Molecular Ion Beam Imaging (MIBI) Survey |
Introduction to MIBI
The objective of this survey is to assess the potential usage of a multiplexed imaging platform that could be acquired at UCD-AMC.
Molecular Ion Beam Imaging (MIBI) is a technique that extends the multiplexed analysis capabilities of mass cytometry to make spatially resolved measurements. This approach uses high-resolution nanoscale secondary ion mass spectrometry to image antibodies tagged with isotopically pure metal reporters, avoiding fluorescence spectral overlap and background autofluorescence. MIBI is capable of analyzing up to 100 targets (proteins and RNA) simultaneously on FFPE or fresh tissue samples, with over five-log dynamic range and cellular resolution of 100 nanometers. The resulting data can be analyzed by 1) “traditional” imaging analysis tools (Cell Profiler, Image J, Definiens, Halo), as well as 2) open-sourced software designed for high-dimensional single-cell data such as visNE.
This instrument would be managed by a core facility on campus, which will integrate experimental guidance, technical expertise, and support for data analysis. Acquisition of this instrument on campus would make UCD-AMC one of four institutions in the world with access to this technology, elevating our ability to dissect disease mechanisms in situ, with applications for basic research, drug discovery, and clinical diagnostics.
Molecular Ion Beam Imaging (MIBI) is a technique that extends the multiplexed analysis capabilities of mass cytometry to make spatially resolved measurements. This approach uses high-resolution nanoscale secondary ion mass spectrometry to image antibodies tagged with isotopically pure metal reporters, avoiding fluorescence spectral overlap and background autofluorescence. MIBI is capable of analyzing up to 100 targets (proteins and RNA) simultaneously on FFPE or fresh tissue samples, with over five-log dynamic range and cellular resolution of 100 nanometers. The resulting data can be analyzed by 1) “traditional” imaging analysis tools (Cell Profiler, Image J, Definiens, Halo), as well as 2) open-sourced software designed for high-dimensional single-cell data such as visNE.
This instrument would be managed by a core facility on campus, which will integrate experimental guidance, technical expertise, and support for data analysis. Acquisition of this instrument on campus would make UCD-AMC one of four institutions in the world with access to this technology, elevating our ability to dissect disease mechanisms in situ, with applications for basic research, drug discovery, and clinical diagnostics.