. Sontag & Ronald J. Moore & Dehong Hu & Hardeep S. Mehta & Joshua Cantlon-Bruce & T, 2021. "High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    11. Wenping Zhou & Wenxue Li & Shisheng Wang & Barbora Salovska & Zhenyi Hu & Bo Tao & Yi Di & Ujwal Punyamurtula & Benjamin E. Turk & William C. Sessa & Yansheng Liu, 2023. "An optogenetic-phosphoproteomic study reveals dynamic Akt1 signaling profiles in endothelial cells," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    12. Valdemaras Petrosius & Pedro Aragon-Fernandez & Nil Üresin & Gergo Kovacs & Teeradon Phlairaharn & Benjamin Furtwängler & Jeff Op De Beeck & Sarah L. Skovbakke & Steffen Goletz & Simon Francis Thomsen, 2023. "Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    13. Yi Yang & Qun Fang, 2024. "Prediction of glycopeptide fragment mass spectra by deep learning," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    14. Min Ma & Shihan Huo & Ming Zhang & Shuo Qian & Xiaoyu Zhu & Jie Pu & Sailee Rasam & Chao Xue & Shichen Shen & Bo An & Jianmin Wang & Jun Qu, 2022. "In-depth mapping of protein localizations in whole tissue by micro-scaffold assisted spatial proteomics (MASP)," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    15. Yulin Sun & Zhengguang Guo & Xiaoyan Liu & Lijun Yang & Zongpan Jing & Meng Cai & Zhaoxu Zheng & Chen Shao & Yefan Zhang & Haidan Sun & Li Wang & Minjie Wang & Jun Li & Lusong Tian & Yue Han & Shuangm, 2022. "Noninvasive urinary protein signatures associated with colorectal cancer diagnosis and metastasis," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    16. Wen-Feng Zeng & Xie-Xuan Zhou & Sander Willems & Constantin Ammar & Maria Wahle & Isabell Bludau & Eugenia Voytik & Maximillian T. Strauss & Matthias Mann, 2022. "AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    17. Brad A. Palanski & Nielson Weng & Lichao Zhang & Andrew J. Hilmer & Lalla A. Fall & Kavya Swaminathan & Bana Jabri & Carolina Sousa & Nielsen Q. Fernandez-Becker & Chaitan Khosla & Joshua E. Elias, 2022. "An efficient urine peptidomics workflow identifies chemically defined dietary gluten peptides from patients with celiac disease," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    18. Kevin L. Yang & Fengchao Yu & Guo Ci Teo & Kai Li & Vadim Demichev & Markus Ralser & Alexey I. Nesvizhskii, 2023. "MSBooster: improving peptide identification rates using deep learning-based features," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34824-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.