Multiplexed imaging of tissues using mass tags and secondary ion mass spectrometry
A method of generating a high resolution two-dimensional image of a sample comprising cells and extracellular structures is provided. In certain embodiments, the method comprises: labeling a sample with at least one mass tag, thereby producing a labeled sample; scanning the sample with a secondary ion mass spectrometer (SIMS) ion beam to generate a data set that comprises spatially-addressable measurements of the abundance of the mass tag across an area of the sample; and outputting the data set. In many embodiments, the data set contains the identity and abundance of the mass tag. A system for performing the method is also provided.
1. A method of generating a high resolution two-dimensional image of a tissue sample comprising cells and extracellular structures, the method comprising:
labeling a tissue section with a plurality of distinguishable elemental isotopic mass tags, thereby producing a labeled tissue section in which biological features are bound to the elemental isotopic mass tags;
scanning a plurality of positions across an area of the labeled tissue section with a secondary ion mass spectrometer (SIMS) ion beam to, at each position, simultaneously measure the plurality of elemental isotopic mass tags, to thereby generate a data set that comprises identity and spatially-addressable measurements of the abundance of each of the plurality of elemental isotopic mass tags at each of the plurality of positions in the tissue section; and
outputting an image of the tissue section showing the biological features therein.
2. The method of claim 1 , wherein said labeling is done using antibodies that are linked to the elemental isotopic mass tags.
3. The method of claim 1 , wherein the tissue section is a formalin-fixed, paraffin-embedded (FFPE) section.
4. The method of claim 1 , wherein said elemental isotopic mass tags are isotopes of elements having an atomic number in the range of 21-92.
5. The method of claim 4 , wherein each element is a lanthanide.
6. The method of claim 1 , wherein the image has a resolution of at least 500 nm.
7. The method of claim 1 , further comprising defining the boundaries of individual cells, and, optionally, subcellular features in individual cells, in said image.
8. The method of claim 7 , further comprising integrating the data set that corresponds to each of the individual cells, or a subcellular feature thereof, in said image.
9. The method of claim 8 , further comprising categorizing said cells based on the integrated data obtained for each of the cells or a subcellular feature thereof.
10. The method of claim 9 , further comprising displaying the image of said tissue section, wherein the cells are color-coded by their category.
11. The method of claim 10 , wherein, in any one pixel of the image, intensity of a color of said pixel correlates with magnitude of a signal obtained for that pixel by said scanning.
12. The method of claim 1 , wherein said tissue section is mounted on a conductive substrate.
13. The method of claim 1 , wherein said ion beam is rastered over said tissue section.
14. A system for analyzing a tissue sample comprising cells, the system comprising:
a) a secondary ion mass spectrometry (SIMS) system comprising a holder for retaining a substrate comprising a tissue section, wherein the system is configured to (i) scan a plurality of positions across an area of the tissue section with a SIMS ion beam to, at each position, simultaneously measure a plurality of elemental isotopic mass tags that are bound to biological features in the tissue section, (ii) generate a data set that comprises the identity and spatially-addressable measurements of the abundance of each of the plurality of elemental isotopic mass tags at the plurality of positions across the area of said tissue section, and (iii) output the data set; and
b) a computer comprising an image analysis module that processes said data set to produce an image of said tissue section.
15. The system of claim 14 , wherein said image analysis module can define the boundaries of individual cells, and, optionally, subcellular features in individual cells, in said image.
16. The system of claim 15 , wherein said image analysis module integrates the data set for individual cells in the image or a subcellular feature thereof.
17. The system of claim 16 , wherein said image analysis module categorizes said individual cells based on the integrated data obtained for each of the cells.
18. The system of claim 17 , wherein said image analysis module displays an image of said tissue section, wherein the cells are color-coded by their category.
19. The system of claim 18 , wherein, in any one pixel of the image, the intensity of color of said pixel correlates with magnitude of a signal obtained for that pixel by the SIMS system.