IP Library Granted Patent US 9,953,209
Granted Patent B2
US 9,953,209 · App. 15/085,175 · Granted Apr 24, 2018

Systems, methods, and apparatus for in vitro single-cell identification and recovery

Inventors: Viktor A. Adalsteinsson (Wakefield, MA); Denis Loginov (Dorchester Center, MA); J. Christopher Love (Somerville, MA); Alan Stockdale (Providence, RI); Todd Gierahn (Brookline, MA)
Assignee: Massachusetts Institute of Technology
G06K9/00147B01L3/5085G01N15/1425G01N15/1463G01N33/4833G01N35/00029G01N35/00871G02B21/16G02B21/26G06K9/0014G06K9/036G06K9/4647G06K9/4652G06K9/4661H04N5/2256B01L2300/0654B01L2300/0829B01L2300/0851B01L2300/0896B01L2300/12G01N2015/0065G01N2015/1006G01N2035/00148
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Quick Facts
Patent No.
US 9,953,209
App. No.
15/085,175
Granted
Apr 24, 2018
Kind
B2
Abstract

Described herein are systems, methods, and apparatus for automatically identifying and recovering individual cells of interest from a sample of biological matter, e.g., a biological fluid. Also described are methods of enriching a cell type of interest. These systems, methods, and apparatus allow for coordinated performance of two or more of the following, e.g., all with the same device, thereby enabling high throughput: cell enrichment, cell identification, and individual cell recovery for further analysis (e.g., sequencing) of individual recovered cells.

Claims (44)

1. A system for performing spectral spillover compensation in multicolor slide cytometry, the system comprising at least one memory and a processor of a computing device communicatively coupled to the at least one memory, wherein the processor is operable to perform steps (i) to (xi) as follows:

(i) identify location of one or more beads;

(ii) extract a signal intensity of each pixel in each of a plurality of spectral channels for each bead;

(iii) create one or more 3D probability matrices relating intensity of signal in the spectral channel assigned to a fluorophore to the signal in each of the other channels;

(iv) identify a location of cells in one or more images;

(v) extract a signal in each of the plurality of spectral channels for each cell;

(vi) extract a background signal;

(vii) determine an amount of each fluorophore on each cell using one or more average spillover values extracted from the one or more probability matrices;

(viii) create n-replicas of the compensated fluorophore content of each cell;

(ix) sample at least one of the one or more 3D probability matrices to calculate an expected distribution of raw fluorescent signal in each channel based on concentration of each fluorophore;

(x) compensate reconstructed pseudo-raw fluorescent values to create a distribution of calculated signal on cells identified as having no actual fluorophores present; and

(xi) resample a plurality of times for each cell to generate an expected negative cell distribution for each individual cell.

2. The system of claim 1 , wherein the processor is operable to perform step (iii) by performing (a) to (e), as follows:

(a) determine an average amount of light emitted in channel B by fluorophore A;

(b) normalize B signal to 0;

(c) bin data into overlapping bins based on fluorophore A concentration;

(d) create a 2D probability distribution of B signal for each bin; and

(e) combine the 2D distributions into a 3D spectral probability matrix.

3. The system of claim 1 , further comprising an imaging device.

4. The system of claim 1 , wherein the processor is operable to perform five or more of steps (i) to (xi).

5. The system of claim 1 , wherein the plurality of spectral channels comprises from 10 to 30 spectral channels.

6. The system of claim 1 , wherein the background signal in step (vi) is extracted from one or more areas similar in size to an area from which a cell signal is extracted.

7. The system of claim 1 , wherein step (viii) comprises, for each replica, one fluorophore content being zeroed by replacing the value with a sample taken from the background signal distribution.

8. The system of claim 1 , wherein the plurality of times in step (xi) is at least 5k times.

9. The system of claim 2 , wherein the average amount of light in step (a) is determined through linear regression.

10. The system of claim 2 , wherein the B signal is normalized in step (b) by subtracting a product fluorophore A concentration and slope of the linear regression in step (a).

11. The system of claim 2 , wherein the 2D probability distribution of B signal for each bin is normalized to 1.

12. The system of claim 1 , wherein the processor is operable to perform at least 5 of steps (i) to (xi).

13. The system of claim 1 , wherein the plurality of spectral channels comprises from 10 to 30 spectral channels.

14. The system of claim 1 , wherein the background signal in step (vi) is extracted from one or more areas similar in size to an area from which a cell signal is extracted.

15. The system of claim 1 , wherein step (viii) comprises, for each replica, one fluorophore content is zeroed by replacing the value with a sample taken from the background signal distribution.

16. The system of claim 1 , wherein the plurality of times in step (xi) is at least 5k times.

17. A method for performing spectral spillover compensation in multicolor slide cytometry, the method comprising performing steps (i) to (xi) as follows using a processor of a computing device:

(i) identifying location(s) of one or more beads;

(ii) extracting a signal intensity of each pixel in each of a plurality of spectral channels for each bead;

(iii) creating one or more 3D probability matrices relating intensity of signal in the spectral channel assigned to a fluorophore to the signal in each of the other channels;

(iv) identifying a location of cells in one or more images;

(v) extracting a signal in each of the plurality of spectral channels for each cell;

(vi) extracting a background signal;

(vii) determining an amount of each fluorophore on each cell using one or more average spillover values extracted from the one or more probability matrices;

(viii) creating n-replicas of the compensated fluorophore content of each cell;

(ix) sampling at least one of the one or more 3D probability matrices to calculate an expected distribution of raw fluorescent signal in each channel based on concentration of each fluorophore;

(x) compensating reconstructed pseudo-raw fluorescent values to create a distribution of calculated signal on cells identified as having no actual fluorophores present; and

(xi) resampling a plurality of times for each cell to generate an expected negative cell distribution for each individual cell.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 9, 2018
From: ADALSTEINSSON, VIKTOR A.; LOGINOV, DENIS; LOVE, J. CHRISTOPHER; STOCKDALE, ALAN; GIERAHN, TODD
To: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
Reel/Frame 044886/0254 →
CONFIRMATORY LICENSE Recorded Jul 5, 2016
From: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
To: NATIONAL INSTITUTES OF HEALTH (NIH), U.S. DEPT. OF HEALTH AND HUMAN SERVICES (DHHS), U.S. GOVERNMENT
Reel/Frame 039252/0964 →
Continuity (3)
Continuation 14997439 · Jan 15, 2016
Provisional Application 62104036 · Jan 15, 2015
Related Publication 20160217315A1 · Jul 28, 2016