Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

An Author Correction to this article was published on 01 March 2024

This article has been updated

Abstract

The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Molecular coverage and spatial scale of different assay types.
Fig. 2: Organs and assay types publicly available via the HuBMAP portal (as of May 2023).
Fig. 3: Unique FTU neighbourhoods in different biological contexts in the human body.
Fig. 4: New technologies, resources, integrated knowledge base and mapping in the production phase.

Similar content being viewed by others

Code availability

The HuBMAP Consortium GitHub at https://github.com/hubmapconsortium has 120 repositories that support data ingest, analysis, visualization and search plus HRA construction and usage. Documentation is available at https://software.docs.hubmapconsortium.org/apis.html.

Change history

References

  1. Snyder, M. P. et al. The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature 574, 187–192 (2019).

    Article  ADS  Google Scholar 

  2. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Börner, K. et al. Anatomical structures, cell types and biomarkers of the Human Reference Atlas. Nat. Cell Biol. 23, 1117–1128 (2021).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  4. Hickey, J. W. et al. Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging. Nat. Methods 19, 284–295 (2022).

    Article  CAS  PubMed  Google Scholar 

  5. Quardokus, E. M. et al. Organ Mapping Antibody Panels: a community resource for standardized multiplexed tissue imaging. Nat. Methods https://doi.org/10.1038/s41592-023-01846-7 (2023).

  6. Neumann, E. K. et al. A multiscale lipid and cellular atlas of the human kidney. Preprint at bioRxiv https://doi.org/10.1101/2022.04.07.487155 (2022).

  7. Ghose, S. et al. Human digital twin: automated cell type distance computation and 3D atlas construction in multiplexed skin biopsies. Preprint at bioRxiv https://doi.org/10.1101/2022.03.30.486438 (2022).

  8. Canela, V. H. et al. A spatially anchored transcriptomic atlas of the human kidney papilla identifies significant immune injury and matrix remodeling in patients with stone disease. Nat. Commun. https://doi.org/10.1038/s41467-023-38975-8 (2023).

  9. Hickey, J. et al. High resolution single cell maps reveals distinct cell organization and function across different regions of the human intestine. Nature https://doi.org/10.1038/s41586-023-05915-x (2023).

  10. Greenbaum, S. et al. Spatiotemporal coordination at the maternal–fetal interface promotes trophoblast invasion and vascular remodeling in the first half of human pregnancy. Nature https://doi.org/10.1038/s41586-023-06298-9 (2023).

  11. Blue, B. L. et al. An atlas of healthy and injured cell states and niches in the human kidney. Nature https://doi.org/10.1038/s41586-023-05769-3 (2023).

  12. Eng, C.-H. L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH. Nature 568, 235–239 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  13. Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  14. Guilliams, M. et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell 185, 379–396.e38 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Stelzer, E. H. K. Light-sheet fluorescence microscopy for quantitative biology. Nat. Methods 12, 23–26 (2015).

    Article  CAS  PubMed  Google Scholar 

  16. Black, S. et al. CODEX multiplexed tissue imaging with DNA-conjugated antibodies. Nat. Protoc. 16, 3802–3835 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Neumann, E. K. et al. Protocol for multimodal analysis of human kidney tissue by imaging mass spectrometry and CODEX multiplexed immunofluorescence. STAR Protoc. 2, 100747 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Spraggins, J. M. et al. High-performance molecular imaging with MALDI trapped ion-mobility time-of-flight (timsTOF) mass spectrometry. Anal. Chem. 91, 14552–14560 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Börner, K. et al. Tissue registration and exploration user interfaces in support of a human reference atlas. Commun. Biol. 5, 1369 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Rozenblatt-Rosen, O. et al. The Human Tumor Atlas Network: charting tumor transitions across space and time at single-cell resolution. Cell 181, 236–249 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Rozenblatt-Rosen, O., Stubbington, M. J. T., Regev, A. & Teichmann, S. A. The Human Cell Atlas: from vision to reality. Nature 550, 451–453 (2017).

    Article  ADS  CAS  PubMed  Google Scholar 

  22. Mungall, C. J., Torniai, C., Gkoutos, G. V., Lewis, S. E. & Haendel, M. A. Uberon, an integrative multi-species anatomy ontology. Genome Biol. 13, R5 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Rosse, C. & Mejino, J. L. V. A reference ontology for biomedical informatics: the Foundational Model of Anatomy. J. Biomed. Inform. 36, 478–500 (2003).

    Article  PubMed  Google Scholar 

  24. Golbreich, C., Grosjean, J. & Darmoni, S. J. The Foundational Model of Anatomy in OWL 2 and its use. Artif. Intell. Med. 57, 119–132 (2013).

    Article  PubMed  Google Scholar 

  25. Meehan, T. F. et al. Logical development of the cell ontology. BMC Bioinform. 12, 6 (2011).

    Article  Google Scholar 

  26. Eraslan, G. et al. Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function. Science 376, eabl4290 (2022).

  27. de Boer, I. H. et al. Rationale and design of the Kidney Precision Medicine Project. Kidney Int. 99, 496–510 (2021).

    Article  Google Scholar 

  28. Manz, T. et al. Viv: multiscale visualization of high-resolution multiplexed bioimaging data on the web. Nat. Methods 19, 515–516 (2022).

  29. Lee, P. J. et al. NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health. Nat. Aging 2, 1090–1100 (2022).

    Article  Google Scholar 

  30. Keren, L. et al. MIBI-TOF: a multiplexed imaging platform relates cellular phenotypes and tissue structure. Sci. Adv. 5, eaax5851 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  31. He, S. et al. High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging. Nat. Biotechnol. 40, 1794–1806 (2022).

    Article  CAS  PubMed  Google Scholar 

  32. Tian, H. et al. Successive high-resolution (H2O)n-GCIB and C60-SIMS imaging integrates multi-omics in different cell types in breast cancer tissue. Anal. Chem. 93, 8143–8151 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Xu, T.-Y., Calandrelli, R., Lin, P., Zhu, D. & Zhong, S. HiFi-Slide spatial RNA-sequencing. Protocol.io https://doi.org/10.17504/protocols.io.3byl4by18vo5/v1 (2022).

  34. Fung, A. A. & Shi, L. Mammalian cell and tissue imaging using Raman and coherent Raman microscopy. Wiley Interdiscip. Rev. Syst. Biol. Med. 12, e1501 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Zhang, W. et al. Multi-molecular hyperspectral PRM-SRS imaging. Preprint at bioRxiv https://doi.org/10.1101/2022.07.25.501472 (2022).

  36. Balaratnasingam, C. et al. Histologic and optical coherence tomographic correlates in drusenoid pigment epithelium detachment in age-related macular degeneration. Ophthalmology 124, 644–656 (2017).

    Article  PubMed  Google Scholar 

  37. Spaide, R. F. & Curcio, C. A. Anatomical correlates to the bands seen in the outer retina by optical coherence tomography: literature review and model. Retina 31, 1609 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zhu, Y. et al. Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells. Nat. Commun. 9, 882 (2018).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  39. Ardini-Poleske, M. E. et al. LungMAP: the molecular atlas of lung development program. Am. J. Physiol. Lung Cell. Mol. Physiol. 313, L733–L740 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Uhlén, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).

    Article  PubMed  Google Scholar 

  41. Lonsdale, J. et al. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580–585 (2013).

    Article  CAS  Google Scholar 

  42. Brbić, M. et al. Annotation of spatially resolved single-cell data with STELLAR. Nat. Methods 19, 1411–1418 (2022).

    Article  PubMed  Google Scholar 

  43. Govind, D. et al. PodoSighter: A cloud-based tool for label-free podocyte detection in kidney whole-slide images. J. Am. Soc. Nephrol. 32, 2795–2813 (2021).

  44. Lutnick, B. et al. A user-friendly tool for cloud-based whole slide image segmentation with examples from renal histopathology. Commun. Med. 2, 105–109 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Van de Plas, R., Yang, J., Spraggins, J. & Caprioli, R. M. Image fusion of mass spectrometry and microscopy: a multimodality paradigm for molecular tissue mapping. Nat. Methods 12, 366–372 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Tideman, L. E. M. et al. Automated biomarker candidate discovery in imaging mass spectrometry data through spatially localized Shapley additive explanations. Anal. Chim. Acta 1177, 338522 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Weber, G. M., Ju, Y. & Börner, K. Considerations for using the vasculature as a coordinate system to map all the cells in the human body. Front. Cardiovasc. Med. 7, 29 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Melani, R. D. et al. The Blood Proteoform Atlas: a reference map of proteoforms in human hematopoietic cells. Science 375, 411–418 (2022).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  49. Mackenzie, N. J. et al. Modelling the tumor immune microenvironment for precision immunotherapy. Clin. Transl. Immunol. 11, e1400 (2022).

    Article  CAS  Google Scholar 

  50. Becker, W. R. et al. Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer. Nat. Genet. 54, 985–995 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Wallace, D. C. Mitochondrial DNA variation in human radiation and disease. Cell 163, 33–38 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Wallace, D. C. Mitochondrial genetic medicine. Nat. Genet. 50, 1642–1649 (2018).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank L. M. McGuire, SciStories, F. Goncalves, H. Schlehlein and V. A. Deshpande for their efforts in designing and creating graphics. We thank A. Honkala for assistance with manuscript formatting. We thank Z. Galis from the National Heart, Lung, and Blood Institute for many useful comments. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. The authors gratefully acknowledge NIH HuBMAP grants U54HL165442 and U01HL166058 (L.P.); U54DK134301 and OT2OD033753 (S.J.); U54EY032442, U54DK120058 and U54DK134302 (J.M.S.); OT2OD033756 and OT2OD026671 (K.B.); UH3CA246635 (N.L.K.); UG3CA256967 (H.L.); U54HG010426 (M.P.S.); UH3CA246633 (M.A.); U54HD104393 (L.C.L. and P.R.); U54DK127823 (E.S.N., J.P.C. and W.-J.Q.); OT2OD033758 (N.G.); UH3CA246594 (F.G.); U54EY032442 and U54DK134302 (J.P.G.); U54HL145611 (S.L. and Y.L.); U01HG012680 (A.N.); U54DK120058, U54EY032442 and U54DK134302 (B.R.S.); UG3CA256959 (M.Z.); and U54HL165440 (I.S.V.). The authors are also supported by these grants: 2U01DK114933, P50DK133943 and U24DK135157 (S.J.); U54HL145608 and U54HL165443 (J.S.H.); U24CA268108 and U2CDK114886 (K.B.); Department of Defense W81XWH-22-1-0058 and Additional Ventures (L.P.). J.W.H. was supported by an NIH T32 Fellowship (T32CA196585) and an American Cancer Society: Roaring Fork Valley Postdoctoral Fellowship (PF-20-032-01-CSM). This work was supported, in part, by the Intramural Research Program of the NIH, National Institute of Allergy and Infectious Diseases (NIAID) and National Cancer Institute (NCI) (A.J.R.).

Author information

Authors and Affiliations

Authors

Consortia

Contributions

S.J., L.P., J.M.S., K.B. and M.P.S. conceived the idea and wrote the first draft of the manuscript and revisions. M.A., J.P.C., N.G., F.G., J.P.G., J.S.H., J.W.H., N.L.K., L.C.L., S.L., Y.L., H.L., A.N., E.S.N., W.-J.Q., A.R., P.R., B.R.S., R.V., I.S.V. and M.Z. contributed to manuscript revision.

Corresponding authors

Correspondence to Sanjay Jain, Liming Pei, Jeffrey M. Spraggins, Katy Börner or Michael P. Snyder.

Ethics declarations

Competing interests

The authors declare the following competing interests. F.G. is an employee of GE Research. B.R.S. is an inventor on patents and patent applications involving small-molecule-drug discovery and the 3F3 anti-Ferroptotic Membrane (3F3-FMA) antibody; co-founded and serves as a consultant to Inzen Therapeutics, Nevrox, Exarta Therapeutics and ProJenX; and serves as a consultant to Weatherwax Biotechnologies and Akin Gump Strauss Hauer and Feld. M.P.S. is a co-founder and an advisory board member of Personalis, Qbio, January AI, Mirvie, Filtricine, Fodsel, Lollo and Protos. I.S.V. consults for Guidepoint Global, Cowen, Mosaic and NextRNA. N.G. is a co-founder and an equity owner of Datavisyn. H.L. is a co-founder and an equity owner of ExoMira Medicine. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jain, S., Pei, L., Spraggins, J.M. et al. Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP). Nat Cell Biol 25, 1089–1100 (2023). https://doi.org/10.1038/s41556-023-01194-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41556-023-01194-w

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing