IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-36071-5.html
   My bibliography  Save this article

Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples

Author

Listed:
  • Reza Mirzazadeh

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Zaneta Andrusivova

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Ludvig Larsson

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Phillip T. Newton

    (Karolinska University Hospital)

  • Leire Alonso Galicia

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Xesús M. Abalo

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Mahtab Avijgan

    (Karolinska University Hospital)

  • Linda Kvastad

    (KTH Royal Institute of Technology, Science for Life Laboratory)

  • Alexandre Denadai-Souza

    (Katholieke Universiteit te Leuven)

  • Nathalie Stakenborg

    (Katholieke Universiteit te Leuven)

  • Alexandra B. Firsova

    (Wenner-Gren Institute, Stockholm University, Science for Life Laboratory)

  • Alia Shamikh

    (Karolinska Institutet
    Karolinska University Hospital)

  • Aleksandra Jurek

    (10x Genomics)

  • Niklas Schultz

    (Karolinska Institutet, BioClinicum, Karolinska University Hospital)

  • Monica Nistér

    (Karolinska Institutet, BioClinicum, Karolinska University Hospital)

  • Christos Samakovlis

    (Wenner-Gren Institute, Stockholm University, Science for Life Laboratory)

  • Guy Boeckxstaens

    (Katholieke Universiteit te Leuven)

  • Joakim Lundeberg

    (KTH Royal Institute of Technology, Science for Life Laboratory)

Abstract

Spatially resolved transcriptomics has enabled precise genome-wide mRNA expression profiling within tissue sections. The performance of methods targeting the polyA tails of mRNA relies on the availability of specimens with high RNA quality. Moreover, the high cost of currently available spatial resolved transcriptomics assays requires a careful sample screening process to increase the chance of obtaining high-quality data. Indeed, the upfront analysis of RNA quality can show considerable variability due to sample handling, storage, and/or intrinsic factors. We present RNA-Rescue Spatial Transcriptomics (RRST), a workflow designed to improve mRNA recovery from fresh frozen specimens with moderate to low RNA quality. First, we provide a benchmark of RRST against the standard Visium spatial gene expression protocol on high RNA quality samples represented by mouse brain and prostate cancer samples. Then, we test the RRST protocol on tissue sections collected from five challenging tissue types, including human lung, colon, small intestine, pediatric brain tumor, and mouse bone/cartilage. In total, we analyze 52 tissue sections and demonstrate that RRST is a versatile, powerful, and reproducible protocol for fresh frozen specimens of different qualities and origins.

Suggested Citation

  • Reza Mirzazadeh & Zaneta Andrusivova & Ludvig Larsson & Phillip T. Newton & Leire Alonso Galicia & Xesús M. Abalo & Mahtab Avijgan & Linda Kvastad & Alexandre Denadai-Souza & Nathalie Stakenborg & Ale, 2023. "Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36071-5
    DOI: 10.1038/s41467-023-36071-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-36071-5
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-36071-5?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. Rasa Elmentaite & Natsuhiko Kumasaka & Kenny Roberts & Aaron Fleming & Emma Dann & Hamish W. King & Vitalii Kleshchevnikov & Monika Dabrowska & Sophie Pritchard & Liam Bolt & Sara F. Vieira & Lira Mam, 2021. "Cells of the human intestinal tract mapped across space and time," Nature, Nature, vol. 597(7875), pages 250-255, September.
    2. Phillip T. Newton & Lei Li & Baoyi Zhou & Christoph Schweingruber & Maria Hovorakova & Meng Xie & Xiaoyan Sun & Lakshmi Sandhow & Artem V. Artemov & Evgeny Ivashkin & Simon Suter & Vyacheslav Dyachuk , 2019. "A radical switch in clonality reveals a stem cell niche in the epiphyseal growth plate," Nature, Nature, vol. 567(7747), pages 234-238, March.
    3. Branavan Manoranjan & Chitra Venugopal & David Bakhshinyan & Ashley A. Adile & Laura Richards & Michelle M. Kameda-Smith & Owen Whitley & Anna Dvorkin-Gheva & Minomi Subapanditha & Neil Savage & Nazan, 2020. "Wnt activation as a therapeutic strategy in medulloblastoma," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    4. Kyle J. Travaglini & Ahmad N. Nabhan & Lolita Penland & Rahul Sinha & Astrid Gillich & Rene V. Sit & Stephen Chang & Stephanie D. Conley & Yasuo Mori & Jun Seita & Gerald J. Berry & Joseph B. Shrager , 2020. "A molecular cell atlas of the human lung from single-cell RNA sequencing," Nature, Nature, vol. 587(7835), pages 619-625, November.
    5. Alma Andersson & Ludvig Larsson & Linnea Stenbeck & Fredrik Salmén & Anna Ehinger & Sunny Z. Wu & Ghamdan Al-Eryani & Daniel Roden & Alex Swarbrick & Åke Borg & Jonas Frisén & Camilla Engblom & Joakim, 2021. "Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    6. Anjali Rao & Dalia Barkley & Gustavo S. França & Itai Yanai, 2021. "Exploring tissue architecture using spatial transcriptomics," Nature, Nature, vol. 596(7871), pages 211-220, August.
    Full references (including those not matched with items on IDEAS)

    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. Arezou Rahimi & Luis A. Vale-Silva & Maria Fälth Savitski & Jovan Tanevski & Julio Saez-Rodriguez, 2024. "DOT: a flexible multi-objective optimization framework for transferring features across single-cell and spatial omics," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    2. Lulu Shang & Xiang Zhou, 2022. "Spatially aware dimension reduction for spatial transcriptomics," Nature Communications, Nature, vol. 13(1), pages 1-22, December.
    3. Honglei Ren & Benjamin L. Walker & Zixuan Cang & Qing Nie, 2022. "Identifying multicellular spatiotemporal organization of cells with SpaceFlow," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Xiaoxiao Wang & David Venet & Frédéric Lifrange & Denis Larsimont & Mattia Rediti & Linnea Stenbeck & Floriane Dupont & Ghizlane Rouas & Andrea Joaquin Garcia & Ligia Craciun & Laurence Buisseret & Mi, 2024. "Spatial transcriptomics reveals substantial heterogeneity in triple-negative breast cancer with potential clinical implications," Nature Communications, Nature, vol. 15(1), pages 1-22, December.
    5. Qiang Zhang & Sai Ma & Zhengzhi Liu & Bohan Zhu & Zirui Zhou & Gaoshan Li & J. Javier Meana & Javier González-Maeso & Chang Lu, 2023. "Droplet-based bisulfite sequencing for high-throughput profiling of single-cell DNA methylomes," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    6. Qingnan Liang & Yuefan Huang & Shan He & Ken Chen, 2023. "Pathway centric analysis for single-cell RNA-seq and spatial transcriptomics data with GSDensity," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    7. Pietro Demela & Nicola Pirastu & Blagoje Soskic, 2023. "Cross-disorder genetic analysis of immune diseases reveals distinct gene associations that converge on common pathways," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    8. Yuchen Liang & Guowei Shi & Runlin Cai & Yuchen Yuan & Ziying Xie & Long Yu & Yingjian Huang & Qian Shi & Lizhe Wang & Jun Li & Zhonghui Tang, 2024. "PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    9. Chenglong Sun & Anqiang Wang & Yanhe Zhou & Panpan Chen & Xiangyi Wang & Jianpeng Huang & Jiamin Gao & Xiao Wang & Liebo Shu & Jiawei Lu & Wentao Dai & Zhaode Bu & Jiafu Ji & Jiuming He, 2023. "Spatially resolved multi-omics highlights cell-specific metabolic remodeling and interactions in gastric cancer," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    10. Yuyao Liu & Zhen Li & Xiaoyang Chen & Xuejian Cui & Zijing Gao & Rui Jiang, 2025. "INSTINCT: Multi-sample integration of spatial chromatin accessibility sequencing data via stochastic domain translation," Nature Communications, Nature, vol. 16(1), pages 1-23, December.
    11. Susanne Kessler & Bradly Burke & Geoffroy Andrieux & Jan Schinköthe & Lea Hamberger & Johannes Kacza & Shijun Zhan & Clara Reasoner & Taru S. Dutt & Maria Kaukab Osman & Marcela Henao-Tamayo & Julian , 2024. "Deciphering bat influenza H18N11 infection dynamics in male Jamaican fruit bats on a single-cell level," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    12. Moujtaba Y. Kasmani & Paytsar Topchyan & Ashley K. Brown & Ryan J. Brown & Xiaopeng Wu & Yao Chen & Achia Khatun & Donia Alson & Yue Wu & Robert Burns & Chien-Wei Lin & Matthew R. Kudek & Jie Sun & We, 2023. "A spatial sequencing atlas of age-induced changes in the lung during influenza infection," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    13. Agnieska Brazovskaja & Tomás Gomes & Rene Holtackers & Philipp Wahle & Christiane Körner & Zhisong He & Theresa Schaffer & Julian Connor Eckel & René Hänsel & Malgorzata Santel & Makiko Seimiya & Timm, 2024. "Cell atlas of the regenerating human liver after portal vein embolization," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    14. Hua Zhang & Yuan Liu & Lauren Fields & Xudong Shi & Penghsuan Huang & Haiyan Lu & Andrew J. Schneider & Xindi Tang & Luigi Puglielli & Nathan V. Welham & Lingjun Li, 2023. "Single-cell lipidomics enabled by dual-polarity ionization and ion mobility-mass spectrometry imaging," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    15. Yuma Takano & Jun Suzuki & Kotaro Nomura & Gento Fujii & Junko Zenkoh & Hitomi Kawai & Yuta Kuze & Yukie Kashima & Satoi Nagasawa & Yuka Nakamura & Motohiro Kojima & Katsuya Tsuchihara & Masahide Seki, 2024. "Spatially resolved gene expression profiling of tumor microenvironment reveals key steps of lung adenocarcinoma development," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    16. Chuhan Wang & Adam S. Chan & Xiaohang Fu & Shila Ghazanfar & Jinman Kim & Ellis Patrick & Jean Y. H. Yang, 2025. "Benchmarking the translational potential of spatial gene expression prediction from histology," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    17. Johannes Wirth & Nina Huber & Kelvin Yin & Sophie Brood & Simon Chang & Celia P. Martinez-Jimenez & Matthias Meier, 2023. "Spatial transcriptomics using multiplexed deterministic barcoding in tissue," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    18. Akshaya Ramakrishnan & Aikaterini Symeonidi & Patrick Hanel & Katharina T. Schmid & Maria L. Richter & Michael Schubert & Maria Colomé-Tatché, 2023. "epiAneufinder identifies copy number alterations from single-cell ATAC-seq data," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    19. Michaela Schwaiger-Haber & Ethan Stancliffe & Dhanalakshmi S. Anbukumar & Blake Sells & Jia Yi & Kevin Cho & Kayla Adkins-Travis & Milan G. Chheda & Leah P. Shriver & Gary J. Patti, 2023. "Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    20. Xiaomeng Wan & Jiashun Xiao & Sindy Sing Ting Tam & Mingxuan Cai & Ryohichi Sugimura & Yang Wang & Xiang Wan & Zhixiang Lin & Angela Ruohao Wu & Can Yang, 2023. "Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope," Nature Communications, Nature, vol. 14(1), pages 1-22, 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:14:y:2023:i:1:d:10.1038_s41467-023-36071-5. 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.