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Cell2location maps fine-grained cell types in spatial transcriptomics

Cell2location maps fine-grained cell types in spatial transcriptomics

Summary

Spatial transcriptomic technologies promise to resolve cell wiring diagrams of tissues in successfully being and illness, but comprehensive mapping of cell styles in situ stays a problem. Right here we most up-to-date сell2location, a Bayesian model that can resolve lovely-grained cell styles in spatial transcriptomic recordsdata and grasp comprehensive cell maps of diverse tissues. Cell2location accounts for technical sources of variation and borrows statistical strength all over locations, thereby enabling the combination of single-cell and spatial transcriptomics with larger sensitivity and resolution than unusual tools. We assessed cell2location in three assorted tissues and tell improved mapping of lovely-grained cell styles. In the mouse brain, we realized lovely regional astrocyte subtypes all over the thalamus and hypothalamus. In the human lymph node, we spatially mapped a uncommon pre-germinal center B cell inhabitants. In the human gut, we resolved lovely immune cell populations in lymphoid follicles. Collectively, our results most up-to-date сell2location as a versatile diagnosis tool for mapping tissue architectures in a comprehensive system.

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Records availability

Records generated for this manuscript (snRNA-seq and Visium from adjoining sections within the mouse brain (Fig. 2a), sequencing reads as successfully as Cell Ranger and Dwelling Ranger output) were submitted to ArrayExpress below accession numbers E-MTAB-11114 (Visium) and E-MTAB-11115 (snRNA-seq). Annotated snRNA-seq recordsdata are publicly available via cellxgene portals64: elephantine dataset (annotation_1_print column denotes cell styles) and astrocyte subclusters. The constructed-in secondary lymphoid organ scRNA-seq recordsdata are publicly available for fetch by S3 bucket. Image recordsdata generated on this manuscript were deposited to the BioImage Archive (accession no. S-BIAD207).

Ground fact annotations of germinal center zones in lymph node Visium recordsdata can be realized on GitHub. Ground fact annotations of the gut lymphoid follicles can be realized on GitHub.

Printed datasets. snRNA-seq recordsdata from Yao et al. were downloaded from the Allen Brain Institute recordsdata portal. Scuttle-seq V2 recordsdata from Stickels et al. were downloaded from the Mountainous Institute recordsdata portal (discipline to spend agreement). Visium recordsdata of human lymph nodes can be downloaded from the 10x website (via a feature within the scanpy package).

Code availability

The cell2location package is equipped at https://github.com/BayraktarLab/cell2location/. Documentation and tutorials can be found in at https://cell2location.readthedocs.io/.

Code typical to generate synthetic recordsdata is equipped at https://github.com/vitkl/cell2location_paper/blob/master/notebooks/benchmarking/synthetic_data_construction_improved_real_mg.ipynb. Code typical to segment nuclei in histology photos is equipped at https://github.com/yozhikoff/segmentation. Jupyter notebooks covering the diagnosis on this paper can be found in at https://github.com/vitkl/cell2location_paper/ and upon practical quiz.

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Acknowledgements

We thank B. Velten, Y. Huang and L. Marconato for feedback on the cell2location model; M. Prete and V. Kiselev for dockerizing the cell2location tool and rising the fetch portals for sharing our recordsdata; N. Kumasaka for indispensable comments on single-cell diagnosis; S. Leonard and K. Polanski for assist with spatial and single-nucleus recordsdata processing; K. James for advice on gut immune cell styles; K. Roberts for advice on smFISH; J. E. Kwa for advice on snRNA-seq; J. Eliasova for illustrations and designate grasp; K. James advice on human gut immune cells; A. Antanaviciute, H. Koohy and A. Simmons for sharing gut Visium recordsdata; F. Obermeyer and M. Jankowiak for assist with stepped forward spend of pyro code depraved; and D. Rowitch and S. Teichmann for comments on the manuscript. H.W.K. used to be funded by a Sir Henry Wellcome Postdoctoral Fellowship (213555/Z/18/Z). This look used to be supported by Wellcome Have confidence Core Funding to O.A.B.

Author recordsdata

Affiliations

  1. Wellcome Sanger Institute, Hinxton, Cambridge, UK

    Vitalii Kleshchevnikov, Artem Shmatko, Emma Dann, Alexander Aivazidis, Hamish W. King, Tong Li, Rasa Elmentaite, Veronika Kedlian, Mika Sarkin Jain, Jun Sung Park, Lauma Ramona, Elizabeth Tuck, Anna Arutyunyan, Roser Vento-Tormo, Oliver Stegle & Omer Ali Bayraktar

  2. Moscow Affirm College, Leninskie Gory, Moscow, Russia

    Artem Shmatko

  3. Centre for Immunobiology, Blizard Institute, Queen Mary College of London, London, UK

    Hamish W. King & Louisa James

  4. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK

    Artem Lomakin, Jun Sung Park & Moritz Gerstung

  5. European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany

    Artem Lomakin, Moritz Gerstung & Oliver Stegle

  6. Center for Computational Biology, College of California, Berkeley, Berkeley CA, USA

    Adam Gayoso

  7. Thought of Condensed Matter, Department of Physics, Cavendish Laboratory, College of Cambridge, Cambridge, UK

    Mika Sarkin Jain

  8. Division of Computational Genomics and Methods Genetics, German Cancer Compare Center (DKFZ), Heidelberg, Germany

    Oliver Stegle

Contributions

V.K., O.S. and O.A.B. conceived the look. V.K. developed and implemented the cell2location model with feedback from O.S. and labored on validation, mouse brain, human lymph node, gut and benchmarking analyses. A.S. conducted Scuttle-seq and hyperparameter sensitivity diagnosis, conducted histology portray segmentation, wrote recordsdata visualization modules and contributed to implementation of cell2location in pyro and benchmarking analyses. E.D. labored on producing synthetic recordsdata, mouse brain cell annotation and validation of cell kind mapping and contributed to lymph node diagnosis. V.KE. and A.S. contributed to the enchancment and interpretation of the model for estimating cell kind signatures. A.L., M.G., A.A.I. and M.S.J. contributed to the rising of model structure, writing the model and downstream diagnosis code, interpretation of the cell2location results as successfully as downstream clustering and NMF. A.A.R. conducted benchmarking of stereoscope, supervised by R.V.-T. and O.S. A.G. contributed to implementation of cell2location the spend of scvi-tools and pyro. H.W.K. contributed to lymph node recordsdata diagnosis and interpretation, supervised by L.J. R.E. contributed to gut recordsdata diagnosis. L.R. conducted snRNA-seq experiments. L.T. conducted Visium experiments. J.S.P. conducted smFISH experiments and imaging. T.L. conducted smFISH portray processing and astrocyte segmentation diagnosis. V.K., O.S. and O.A.B. wrote the manuscript, with feedback from all authors.

Corresponding authors

Correspondence to
Oliver Stegle or Omer Ali Bayraktar.

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Competing interests

The authors notify no competing interests.

Additional recordsdata

Perceive evaluate recordsdata Nature Biotechnology thanks Steven Sloan, Xiaoqun Wang and the opposite, nameless, reviewer(s) for their contribution to the hit upon evaluate of this work.

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Supplementary recordsdata

Supplementary Files

Supplementary Figs. 1–27 and Supplementary Methods

Supplementary Recordsdata 1–13

Supplementary Recordsdata 1–13 tell spatial cell and mRNA abundance (color) of all cell styles (panels) estimated by cell2location in 10x Visium recordsdata for the respective tissues and samples.

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Kleshchevnikov, V., Shmatko, A., Dann, E. et al. Cell2location maps lovely-grained cell styles in spatial transcriptomics.
Nat Biotechnol (2022). https://doi.org/10.1038/s41587-021-01139-4

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