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386 results on '"Spraggins, Jeffrey M."'

1. Harmonizing the Generation and Pre-publication Stewardship of FAIR Image Data

Author

Bialy, Nikki, Alber, Frank, Andrews, Brenda, Angelo, Michael, Beliveau, Brian, Bintu, Lacramioara, Boettiger, Alistair, Boehm, Ulrike, Brown, Claire M., Maina, Mahmoud Bukar, Chambers, James J., Cimini, Beth A., Eliceiri, Kevin, Errington, Rachel, Faklaris, Orestis, Gaudreault, Nathalie, Germain, Ronald N., Goscinski, Wojtek, Grunwald, David, Halter, Michael, Hanein, Dorit, Hickey, John W., Lacoste, Judith, Laude, Alex, Lundberg, Emma, Ma, Jian, Malacrida, Leonel, Moore, Josh, Nelson, Glyn, Neumann, Elizabeth Kathleen, Nitschke, Roland, Onami, Shuichi, Pimentel, Jaime A., Plant, Anne L., Radtke, Andrea J., Sabata, Bikash, Schapiro, Denis, Schöneberg, Johannes, Spraggins, Jeffrey M., Sudar, Damir, Vierdag, Wouter-Michiel Adrien Maria, Volkmann, Niels, Wählby, Carolina, Siyuan, Wang, Yaniv, Ziv, and Strambio-De-Castillia, Caterina

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured image data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable image data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled Enabling Global Image Data Sharing in the Life Sciences, which is published in parallel and addresses the need to build the cyberinfrastructure for sharing the digital array data. In this White Paper, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse image data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made considerable progress toward generating community standard practices for imaging Quality Control (QC) and metadata. We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges and democratize access to everyday practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location., Comment: This manuscript is published with a closely related companion entitled, Enabling Global Image Data Sharing in the Life Sciences, which can be found at the following link, arXiv:2401.13023 [q-bio.OT]

Published
2024

2. Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement

Author

Lee, Ho Hin, Saunders, Adam M., Kim, Michael E., Remedios, Samuel W., Remedios, Lucas W., Tang, Yucheng, Yang, Qi, Yu, Xin, Bao, Shunxing, Cho, Chloe, Mawn, Louise A., Rex, Tonia S., Schey, Kevin L., Dewey, Blake E., Spraggins, Jeffrey M., Prince, Jerry L., Huo, Yuankai, and Landman, Bennett A.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Purpose: Eye morphology varies significantly across the population, especially for the orbit and optic nerve. These variations limit the feasibility and robustness of generalizing population-wise features of eye organs to an unbiased spatial reference. Approach: To tackle these limitations, we propose a process for creating high-resolution unbiased eye atlases. First, to restore spatial details from scans with a low through-plane resolution compared to a high in-plane resolution, we apply a deep learning-based super-resolution algorithm. Then, we generate an initial unbiased reference with an iterative metric-based registration using a small portion of subject scans. We register the remaining scans to this template and refine the template using an unsupervised deep probabilistic approach that generates a more expansive deformation field to enhance the organ boundary alignment. We demonstrate this framework using magnetic resonance images across four different tissue contrasts, generating four atlases in separate spatial alignments. Results: For each tissue contrast, we find a significant improvement using the Wilcoxon signed-rank test in the average Dice score across four labeled regions compared to a standard registration framework consisting of rigid, affine, and deformable transformations. These results highlight the effective alignment of eye organs and boundaries using our proposed process. Conclusions: By combining super-resolution preprocessing and deep probabilistic models, we address the challenge of generating an eye atlas to serve as a standardized reference across a largely variable population., Comment: Revised for submission to SPIE Journal of Medical Imaging. 26 pages, 6 figures

Published
2024

3. Multi-Contrast Computed Tomography Atlas of Healthy Pancreas

Author

Zhou, Yinchi, Lee, Ho Hin, Tang, Yucheng, Yu, Xin, Yang, Qi, Bao, Shunxing, Spraggins, Jeffrey M., Huo, Yuankai, and Landman, Bennett A.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

With the substantial diversity in population demographics, such as differences in age and body composition, the volumetric morphology of pancreas varies greatly, resulting in distinctive variations in shape and appearance. Such variations increase the difficulty at generalizing population-wide pancreas features. A volumetric spatial reference is needed to adapt the morphological variability for organ-specific analysis. Here, we proposed a high-resolution computed tomography (CT) atlas framework specifically optimized for the pancreas organ across multi-contrast CT. We introduce a deep learning-based pre-processing technique to extract the abdominal region of interests (ROIs) and leverage a hierarchical registration pipeline to align the pancreas anatomy across populations. Briefly, DEEDs affine and non-rigid registration are performed to transfer patient abdominal volumes to a fixed high-resolution atlas template. To generate and evaluate the pancreas atlas template, multi-contrast modality CT scans of 443 subjects (without reported history of pancreatic disease, age: 15-50 years old) are processed. Comparing with different registration state-of-the-art tools, the combination of DEEDs affine and non-rigid registration achieves the best performance for the pancreas label transfer across all contrast phases. We further perform external evaluation with another research cohort of 100 de-identified portal venous scans with 13 organs labeled, having the best label transfer performance of 0.504 Dice score in unsupervised setting. The qualitative representation (e.g., average mapping) of each phase creates a clear boundary of pancreas and its distinctive contrast appearance. The deformation surface renderings across scales (e.g., small to large volume) further illustrate the generalizability of the proposed atlas template.

Published
2023

8. New views of old proteins: clarifying the enigmatic proteome

Author

Functional, Participants in a NIH Workshop on, Proteomics, Integrative, Johnson, Kristin E. Burnum, Conrads, Thomas P., Drake, Richard R., Herr, Amy E., Iyengar, Ravi, Kelly, Ryan T., Lundberg, Emma, MacCoss, Michael J., Naba, Alexandra, Nolan, Garry P., Pevzner, Pavel A., Rodland, Karin D., Sechi, Salvatore, Slavov, Nikolai, Spraggins, Jeffrey M., Van Eyk, Jennifer E., Vidal, Marc, Vogel, Christine, Walt, David R., and Kelleher, Neil L.

Subjects
Quantitative Biology - Biomolecules
Abstract

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide provocative projections for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we offer potential futures for a next generation of disruptive approaches to define, quantify and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade., Comment: Submitted to Nature. 22 Pages. 6 Figures. Corresponding author Neil L. Kelleher

Published
2021

9. Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

Author

Hickey, John W., Neumann, Elizabeth K., Radtke, Andrea J., Camarillo, Jeannie M., Beuschel, Rebecca T., Albanese, Alexandre, McDonough, Elizabeth, Hatler, Julia, Wiblin, Anne E., Fisher, Jeremy, Croteau, Josh, Small, Eliza C., Sood, Anup, Caprioli, Richard M., Angelo, R. Michael, Nolan, Garry P., Chung, Kwanghun, Hewitt, Stephen M., Germain, Ronald N., Spraggins, Jeffrey M., Lundberg, Emma, Snyder, Michael P., Kelleher, Neil L., and Saka, Sinem K.

Subjects
Quantitative Biology - Tissues and Organs
Abstract

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 are largely based on transcriptomic single-cell approaches that lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient coverage depth, several multiplexed protein imaging methods have recently been developed. Though these antibody-based 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 and key considerations for obtaining robust and reproducible multiplexed antibody-based imaging data compiling specialized knowledge from domain experts and technology developers., Comment: {\ddag}authors contributed equally to this work

Published
2021

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

Author

Jain, Sanjay, Pei, Liming, Spraggins, Jeffrey M., Angelo, Michael, Carson, James P., Gehlenborg, Nils, Ginty, Fiona, Gonçalves, Joana P., Hagood, James S., Hickey, John W., Kelleher, Neil L., Laurent, Louise C., Lin, Shin, Lin, Yiing, Liu, Huiping, Naba, Alexandra, Nakayasu, Ernesto S., Qian, Wei-Jun, Radtke, Andrea, Robson, Paul, Stockwell, Brent R., Van de Plas, Raf, Vlachos, Ioannis S., Zhou, Mowei, Börner, Katy, and Snyder, Michael P.

Published
2023
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11. Author Correction: Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

Author

Jain, Sanjay, Pei, Liming, Spraggins, Jeffrey M., Angelo, Michael, Carson, James P., Gehlenborg, Nils, Ginty, Fiona, Gonçalves, Joana P., Hagood, James S., Hickey, John W., Kelleher, Neil L., Laurent, Louise C., Lin, Shin, Lin, Yiing, Liu, Huiping, Naba, Alexandra, Nakayasu, Ernesto S., Qian, Wei-Jun, Radtke, Andrea, Robson, Paul, Stockwell, Brent R., Van de Plas, Raf, Vlachos, Ioannis S., Zhou, Mowei, Börner, Katy, and Snyder, Michael P.

Published
2024
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12. Multi-Contrast Computed Tomography Healthy Kidney Atlas

Author

Lee, Ho Hin, Tang, Yucheng, Xu, Kaiwen, Bao, Shunxing, Fogo, Agnes B., Harris, Raymond, de Caestecker, Mark P., Heinrich, Mattias, Spraggins, Jeffrey M., Huo, Yuankai, and Landman, Bennett A.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

The construction of three-dimensional multi-modal tissue maps provides an opportunity to spur interdisciplinary innovations across temporal and spatial scales through information integration. While the preponderance of effort is allocated to the cellular level and explore the changes in cell interactions and organizations, contextualizing findings within organs and systems is essential to visualize and interpret higher resolution linkage across scales. There is a substantial normal variation of kidney morphometry and appearance across body size, sex, and imaging protocols in abdominal computed tomography (CT). A volumetric atlas framework is needed to integrate and visualize the variability across scales. However, there is no abdominal and retroperitoneal organs atlas framework for multi-contrast CT. Hence, we proposed a high-resolution CT retroperitoneal atlas specifically optimized for the kidney across non-contrast CT and early arterial, late arterial, venous and delayed contrast enhanced CT. Briefly, we introduce a deep learning-based volume of interest extraction method and an automated two-stage hierarchal registration pipeline to register abdominal volumes to a high-resolution CT atlas template. To generate and evaluate the atlas, multi-contrast modality CT scans of 500 subjects (without reported history of renal disease, age: 15-50 years, 250 males & 250 females) were processed. We demonstrate a stable generalizability of the atlas template for integrating the normal kidney variation from small to large, across contrast modalities and populations with great variability of demographics. The linkage of atlas and demographics provided a better understanding of the variation of kidney anatomy across populations., Comment: 8 pages, 5 figures

Published
2020

13. High-Resolution Imaging Mass Spectrometry of Human Donor Eye: Photoreceptors Cells and Basal Laminar Deposit of Age-Related Macular Degeneration

Author

Anderson, David M. G., Kotnala, Ankita, Messinger, Jeffrey D., Patterson, Nathan Heath, Spraggins, Jeffrey M., Curcio, Christine A., Caprioli, Richard M., Schey, Kevin L., Crusio, Wim E., Series Editor, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, Ash, John D., editor, Pierce, Eric, editor, Anderson, Robert E., editor, Bowes Rickman, Catherine, editor, Hollyfield, Joe G., editor, and Grimm, Christian, editor

Published
2023
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14. Construction and Usage of a Human Body Common Coordinate Framework Comprising Clinical, Semantic, and Spatial Ontologies

Author

Börner, Katy, Quardokus, Ellen M., Herr II, Bruce W., Cross, Leonard E., Record, Elizabeth G., Ju, Yingnan, Bueckle, Andreas D., Sluka, James P., Silverstein, Jonathan C., Browne, Kristen M., Jain, Sanjay, Wasserfall, Clive H., Jorgensen, Marda L., Spraggins, Jeffrey M., Patterson, Nathan H., Musen, Mark A., and Weber, Griffin M.

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computation and Language, Computer Science - Digital Libraries
Abstract

The National Institutes of Health's (NIH) Human Biomolecular Atlas Program (HuBMAP) aims to create a comprehensive high-resolution atlas of all the cells in the healthy human body. Multiple laboratories across the United States are collecting tissue specimens from different organs of donors who vary in sex, age, and body size. Integrating and harmonizing the data derived from these samples and 'mapping' them into a common three-dimensional (3D) space is a major challenge. The key to making this possible is a 'Common Coordinate Framework' (CCF), which provides a semantically annotated, 3D reference system for the entire body. The CCF enables contributors to HuBMAP to 'register' specimens and datasets within a common spatial reference system, and it supports a standardized way to query and 'explore' data in a spatially and semantically explicit manner. [...] This paper describes the construction and usage of a CCF for the human body and its reference implementation in HuBMAP. The CCF consists of (1) a CCF Clinical Ontology, which provides metadata about the specimen and donor (the 'who'); (2) a CCF Semantic Ontology, which describes 'what' part of the body a sample came from and details anatomical structures, cell types, and biomarkers (ASCT+B); and (3) a CCF Spatial Ontology, which indicates 'where' a tissue sample is located in a 3D coordinate system. An initial version of all three CCF ontologies has been implemented for the first HuBMAP Portal release. It was successfully used by Tissue Mapping Centers to semantically annotate and spatially register 48 kidney and spleen tissue blocks. The blocks can be queried and explored in their clinical, semantic, and spatial context via the CCF user interface in the HuBMAP Portal., Comment: 24 pages with SI, 6 figures, 5 tables

Published
2020

16. Participant Experience with Protocol Research Kidney Biopsies in the Kidney Precision Medicine Project

Author

Victoria-Castro, Angela M., Corona-Villalobos, Celia P., Xu, Alan Y., Onul, Ingrid, Huynh, Courtney, Chen, Sarah W., Ugwuowo, Ugochukwu, Sarkisova, Natalya, Dighe, Ashveena L., Blank, Kristina N., Blanc, Victoria M., Rose, Michael P., Himmelfarb, Jonathan, de Boer, Ian H., Tuttle, Katherine R., Roberts, Glenda V., Alexandrov, Theodore, Alloway, Rita R., Alpers, Charles E., Amodu, Afolarin A., Anderton, Christopher R., Anjani, Kavya, Appelbaum, Paul, Ardayfio, Joseph, Arora, Tanima, Ascani, Heather, El-Achkar, Tarek M., Aulisio, Mark, Azeloglu, Evren U., Balderes, Olivia, Balis, Ulysses G.J., Bansal, Shweta, Barasch, Jonathan M., Bansal, Shweta, Barkell, Alex, Barwinska, Daria, Basit, Mujeeb, Basta, Jeanine, Bebiak, Jack, Beck, Laurence H., Bender, Filitsa, Berglund, Ashley, Bernard, Lauren, Berrouet, Cecilia, Berry, Brooke, Bjornstad, Petter M., Blanc, Victoria M., Blank, Kristina N., Bledsoe, Sharon, Boada, Patrick, Bogen, Steve, Bomback, Andrew S., Bonevich, Nikole, Borner, Katy, Brown, Keith, Bueckle, Andreas, Burg, Ashley R., Burgess, Adam, Bush, Lakeshia, Bush, William S., Campbell, Catherine E., Campbell, Taneisha, Canetta, Pietro A., Cantley, Lloyd G., Caprioli, Richard M., Carson, Jonas, Chen, Sarah, Chen, Yijiang M., Cheng, Yinghua, Cimino, Jim, Colona, Mia R., Conser, Ninive C., Cooperman, Leslie, Crawford, Dana C., DʼAgati, Vivette D., Dagher, Pierre C., Daniel, Stephen, Daratha, Kenn, de Boer, Ian H., Diettman, Sabine M., Dighe, Ashveena L., Donohoe, Isabel, Dowd, Frederick, Dunn, Kenneth W., Eadon, Michael T., Eddy, Sean, Elder, Michele M., Ferkowicz, Michael J., Frey, Renee, Gadegbeku, Crystal A., Gaut, Joseph P., Gilliam, Matthew, Ginley, Brandon, Gisch, Debora, Goltsev, Yury, Gonzalez-Vicente, Agustin, Greka, Anna, Grewenow, Stephanie M., Hacohen, Nir, Hall, Daniel E., Hansen, Jens, Hayashi, Lynda, He, Cijang, He, Yougqun, Hedayati, S. Susan, Henderson, Joel M., Hendricks, Allen H., Herlitz, Leal, Herr, Bruce W., Himmelfarb, Jonathan, Hodgin, Jeffrey B., Hoofnagle, Andrew N., Hoover, Paul J., Ilori, Titlayo, Iyengar, Ravi, Jain, Sanjay, Jain, Yashvardhan, Janowczyk, Andrew, Jefferson, Nichole, Johansen, Camille, Jolly, Stacey, Kakade, Vijaykumar R., Kellum, John A., Kelly, Katherine J., Kermani, Asra, Kiryluk, Krzysztof, Knight, Richard, Koewler, Robert, Kretzler, Matthias, Kudose, Satoru, Lake, Blue B., Larson, Brandon, Laszik, Zoltan G., Lecker, Stewart H., Lee, Paul J., Lee, Simon C., Lienczewski, Chrysta, Limonte, Christine, Lu, Christopher Y., Lucarelli, Nicholas, Lukowski, Jessica, Luo, Jinghui, Lutnick, Brendon, Ma, Shihong, Madabhushi, Anant, Madhavan, Sethu M., Maikhor, Shana, Mariani, Laura H., Marshall, Jamie L., McClelland, Robyn L., McMahon, Gearoid M., Mehl, Karla, Ferreira, Ricardo Melo, Menez, Steven, Menon, Rajasree, Miller, R. Tyler, Moe, Orson W., Moledina, Dennis, Montellano, Richard, Mooney, Sean D., Morales, Martha Catalina, Mukatash, Tariq, Murugan, Raghavan, Nam, Yunbi, Nguyen, Jane, Nolan, Garry, Oʼtoole, John, Oliver, George (Holt), Onul, Ingrid, Otto, Edgar, Palevsky, Paul M., Palmer, Ellen, Pamreddy, Annapurna, Parikh, Chirag R., Parikh, Samir, Park, Christopher, Park, Harold, Pasa-Tolic, Ljiljana, Patel, Jiten, Patterson, Nathan, Phuong, Jim, Pillai, Anil, Pinkeney, Roy, Poggio, Emilio, Pollack, Ari, Prasad, Pottumarthi, Pyle, Laura, Quardokus, Ellen M., Randhawa, Parmjeet, Rauchman, Michael I., Record, Elizabeth, Rennke, Helmut, Rezaei, Kasra, Rike, Adele, Rivera, Marcelino, Roberts, Glenda V., Rosas, Sylvia E., Rosenberg, Avi, Rosengart, Matthew, Rovin, Brad, Roy, Neil, Sabatello, Maya, Sambandam, Kamalanathan, Sarder, Pinaki, Sarkisova, Natalya, Sarwal, Minnie, Saul, John, Schaub, Jennifer, Schmidt, Insa, Sealfon, Rachel, Sedor, John, Sendrey, Dianna, Shang, Ning, Shankland, Stuart, Shapiro, John P., Sharma, Kumar, Sharman, Kavya, Shaw, Melissa M., Shi, Tiffany, Shpigel, Anna, Sigdel, Tara, Slade, Austen, Snyder, Jamie, Spates-Harden, Kassandra, Spraggins, Jeffrey M., Srivastava, Anand, Steck, Becky, Stillman, Isaac, Stutzke, Christy, Su, Jing, Sun, Jennifer, Sutton, Timothy A., Taliercio, Jonathan, Tan, Roderick, Torrealba, Jose, Toto, Robert D., Troyanskaya, Olga, Tublin, Mitchell, Tuttle, Katherine R., Ugwuowo, Ugochukwu, Valerius, M. Todd, Van de Plas, Raf, Varela, German, Vazquez, Miguel, Velickovic, Dusan, Venkatachalam, Manjeri, Verma, Ashish, Victoria-Castro, Angela M., Vijayan, Anitha, Corona-Villalobos, Celia P., Vinovskis, Carissa, Viswanathan, Vidya S., Vita, Tina, Waikar, Sushrut, Wang, Ashley, Wang, Ruikang, Wang, Nancy, Weins, Astrid, Wen, Natasha, Wen, Yumeng, Wilcox, Adam, Williams, James C., Jr., Kayleen Williams, Williams, Mark, Wilson, Francis P., Winfree, Seth, Winters, James, Wofford, Stephanie, Wong, Aaron, Woodle, E. Steve, Xiong, Yuguang, Xu, Alan, Yadati, Pranav, Ye, Hongping, Yu, Guanghao, Zhang, Dianbo, Zhang, Guanshi, and Zhang, Kun

Published
2024
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17. The human body at cellular resolution: the NIH Human Biomolecular Atlas Program

Author

Snyder, Michael P, Lin, Shin, Posgai, Amanda, Atkinson, Mark, Regev, Aviv, Rood, Jennifer, Rozenblatt-Rosen, Orit, Gaffney, Leslie, Hupalowska, Anna, Satija, Rahul, Gehlenborg, Nils, Shendure, Jay, Laskin, Julia, Harbury, Pehr, Nystrom, Nicholas A, Silverstein, Jonathan C, Bar-Joseph, Ziv, Zhang, Kun, Börner, Katy, Lin, Yiing, Conroy, Richard, Procaccini, Dena, Roy, Ananda L, Pillai, Ajay, Brown, Marishka, Galis, Zorina S, Cai, Long, Trapnell, Cole, Jackson, Dana, Nolan, Garry, Greenleaf, William James, Plevritis, Sylvia, Ahadi, Sara, Nevins, Stephanie A, Lee, Hayan, Schuerch, Christian Martijn, Black, Sarah, Venkataraaman, Vishal Gautham, Esplin, Ed, Horning, Aaron, Bahmani, Amir, Sun, Xin, Jain, Sanjay, Hagood, James, Pryhuber, Gloria, Kharchenko, Peter, Bodenmiller, Bernd, Brusko, Todd, Clare-Salzler, Michael, Nick, Harry, Otto, Kevin, Wasserfall, Clive, Jorgensen, Marda, Brusko, Maigan, Maffioletti, Sergio, Caprioli, Richard M, Spraggins, Jeffrey M, Gutierrez, Danielle, Patterson, Nathan Heath, Neumann, Elizabeth K, Harris, Raymond, deCaestecker, Mark, Fogo, Agnes B, van de Plas, Raf, Lau, Ken, Yuan, Guo-Cheng, Zhu, Qian, Dries, Ruben, Yin, Peng, Saka, Sinem K, Kishi, Jocelyn Y, Wang, Yu, Goldaracena, Isabel, Ye, DongHye, Burnum-Johnson, Kristin E, Piehowski, Paul D, Ansong, Charles, Zhu, Ying, Desai, Tushar, Mulye, Jay, Chou, Peter, Nagendran, Monica, Teichmann, Sarah A, Paten, Benedict, Murphy, Robert F, Ma, Jian, Kiselev, Vladimir Yu, Kingsford, Carl, and Ricarte, Allyson

Subjects
Human Genome, Genetics, Networking and Information Technology R&D, Bioengineering, Aging, Atlases as Topic, Biomedical Research, Female, Health, Humans, International Cooperation, Male, Models, Anatomic, Molecular Biology, National Institutes of Health (U.S.), Organ Specificity, Single-Cell Analysis, United States, q-bio.OT, General Science & Technology
Abstract

Transformative technologies are enabling the construction of threedimensional (3D) maps of tissues with unprecedented spatial and molecularresolution. Over the next seven years, the NIH Common Fund Human BiomolecularAtlas Program (HuBMAP) intends to develop a widely accessible framework forcomprehensively mapping the human body at single-cell resolution by supportingtechnology development, data acquisition, and detailed spatial mapping. HuBMAPwill integrate its efforts with other funding agencies, programs, consortia,and the biomedical research community at large towards the shared vision of acomprehensive, accessible 3D molecular and cellular atlas of the human body, inhealth and various disease settings.

Published
2019

20. Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

Author

Hickey, John W., Neumann, Elizabeth K., Radtke, Andrea J., Camarillo, Jeannie M., Beuschel, Rebecca T., Albanese, Alexandre, McDonough, Elizabeth, Hatler, Julia, Wiblin, Anne E., Fisher, Jeremy, Croteau, Josh, Small, Eliza C., Sood, Anup, Caprioli, Richard M., Angelo, R. Michael, Nolan, Garry P., Chung, Kwanghun, Hewitt, Stephen M., Germain, Ronald N., Spraggins, Jeffrey M., Lundberg, Emma, Snyder, Michael P., Kelleher, Neil L., and Saka, Sinem K.

Published
2022
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22. Validation of an Organ Mapping Antibody Panel for Cyclical Immunofluorescence Microscopy on Normal Human Kidneys

Author

Brewer, Maya, primary, Migas, Lukasz G., additional, Clouthier, Kelly A., additional, Allen, Jamie L., additional, Anderson, David M., additional, Pingry, Ellie, additional, Farrow, Melissa, additional, Quardokus, Ellen M., additional, Spraggins, Jeffrey M., additional, Van de Plas, Raf, additional, and de Caestecker, Mark P., additional

Published
2024
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24. Cadherin-11, Sparc-related modular calcium binding protein-2, and Pigment epithelium-derived factor are promising non-invasive biomarkers of kidney fibrosis

Author

Knight, Richard, Lecker, Stewart H., Stillman, Isaac, Bogen, Steve, Amodu, Afolarin A., Ilori, Titlayo, Maikhor, Shana, Schmidt, Insa M., Beck, Laurence H., Henderson, Joel M., Onul, Ingrid, Verma, Ashish, McMahon, Gearoid M., Valerius, M. Todd, Waikar, Sushrut, Weins, Astrid, Colona, Mia R., Greka, Anna, Hacohen, Nir, Hoover, Paul J., Marshall, Jamie L., Aulisio, Mark, Chen, Yijiang M., Janowczyk, Andrew, Jayapandian, Catherine, Viswanathan, Vidya S., Bush, William S., Crawford, Dana C., Madabhushi, Anant, Bush, Lakeshia, Cooperman, Leslie, Gonzalez-Vicente, Agustin, Herlitz, Leal, Jolly, Stacey, Nguyen, Jane, O’toole, John, Palmer, Ellen, Poggio, Emilio, Sedor, John, Sendrey, Dianna, Spates-Harden, Kassandra, Taliercio, Jonathan, Bjornstad, Petter M., Pyle, Laura, Vinovskis, Carissa, Appelbaum, Paul, Balderes, Olivia, Barasch, Jonathan M., Bomback, Andrew S., Canetta, Pietro A., D’Agati, Vivette D., Kiryluk, Krzysztof, Kudose, Satoru, Mehl, Karla, Shang, Ning, Bansal, Shweta, Alexandrov, Theodore, Rennke, Helmut, El-Achkar, Tarek M., Barwinska, Daria, Bledso, Sharon, Borner, Katy, Bueckle, Andreas, Cheng, Yinghua, Dagher, Pierre C., Dunn, Kenneth W., Eadon, Michael T., Ferkowicz, Michael J., Herr, Bruce W., Kelly, Katherine J., Ferreira, Ricardo Melo, Quardokus, Ellen M., Record, Elizabeth, Rivera, Marcelino, Su, Jing, Sutton, Timothy A., Williams, James C., Jr., Winfree, Seth, Jain, Yashvardhan, Menez, Steven, Parikh, Chirag R., Rosenberg, Avi, Corona-Villalobos, Celia P., Wen, Yumeng, Johansen, Camille, Rosas, Sylvia E., Roy, Neil, Sun, Jennifer, Williams, Mark, Azeloglu, Evren U., Hansen, Jens, He, Cijang, Iyengar, Ravi, Xiong, Yuguang, Prasad, Pottumarthi, Srivastava, Anand, Madhavan, Sethu M., Parikh, Samir, Rovin, Brad, Shapiro, John P., Anderton, Christopher R., Lukowski, Jessica, Pasa-Tolic, Ljiljana, Velickovic, Dusan, Oliver, George (Holt), Ardayfio, Joseph, Bebiak, Jack, Brown, Keith, Campbell, Taneisha, Campbell, Catherine E., Hayashi, Lynda, Jefferson, Nichole, Roberts, Glenda V., Saul, John, Shpigel, Anna, Stutzke, Christy, Koewler, Robert, Pinkeney, Roy, Sealfon, Rachel, Troyanskaya, Olga, Wong, Aaron, Tuttle, Katherine R., Pollack, Ari, Goltsev, Yury, Ginley, Brandon, Lucarelli, Nicholas, Lutnick, Brendon, Sarder, Pinaki, Lake, Blue B., Zhang, Kun, Boada, Patrick, Laszik, Zoltan G., Nolan, Garry, Anjani, Kavya, Sarwal, Minnie, Mukatash, Tariq, Sigdel, Tara, Alloway, Rita R., Burg, Ashley R., Lee, Paul J., Rike, Adele, Shi, Tiffany, Woodle, E. Steve, Ascani, Heather, Balis, Ulysses G.J., Blanc, Victoria M., Conser, Ninive C., Eddy, Sean, Frey, Renee, He, Yougqun, Hodgin, Jeffrey B., Kretzler, Matthias, Lienczewski, Chrysta, Luo, Jinghui, Mariani, Laura H., Menon, Rajasree, Otto, Edgar, Schaub, Jennifer, Steck, Becky, Elder, Michele M., Gilliam, Matthew, Hall, Daniel E., Murugan, Raghavan, Palevsky, Paul M., Randhawa, Parmjeet, Rosengart, Matthew, Tublin, Mitchell, Vita, Tina, Winters, James, Kellum, John A., Alpers, Charles E., Berglund, Ashley, Berry, Brooke, Blank, Kristina N., Carson, Jonas, Daniel, Stephen, De Boer, Ian H., Dighe, Ashveena L., Dowd, Frederick, Grewenow, Stephanie M., Himmelfarb, Jonathan, Hoofnagle, Andrew N., Limonte, Christine, McClelland, Robyn L., Mooney, Sean D., Rezaei, Kasra, Shankland, Stuart, Snyder, Jamie, Wang, Ruikang, Wilcox, Adam, Williams, Kayleen, Park, Christopher, Montellano, Richard, Pamreddy, Annapurna, Sharma, Kumar, Venkatachalam, Manjeri, Ye, Hongping, Zhang, Guanshi, Basit, Mujeeb, Hedayati, S. Susan, Kermani, Asra, Lee, Simon C., Lu, Christopher Y., Miller, R. Tyler, Moe, Orson W., Patel, Jiten, Pillai, Anil, Sambandam, Kamalanathan, Torrealba, Jose, Toto, Robert D., Vazquez, Miguel, Wang, Nancy, Wen, Natasha, Zhang, Dianbo, Park, Harold, Caprioli, Richard M., Patterson, Nathan, Sharman, Kavya, Spraggins, Jeffrey M., Van de Plas, Raf, Basta, Jeanine, Diettman, Sabine M., Gaut, Joseph P., Jain, Sanjay, Rauchman, Michael I., Vijayan, Anitha, Cantley, Lloyd G., Kakade, Vijaykumar R., Moledina, Dennis, Shaw, Melissa M., Ugwuowo, Ugochukwu, Wilson, Francis P., Arora, Tanima, Kestenbaum, Bryan R., Alexopoulos, Leonidas G., Palsson, Ragnar, Liu, Jing, Stillman, Isaac E., Rennke, Helmut G., Vaidya, Vishal S., Wu, Haojia, Humphreys, Benjamin D., and Waikar, Sushrut S.

Published
2021
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25. Thermal Denaturation of Fresh Frozen Tissue Enhances Mass Spectrometry Detection of Peptides

Author

Kruse, Angela R.S., Judd, Audra M., Gutierrez, Danielle B., Allen, Jamie L., Dufresne, Martin, Farrow, Melissa A., Powers, Alvin C., Norris, Jeremy L., Caprioli, Richard M., and Spraggins, Jeffrey M.

Abstract

Thermal denaturation (TD), known as antigen retrieval, heats tissue samples in a buffered solution to expose protein epitopes. Thermal denaturation of formalin-fixed paraffin-embedded samples enhances on-tissue tryptic digestion, increasing peptide detection using matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS). We investigated the tissue-dependent effects of TD on peptide MALDI IMS and liquid chromatography-tandem mass spectrometry signal in unfixed, frozen human colon, ovary, and pancreas tissue. In a triplicate experiment using time-of-flight, orbitrap, and Fourier-transform ion cyclotron resonance mass spectrometry platforms, we found that TD had a tissue-dependent effect on peptide signal, resulting in a (22.5%) improvement in peptide detection from the colon, a (73.3%) improvement in ovary tissue, and a (96.6%) improvement in pancreas tissue. Biochemical analysis of identified peptides shows that TD facilitates identification of hydrophobic peptides.

Published
2024
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26. Protein N-Glycans in Healthy and Sclerotic Glomeruli in Diabetic Kidney Disease

Author

Veličković, Dušan, Shapiro, John P., Parikh, Samir V., Rovin, Brad, Toto, Robert D., Vazquez, Miguel A., Poggio, Emilio D., O'Toole, John F., Sedor, John R., Alexandrov, Theodore, Jain, Sanjay, Bitzer, Markus, Hodgin, Jeffrey, Veličković, Marija, Sharma, Kumar, Anderton, Christopher R., Adeyi, Oyedele A., Alakwaa, Fadhl, Alexandrov, Theodore, Allen, Jamie L., Alpers, Charles E., Alvear, Alison Bunio, Ambekar, Akhil, Ancheta, Joed, Anderton, Christopher R., Angus, Sophia A., Anjani, Kavya, Appelbaum, Paul S., Ardayfio, Joseph, Arora, Tanima, Ascani, Heather K., Asghari, Mahla, El-Achkar, Tarek M., Athar, Humra, Atta, Mohamed G., Aulisio, Mark P., Aw, Stephanie J., Azeloglu, Evren U., Bagne, Cathy A., Balderes, Olivia, Balis, Ulysses G.J., Barasch, Jonathan, Barisoni, Laura, Barwinska, Daria, Basta, Jeannine, Bebiak, Jack, Beck, Laurence H., Berge, Jerica M., Berglund, Ashley C., Bernard, Lauren, Berry, Brooke, Beyda, David H., Bhanushali, Jini Ashok, Bitzer, Markus, Bjornstad, Petter, Blanc, Victoria M., Blank, Kristina N., Bledsoe, Sharon B., Bogen, Steve, Bomback, Andrew S., Bonevich, Nikole, Border, Samuel, Börner, Katy, Bowen, William S., Boys, Charlotte, Bracamonte, Erika R., Bream, Peter R., Brosius, Frank C., Brown, Keith D., Budiman, Tifanny, Bueckle, Andreas, Bui, J.T., James, T., Burg, Ashley R., Burgess, Adam, Bush, Lakeshia, Bush, William S., Cai, Qi, Calixte, Marie Florence, Cameron-Wheeler, Tashas, Campbell, Kirk N, Campbell, Taneisha, Campbell, Catherine, Campos, Baltazar, Canetta, Pietro A., Cantley, Lloyd G, Caramori, M. Luiza, Carmona-Powell, Eunice, Carson, Jonas M, Chan, Lili, Chen, Sarah W, Chen, Yijiang, Cheng, Ying-Hua, Bejarano, Maria Chilo, Choe, Kisurb, Cimino, James G., Coca, Steven G., Coleman, Alyson, Colley, Madeline E., Collie, Mary M., Colona, Mia R., Commander, Clayton W., Conlon, Kristine, Conser, Ninive, Cooperman, Leslie, Corona-Villalobos, Celia P., Crawford, Dana C., Creger, Nathan, Cuevas-Rios, Yarieli, D'Agati, Vivette ., Dagher, Pierre c., de Boer, Ian H., de Caestecker, M.P, de Cos, Marina, Gonçalves, Joana P., Dekker, Matthew, Demeke, Dawit, Dighe, Ashveena L, Ding, Yanli, Djambazova, Katerina V., Donohoe, Isabel, Dowd, Frederick, Drawz, P.E., Dufresne, Martin, Dull, Rachel, Dunn, Kenneth W., Duran, Daniel Damian, Eadon, Michael T, Eddy, Sean, Elder, Michele M, Fallegger, Robin, Farrow, Melissa A, Ferkowicz, Michael, Fine, Derek M., Flanagan, Siobhan M., Fogo, Agnes B., Fox, Monica L., Frey, Renee, Froment, Anne, Gaba, Ron C., Gadegbeku, Crystal A, Gaut, Joseph P., Gehlenborg, Nils, Geraghty, Molly C, Ghag, Reetika, Gilliam, Matthew, Ginley, Brandon, Gisch, Debora, Gordon, Ronald E., Gorman, Brittney L., Greka, Anna, Grewenow, Stephanie M., Gurung, Bhupendra Kumar, Guthrie, Leah, Hacohen, Nir, Haddad, Samuel, Hall, Daniel E., Hansen, Jens, Harindhanavudhi, Tasma, Hartman, John, Hayashi, Lynda, Haydak, Jonathan, He, John Cijiang, He, Yongqun, Hedayati, S. Susan, Henderson, Dori, Henderson, Joel M, Hendricks, Allen R, Henshaw, Asari, Herlitz, Leal, Hernandez, Jeanine, Herr, Bruce W., Himmelfarb, Jonathan, Hodgin, Jeffrey B., Hoofnagle, Andrew N, Horowitz, Carol R., Hsieh, E.W.Y., Huynh, Courtney, Iyengar, Ravi, Jain, Sanjay, Janowczyk, Andrew, Jeffers, Vivian, Jefferson, Nichole M., Jennette, J Charles, Johansen, Camille, Jolly, Stacey, Jones, Christopher J., Jones, Jennifer L., Jones, Kiasha, Joyeux, Cienn N., Ju, Wenjun, Judd, Audra M., Kakade, Vijayakumar R, Kakarla, Dhatri, Kaspari, Rachel R., Kaushal, Madhurima, Keefe, Nicole, Keller, Mark S., Kelley, Sara S., Kellum, John A., Kelly, K. J., Kelly, Tanika N., Kermani, Asra, Kiryluk, Krzysztof, Klett, Susan, Knight, Richard A., Knoten, Amanda, Koch, Gina, Koewler, Robert, Kretzler, Matthias, Kruse, Angela R.S., Küchenhoff, Leonie, Lake, Blue B., Lardenoije, Roy, Larson, Astrid, Larson, Brandon G, Lash, James P., Laszik, Zoltan G., Lecker, Stewart H., Lee, Simon C., Lee, Sora, Lefferts, Sean, Li, Xiang, Lienczewski, Chrysta C, Limonte, Christine P, Lucarelli, Nicholas, Lukowski, Jessica, Lutnick, Brendon, Ma, Shihong, Ma, Sisi, Madabhushi, Anant, Maikhor, Shana, Mao, Weiguang, Mariani, Laura H., Markovic, Marina, Marquez, Nicole, Marshall, Jamie L., McAdams, Meredith C, McClelland, Robyn L., McCown, Phillip J., McMahon, Gearoid Michael, McMurray, Amy, Mehl, Karla, Meliambro, Kristin, Ferreira, Ricardo Melo, Mendoza, Katherine, Menez, Steven, Menon, Rajasree, Meza, Natalie, Migas, Lukasz G., Miller, R. Tyler, Mimar, Sayat, Minor, Brittany C, Mody, Priya, Moeckel, Gilbert W., Moledina, D.G., Molina-Guzman, Jenny, Monroy-Trujillo, Jose M, Morales, Alexander, Moreno, Vanessa, Mottl, Amy K., Mukatash, Tariq, Munar, Dane, Murugan, Raghavan, Nachman, Patrick H., Nadkarni, Girish N, Naglah, Ahmed, Nair, Viji, Nam, Yunbi, Narasimhan, R., Nwanne, Gerald, O'Malley, Charles, O'Toole, John F., Toro, Fernanda Ochoa, Oliver, George (Holt), Onul, Ingrid F, Otto, Edgar A., Palevsky, Paul M., Palmer, Ellen, Pamreddy, Annapurna, Parikh, Chirag R., Parikh, Samir V, Park, Christopher, Park, Harold, Paša-Tolić, Ljiljana, Patel, Jiten, Patel, Marissa, Patlis, Boris S., Paul, Anindya S., Phuong, Jimmy, Pillai, Anil, Pinkeney, Roy, Plisiewicz, Alexa, Poggio, Emilio D, Pollack, Ari, Prasad, Pottumarthi V, Pyle, Laura, Quardokus, Ellen M., Quiroga, Arabela, Ragi, Nagarjunachary, Randhawa, Parmjeet, Randle, Teresa, Rao, Via, Rauchman, Michael, Rauwolf, Nicolas J, Reamy, Rebecca, Record, Elizabeth G., Redmond, Devona, Rennke, Helmut, Renteria, Amada, Rezaei, Kasra A, Rhodes, Rosamond, Ricardo, Ana C., Rice, Samuel, Rivera, Marcelino, Roberts, Glenda V., Rosas, R., Sylvia, E., Rose, Michael P., Rosen, Seymour, Rosenberg, Avi Z., Rosenberg, Michael S., Rosengart, Matthew R., Rovin, Brad H., Roy, Neil, Roy-Chaudhury, Prabir, Rubinsky, Melissa D., Sabo, Angela R., Saez-Rodriguez, Julio, Safadi, Sami, Samari, Imane H., Sanora, Ana Celina, Sarder, Pinaki, Sarkisova, Natalya, Sarwal, Minnie M, Saul, John, Saunders, Milda R., Schaub, Jennifer A., Schmidt, IM, Scott, Raymond, Scroggins, Aaron, Sealfon, Rachel S. G., Sedor, John R., Sendrey, Dianna, Setty, Suman, Shah, Sonya, Shariff, Saad Mohammed, Sharma, Kumar, Shaw, Melissa M., Sigdel, Tara K, Silva, Paolo S., Snyder, Jaime, Snyder, Michelle L., Spates-Harden, Kassandra, Sperati, C. John, Spraggins, Jeffrey M., Srivastava, Anand, Stashevsky, Jennifer, Steck, Becky, Stillman, Isaac E, Stutzke, Christy, Subramanian, Lalita, Sun, Jennifer K., Rajan, Sandhya Sundar, Sutton, Timothy A., Taliercio, Jonathan J, Tan, Roderick, Tanevski, Jovan, Thajudeen, Bijin, Thurman, Joshua M., Tokita, Joji, Torrealba, Jose R., Toto, Robert D, Tout, Haneen, Troyanskaya, Olga G, Tsosie, Rebecca, Turner, Jeffrey M, Tuttle, Katherine R., Ugwuowo, Ugochukwu, Upadhyay, Ashish, Valerius, M. Todd, Van de Plas, Raf, Varela, German, Vazquez, Miguel A., Velickovic, Dusan, Venkatachalam, Manjeri, Verdoes, Abraham, Verma, Ashish, Victoria-Castro, Angela M., Vijayan, Anitha, Villalobos, Alexander, Viloria, Noralinda B., Vinovskis, Carissa, Vita, Tina, Waikar, Sushrut S., Wang, Ashley R., Wang, Bangchen, Wang, Nancy, Wang, Ruikang, Wangperawong, Artit, Ward, Stephen C, Warfield, Curtis, Weins, Astrid, Wen, Natasha, Wen, Yumeng, Wilcox, Adam, Williams, James C., Williams, Kayleen, Williams, Mark E., Wilson, F. Perry, Winfree, Seth, Winters, James, Wofford, Stephanie, Wolf, Susan M., Wong, Aaron, Woodhead, Gregory, Wright, Devin M., Wright, Zach, Wright, Zoe, Wrobel, Julia, Xing, Fuyong, Xu, Alan, Yadati, Pranav, Ye, Hongping, Young, Bessie A., Yu, Guanghao, Mon-Wei Yu, Samuel, Zeinoun, Gabriel, Zeitler, Evan M., Zhang, Bo, Zhang, Guanshi, and Zhang, Yi

Published
2024
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28. Validation of an organ mapping antibody panel for cyclical immunofluorescence microscopy on normal human kidneys.

Author

Brewer, Maya, Migas, Lukasz G., Clouthier, Kelly A., Allen, Jamie L., Anderson, David M., Pingry, Ellie, Farrow, Melissa, Quardokus, Ellen M., Spraggins, Jeffrey M., Van de Plas, Raf, and de Caestecker, Mark P.

Subjects
IMMUNOFLUORESCENCE, MICROSCOPY, IMAGE registration, FLUORESCENCE microscopy, KIDNEYS
Abstract

The lack of standardization in antibody validation remains a major contributor to irreproducibility of human research. To address this, we have applied a standardized approach to validate a panel of antibodies to identify 18 major cell types and 5 extracellular matrix compartments in the human kidney by immunofluorescence (IF) microscopy. We have used these to generate an organ mapping antibody panel for two-dimensional (2-D) and three-dimensional (3-D) cyclical IF (CyCIF) to provide a more detailed method for evaluating tissue segmentation and volumes using a larger panel of markers than would normally be possible using standard fluorescence microscopy. CyCIF also makes it possible to perform multiplexed IF microscopy of whole slide images, which is a distinct advantage over other multiplexed imaging technologies that are applicable to limited fields of view. This enables a broader view of cell distributions across larger anatomical regions, allowing a better chance to capture localized regions of dysfunction in diseased tissues. These methods are broadly accessible to any laboratory with a fluorescence microscope, enabling spatial cellular phenotyping in normal and disease states. We also provide a detailed solution for image alignment between CyCIF cycles that can be used by investigators to perform these studies without programming experience using opensourced software. This ability to perform multiplexed imaging without specialized instrumentation or computational skills opens the door to integration with more highly dimensional molecular imaging modalities such as spatial transcriptomics and imaging mass spectrometry, enabling the discovery of molecular markers of specific cell types, and how these are altered in disease. NEW & NOTEWORTHY We describe here validation criteria used to define on organ mapping panel of antibodies that can be used to define 18 cell types and five extracellular matrix compartments using cyclical immunofluorescence (CyCIF) microscopy. As CyCIF does not require specialized instrumentation, and image registration required to assemble CyCIF images can be performed by any laboratory without specialized computational skills, this technology is accessible to any laboratory with access to a fluorescence microscope and digital scanner. [ABSTRACT FROM AUTHOR]

Published
2024
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30. RevealingIn SituMolecular Profiles of Glomerular Cell Types and Substructures with Integrated Imaging Mass Spectrometry and Multiplexed Immunofluorescence Microscopy

Author

Esselman, Allison B., primary, Moser, Felipe A., additional, Tideman, Léonore, additional, Migas, Lukasz G., additional, Djambazova, Katerina V., additional, Colley, Madeline E., additional, Pingry, Ellie L., additional, Patterson, Nathan Heath, additional, Farrow, Melissa A., additional, Yang, Haichun, additional, Fogo, Agnes B., additional, de Caestecker, Mark, additional, Van de Plas, Raf, additional, and Spraggins, Jeffrey M., additional

Published
2024
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40. Organ Mapping Antibody Panels: a community resource for standardized multiplexed tissue imaging

Author

Quardokus, Ellen M., primary, Saunders, Diane C., additional, McDonough, Elizabeth, additional, Hickey, John W., additional, Werlein, Christopher, additional, Surrette, Christine, additional, Rajbhandari, Presha, additional, Casals, Anna Martinez, additional, Tian, Hua, additional, Lowery, Lisa, additional, Neumann, Elizabeth K., additional, Björklund, Frida, additional, Neelakantan, Taruna V., additional, Croteau, Josh, additional, Wiblin, Anne E., additional, Fisher, Jeremy, additional, Livengood, April J., additional, Dowell, Karen G., additional, Silverstein, Jonathan C., additional, Spraggins, Jeffrey M., additional, Pryhuber, Gloria S., additional, Deutsch, Gail, additional, Ginty, Fiona, additional, Nolan, Garry P., additional, Melov, Simon, additional, Jonigk, Danny, additional, Caldwell, Michael A., additional, Vlachos, Ioannis S., additional, Muller, Werner, additional, Gehlenborg, Nils, additional, Stockwell, Brent R., additional, Lundberg, Emma, additional, Snyder, Michael P., additional, Germain, Ronald N., additional, Camarillo, Jeannie M., additional, Kelleher, Neil L., additional, Börner, Katy, additional, and Radtke, Andrea J., additional

Published
2023
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44. Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

Author

Jain, Sanjay (author), Pei, Liming (author), Spraggins, Jeffrey M. (author), Angelo, Michael (author), Carson, James P. (author), Gehlenborg, Niels (author), Ginty, Fiona (author), P. Gonçalves, Joana (author), Van de Plas, Raf (author), Jain, Sanjay (author), Pei, Liming (author), Spraggins, Jeffrey M. (author), Angelo, Michael (author), Carson, James P. (author), Gehlenborg, Niels (author), Ginty, Fiona (author), P. Gonçalves, Joana (author), and Van de Plas, Raf (author)

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., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Pattern Recognition and Bioinformatics, Team Raf Van de Plas

Published
2023
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45. MALDI IMS-Derived Molecular Contour Maps: Augmenting Histology Whole-Slide Images

Author

Sharman, Kavya (author), Patterson, Nathan Heath (author), Migas, L.G. (author), Neumann, Elizabeth K. (author), Allen, Jamie (author), Gibson-Corley, Katherine N. (author), Spraggins, Jeffrey M. (author), Van de Plas, Raf (author), Skaar, Eric P. (author), Caprioli, Richard M. (author), Sharman, Kavya (author), Patterson, Nathan Heath (author), Migas, L.G. (author), Neumann, Elizabeth K. (author), Allen, Jamie (author), Gibson-Corley, Katherine N. (author), Spraggins, Jeffrey M. (author), Van de Plas, Raf (author), Skaar, Eric P. (author), and Caprioli, Richard M. (author)

Abstract

Imaging mass spectrometry (IMS) provides untargeted, highly multiplexed maps of molecular distributions in tissue. Ion images are routinely presented as heatmaps and can be overlaid onto complementary microscopy images that provide greater context. However, heatmaps use transparency blending to visualize both images, obscuring subtle quantitative differences and distribution gradients. Here, we developed a contour mapping approach that combines information from IMS ion intensity distributions with that of stained microscopy. As a case study, we applied this approach to imaging data from Staphylococcus aureus-infected murine kidney. In a univariate, or single molecular species, use-case of the contour map representation of IMS data, certain lipids colocalizing with regions of infection were selected using Pearson’s correlation coefficient. Contour maps of these lipids overlaid with stained microscopy showed enhanced visualization of lipid distributions and spatial gradients in and around the bacterial abscess as compared to traditional heatmaps. The full IMS data set comprising hundreds of individual ion images was then grouped into a smaller subset of representative patterns using non-negative matrix factorization (NMF). Contour maps of these multivariate NMF images revealed distinct molecular profiles of the major abscesses and surrounding immune response. This contour mapping workflow also enabled a molecular visualization of the transition zone at the host-pathogen interface, providing potential clues about the spatial molecular dynamics beyond what histological staining alone provides. In summary, we developed a new IMS-based contour mapping approach to augment classical stained microscopy images, providing an enhanced and more interpretable visualization of IMS-microscopy multimodal molecular imaging data sets., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Team Raf Van de Plas

Published
2023
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46. MALDI TIMS IMS of Disialoganglioside Isomers GD1a and GD1b in Murine Brain Tissue

Author

Djambazova, Katerina V. (author), Dufresne, Martin (author), Migas, L.G. (author), Kruse, Angela R.S. (author), Van de Plas, Raf (author), Caprioli, Richard M. (author), Spraggins, Jeffrey M. (author), Djambazova, Katerina V. (author), Dufresne, Martin (author), Migas, L.G. (author), Kruse, Angela R.S. (author), Van de Plas, Raf (author), Caprioli, Richard M. (author), and Spraggins, Jeffrey M. (author)

Abstract

Gangliosides are acidic glycosphingolipids, containing ceramide moieties and oligosaccharide chains with one or more sialic acid residue(s) and are highly diverse isomeric structures with distinct biological roles. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) enables the untargeted spatial analysis of gangliosides, among other biomolecules, directly from tissue sections. Integrating trapped ion mobility spectrometry with MALDI IMS allows for the analysis of isomeric lipid structures in situ. Here, we demonstrate the gas-phase separation and identification of disialoganglioside isomers GD1a and GD1b that differ in the position of a sialic acid residue, in multiple samples, including a standard mixture of both isomers, a biological extract, and directly from thin tissue sections. The unique spatial distributions of GD1a/b (d36:1) and GD1a/b (d38:1) isomers were determined in rat hippocampus and spinal cord tissue sections, demonstrating the ability to structurally characterize and spatially map gangliosides based on both the carbohydrate chain and ceramide moieties., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Team Raf Van de Plas

Published
2023
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47. Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue

Author

Sharman, Kavya (author), Patterson, Nathan Heath (author), Weiss, Andy (author), Neumann, Elizabeth K. (author), Guiberson, Emma R. (author), Ryan, Daniel J. (author), Gutierrez, Danielle B. (author), Spraggins, Jeffrey M. (author), Van de Plas, Raf (author), Skaar, Eric P. (author), Caprioli, Richard M. (author), Sharman, Kavya (author), Patterson, Nathan Heath (author), Weiss, Andy (author), Neumann, Elizabeth K. (author), Guiberson, Emma R. (author), Ryan, Daniel J. (author), Gutierrez, Danielle B. (author), Spraggins, Jeffrey M. (author), Van de Plas, Raf (author), Skaar, Eric P. (author), and Caprioli, Richard M. (author)

Abstract

Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Team Raf Van de Plas

Published
2023
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