January 22, 2024
Research Highlight

Chemical and Computational Advances Enable 2D Proteomics Measurements of Spatial Signals

Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches

Photo of a researcher in safety goggles and gloves holding a piece of science equipment in front of themselves.

MicroPOTS is a chip-based approach developed by Pacific Northwest National Laboratory that allows sample processing in a microliter droplet to greatly improve the sensitivity of proteomics measurements.

(Photo by Andrea Starr | Pacific Northwest National Laboratory)

The Science

Human tissue is composed of distinct cell types arranged in complex structures that send protein signals both within a single cell and between cells. In standard proteomics measurements, these cell structures mix to blend this network of signals together. Scientists at Pacific Northwest National Laboratory (PNNL) used stained human pancreas samples to enable visualization of the islet (insulin producing micro-organs) regions of the pancreas and showcase how the microPOTS proteomics technology can be used to characterize region-specific protein signals. This approach revealed insulin signaling proteins within the human pancreas samples were localized around the islet cells, not farther away.

The Impact

Currently, most ‘omics measurements derived from genes, transcripts, proteins, or metabolites come from bulk tissue. However, when scientists measure an entire tissue segment, microscopic changes that occur across the biological specimen are often missed.

New research demonstrates how standard analysis pipelines can be used on spatial proteomics measurements, enabling researchers to identify trends across the tissue that cannot be measured at the bulk tissue level. By applying these computational tools to the microPOTS data, biological signaling pathways that are altered within a specific area of the tissue can be identified. This finding proves that these computational approaches can be used to interpret additional spatial proteomics measurements and identify novel biology.


The need for a clinically accessible method to match protein activity within heterogeneous tissues is currently unmet by existing technologies. MicroPOTS can be used to measure relative protein abundance in micron-scale samples alongside the spatial location of each measurement, thereby tying biologically interesting proteins and pathways to distinct regions. However, given the smaller pixel/voxel number and amount of tissue measured, standard mass spectrometric analysis pipelines have proven inadequate.

New research adapts existing computational approaches to answer specific biological questions asked in spatial proteomics experiments. This new approach presents an unbiased characterization of the human islet microenvironment comprising the entire complex array of cell types involved while maintaining spatial information and the degree of the islet’s sphere of influence. Researchers identify specific functional activity unique to the pancreatic islet cells and demonstrate how far their signature can be detected in the adjacent tissue. Results show that pancreatic islet cells can be distinguished from the neighboring exocrine tissue environment, recapitulate known biological functions of islet cells, and identify a spatial gradient in the expression of RNA processing proteins within the islet microenvironment.

This work was done using the Environmental Molecular Sciences Laboratory’s Isotope and Chemical Analysis Integrated Research Platform.


This work was funded by the National Institutes of Health HubMAP initiative. Mass spectrometry was performed in EMSL, the Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility at PNNL. EMSL is sponsored by the Biological and Environmental Research program. PNNL is operated by Battelle for the Department of Energy.

Published: January 22, 2024

Gosline, S. J. C., M. Veličković, J. C. Pino, L. Z. Day, I. K. Attah, A. C. Swensen, V. Danna, C. Posso, K. D. Rodland, J. Chen, C. E. Matthews, M. Campbell-Thompson, J. Laskin, K. Burnum-Johnson, Y. Zhu, P. D. Piehowski. 2023. “Proteome Mapping of the Human Pancreatic Islet Microenvironment Reveals Endocrine–Exocrine Signaling Sphere of Influence.” Molecular & Cellular Proteomics. Volume 22, Issue 8, 100592.