METHOD AND SYSTEM FOR DETECTING FLUOROCHROMES IN A FLOW CYTOMETER

• US 20110204259A1
• Filed: 02/23/2011
• Published: 08/25/2011
• Est. Priority Date: 02/23/2010
• Status: Active Grant

• Current Assignee: Accuri Cytometers, Inc. (Becton Dickinson & Co)
• Original Assignee: Accuri Cytometers, Inc. (Becton Dickinson & Co)
• Inventors: Rogers, Clare E., Rich, Collin A., Ball, Jack T.
• Granted Patent: US 8,779,387 B2
• Time in Patent Office: Days
• US Class Current: 250/459.1
• CPC Class Codes: G01N 15/1429 Signal processing
• CPC Class Codes: G01N 15/1459 the analysis being performed on a sample stream

Abstract

A method for detecting fluorochromes in a flow cytometer, including: receiving a sample including particles each tagged with at least one of a first fluorochrome and a second fluorochrome, in which the first and second fluorochromes having distinct spillover coefficients; detecting the particles, including detecting the first and second fluorochromes with a first detector and a second detector; forming a data set for detected particles based on the detection of the first and second fluorochromes; characterizing a detected spillover coefficient for each detected fluorochrome from the data set; and sorting the detected particles into predicted fluorochrome populations based on the detected spillover coefficients. A system for detecting fluorochromes in a flow cytometer, including a flow cell, a fixed gain detection system, and a processor that generates a detected spillover coefficient for each detected particle and sorts the detected particle into predicted fluorochrome populations based on the detected spillover coefficient.

Claims

1. A method for detecting fluorochromes in a flow cytometer, comprising:

receiving a sample including particles each tagged with at least one of a first fluorochrome and a second fluorochrome, wherein the first and second fluorochromes have distinct spillover coefficients;

detecting particles of the sample, including detecting the first and second fluorochromes of the particles with a first detector and a second detector;

forming a data set for detected particles based on the detection of the first and second fluorochromes of the particles;

characterizing a detected spillover coefficient for each detected fluorochrome from the data set; and

sorting the detected particles into predicted fluorochrome populations based on the detected spillover coefficients.

2. The method of claim 1, wherein detecting particles includes detecting fluorochromes with detectors having a fixed gain.

3. The method of claim 1, wherein detecting particles includes detecting fluorochromes with detectors having a broad dynamic range.

4. The method of claim 3, wherein detecting particles includes detecting fluorochromes with detectors having a range of at least six decades.

5. The method of claim 1, wherein detecting particles includes detecting particles tagged with the first fluorochrome primarily with the first detector and detecting particles tagged with the second fluorochrome primarily with the second detector.

6. The method of claim 1, wherein forming a data set includes forming a first data set based on the detection of the first fluorochrome and forming a second data set based on the detection of the second fluorochrome.

7. The method of claim 6, wherein forming a data set includes forming an array of channel numbers each corresponding to detected brightness of a fluorochrome signal.

8. The method of claim 7, wherein forming an array of channel numbers includes forming an array of pairs of channel numbers, wherein each pair includes a channel number for a primary detector and another channel number for a secondary detector.

9. The method of claim 1, wherein forming a data set includes forming a first data set based on the detections by the first detector and forming a second data set based on the detections by the second detector.

10. The method of claim 1, wherein characterizing a detected spillover coefficient includes plotting the data set on a spectral spillover data plot representing at least a portion of the detected particles.

11. The method of claim 10, wherein plotting the data set includes plotting measurements of the first detector on a first axis of the plot and measurements of the second detector on a second axis of the spectral spillover data plot.

12. The method of claim 11, wherein plotting the first and second data sets includes plotting channel numbers of the first detector on the first axis and channel numbers of the second detector on the second axis.

13. The method of claim 11, wherein sorting the detected particles into predicted fluorochrome populations includes identifying a cluster of data points on the spectral spillover data plot corresponding to the first fluorochrome.

14. The method of claim 10, further comprising displaying the spectral spillover data plot to a user.

15. The method of claim 1, wherein characterizing a detected spillover coefficient includes calculating the detected spillover coefficient from the data set for each of at least a portion of the detected particles.

16. The method of claim 15, wherein calculating the detected spillover coefficient includes dividing data set elements corresponding to detection of a particle by a secondary detector by data set elements corresponding to detection of the particle by a primary detector.

17. The method of claim 16, wherein sorting the detected particles includes comparing the detected spillover coefficient to an expected spillover coefficient estimated with a best-fit line corresponding to the first or second fluorochrome on a spectral spillover calibration plot.

18. The method of claim 17, wherein comparing the detected spillover coefficient to an expected spillover coefficient includes comparing the detected spillover coefficient to the slope of the best-fit line.

19. The method of claim 1, wherein sorting the detected particles into predicted fluorochrome populations includes comparing the detected spillover coefficient to an expected spillover coefficient of at least one of the first and second fluorochromes.

20. The method of claim 1, wherein sorting the detected particles includes sorting each of at least a portion of the detected particles into a first predicted fluorochrome population corresponding to the first fluorochrome or into a second predicted fluorochrome population corresponding to the second fluorochrome.

21. The method of claim 1, wherein detecting particles further includes detecting a third fluorochrome of the particles having a third spillover coefficient and sorting the detected particles further includes sorting each of at least a portion of the detected particles into a third predicted fluorochrome population corresponding to the third fluorochrome.

22. The method of claim 21, wherein detecting the third fluorochrome includes detecting the third fluorochrome with the first and second detectors.

23. A system for detecting fluorochromes in a flow cytometer, comprising:

an interrogation zone that receives a sample including particles tagged with at least one of a first fluorochrome and a second fluorochrome, wherein the first and second fluorochromes have distinct spillover coefficients;

a detection system that detects particles passing through the flow cell, by detecting the first and second fluorochromes of the particles, and forms a data set based on detection of the first and second fluorochromes, respectively; and

a processor that generates a detected spillover coefficient for each detected particle from the data set and sorts the detected particles into predicted fluorochrome populations based on the detected spillover coefficient.

24. The system of claim 23, wherein the detection system has a fixed gain.

25. The system of claim 23, wherein the detection system has a broad dynamic range.

26. The system of claim 25, wherein the detection system has a range of at least six decades.

27. The system of claim 23, wherein the processor plots the data set on a spectral spillover data plot such that detections of the first detector are on a first axis of the plot and detections of the second detector are on a second axis of the spectral spillover data plot.

28. The system of claim 27, further comprising a display that presents the spectral spillover data plot to a user.

29. The system of claim 23, wherein the processor sorts a detected particle into a particular fluorochrome population by comparing the detected spillover coefficient for the detected particle to an expected spillover coefficient.

30. The system of claim 29, wherein the processor calculates the expected spillover coefficient using a known best-fit line corresponding to the particular fluorochrome population on a spectral spillover data plot.