Fluorescence analyzer and fluorescence analysis method

Abstract

This invention provides an apparatus and method that can perform highly accurate fluorescence analysis even when using many different types of fluorescent dyes. [Solution] The fluorescence analysis method comprises a first determination step S1, a first separation step S2, and an identification step S5. In the first determination step S1, it is determined whether multiple samples can be separated into two or more groups based on measurement data from one or more detection channels among multiple detection channels. In the first separation step S2, if it is determined in the first determination step S1 that the samples can be separated into two or more groups, one of those groups is separated. The processes of the first determination step S1 and the first separation step S2 are repeated for multiple samples, excluding the samples already identified, until it is determined in the first determination step S1 that the samples cannot be separated into two or more groups.

Description

Technical Field

[0001] The present invention relates to a fluorescence analysis apparatus and a fluorescence analysis method.

Background Art

[0002] A fluorescence analysis technique for discriminating a plurality of samples labeled with any one of a plurality of types of fluorescent dyes according to the type of the fluorescent dye is important, for example, in flow cytometry (FCM). FCM aligns a large number of fluorescently labeled samples (for example, microparticles such as cells) one by one and flows them through a flow path, and detects the intensity of fluorescence and scattered light generated when each sample flowing through the flow path is irradiated with laser light, and discriminates the samples by analyzing the measurement data obtained by the detection.

[0003] In FCM, a plurality of types of fluorescent dyes that specifically bind to samples belonging to each specific population are used, and each of the plurality of samples is labeled with any one of the plurality of types of fluorescent dyes, and the intensity of fluorescence generated by irradiating each sample with laser light is detected to obtain measurement data. At the time of this fluorescence detection, a detection device having a plurality of detection channels that selectively detect fluorescence in each specific wavelength band is used to measure the intensity of fluorescence in each wavelength band. Such measurement is called multi-color measurement. By performing analysis based on this measurement data, the samples can be discriminated according to the type of the labeled fluorescent dye, that is, the samples can be discriminated for each population. Such analysis is called multi-color analysis.

[0004] During multicolor measurements, fluorescence generated by a certain type of fluorescent dye may be detected not only by the detection channel corresponding to that type of fluorescent dye, but also by one or more other detection channels corresponding to other types of fluorescent dyes. This phenomenon is called fluorescence spillover. When fluorescence spillover occurs, even if a sample is originally labeled with only one type of fluorescent dye, the measurement data will appear as if it were labeled with other types of fluorescent dyes as well, leading to errors in the results of multicolor analysis using this measurement data. To address this problem, prior to sample discrimination, a calculation process is performed to subtract the fluorescence intensity of spillover from the fluorescence measurement data obtained by each detection channel. This includes calculations such as fluorescence compensation as described in Patent Documents 1 and 2, or fluorescence unmixing as described in Patent Document 3. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2011-232254 [Patent Document 2] Japanese Patent Publication No. 2011-232259 [Patent Document 3] Patent No. 7564408 [Overview of the Initiative] [Problems that the invention aims to solve]

[0006] Performing computational processing to address fluorescence leakage can increase the variability of measurement data, potentially degrading analytical accuracy. Specifically, in a cytogram plotting measurement data obtained from two detection channels on a two-dimensional map, multiple samples labeled with a single fluorescent dye are displayed as a single group. If fluorescence leakage occurs, the group on the cytogram will appear as if it were labeled with multiple fluorescent dyes, even if it was only labeled with one. While computational processing makes the group appear as if it were labeled with only one fluorescent dye, the increased variability in the measurement data results in a wider distribution compared to the group before computation. If there are two groups on the cytogram, even if they were separable before computation, they may become difficult to separate after computation due to their wider distribution. As a result, analytical accuracy may suffer. This problem becomes more pronounced with increasing numbers of fluorescent dyes used.

[0007] This invention was made to solve the above-mentioned problems and aims to provide an apparatus and method that can perform high-precision fluorescence analysis even when using many types of fluorescent dyes. [Means for solving the problem]

[0008] The fluorescence analyzer of the present invention is a device that detects the fluorescence generated when excitation light is irradiated onto each of several samples labeled with one of several types of fluorescent dyes, and analyzes the pre-processing measurement data obtained by this detection using multiple detection channels to discriminate the samples according to the type of fluorescent dye used for labeling.

[0009] A first aspect of the fluorescence analyzer of the present invention comprises: (1) a first determination unit that determines whether multiple samples can be separated into two or more groups based on measurement data from one or more detection channels among a plurality of detection channels; and (2) a first separation unit that separates one of the groups if the first determination unit determines that the samples can be separated into two or more groups. The first determination unit and the first separation unit repeatedly perform their respective processes on multiple samples, excluding the samples already separated, until the first determination unit determines that the samples cannot be separated into two or more groups, and the samples included in the group that is determined not to be separated are separated as samples labeled with one of the fluorescent dyes.

[0010] A second aspect of the fluorescence analyzer of the present invention further comprises, in addition to the first aspect, (3) a second determination unit that determines whether a plurality of samples included in a separated population can be further separated into two or more populations based on measurement data from any one or more detection channels among a plurality of detection channels, and (4) a second separation unit that separates one of the populations when the second determination unit determines that the samples can be further separated into two or more populations. The processing of the second determination unit and the second separation unit is repeated for a plurality of samples excluding the already separated samples until the second determination unit determines that the samples cannot be separated into two or more populations, and the samples included in the population that has been determined not to be separable are distinguished as samples labeled with any fluorescent dye.

[0011] A third aspect of the fluorescence analyzer of the present invention further comprises, in addition to the first or second aspect, an identification unit that identifies samples that have been identified as being labeled with any of the fluorescent dyes, based on fluorescence spectra obtained from measurement data from multiple detection channels.

[0012] In a fourth aspect of the fluorescence analyzer of the present invention, in addition to any of the first to third aspects, the first determination unit makes a determination based on measurement data obtained by detecting the fluorescence generated when each of several samples labeled with one of several types of fluorescent dyes is irradiated with excitation light of multiple wavelengths using multiple detection channels.

[0013] In a fifth aspect of the fluorescence analyzer of the present invention, in addition to any of the first to fourth aspects, the first determination unit performs a determination after binning the measurement data.

[0014] The fluorescence analysis method of the present invention involves detecting the fluorescence generated when excitation light is irradiated onto each of several samples labeled with one of several types of fluorescent dyes using multiple detection channels, analyzing the pre-processed measurement data obtained, and discriminating the samples according to the type of fluorescent dye used for labeling.

[0015] A first aspect of the fluorescence analysis method of the present invention comprises: (1) a first determination step of determining whether multiple samples can be separated into two or more groups based on measurement data from one or more detection channels among a plurality of detection channels; and (2) a first separation step of separating one of the groups if it is determined in the first determination step that the samples can be separated into two or more groups. The first determination step and the first separation step are repeated for multiple samples, excluding the samples already separated, until it is determined in the first determination step that the samples cannot be separated into two or more groups, and the samples included in the group that is determined not to be separated are separated as samples labeled with one of the fluorescent dyes.

[0016] A second aspect of the fluorescence analysis method of the present invention further comprises, in addition to the first aspect: (3) a second determination step of determining whether a plurality of samples included in a separated population can be further separated into two or more populations based on measurement data from any one or more detection channels among a plurality of detection channels; and (4) a second separation step of separating any one of the populations if it is determined in the second determination step that the samples can be further separated into two or more populations. The second determination step and the second separation step are repeated for a plurality of samples, excluding the samples already separated, until it is determined in the second determination step that the samples cannot be separated into two or more populations, and the samples included in the population that is determined not to be separable are separated as samples labeled with any fluorescent dye.

[0017] A third aspect of the fluorescence analysis method of the present invention further comprises, in addition to the first or second aspect, an identification step in which a sample identified as being labeled with any of the fluorescent dyes is identified based on a fluorescence spectrum obtained from measurement data from multiple detection channels.

[0018] In a fourth aspect of the fluorescence analysis method of the present invention, in addition to any of the first to third aspects, in the first determination step, a determination is made based on measurement data obtained by detecting the fluorescence generated when each of several samples labeled with one of several types of fluorescent dyes is irradiated with excitation light of multiple wavelengths using multiple detection channels.

[0019] In the fifth aspect of the fluorescence analysis method of the present invention, in addition to any of the first to fourth aspects, in the first determination step, the determination is made after binning the measurement data. [Effects of the Invention]

[0020] According to the present invention, high-precision fluorescence analysis can be performed even when using many types of fluorescent dyes. [Brief explanation of the drawing]

[0021] [Figure 1] FIG. 1 is a diagram showing the configuration of the fluorescence analysis apparatus 10. [Figure 2] FIG. 2 is an example of a flowchart of the fluorescence analysis method. [Figure 3] FIG. 3 is another example of a flowchart of the fluorescence analysis method. [Figure 4] FIG. 4 is a diagram showing an example of the fluorescence spectra of each of the fluorescent dyes A to C. [Figure 5] FIG. 5 is a diagram schematically showing four types of samples. [Figure 6] FIG. 6 is a diagram showing a cytogram of measurement data in the first cycle. [Figure 7] FIG. 7 is a diagram showing a cytogram of measurement data of the population X (population A) separated in the first cycle. [Figure 8] FIG. 8(a) is a diagram showing the fluorescence spectra of each of the four populations A to D. FIG. 8(b) is a diagram showing the fluorescence spectrum of only the separated population A. FIG. 8(c) is a diagram showing the fluorescence spectra of the other populations B to D. [Figure 9] FIG. 9(a) is a diagram showing the distribution when a plurality of populations including the population X in the cytogram C1 of ch2 and ch7 are divided into each of the four populations A to D. FIG. 9(b) is a diagram showing the distribution of only the population X (population A) in the cytogram C1 of ch2 and ch7. FIG. 9(c) is a diagram showing the distribution when the other populations in the cytogram C1 of ch2 and ch7 are divided into each of the populations B to D. [Figure 10] FIG. 10 is a diagram showing a cytogram of measurement data in the second cycle (however, excluding the measurement data of the already separated population A). [Figure 11] FIG. 11 is a diagram showing a cytogram of measurement data of the population Y (population D) separated in the second cycle. [Figure 12]Figure 12(a) shows the fluorescence spectra of the three groups B to D. Figure 12(b) shows the fluorescence spectrum of only the separated group D. Figure 12(c) shows the fluorescence spectra of the other groups B and C. [Figure 13] Figure 13(a) shows the distribution of multiple populations, including population Y, in the cytogram C2 of ch6 and ch7, when they are divided into three populations B to D. Figure 13(b) shows the distribution of only population Y (population D) in the cytogram C2 of ch6 and ch7. Figure 13(c) shows the distribution of the other populations in the cytogram C2 of ch6 and ch7 when they are divided into populations B and C. [Figure 14] Figure 14 shows the cytogram of the measurement data in the third cycle (excluding the measurement data of populations A and D, which have already been separated). [Figure 15] Figure 15 shows the cytogram of the measurement data for one separate group (group C) in the third cycle. [Figure 16] Figure 16(a) shows the fluorescence spectra of the two groups B and C. Figure 16(b) shows the fluorescence spectrum of only the separated group C. Figure 16(c) shows the fluorescence spectrum of the other group B. [Figure 17] Figure 17(a) shows the distribution of the two populations in the cytogram C3 of ch5 and ch6, when they are divided into populations B and C. Figure 17(b) shows the distribution of only one population (population C) in the cytogram C3 of ch5 and ch6. Figure 17(c) shows the distribution of the other population (population B) in the cytogram C3 of ch5 and ch6. [Figure 18] Figure 18 shows the cytogram of the measurement data in the fourth cycle (excluding the measurement data of already separated populations A, C, and D). [Figure 19] Figure 19 shows the cytogram of the measurement data in the second cycle (excluding the measurement data of the already separated group X (group A)). [Figure 20]Figure 20 shows the cytogram of the measurement data for the separated populations (an apparent single population Z including populations B and C) in the second cycle. [Figure 21] Figure 21(a) shows the distribution when multiple populations in the cytogram C4 of ch2 and ch7 are divided into three populations B to D. Figure 21(b) shows the distribution of an apparent single population Z, which includes populations B and C, in the cytogram C4 of ch2 and ch7. [Figure 22] Figures 22(a) to (f) show the fluorescence spectra of the six separated groups. [Figure 23] Figures 23(a) to (d) illustrate the method and results for identifying samples included in the population showing the fluorescence spectrum in Figure 22(a) by fitting. [Figure 24] Figures 24(a) to (d) illustrate the results of identifying samples included in the populations showing the respective fluorescence spectra in Figures 22(b) to (e) through fitting. [Modes for carrying out the invention]

[0022] Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the attached drawings. In the description of the drawings, the same elements will be denoted by the same reference numerals, and redundant descriptions will be omitted. The present invention is not limited to these examples, but is indicated by the claims, and all modifications within the meaning and scope equivalent to the claims are intended to be included.

[0023] Figure 1 shows the configuration of the fluorescence analyzer 10. The fluorescence analyzer 10, together with the detection device 20, constitutes a flow cytometer.

[0024] The detection device 20 arranges a large number of fluorescently labeled samples (e.g., minute particles such as cells) one by one and flows them through a channel. When laser light (excitation light) is irradiated onto each sample flowing through the channel, the detection device detects the intensity of the fluorescence and scattered light generated and acquires measurement data obtained from this detection. The detection device 20 has multiple detection channels, each selectively detecting fluorescence in a specific wavelength band. The multiple detection channels for fluorescence detection as a whole may be able to detect a continuous fluorescence spectrum, or they may be able to detect a fluorescence spectrum excluding certain bands. The detection device 20 also has detection channels for detecting scattered light, such as side scatter (SSC) and forward scatter (FSC) generated when laser light is irradiated. The laser light may have multiple wavelengths.

[0025] The fluorescence analyzer 10 receives measurement data acquired by the detection device 20, analyzes this pre-processing measurement data, and discriminates the sample according to the type of labeled fluorescent dye. The fluorescence analyzer 10 may be a computer. The fluorescence analyzer 10 comprises a first determination unit 11, a first separation unit 12, a second determination unit 13, a second separation unit 14, an identification unit 15, an input unit 16, a display unit 17, and a storage unit 18.

[0026] The input unit 16 receives measurement data acquired by the detection device 20, as well as analysis conditions. The display unit 17 displays the status during the analysis and the analysis results on the screen. The display format of the display unit 17 is arbitrary and may be, for example, a cytogram or a histogram. The storage unit 18 stores the measurement data input from the detection device 20 before calculation processing, as well as data during the analysis and data at the end of the analysis. The storage unit 18 also stores programs for executing the processing of the first determination unit 11, the first separation unit 12, the second determination unit 13, the second separation unit 14, and the identification unit 15. The processing of the first determination unit 11, the first separation unit 12, the second determination unit 13, the second separation unit 14, and the identification unit 15 will be described later.

[0027] Figure 2 is an example of a flowchart for a fluorescence analysis method. In the flowchart shown in this figure, the fluorescence analysis method comprises a first determination step S1, a first separation step S2, and an identification step S5. The first determination step S1 is a process performed by the first determination unit 11. The first separation step S2 is a process performed by the first separation unit 12. The identification step S5 is a process performed by the identification unit 15. In this fluorescence analysis method, the fluorescence analyzer 10 does not necessarily have to include a second determination unit 13 and a second separation unit 14.

[0028] In the first determination step S1, the first determination unit 11 determines whether the multiple samples flowing through the flow path can be separated into two or more groups based on measurement data from one or more detection channels among the multiple detection channels of the detection device 20. In the first separation step S2, if the first determination unit 11 determines that the samples can be separated into two or more groups, the first separation unit 12 separates one of those groups.

[0029] The processes of the first determination step S1 and the first separation step S2 are repeated for multiple samples, excluding those already separated, until it is determined that the samples cannot be separated into two or more groups in the first determination step S1. Samples included in the group that is determined not to be separated are separated as samples labeled with one of the fluorescent dyes.

[0030] In identification step S5, the identification unit 15 identifies the samples that have been identified as being labeled with any of the fluorescent dyes based on the fluorescence spectra obtained from measurement data from multiple detection channels.

[0031] Figure 3 shows another example of a flowchart for a fluorescence analysis method. In this flowchart, the fluorescence analysis method includes a first determination step S1, a first separation step S2, and an identification step S5, as well as a second determination step S3 and a second separation step S4. The second determination step S3 is a process performed by the second determination unit 13. The second separation step S4 is a process performed by the second separation unit 14.

[0032] In the second determination step S3, the second determination unit 13 determines whether the multiple samples included in the group separated by the first separation unit 12 or the second separation unit 14 can be further separated into two or more groups based on the measurement data from one or more detection channels among the multiple detection channels. In the second separation step S4, if the second determination unit 13 determines that the samples can be further separated into two or more groups, the second separation unit 14 separates one of those groups.

[0033] The processes of the second determination step S3 and the second separation step S4 are repeated for multiple samples, excluding those already differentiated, until it is determined in the second determination step S3 that the samples cannot be separated into two or more groups. If it is determined in the second determination step S3 that the samples cannot be separated into two or more groups, identification is performed in the identification step S5. In other words, the samples included in the group that was determined not to be separable are differentiated as samples labeled with one of the fluorescent dyes.

[0034] The fluorescence analysis flowcharts shown in Figures 2 and 3 are illustrative examples, and other forms of fluorescence analysis flowcharts are possible. In the identification step S5, each time a group is determined to be inseparable by the first determination step S1 or the second determination step S3, the sample included in that group may be identified. Also, if it is determined in the second determination step S3 that the sample cannot be separated into two or more groups, instead of performing identification in the identification step S5, the process may return to the first determination step S1 and select a different group. In the first determination step S1 or the second determination step S3, the determination may be made after binning the measurement data. When separating one group from other groups on the cytogram display, an arbitrary threshold may be set. For example, if the threshold is set to 0 counts, a region that can be surrounded by 0 counts and does not contain any other groups is defined, and one group within that range is separated.

[0035] The first determination step S1, the first separation step S2, the second determination step S3, and the second separation step S4 may be performed based on a cytogram, histogram, etc., displayed on the display unit 17, or they may be performed automatically by numerical calculation without being displayed on the display unit 17. When a cytogram, histogram, etc., is displayed on the display unit 17, the determination and separation may be performed automatically, or the operator may perform the determination and separation manually. When the determination and separation are performed automatically by numerical calculation, the determination and separation can be performed without providing prior knowledge about the measurement data using unsupervised learning machine learning methods.

[0036] Next, the fluorescence analysis method shown in Figure 2 will be further explained using Figures 4 to 18. Here, the number of detection channels for fluorescence detection is set to 12, and the 12 detection channels are designated as ch1 to ch12 in order from the short wavelength side. Three types of fluorescent dyes A to C will be used. Figure 4 is a diagram showing an example of the fluorescence spectrum of each of the fluorescent dyes A to C. There are four types of samples: a sample labeled with one fluorescent dye A, a sample labeled with one fluorescent dye B, a sample labeled with one fluorescent dye C, and a sample that is not labeled with any fluorescent dye. Figure 5 is a diagram schematically showing the four types of samples. Hereafter, the group of samples labeled with one fluorescent dye A will be called group A, the group of samples labeled with one fluorescent dye B will be called group B, the group of samples labeled with one fluorescent dye C will be called group C, and the group of samples that are not labeled with any fluorescent dye will be called group D. In reality, the relationship between each population and the fluorescent dye cannot be determined without performing identification in identification step S5. However, for the sake of simplicity, the notation in the cytogram will be linked to the above-mentioned populations A to D, and the explanation will be provided accordingly.

[0037] Figures 6 to 9 illustrate the processing of the first cycle in the iterative processing of the first determination step S1 and the first separation step S2.

[0038] Figure 6 shows a cytogram of the measurement data before processing. In actual cytograms, as shown in this figure, the overlapping of the four groups is not explicitly shown and is displayed as a simple grayscale; however, as above, for the sake of simplicity of explanation, the four groups A to D will be explicitly shown from here on. This figure shows cytograms for all combinations of two detection channels selected from the 12 detection channels. As shown in this figure, in many cytogram displays, two or more of the four groups (here, groups A to D) overlap with each other, making it impossible to separate the four groups individually. However, in a certain cytogram display (for example, cytogram C1 in Figure 6, which plots the measurement data for ch2 and ch7 on a two-dimensional map), one group X (here, group A) and the other groups (here, groups B to D) do not overlap with each other and can be separated (Figure 9). Therefore, in the first determination step S1, it is determined that group X can be separated from the other groups in the cytogram display of ch2 and ch7. Then, in the first separation step S2, group X is separated from the four groups.

[0039] Figure 7 shows the cytogram of the measurement data for the separated population X. This figure also shows the cytogram for all combinations of two detection channels selected from the 12 detection channels. Based on the display of these cytograms, it is not possible to perceive the existence of multiple populations, so it can be confirmed that population X is only one population (in this case, population A).

[0040] Figure 8(a) shows the fluorescence spectra of the four groups A to D. Figure 8(b) shows the fluorescence spectrum of only the separated group A. Figure 8(c) shows the fluorescence spectra of the other groups B to D. Figure 9(a) shows the distribution of multiple groups, including group X, in the cytogram C1 of ch2 and ch7, when they are divided into four groups A to D. Figure 9(b) shows the distribution of only group X (group A) in the cytogram C1 of ch2 and ch7. Figure 9(c) shows the distribution of the other groups in the cytogram C1 of ch2 and ch7 when they are divided into groups B to D.

[0041] Figures 10 to 13 illustrate the processing of the second cycle of the iterative processing of the first determination step S1 and the first separation step S2.

[0042] Figure 10 shows the cytogram of the measurement data before processing (excluding the measurement data of group X (group A) that has already been separated). This figure also shows the cytogram for all combinations of two detection channels selected from the 12 detection channels. As shown in this figure, in many cytogram displays, two or more of the three groups (groups B to D in this case) overlap with each other, making it impossible to separate the three groups individually. However, in a certain cytogram display (for example, cytogram C2 in Figure 10, which plots the measurement data of ch6 and ch7 on a two-dimensional map), one group Y (group D in this case) and the other groups (groups B and C in this case) do not overlap with each other and can be separated (Figure 13). Therefore, in the first determination step S1, it is determined that group Y can be separated from the other groups in the cytogram display of ch6 and ch7. Then, in the first separation step S2, group Y is separated from the three groups.

[0043] Figure 11 shows the cytogram of the measurement data for the separated population Y. This figure also shows the cytogram for all combinations of two detection channels selected from the 12 detection channels. Based on the display of these cytograms, it is not apparent that multiple populations exist, so it can be confirmed that population Y is only one population (in this case, population D).

[0044] Figure 12(a) shows the fluorescence spectra of each of the three groups B to D. Figure 12(b) shows the fluorescence spectrum of only the separated group D. However, since the sample of group D is not fluorescently labeled, the fluorescence from the sample of group D is not due to the target fluorescent dye, but is autofluorescence from the sample. In this embodiment, for the sake of simplicity of explanation, autofluorescence will not be considered. Figure 12(c) shows the fluorescence spectra of the other groups B and C. Figure 13(a) shows the distribution when multiple groups, including group Y, in the cytogram C2 of ch6 and ch7 are divided into three groups B to D. Figure 13(b) shows the distribution of only group Y (group D) in the cytogram C2 of ch6 and ch7. Figure 13(c) shows the distribution when the other groups in the cytogram C2 of ch6 and ch7 are divided into groups B and C.

[0045] Figures 14 to 17 illustrate the processing of the third cycle of the iterative processing of the first determination step S1 and the first separation step S2.

[0046] Figure 14 shows the cytogram of the measurement data before calculation (excluding the measurement data of already separated groups X and Y (groups A and D)). This figure also shows the cytogram for all combinations of two detection channels selected from the 12 detection channels. As shown in this figure, in the display of a certain cytogram (for example, in Figure 14, cytogram C3, which plots the measurement data of ch5 and ch6 on a two-dimensional map), the two groups (group B and group C in this case) do not overlap and can be separated from each other (Figure 17). Therefore, in the first determination step S1, it is determined that the two groups can be separated into separate groups based on the display of the cytograms of ch5 and ch6. Then, in the first separation step S2, one group (group C in this case) is separated from the two groups.

[0047] Figure 15 shows the cytogram of the measurement data for the separated population C. This figure also shows the cytogram for all combinations of two detection channels selected from the 12 detection channels. Based on the display of these cytograms, it is not apparent that multiple populations exist, so it can be confirmed that there is only one population (in this case, population C).

[0048] Figure 16(a) shows the fluorescence spectra of the two groups B and C. Figure 16(b) shows the fluorescence spectrum of only the separated group C. Figure 16(c) shows the fluorescence spectrum of the other group B. Figure 17(a) shows the distribution of the two groups B and C in the cytogram C3 of ch5 and ch6. Figure 17(b) shows the distribution of only one group (group C) in the cytogram C3 of ch5 and ch6. Figure 17(c) shows the distribution of the other group (group B) in the cytogram C3 of ch5 and ch6.

[0049] Figure 18 shows the cytograms of the measurement data in the fourth cycle (excluding the measurement data of already separated populations (populations A, C, and D in this case)). This figure also shows the cytograms for all combinations of two detection channels selected from the 12 detection channels. As shown in this figure, based on the display of these cytograms, it is not possible to recognize the existence of multiple populations, so it can be confirmed that there is only one population (population B in this case). In this fourth cycle, in the first determination step S1, it is determined that no further separation of populations is possible.

[0050] In this way, by repeatedly performing the first determination step S1 and the first separation step S2, the samples can be separated into four groups (groups A to D). Samples in each group that are determined to be beyond further separation are distinguished as samples labeled with one of the fluorescent dyes. Then, in the identification step S5, the samples distinguished as labeled with one of the fluorescent dyes are identified based on the fluorescence spectra obtained from measurement data from multiple detection channels. In other words, as a result of the identification step S5, it is possible to determine which of groups A to D each individually separated group belongs to.

[0051] Next, the fluorescence analysis method shown in Figure 3 will be further explained using Figures 19 to 21. Here, we will explain the case where the same processing as the first cycle described above is performed, followed by a different processing than that of the second cycle described above.

[0052] Figure 19 shows the cytogram of the measurement data before processing (excluding the measurement data of group X (group A) that has already been separated). This figure is similar to the cytogram shown in Figure 10, but here we will focus on the cytogram C4 of ch2 and ch7. In the display of the cytogram C4 of ch2 and ch7, groups B, C and group D do not overlap with each other and can be separated (Figure 21). However, in the display of cytogram C4, groups B and C overlap with each other, so they appear to be displayed as one group Z. Therefore, in the first determination step S1, it is determined that the cytogram C4 of ch2 and ch7 can be separated into group Z (groups B, C) and group D. Then, in the first separation step S2, from the two groups, the apparent single group Z, which includes groups B and C, is separated.

[0053] Figure 20 shows the cytograms of the measurement data for the separated population Z (here, an apparent single population including populations B and C). Looking at the cytograms C51 for ch2 and ch6, C52 for ch3 and ch6, C53 for ch4 and ch6, and C54 for ch5 and ch6, it can be seen from these representations that population Z separated in the first separation step S2 can actually be separated into two populations. Therefore, in the second determination step S3, it is determined that population Z separated in the first separation step S2 can be further separated into multiple populations. Then, in the second separation step S4, one of these multiple populations is separated. The second determination step S3 and the second separation step S4 can be repeated in this manner.

[0054] Figure 21(a) shows the distribution when multiple populations in the cytogram C4 of ch2 and ch7 are divided into three populations B to D. Figure 21(b) shows the distribution of an apparent single population Z, which includes populations B and C, in the cytogram C4 of ch2 and ch7.

[0055] Next, the process of identification step S5 will be further explained using Figures 22 to 24. In identification step S5, samples included in the population that were determined not to be further separated in the first determination step S1 or the second determination step S3 are identified based on the fluorescence spectrum obtained from measurement data from multiple detection channels for fluorescence detection. Each sample included in a single population is assumed to be similarly labeled with a fluorescent dye. A sample may not be labeled with any fluorescent dye, may be labeled with only one of several types of fluorescent dyes, or may be labeled with two or more types of fluorescent dyes. Furthermore, if a sample is labeled with two or more types of fluorescent dyes, the number of dyes may differ depending on the type of fluorescent dye. The fluorescence spectrum measured for each sample included in a single population will correspond to the type and number of fluorescent dyes that label each sample.

[0056] In identification step S5, the type and number of fluorescent dyes labeling each sample are identified. Identification can be done either by direct comparison with the fluorescence spectra of each type of fluorescent dye, or by computational processing. The former allows for faster processing because no computation is required. However, as will be discussed later in Figures 22-24, when the relationship between the sample and the fluorescent dye can take various forms, identification is often difficult without computational processing. Various computational processing methods exist, such as fluorescence correction and fluorescence intensity calculation. More specifically, methods include obtaining the fluorescence spectra of each type of fluorescent dye in advance and using them as references for fitting, or methods that do not require the use of references (see Patent Document 3). Below, as an example, an identification method using fitting with references will be described. Here, we will assume that three types of fluorescent dyes A-C are used, and their fluorescence spectra (references) are as shown in Figure 4. Furthermore, we will assume that the samples were separated into six groups in the first separation step S2 or the second separation step S4.

[0057] Figures 22(a) to (f) show the fluorescence spectra of the six separated groups. Of these, the fluorescence spectra in Figures 22(a) to (e) differ from the fluorescence spectra shown in Figure 4, indicating fluorescence generated in samples labeled with two or more fluorescent dyes. The fluorescence spectrum in Figure 22(f) shows no fluorescence generation from the fluorescent dye, indicating autofluorescence of a sample that was not labeled with any fluorescent dye.

[0058] Figure 23(a) shows the fluorescence spectrum of Figure 22(a) and the fluorescence spectrum (reference) of fluorescent dye A in Figure 4. Figure 23(b) shows the fluorescence spectrum of Figure 22(a) and the fluorescence spectrum (reference) of fluorescent dye B in Figure 4. Figure 23(c) shows the fluorescence spectrum of Figure 22(a) and the fluorescence spectrum (reference) of fluorescent dye C in Figure 4. The fluorescence spectrum of Figure 22(a) is a composite spectrum represented by a linear sum of the fluorescence spectra (reference) of fluorescent dyes A to C. In reality, the composite spectrum is represented by a linear sum of the fluorescence spectra (reference) including the autofluorescence of the sample, but in this embodiment, for the sake of simplicity of explanation, the influence of the autofluorescence of the sample is assumed to be negligible (not considered) as described above. When fitting is performed using this, it can be seen that the samples included in this group are labeled with one fluorescent dye A, two fluorescent dyes B, and one fluorescent dye C (Figure 23(d)).

[0059] Similarly, by performing a fitting process, it can be seen that the samples included in the group showing the fluorescence spectrum in Figure 22(b) are labeled with one fluorescent dye A, one fluorescent dye B, and one fluorescent dye C (Figure 24(a)). The samples included in the group showing the fluorescence spectrum in Figure 22(c) are labeled with one fluorescent dye B and one fluorescent dye C (Figure 24(b)). The samples included in the group showing the fluorescence spectrum in Figure 22(d) are labeled with two fluorescent dyes B and one fluorescent dye C (Figure 24(c)). The samples included in the group showing the fluorescence spectrum in Figure 22(e) are labeled with one fluorescent dye A and one fluorescent dye B (Figure 24(d)).

[0060] As described above, in this embodiment, population separation is performed as much as possible using measurement data before computational processing, and then identification is performed based on the fluorescence spectra of the samples in each separated population. Therefore, variability in measurement data due to computational processing is suppressed, and the accuracy of the analysis can be improved. In addition, limitations due to fluorescence intensity and fluorescence wavelength band are relaxed, and it becomes possible to increase the number of types of fluorescent dyes that can be used. [Explanation of Symbols]

[0061] 10...Fluorescence analyzer, 11...First determination unit, 12...First separation unit, 13...Second determination unit, 14...Second separation unit, 15...Identification unit, 16...Input unit, 17...Display unit, 18...Storage unit, 20...Detection device.

Claims

1. A device that detects the fluorescence generated when excitation light is irradiated onto each of several samples labeled with one of several types of fluorescent dyes, and analyzes the pre-processing measurement data obtained by this detection using multiple detection channels to discriminate samples according to the type of fluorescent dye used for labeling. A first determination unit determines whether the plurality of samples can be separated into two or more groups based on measurement data from one or more detection channels among the plurality of detection channels, If the first determination unit determines that the data can be separated into two or more groups, the first separation unit separates one of those groups, Equipped with, The first determination unit repeatedly processes multiple samples, excluding those already discriminated, until it is determined that they cannot be separated into two or more groups. Samples included in the group determined to be inseparable are then discriminated as samples labeled with one of the fluorescent dyes. Fluorescence analyzer.

2. A second determination unit determines whether multiple samples included in the separated population can be further separated into two or more populations based on measurement data from one or more of the multiple detection channels, If the second determination unit determines that the group can be further separated into two or more groups, the second separation unit separates one of those groups, Furthermore, The second determination unit repeatedly processes multiple samples, excluding those already discriminated, until it is determined that they cannot be separated into two or more groups. Samples included in the group determined to be inseparable are then discriminated as samples labeled with one of the fluorescent dyes. The fluorescence analyzer according to claim 1.

3. The system further includes an identification unit that identifies samples that have been identified as being labeled with any of the fluorescent dyes, based on the fluorescence spectra obtained from the measurement data of the multiple detection channels. The fluorescence analyzer according to claim 1.

4. The first determination unit makes a determination based on measurement data obtained by detecting the fluorescence generated when each of several samples labeled with one of several types of fluorescent dyes is irradiated with excitation light of multiple wavelengths using multiple detection channels. The fluorescence analyzer according to claim 1.

5. The first determination unit performs a determination after binning the measurement data. The fluorescence analyzer according to claim 1.

6. A method for discriminating samples according to the type of fluorescent dye used for labeling, which involves detecting the fluorescence generated when excitation light is irradiated onto each of several samples labeled with one of several types of fluorescent dyes using multiple detection channels, and analyzing the pre-processing measurement data obtained from this analysis. A first determination step of determining whether the plurality of samples can be separated into two or more groups based on measurement data from one or more detection channels among the plurality of detection channels, If it is determined in the first determination step that the group can be separated into two or more groups, the first separation step involves separating one of those groups, Equipped with, The first determination step and the first separation step are repeated for multiple samples, excluding those already separated, until it is determined that they cannot be separated into two or more groups in the first determination step. Samples included in the group that is determined not to be separated are then separated as samples labeled with one of the fluorescent dyes. Fluorescence analysis methods.

7. A second determination step involves determining whether multiple samples included in the separated population can be further separated into two or more populations based on measurement data from one or more of the multiple detection channels, If it is determined in the second determination step that the group can be further separated into two or more groups, a second separation step is performed to separate one of those groups, Furthermore, The second determination step and the second separation step are repeated for multiple samples, excluding those already separated, until it is determined that the samples cannot be separated into two or more groups in the second determination step. Samples included in the group that is determined not to be separated are then separated as samples labeled with one of the fluorescent dyes. The fluorescence analysis method according to claim 6.

8. The system further includes an identification step in which, for samples that have been identified as being labeled with any of the fluorescent dyes, identification is performed based on the fluorescence spectrum obtained from the measurement data of the multiple detection channels. The fluorescence analysis method according to claim 6.

9. In the first determination step, a determination is made based on measurement data obtained by detecting the fluorescence generated when each of several samples labeled with one of several types of fluorescent dyes is irradiated with excitation light of multiple wavelengths using multiple detection channels. The fluorescence analysis method according to claim 6.

10. In the first determination step, the determination is made after binning the measurement data. The fluorescence analysis method according to claim 6.

Images