Proteoforms are the key effectors in human health and disease. Understanding proteoform distributions in human tissues is critical to pathogenic studies and therapeutics. Imaging mass spectrometry (IMS) is a powerful technique for mapping proteins in tissues. Despite the high spatial resolution and detection sensitivity achieved, IMS is limited by proteome coverage and the ability to characterize proteoforms. Herein, we introduce proteoform imaging mass spectrometry (PiMS) to image intact tissue proteoforms up to 70 kDa. PiMS utilizes nano-DESI as a sampling and ionization probe, and charge detection via Orbitrap-based individual ion mass spectrometry (I²MS) is employed in MS data acquisition. In a PiMS experiment, proteoforms from different locations on tissue are sampled and detected as multiply-charged individual ions. By means of I²MS processing, molecular masses of proteoforms are directly obtained, and putative proteoform IDs are assigned using intact mass tag (IMT) approach from a lookup in the human proteoform atlas. For each assigned proteoform, an ion image is constructed by plotting the absolute individual ion count against the spatial coordinates on tissue.
A first demonstration of PiMS on a human kidney tissue section results in the identification of 169 of the ~400 detected proteoforms up to 70 kDa, including key enzymes in primary cell metabolisms, blood proteoforms, structural proteoforms, etc. The identified proteoforms show distinct localizations to the cortex, the medulla, and the vasculature in kidney.
To further characterize the detected proteoforms, we developed a multiplexed PiMS² workflow to maximize proteoform identification. This workflow utilizes a MS¹ PiMS line scan on tissue as a survey of the intact masses, charge states, and spatial distributions of the proteoforms. Subsequent MS² experiments were performed on an adjacent line region, where spatial distributions of the proteoforms are considered identical. MS² data was collected using a hybrid approach of ensemble and individual ion MS², which enables efficient detection of fragments in a wide mass range. In a proof-of-concept experiment performed on a human ovarian cancer tissue, 40 out of 69 targets in the 3-18 kDa range at >8% relative abundance in a singular line scan can be identified at MS² level. We envision PiMS as a powerful imaging tool for biomarker discovery and disease diagnostics in various human tissues.

Dr. Neil L. Kelleher

Professor, Northwestern University

Appearances