Novel Approach Improves Protein Characterization in Human Tissue

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Huiping Liu, MD, PhD, associate professor of Pharmacology and of Medicine in the Division of Hematology and Oncology, was a co-author of the study published in Nature Communications.   

Scientists at Northwestern University Feinberg School of Medicine and Pacific Northwest National Laboratory (PNNL) have developed a novel, robust proteomics technique that can more accurately identify and spatially characterize thousands of proteins in single cells within human tissue samples, as detailed in a recent study published in Nature Communications.  

“This technology can give you a global picture of the proteins included in one specific cell or tissue region as small as possible that can be laser captured and microdissected. This technology can be broadly applied to analyzing any cell in any tissue in a spatially-preserved manner,” said Huiping Liu, MD, PhD, associate professor of Pharmacology and of Medicine in the Division of Hematology and Oncology, who was a co-author of the study.  

Advanced mass spectrometry (MS)-based proteomics is used to identify and characterize proteins across the genome in human tissue. However, current methods for bulk tumor tissue analyses lack spatial resolution and fail to capture precisely how proteins differ within the tissue microenvironment.  

To address this issue, Liu and her collaborators at PNNL developed a novel, spatial proteomic processing method called wcSOP (wet collection of single microscale tissue voxels and Surfactant-assisted One-Pot voxel processing), enabling high-efficiency MS analysis for sensitive label-free single voxel proteomics. Single voxel proteomics involves analyzing the proteome within three-dimensional tissue samples called voxels, which allows for high-resolution mapping of protein expression and the tumor microenvironment.  

The tool can also more accurately identify protein patterns and signaling pathways than traditional methods to improve the spatial understanding of tissue function, according to the authors. The investigators validated their approach using various types of human tissue samples, including spleen and breast tissue as well as brain tissue from patients with Alzheimer’s disease.  

Liu said she and her team plan to integrate artificial intelligence modeling alongside the new approach to provide a more comprehensive understanding of tissue biology.  

“With its convenient accessibility (e.g., low-cost PCR tube cap and surfactant) and broad applicability to different types of tissues, wcSOP-MS can be readily implemented in any MS laboratory where laser capture microdissection and MS instruments are available,” the authors said.  

Tujin Shi, PhD, a staff scientist at PNNL, was senior author of the study. Reta Birhanu Kitata, PhD, a Proteomics Biomedical Scientist at PNNL, was lead author of the study.  

David Scholten, a student in the Driskill Graduate Program in Life Sciences, was a co-author of the study. 

Liu is also a member of the Robert H. Lurie Comprehensive Cancer Center of Northwestern University.  

This work was supported by a UH3CA256967 grant from the National Institutes of Health (NIH) Common Fund; Human Biomolecular Atlas Program (HuBMAP) grant; NIH grants RF1MH128885, R01GM139858, P41GM103493, R01CA245699 and ACS127951-RSG-15-025-01-CSM; and the National Cancer Institute Early EDRN Interagency Agreement ACN20007-001.