HuBMAP tools and data are being used by researchers to advance discovery in their fields. View our publications to learn more about advances in single cell genomics, spatial mapping, and biomedical sciences.
Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging
Hickey JW, Neumann EK, Radtke AJ, Camarillo JM, Beuschel RT, Albanese A, McDonough E, Hatler J, Wiblin AE, Fisher J, Croteau J, Small EC, Sood A, Caprioli RM, Angelo RM, Nolan GP, Chung K, Hewitt SM, Germain RN, Spraggins JM, Lundberg E, Snyder MP, Kelleher NL, Saka SK.
Published In Nature Methods, November 2021.
This paper was born out of consortium meetings where many stakeholders in the field, including technology developers, users, vendors, funders, and publishers, were able to exchange perspectives and knowledge.
Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells have been largely based on single-cell sequencing approaches, which lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient depth, several multiplexed protein imaging methods have been recently developed. Though these technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this Perspective, we provide essential resources, key considerations for obtaining robust and reproducible imaging data, and specialized knowledge from domain experts and technology developers.
Andrea J. Radtke and Sinem K. Saka
- Tissue Mapping Center, Vanderbilt University (kidney)
- Tissue Mapping Center, Vanderbilt University (pancreas and eye)
- Tissue Mapping Center, Stanford University
- Transformative Technology Development, Harvard University
- Rapid Technology Implementation, Stanford University
- Rapid Technology Implementation, Northwestern University
- Rapid Technology Implementation, General Electric
NIH Award Nos. 1U54 DK120058-01, U54 EY032442, U54 HG010426-01, UG3 HL145600-01, UH3 CA246633-01, and UH3 CA246635-01
geneBasis: an iterative approach for unsupervised selection of targeted gene panels from scRNA-seq
Missarova A, Jain J, Butler A, Ghazanfar S, Stuart T, Brusko M, Wasserfall C, Nick H, Brusko T, Atkinson M, Satija R, Marioni JC.
scRNA-seq datasets are increasingly used to identify gene panels that can be probed using alternative technologies, such as spatial transcriptomics, where choosing the best subset of genes is vital. Existing methods are limited by a reliance on pre-existing cell type labels or by difficulties in identifying markers of rare cells. We introduce an iterative approach, geneBasis, for selecting an optimal gene panel, where each newly added gene captures the maximum distance between the true manifold and the manifold constructed using the currently selected gene panel. Our approach outperforms existing strategies and can resolve cell types and subtle cell state differences.
scRNA-seq spleen datasets
Obtained from the HuBMAP data portal. The HuBMAP dataset IDs are:
Rahul Satija and John Marioni
NIH Award Nos. 1OT2OD026673-01 and 1U54AI142766-01
The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells
Melani RD, Gerbasi VR, Anderson LC, Sikora JW, Toby TK, Hutton JE, Butcher DS, Negrão F, Seckler HS, Srzentić K, Fornelli L, Camarillo JM, LeDuc RD, Cesnik AJ, Lundberg E, Greer JB, Fellers RT, Robey MT, DeHart CJ, Forte E, Hendrickson CL, Abbatiello SE, Thomas PM, Kokaji AI, Levitsky J, Kelleher NL.
Human biology is tightly linked to proteins, yet most measurements do not precisely determine alternatively spliced sequences or posttranslational modifications. Here, we present the primary structures of ~30,000 unique proteoforms, nearly 10 times more than in previous studies, expressed from 1690 human genes across 21 cell types and plasma from human blood and bone marrow. The results, compiled in the Blood Proteoform Atlas (BPA), indicate that proteoforms better describe protein-level biology and are more specific indicators of differentiation than their corresponding proteins, which are more broadly expressed across cell types. We demonstrate the potential for clinical application, by interrogating the BPA in the context of liver transplantation and identifying cell and proteoform signatures that distinguish normal graft function from acute rejection and other causes of graft dysfunction.
Neil Kelleher and J Levitsky
NIH Award No. 1UH3CA246635-02