Proteomics of spatially identified tissues in whole organs
Bhatia, H. S.; Brunner, A.-D.; Rong, Z.; Mai, H.; Thielert, M.; Al-Maskari, R.; Paetzold, J. C.; Kofler, F.; Todorov, M. I.; Ali, M.; Molbay, M.; Kolabas, Z. I.; Kaltenecker, D.; Mueller, S.; Lichtenthaler, S. F.; Menze, B. H.; Theis, F. J.; Mann, M.; Erturk, A.
Show abstract
Spatial molecular profiling of complex tissues is essential to investigate cellular function in physiological and pathological states. However, methods for molecular analysis of biological specimens imaged in 3D as a whole are lacking. Here, we present DISCO-MS, a technology combining whole-organ imaging, deep learning-based image analysis, and ultra-high sensitivity mass spectrometry. DISCO-MS yielded qualitative and quantitative proteomics data indistinguishable from uncleared samples in both rodent and human tissues. Using DISCO-MS, we investigated microglia activation locally along axonal tracts after brain injury and revealed known and novel biomarkers. Furthermore, we identified initial individual amyloid-beta plaques in the brains of a young familial Alzheimers disease mouse model, characterized the core proteome of these aggregates, and highlighted their compositional heterogeneity. Thus, DISCO-MS enables quantitative, unbiased proteome analysis of target tissues following unbiased imaging of entire organs, providing new diagnostic and therapeutic opportunities for complex diseases, including neurodegeneration. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/466753v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1e37035org.highwire.dtl.DTLVardef@dbaa98org.highwire.dtl.DTLVardef@19cece1org.highwire.dtl.DTLVardef@183c032_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDISCO-MS combines tissue clearing, whole-organ imaging, deep learning-based image analysis, and ultra-high sensitivity mass spectrometry C_LIO_LIDISCO-MS yielded qualitative and quantitative proteomics data indistinguishable from fresh tissues C_LIO_LIDISCO-MS enables identification of rare pathological regions & their subsequent molecular analysis C_LIO_LIDISCO-MS revealed core proteome of plaques in 6 weeks old Alzheimer s disease mouse model Supplementary Video can be seen at: http://discotechnologies.org/DISCO-MS/ C_LI
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Data-independent acquisition method for ubiquitinome analysis reveals regulation of circadian biology 95%
- IceR improves proteome coverage and data completeness in global and single-cell proteomics 94%
- Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data 94%
Similar papers in this journal
- Imaging stable isotope labelling kinetics (iSILK) for following spatial Aβ plaque aggregation dynamics in evolving Alzheimers disease pathology 94%
- Single-synapse analyses of Alzheimers disease implicate pathologic tau, DJ1, CD47, and ApoE 92%
- In situ Proteomics Unveils Specialized Domains for Extrasynaptic Signaling on Neuronal Cilia 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.