Single-cell Spatial Proteomic Imaging for Human Neuropathology

Neurodegenerative disorders are characterized by phenotypic changes and hallmark proteopathies. Quantifying these in archival human brain tissues remains indispensable for validating animal models and understanding disease mechanisms. We present a framework for nanometer-scale, spatial proteomics with multiplex ion beam imaging (MIBI) for capturing neuropathological features. MIBI facilitated simultaneous, quantitative imaging of 36 proteins on archival human hippocampus from individuals spanning cognitively normal to dementia. Customized analysis strategies identified cell types and proteopathies in the hippocampus across stages of Alzheimer’s disease (AD) neuropathologic change. We show microglia-pathologic tau interactions in hippocampal CA1 subfield, in AD dementia. Data driven, sample independent creation of spatial proteomic regions identified persistent neurons in pathologic tau neighborhoods expressing mitochondrial protein MFN2, regardless of cognitive status, suggesting a survival advantage. Our study revealed unique insights from multiplexed imaging and data-driven approaches for neuropathologic analysis and serves as a baseline for mechanistic and interventional understanding in human neurodegeneration.

Contents include:

Supplemental Table (.xlsx)
- TableS1: Antibody information
- TableS2: Tissue source information
- TableS3: MIBI run parameters & Segmentation parameters
- TableS4: Cell & Object counts - overall
- TableS5: Cell & Object counts - breakdown by anatomical and de novo regions
- Initial Gating Parameters: additional proteopathy size limiting, post-processing
- ezSeg Log Data: segmentation parameters of objects using the ezSegmenter tool
- Gating Neuron %: distribution of MFN2 vs PHF1-Tau and MFN2 vs Amyloid beta 42 neuronal expression
- Key Resource Table: resources used in the preparation of the study.

Tissue Set 1 (FOV = 400um x 400um, 1024 x 1024 resolution, background removed, de-noised)
- Multiple Brain Regions = Tissue MicroArray (TMA) (.tif)
- Region mapper (.xlsx)

Tissue Set 2 (FOV = 400um x 400um, 1024 x 1024 resolution, background removed, de-noised)
- Partial Hippocampus
- Alzheimer's Disease Dementia (ADD): 85 FOVs (.tif)
- Cell Segmentation Output (.tif, .fcs, .csv, .txt)
- Object Segmentation Output (.tif, .csv, .mat, .txt) <- includes proteopathy
- Combined cell and object data table (.csv)

Tissue Set 3 (FOV = 500um x 500um, 512 x 512 resolution, background removed, de-noised):
- Full Hippocampus
- Cognitively Normal (CN): 275 FOVs (.tif) # broken into three different acquisition runs (Sets 1,2,3)
- Cognitively Impaired, No Dementia (CIND): 259 FOVs (.tif)
- Alzheimer's Disease Dementia (ADD): 196 FOVs (.tif)
- Cell Segmentation Output (.tif, .fcs, .csv, .txt)
- Object Segmentation Output (.tif, .csv, .mat, .txt) <- includes proteopathy
- Combined cell and object data table (.csv)