A three-dimensional flow cytometer and method based on optical detection and ICP-MS

Abstract

The application designs a three-dimensional flow cytometer and method based on optical detection and ICP-MS combination, relates to the technical field of life analysis scientific detection equipment; first, a three-dimensional flow cytometer is provided, a three-dimensional flow cytometer method based on optical detection and ICP-MS combination is designed based on the analyzer, and the flow cytometer can only perform single-parameter flow cytometer analysis of fluorescence, scattering and mass spectrum or multi-parameter flow cytometer analysis in any combination; the data processing software in the analyzer can provide offline processing of flow cytometer analysis data of fluorescence, side scattering light and mass spectrum, identify, calculate and statistically analyze single-cell pulse signals, especially can provide integration and unification among fluorescence, side scattering and mass spectrum single-cell signals, and obtain three-parameter information of the same cell.

Description

Technical Field

[0001] This invention relates to the field of life science detection equipment technology, and in particular to a three-dimensional flow cytometer and method based on optical detection and ICP-MS. Background Technology

[0002] Due to the significant heterogeneity among different cells, analyzing the composition and content of intracellular substances at the single-cell level has become essential for exploring life phenomena and understanding the complex mechanisms of diseases. Among existing single-cell analysis techniques, flow cytometry is the most mature and widely used. Currently, ordinary flow cytometers can easily achieve high-throughput single-cell analysis with four colors and six parameters, while more advanced commercial flow cytometers can simultaneously analyze up to thirty parameters. Furthermore, the target analytes of commercial flow cytometers cover all biological particles from the micrometer to the nanometer scale. Therefore, flow cytometry has become an indispensable technique in basic research fields such as cell biology, as well as in clinical medical testing. However, because fluorescence is a band spectrum, the full width at half maximum (FWHM) of fluorescent probes is typically 20–30 nm, limiting the number of probes that can be accommodated in the visible light region. Therefore, in practical multicolor flow cytometry applications, the number of parameters that a flow cytometer can simultaneously quantify is usually around fourteen.

[0003] The maturity and refinement of flow cytometry have not hindered its further development. In recent years, with the rapid advancements in optoelectronics and microfabrication technologies, and the increasing demand for personalized single-cell analysis, novel flow cytometry techniques such as mass spectrometry, imaging flow cytometry, and spectroscopic flow cytometry have emerged and rapidly achieved commercialization. Among these, mass spectrometry, combining flow cytometry with plasma time-of-flight mass spectrometry (ICP-TOFMS), represents a significant breakthrough in the simultaneous quantification capacity of flow cytometry parameters. Using metal element labels with extremely low background, mass spectrometry can simultaneously quantify up to 45 cell parameters without concern for parameter overlap or crosstalk. This offers a significant advantage for in-depth analysis of cellular immunophenotypic patterns in complex systems. Furthermore, with the continuous development and improvement of metal element labeling technology, mass spectrometry has gradually begun to play a crucial role in research fields such as immunology. However, mass spectrometry also exhibits certain limitations. Firstly, due to limitations imposed by the polymeric chelates used to attach metal-tagged ions, the sensitivity of mass cytometry is about an order of magnitude lower than that of fluorescence cytometry. Secondly, although structural and morphological information of cells can be obtained through specialized elemental labeling methods, these methods are more cumbersome and complex than traditional flow cytometry. Furthermore, mass cytometry is destructive to particles / cells, making cell recovery impossible and preventing the sorting of mixed cell samples.

[0004] The development of single-cell analysis technology has always aimed to achieve higher resolution and simultaneous analysis of more parameters. Since the advantages and limitations of fluorescence cytometry and mass cytometry are closely related to the detection mode, the combination of multiple detection technologies is inevitably an important direction for the future development of flow cytometry single-cell analysis technology. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a three-dimensional flow cytometer and method based on optical detection and ICP-MS.

[0006] A three-dimensional flow cytometer based on optical detection and ICP-MS combined includes a fluid flow system, an optical detection system, a mass spectrometry detection system, and an electronic and software system;

[0007] The fluid flow system focuses and arranges the chaotically dispersed cells in the cell suspension into a single-cell stream, which then passes through the detection sites of the optical detection system one by one at a stable flow rate to acquire optical detection signals for each single cell. Subsequently, the cells are introduced into the mass spectrometry detection system to obtain mass spectrometry single-cell signals. The fluid flow system, optical detection system, and mass spectrometry detection system all operate under the control of the instrument control software in the electronic and software system. The acquired single-cell signals are processed and analyzed by the data processing software in the electronic and software system.

[0008] The optical detection system includes a laser, a laser beam reducer, a first reflecting mirror, a first filter, a dichroic mirror, a first objective lens, a second reflecting mirror, a second filter, an aspherical lens, a first pinhole plate, a first detector, a second objective lens, a third reflecting mirror, a third filter, a second pinhole plate, and a second detector.

[0009] The laser is fixed to the top plate of a dark box constructed of aluminum alloy plates. The dark box is fixed to an optical plate, which is in turn fixed to an aluminum support frame. The first filter, dichroic mirror, second filter, second reflector, lens, first pinhole plate, first detector, third reflector, third filter, second pinhole plate, and second detector are all encapsulated inside the dark box. The laser beam reducer is fixed at the laser beam exit point. The first reflector and objective lens are fixed to the top plate of the dark box. The first, second, and third reflectors are respectively fixed to an angle-adjustable beam deflector. The laser emits... The laser beam passes sequentially through a laser beam reducer, a first reflecting mirror, a first filter, a dichroic mirror, and a first objective lens before being focused onto the sample stream, forming the excitation optical path. The fluorescence generated by the laser beam excitation of the sample is collected by the first objective lens and then sequentially passes through a dichroic mirror, a second reflecting mirror, a second filter, an aspherical lens, and a first pinhole plate before being detected by the first detector, forming the fluorescence collection optical path. The side-scattered light generated by the laser irradiation of the sample is collected by the second objective lens in a direction orthogonal to the excitation optical path, and then sequentially passes through a third reflecting mirror, a third filter, and a second pinhole plate before being detected by the second detector, forming the side-scattered optical path.

[0010] The fluid flow system includes an air compressor, a pressure controller, a flow sensor, a sheath bottle, a sample tube, a syringe, a switching valve, an injection capillary, and a quartz flow cell;

[0011] The system comprises an air compressor placed on the ground, a pressure controller fixed within a support bracket beneath the optical detection system, a flow sensor fixed to the top plate of the optical detection system's dark box, a sheath bottle fixed to an optical plate, and a sample inlet capillary fixed to the optical plate via a lifting slide bar. The air compressor is connected to the pressure controller, providing pressure input. The pressure controller has two outputs, pressure output 1 and pressure output 2, which are connected to the pressure input ports of the sheath bottle and sample tube, respectively. The sample tube is inserted into the inlet end of the sample inlet capillary, and the outlet end of the sample inlet capillary, the sheath bottle, and the syringe are all connected to the quartz flow cell. The sheath fluid lines are connected via Teflon tubing; the pressure lines are all connected via thermoplastic polyurethane tubing; the syringe and flow cell are connected via silicone tubing and equipped with a switch valve; the rinsing fluid is manually actuated; the quartz flow cell is transparent on all four sides and has a focusing channel inside; the quartz flow cell is fixed on a three-dimensional translation stage on the top plate of the optical detection system, and the focusing channel of the quartz flow cell is focused with the optical detection system via the three-dimensional translation stage; the cell suspension is encapsulated and squeezed by the sheath fluid inside the focusing channel to form a single-cell flow, which is then optically detected and subsequently transmitted to the mass spectrometry detection system via the output capillary;

[0012] The mass spectrometry detection system includes a high-efficiency nebulization system and an ICP-MS. The high-efficiency nebulization system consists of a capillary tube, an original nebulizer, an original adapter, and a quartz nebulization chamber. The output capillary of the liquid flow system is connected to the original nebulizer through the capillary tube. The quartz nebulization chamber is equipped with an inlet, an outlet, and a waste outlet. The inlet of the quartz nebulization chamber and the nebulizer are connected and fixed through the original adapter, the outlet is connected to the ICP-MS, and the waste outlet is connected to the waste outlet pipe of the ICP-MS.

[0013] The electronic and software system includes an electronic system, instrument control software, and data processing software. The electronic system includes a signal conversion and amplification module, a data acquisition card, and a host computer. The voltage signal generated by the first detector is directly acquired by the data acquisition card. The current signal generated by the second detector is converted into a voltage signal by the conversion and amplification module and then amplified before being acquired by the data acquisition card. Both the instrument control software and the data processing software are written in LabVIEW and installed on the host computer. The instrument control software controls the pressure controller, the detector gain of the optical detection system, and the data acquisition of the data acquisition card, and controls the synchronous triggering of data acquisition by the optical detection system and the mass spectrometry detection system. The data processing software performs data display, signal recognition, data filtering, integration and unification of fluorescence and scattering single-cell signals, integration and unification of single-cell signals obtained by the optical detection system and the mass spectrometry detection system, and statistical analysis of single-cell signals.

[0014] A three-dimensional flow cytometry analysis method based on optical detection and ICP-MS, implemented using the aforementioned three-dimensional flow cytometry analyzer based on optical detection and ICP-MS, specifically includes the following steps:

[0015] Step 1: First, ignite and preheat the mass spectrometry detection system;

[0016] Step 2: Before each sample test, the liquid flow system needs to be pre-flushed to remove air bubbles and form a stable sheath flow. First, replace the solution in the sample tube with ultrapure water, turn on the air compressor and pressure controller, set the pressure output of the pressure controller on the instrument control software, let the sheath fluid fill the entire liquid flow channel, and run the instrument control software until the pressure output is stable and the sheath fluid flow rate obtained by the flow meter reaches the preset flow rate and the flow rate is stable before proceeding to the next step.

[0017] Step 3: Powering on the optical detection system and setting its parameters: Turn on the laser, set the gain voltage of the first and second detectors, and set the acquisition frequency of the data acquisition card;

[0018] Step 4: Establish the detection method of inductively coupled plasma mass spectrometry: Open the control software MassHunter that comes with ICP-MS, create a new batch in the "Batch Processing" module, and then set the acquisition mode to time-resolved mode, the integration time to 0.1s, the data acquisition time, and select the element to be detected in the new batch.

[0019] Step 5: Sample introduction: Pause the pressure output 2 of the pressure controller to the pressure input of the sample tube, replace the ultrapure water in the sample tube with cell suspension, and continue to apply pressure to the sample tube to introduce the cell suspension;

[0020] Step 6: Perform data acquisition; Set the data acquisition time on the instrument control software, and realize the linkage with MassHunter through the attribute node call method to synchronously trigger the data acquisition of fluorescence, scattering and mass spectrometry intensity time-series spectra of the optical detection system and the mass spectrometry detection system, and obtain fluorescence / side scattering light signal intensity-time spectrum and mass spectrometry signal intensity-time spectrum;

[0021] Step 7: Process the data collected in the above steps; import the collected fluorescence signal intensity-time spectrum data, side-scattered light signal intensity-time spectrum data, and mass spectrometry signal intensity-time spectrum data into data processing software for processing to obtain the peak height, peak area, and peak width information of the single-cell pulse signal spectrum peak for semi-quantitative analysis of the fluorescence signal, and perform statistical analysis to obtain the frequency distribution results of the peak height, peak area, and peak width information of the single-cell pulse signal spectrum peak; then integrate and unify the fluorescence single-cell signal, side-scattered light single-cell signal, and mass spectrometry single-cell signal to obtain single-cell three-parameter analysis data, and perform statistical analysis on them;

[0022] The integration and unification of fluorescence single-cell signals, side-scattered light single-cell signals, and mass spectrometry single-cell signals involves the following steps:

[0023] Step S01: After data processing such as peak identification, obtain a list of fluorescence, side scattering and mass spectrometry single-cell signals recorded in the format of "peak time - peak height - peak area"; after integrating and unifying the fluorescence-side scattering single-cell signals, obtain a list of dual-parameter single-cell signals recorded in the format of "peak time - fluorescence peak height - fluorescence peak area - scattering peak height - scattering peak area".

[0024] Step S02: Extract the peak times from the dual-parameter single-cell signal list and the mass spectrometry single-cell signal list, and compile them into two separate arrays t. O [n] and t M [m], and according to formula L j,k =t Oj -t Mk Calculate all tO [n] element and t M The difference between each element in the [m] array is used to obtain the lag time array L between optical detection and mass spectrometry detection. j,k [n×m];

[0025] Where n is the total number of signals in the two-parameter single-cell signal list, and m is the total number of signals in the mass spectrometry single-cell signal list; t Oj It is the time when the j-th single-particle signal peak appears in the two-parameter single-cell signal list, j = 1, 2, 3, ..., n, n, t Mk It is the time when the k-th single-particle signal peak appears in the mass spectrometry single-cell signal list, k = 1, 2, 3, ... m;

[0026] Step S03: Process the obtained lag time array L j,k Statistical analysis was performed on all elements in [n×m], and a frequency distribution histogram was plotted. The results showed that L... j,k Elements in [n×m] will show significant cumulative peaks;

[0027] Step S04: Adjust the lag time window size W OM Optimize the size; use nested for loops to iterate over L. OM and W OM The size is optimized using two parameters to determine the final W. OM The numerical value; lag time L OM The optimization interval is determined based on the position of the cumulative peak in the frequency distribution histogram; the optimization interval for the lag time window size is determined based on the half-peak width of the cumulative peak in the frequency distribution histogram.

[0028] Step S05: Based on the lag time window size W OM Size of L OM Further confirmation is needed; with L OM ±(W OM / 2) As a lag time window, in t M Search in [m] for whether there is an element belonging to t. Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); If one or more elements belong to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2), then it means that one or more elements may be related to t. Oj Corresponding single-cell signal concurrent mass spectrometry single-cell signal; through L OM Take values ​​and calculate different L values. OM t of concurrent mass spectrometry signals under different valuesO [n] Element count, determining the final L OM Values;

[0029] Step S06: With L OM ±(W OM / 2) As a lag time window, pair them one by one at t M Search in [m] for whether there is an element belonging to t. Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); If there is an element t Mk Belongs to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2), then t Oj The corresponding two-parameter single-cell signal and t Mk These are concurrent single-cell signals; if multiple elements belong to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); After screening and calculation, t is obtained. Oj and t Mk A two-dimensional array;

[0030] Step S07: Combine with t Oj The information in the corresponding two-parameter single-cell list, including "fluorescence peak height – fluorescence peak area – scattering peak height – scattering peak area composition", and its relationship with t Mk The corresponding "peak time - peak height - peak area" are integrated to form a three-dimensional single-cell signal data list recorded as "peak time - fluorescence peak height - fluorescence peak area - scattering peak height - scattering peak area - mass spectrometry signal peak height - mass spectrometry signal peak area", thus completing the integration and unification of three-dimensional single-cell signals.

[0031] Beneficial technical effects of the present invention:

[0032] A three-dimensional flow cytometry analysis method based on optical detection and ICP-MS is disclosed. This method utilizes a three-dimensional flow cytometer based on optical detection and ICP-MS, enabling single-cell flow cytometry analysis of only one parameter (fluorescence, scattering, or mass spectrometry) or any combination of multiple parameters. Specifically, it offers the following advantages:

[0033] 1. The fluorescence collection optical path and the scattered light collection optical path of the present invention are independent of each other, which greatly reduces the difficulty of focusing the optical path while ensuring high detection sensitivity, and the user can adjust the focus himself.

[0034] 2. The liquid flow system and the high-efficiency atomization system of the present invention are connected by an output capillary, which can provide stable cell transport. Moreover, the operating conditions of the liquid flow system and the high-efficiency atomization system are fully compatible, which can provide long-term stable and efficient atomization.

[0035] 3. This invention can provide three-parameter flow cytometry single-cell analysis, which provides semi-quantitative fluorescence information, cell particle size information represented by side scattering, and single-cell elemental content information represented by mass spectrometry signal.

[0036] 4. The instrument control software in this invention provides synchronous triggering of data acquisition for the optical detection system and the mass spectrometry detection system based on the attribute node calling method, ensuring the consistency between parallel measurement data.

[0037] 5. The data processing software of the present invention can provide offline processing of flow cytometry single-cell analysis data of fluorescence, side-scatter light and mass spectrometry, and perform identification, calculation and statistical analysis of single-cell pulse signals. In particular, it can provide integration and unification between fluorescence, side-scatter and mass spectrometry single-cell signals to obtain three-parameter information of the same cell.

[0038] 6. The present invention has a compact structure and small size. Moreover, the present invention is a modular and open design, with the fluid flow system and the detection system being independent of each other. Users can perform flow cytometry single-cell analysis using only the optical system or the mass spectrometry system, or modify the instrument according to their needs or use it in conjunction with sample pretreatment modules such as microfluidic chips to meet personalized single-cell analysis needs. Attached Figure Description

[0039] Figure 1 This invention relates to a structural diagram of a three-dimensional flow cytometer based on optical detection and ICP-MS; wherein, 1-laser, 2-laser beam shrinker, 3-first reflecting mirror, 4-first filter, 5-dichroic mirror, 6-first objective lens, 7-quartz flow cell, 8-second reflecting mirror, 9-second filter, 10-aspheric lens, 11-first pinhole plate, 12-first detector, 13-second objective lens, 14-third reflecting mirror, 15-third filter, 16-second pinhole plate. 17-Second detector, 18-Sample tube, 19-Injection capillary, 20-Sheath liquid bottle, 21-Flow meter, 22-Injector, 23-Switch valve, 24-Air compressor, 25-Pressure controller, 26-Output capillary, 27-High-efficiency nebulization system, 28-Inductively coupled plasma mass spectrometry, 29-Conversion amplification module, 30-Data acquisition card, 31-Host computer, A-Optical detection system, B-Flow system, C-Mass spectrometry detection system, D-Electronic and software system.

[0040] Figure 2The present invention provides an evaluation diagram of the focusing effect of the liquid flow system sample flow; wherein Figure (a) shows the microstructure and dimensions of the focusing channel of the hydrodynamic focusing device, Figure (b) shows the numerical simulation results of the fluid state in the focusing channel, Figure (c) shows the fluorescence image of the focusing effect of the sodium fluorescein solution flow, and Figure (d) shows the image analysis results.

[0041] Figure 3 The original spectra of single-cell analysis in this invention are the original fluorescence (a), scattering (b), and mass spectrometry (c) single-cell signal time sequence diagrams of MCF-7 cells incubated with Ag+ and stained with AO using CytoLM Plus.

[0042] Figure 4 This invention integrates and statistically analyzes the fluorescence-scattering dual-channel single-cell signal data processing results; Figure (a) shows the time sequence diagram of MCF-7 single-cell signals obtained from the fluorescence and scattering channels; Figure (b) shows the frequency distribution histogram of the lag time between single-cell signals in the fluorescence and scattering channels (interval size: 0.2 ms); Figure (c) shows the frequency distribution histogram of the peak area of ​​single-cell fluorescence and scattering pulse signals after unifying the dual-channel signals; Figure (d) shows the scatter plot of the peak area of ​​fluorescence-scattering single-cell signals.

[0043] Figure 5 This invention relates to the correlation analysis and integration parameter optimization of fluorescence-mass spectrometry single-cell signals during the integration of three-dimensional concurrent single-cell signals by fluorescence-mass spectrometry. Figure (a) shows the frequency distribution histogram of lag time between fluorescence-mass spectrometry single-cell signals obtained from three parallel flow cytometry single-cell analyses (interval: 40 ms); Figure (b) shows the frequency distribution histogram of lag time between three sets of uncorrelated fluorescence-mass spectrometry two-dimensional single-cell signals (interval: 40 ms); Figure (c) shows the lag time frequency distribution histograms at W values ​​of 0.04 s, 0.2 s, and 0.6 s. OM And different L OM Under these conditions, it is possible to achieve W corresponding to the fluorescence signal. OM Find the fluorescence signal count of the mass spectrometry signal (L OM With a step size of 0.1s, the peak height of the characteristic peaks in the figure is set to RAA-C. FM Figure (d)L OM (0-10s, step size 0.1s) and W OM Different W values ​​obtained from two-parameter optimization (0-2s, step size 2ms) OM RAA-C under size FM Value; Graph (e) in different L OM The W signal corresponding to the fluorescence signal can be obtained below. OM The fluorescence signal count and the mass signal count (L) of the found mass spectrometry signal. OM Step length 0.1s, W OM (Size is 0.18s).

[0044] Figure 6 The final statistical analysis results of the three-dimensional single-cell analysis by optical-mass spectrometry in this invention; the top three figures show the frequency distribution statistics of each of the three parameters of the single-cell signal; the bottom three figures show the scatter plots of the pairwise combinations of the three parameters;

[0045] Figure 7 The optical detection system of this invention provides the flow cytometry results of single-particle analysis of fluorescent microspheres. Figure (a) shows the fluorescence of a single particle after unifying the dual-channel signals; Figure (b) shows the frequency distribution histogram of the peak area of ​​the scattered pulse signal; Figure (c) shows the scatter plot of the peak area of ​​the fluorescence-scattered single-particle signal; Figure (d) shows the frequency distribution histogram of the peak area of ​​the single-particle signal in Q1 after gate; Figure (e) shows the fluorescence of a single particle after unifying the dual-channel signals; Figure (f) shows the frequency distribution histogram of the peak height of the scattered pulse signal; Figure (g) shows the scatter plot of the peak height of the fluorescence-scattered single-particle signal; and Figure (h) shows the frequency distribution histogram of the peak height of the single-particle signal in Q1 after gate. Detailed Implementation

[0046] The present invention will be further described below with reference to the accompanying drawings and embodiments;

[0047] A three-dimensional flow cytometer based on optical detection and ICP-MS, as shown in the attached document. Figure 1 As shown, it consists of four parts: an optical detection system A, a liquid flow system B, a mass spectrometry detection system C, and an electronic and software system D.

[0048] The optical detection system A includes an excitation optical path, a fluorescence collection optical path, and a side-scattered light collection optical path. The excitation optical path is configured such that the laser beam emitted by the laser 1 passes sequentially through a laser beam reducer 2, a first reflecting mirror 3, a first filter 4, a dichroic mirror 5, and a first objective lens 6 before being focused into the focusing channel of the quartz flow cell 7. The fluorescence collection optical path and the excitation optical path are designed to be confocal. The fluorescence collection optical path is configured such that the laser excites the cell sample in the focusing channel of the quartz flow cell 7 to produce fluorescence. The fluorescence is collected by the first objective lens 6 and then sequentially passes through a dichroic mirror 5, a second reflecting mirror 8, a second filter 9, an aspherical lens 10, and a first pinhole plate 11 before being detected by the first detector 12. The side-scattered light collection path and the excitation light path are orthogonal to each other. The side-scattered light collection path is set up as follows: the cell sample in the focusing channel of the quartz flow cell 7 is irradiated by the laser to generate side-scattered light. The side-scattered light is collected by the second objective lens 13 and then passes through the third reflector 14, the third filter 15, and the second pinhole plate 16 before being detected by the second detector 17.

[0049] Laser 1 is fixed to the top plate of the dark box, which is fixed to an optical plate, which is fixed to an aluminum support. The first reflector 3, the second reflector 8, and the third reflector 14 are respectively fixed to an angle-adjustable beam deflector. The optical system detection system adopts a design combining confocal and orthogonal optical paths, with the fluorescence collection optical path and the side-scattered light collection optical path being independent of each other. This allows the optical path focusing adjustment of the flow cytometer of this application to be completed in only three steps: a) adjusting the angle of the laser emission from the first objective lens 6 in the excitation optical path by adjusting the angle of the first reflector 3; b) adjusting the focusing channel of the quartz flow cell 7 to focus with the focal point of the first objective lens 6 using a three-dimensional translation stage; c) adjusting the position of the entire scattered light collection optical path using a three-dimensional translation stage so that the focal point of the second objective lens 13 coincides with that of the first objective lens 6. This completes the optical path adjustment, greatly reducing the difficulty of optical path adjustment, and the optical path design is more compact, effectively reducing the size of the instrument.

[0050] Specifically, laser 1 is a solid-state laser with an output wavelength of 200–800 nm, a fixed output power of 5–500 mW, and a beam diameter of 0.5–4 mm. Laser beam reducer 2 is a 1–3x beam reducer used to reduce the laser beam diameter. First filter 3, second filter 9, and third filter 15 are all bandpass dielectric filters. First objective lens 6 and second objective lens 13 are 2.5–100x plan achromatic objectives with a working distance of 2–30 mm and a numerical aperture of 0.08–0.8. Dichroic mirror 5 is a long-pass or short-pass dichroic mirror with a starting wavelength of 200 nm–800 nm. Aspherical lens 10 has a focal length of 1–30 mm. First pinhole plate 11 and second pinhole plate 16 have apertures of 0.1–1 mm. The first detector 12 is a voltage-type photomultiplier tube with a maximum response frequency of 0.001–10 MHz, and the second detector 17 is a current-type photomultiplier tube with a maximum output current of 0.01–1 mA. The optical plate is an aluminum alloy plate with a side length of 300 mm and a thickness of 13 mm, with an array of M6 threaded holes on its surface and a hole spacing of 25 mm. The stroke of the three-dimensional translation stage is 4–20 mm; the beam deflector can be adjusted from 2° to 10°.

[0051] The fluid flow system B includes a sample injection line, a sheath fluid line, and a flushing line, all connected to the quartz flow cell 7. The sample injection line injects cell samples into the central sheath fluid channel of the quartz flow cell 7. The sample tube 18 is connected to the quartz flow cell 7 via an inlet capillary 19. The sheath fluid line supplies sheath fluid to the focusing channel of the quartz flow cell 7. The sheath fluid bottle 20 is connected to the quartz flow cell 7 via a Teflon tube, with a flow meter 21 installed between them. The flushing line flushes the focusing channel of the quartz flow cell 7 and removes air bubbles. The flushing syringe 22 is connected to the quartz flow cell 7 via a silicone tubing, with a switching valve 23 installed between them. Both the sheath fluid line and the sample injection line are pressure-driven, with an air compressor 24 providing a pressure source to a pressure controller 25. The pressure controller 25 has two pressure outputs, connected to the sample tube 18 and the sheath fluid bottle 20, respectively. The fluid flow from the quartz flow cell 7 is transmitted to the mass spectrometry detection system C via an output capillary 26. Figure 2 As shown, the sample flow rate was 0.1-100 μL / min, and the sheath fluid flow rate was 10-400 μL / min.

[0052] Fluidized system B can achieve stable cell focusing and alignment at low flow rates and is perfectly matched with the operating conditions of mass spectrometry detection system C, thus achieving high nebulization and detection efficiency. Furthermore, fluidized system B and optical detection system C are independent of each other and feature a modular design; the sample injection tubing, sheath fluid tubing, and rinsing tubing are all independent, facilitating maintenance.

[0053] Specifically, the sample inlet capillary 19 is a quartz capillary with an outer diameter of 0.1–0.4 mm and an inner diameter of 20–200 μm. The outlet end of the sample inlet capillary 19 is ground into a 15°–45° conical tip. The quartz flow cell 7 is a four-sided transparent quartz flow cell with external dimensions of 4 mm × 4 mm × 10 mm to 6 mm × 6 mm × 20 mm, and a central sheath fluid channel of 0.1 mm × 0.1 mm to 0.4 mm × 0.4 mm (rectangular channel). The output capillary 24 is a quartz capillary with an outer diameter of 0.1–0.4 mm and an inner diameter of 20–200 μm. The sample tube volume is 0.5–10 mL, and the sheath fluid bottle volume is 100–2000 mL. The air compressor output gas flow rate is 10–100 L / min, and the gas storage tank capacity is 1–10 L. The pressure controller has a pressure output range of 0–5000 mbar, and provides pressures of 5–2000 mbar and 5–5000 mbar to the sample tube 17 and sheath bottle 18, respectively. The flow meter has a flow measurement range of 0.02–8000 μL / min.

[0054] The mass spectrometry detection system C includes a high-efficiency nebulization system 27 and an inductively coupled plasma mass spectrometer (Agilent 8900) 28. The high-efficiency nebulization system 27 consists of a capillary sleeve, an original nebulizer, an original adapter, and a quartz nebulization chamber connected sequentially. The output capillary 27 of the liquid flow system B is connected to the original nebulizer via the capillary sleeve. The quartz nebulization chamber has an inlet, an outlet, and a waste outlet. The inlet and nebulizer of the quartz nebulization chamber are connected and fixed via the original adapter; the outlet is connected to the inductively coupled plasma mass spectrometer 28; and the waste outlet is connected to the waste outlet pipe of the inductively coupled plasma mass spectrometer 28. During three-dimensional flow cytometry single-cell analysis, the carrier gas flow rate of the inductively coupled plasma mass spectrometer 28 is set to 0.5–1.3 L / min, the purity of the carrier gas argon is 99.999%, the power of the inductively coupled plasma mass spectrometer is 1250–1570 W, and the integration time is 0.1–10 ms.

[0055] The electronic and software system D includes a signal conversion and amplification module 29, a data acquisition card 30, a host computer 31, and instrument control software and data processing software installed on the host computer. In the optical detection system A, the voltage signal generated by the first detector 12 is directly acquired by the data acquisition card 30. The current signal generated by the second detector 17 is converted into a voltage signal by the conversion and amplification module 26 and amplified, then acquired by the data acquisition card 27. Both the instrument control software and the data processing software are written in LabVIEW and installed on the host computer. The functions of the instrument control software include control of the pressure control system, gain control of the first detector 12 and the second detector 17, data acquisition, and synchronous triggering of data acquisition from the optical detection system and the mass spectrometry detection system. The functions of the data processing software include data display, signal recognition, data filtering, integration and unification of fluorescence and scattering single-cell signals, integration and unification of single-cell signals obtained from the optical detection system and the mass spectrometry detection system, and statistical analysis of single-cell signals. The maximum response frequency of the conversion and amplification module 26 is 0.001–10 MHz, and the current-to-voltage conversion factor is 1–±1000 mV / μA. The maximum acquisition frequency of the data acquisition card 30 is 0.001~10MHz, and the maximum output voltage is 1~20V.

[0056] Specifically, the instrument control software uses serial communication to regulate and monitor the pressure output of the pressure controller 25 and monitor the flow meter 21. The software controls the gain of the first detector 12 and the second detector 17 by controlling the output voltage of the data acquisition card 30. Using a producer-consumer model, the software reads the fluorescence and scattered light intensity data acquired by the data acquisition card 22 in real time and stores it in TDMS file format to the host computer, obtaining complete fluorescence intensity-time spectrum data and side-scattered light intensity-time spectrum data, with a maximum data storage frequency of 10 kS / s to 1 MS / s. The instrument control software solves the problem of synchronous triggering of data acquisition between the optical detection system and the mass spectrometry detection system without requiring modifications to commercial mass spectrometry software. This effectively ensures the consistency of the lag time between the single-cell analysis data obtained by the optical detection system A and the mass spectrometry detection system C, greatly reducing the difficulty of integrating and unifying three-dimensional single-cell analysis data.

[0057] Specifically, the data processing software processes fluorescence intensity-time spectrum data, side-scattered light intensity-time spectrum data, and mass spectrometry absorption intensity-time spectrum data in eight steps: data import, peak identification, single-parameter single-cell signal statistical analysis, fluorescence-side-scattered single-cell signal integration and unification, dual-parameter single-cell signal statistical analysis, three-dimensional single-cell signal integration and unification, and result export. Among these, the three-dimensional single-cell signal integration and unification step is the key and challenging aspect of three-dimensional flow cytometry single-cell analysis data processing. Its purpose is to integrate and unify the single-cell signals independently obtained by the optical detection system A and the mass spectrometry detection system C to obtain a three-dimensional three-parameter detection data list for single cells. This invention utilizes a lag time window screening algorithm to quickly and accurately integrate and unify three-dimensional single-cell signals. The specific implementation method is as follows:

[0058] A three-dimensional flow cytometry analysis method based on optical detection and ICP-MS, implemented using the aforementioned three-dimensional flow cytometry analyzer based on optical detection and ICP-MS, specifically includes the following steps:

[0059] Step 1: First, ignite and preheat the mass spectrometry detection system;

[0060] Step 2: Before each sample test, the liquid flow system needs to be pre-flushed to remove air bubbles and form a stable sheath flow. First, replace the solution in the sample tube with ultrapure water, turn on the air compressor and pressure controller, and set the pressure output 1 of the pressure controller to 50-1500 mbar and the pressure output 2 to 50-1000 mbar on the instrument control software. Let the sheath fluid fill the entire liquid flow channel and run for 3 minutes until the pressure output displayed on the instrument control software is stable and the sheath fluid flow rate obtained by the flow meter reaches the preset flow rate and the flow rate is stable. Then you can proceed to the next step.

[0061] Step 3: Power on the optical detection system and set its parameters: Turn on the laser, set the gain voltages of the first detector and the second detector to 0.1 - 1 V, and set the acquisition frequency of the data acquisition card to 1 - 20 kHz;

[0062] Step 4: Establish the detection method for inductively coupled plasma mass spectrometry: Open the control software MassHunter自带的ICP-MS, create a new batch in the "Batch Processing" module, then set the acquisition mode to time-resolved mode in the newly created batch, set the integration time to 0.1 s, set the data acquisition time, and select the elements to be detected;

[0063] Step 5: Sample introduction: Pause the pressure output of the pressure controller 2 to the pressure input of the sample tube, replace the ultrapure water in the sample tube with cell suspension, continue to apply pressure to the sample tube for cell suspension introduction, and the appropriate concentration of the cell suspension is 1×10 4 ~1×10 6 / mL;

[0064] Step 6: Perform data acquisition; Set the data acquisition time on the instrument control software and click data acquisition, and realize the linkage with the MassHunter software through the method called by the property node, synchronously trigger the data acquisition of the fluorescence, scattering and mass spectrometry intensity time-sequential spectra of the optical detection system and the mass spectrometry detection system, and obtain the fluorescence / sidelight scattering signal intensity-time spectrum and the mass spectrometry signal intensity-time spectrum as shown in Figure 3 Figure;

[0065] Step 7: Process the data collected in the above steps; Import the data of the fluorescence signal intensity-time spectrum, sidelight scattering signal intensity-time spectrum and mass spectrometry signal intensity-time spectrum collected respectively into the data processing software for processing, obtain the peak height, peak area and peak width information of the single-cell pulse signal spectrum for semi-quantitative analysis of the fluorescence signal, and perform statistical analysis to obtain the frequency distribution results of the peak height, peak area and peak width information of the single-cell pulse signal spectrum; Then integrate and unify the fluorescence single-cell signal, sidelight scattering single-cell signal and mass spectrometry single-cell signal to obtain single-cell three-parameter analysis data, and perform statistical analysis on it;

[0066] The specific steps for integrating and unifying the fluorescence single-cell signal, sidelight scattering single-cell signal and mass spectrometry single-cell signal are as follows:

[0067] Step S01: After data processing including peak identification, lists of fluorescence, side scattering, and mass spectrometry single-cell signals are obtained, recorded in the format of "peak time – peak height – peak area". After integrating and unifying the fluorescence and side scattering single-cell signals, a dual-parameter single-cell signal list is obtained, recorded in the format of "peak time – fluorescence peak height – fluorescence peak area – scattering peak height – scattering peak area". The results of the integration, unification, and statistical analysis of the fluorescence and side scattering single-cell signals are as follows: Figure 4 As shown;

[0068] Step S02: Extract the peak times from the dual-parameter single-cell signal list and the mass spectrometry single-cell signal list, and compile them into two separate arrays t. O [n] and t M [m], and according to formula L j,k =t Oj -t Mk Calculate all t O [n] element and t M The difference between each element in the [m] array is used to obtain the lag time array L between optical detection and mass spectrometry detection. j,k [n×m];

[0069] Where n is the total number of signals in the two-parameter single-cell signal list, and m is the total number of signals in the mass spectrometry single-cell signal list; t Oj It is the time when the j-th single-particle signal peak appears in the two-parameter single-cell signal list, j = 1, 2, 3, ..., n, n, t Mk It is the time when the k-th single-particle signal peak appears in the mass spectrometry single-cell signal list, k = 1, 2, 3, ... m;

[0070] Step S03: Process the obtained lag time array L j,k Statistical analysis was performed on all elements in [n×m], and a frequency distribution histogram was plotted. The results showed that L... j,k Elements in [n×m] will exhibit significant cumulative peaks, such as Figure 5 As shown in (a, b);

[0071] Step S04: Adjust the lag time window size W OM Optimize the size; use nested for loops to iterate over L. OM and W OM The size is optimized using two parameters to determine the final W. OM The value, such as Figure 5 As shown in (c, d); lag time L OMThe optimization interval is determined based on the position of the cumulative peak in the frequency distribution histogram, for example, [0, -10s], with an optimization step size of 0.1s; the optimization interval for the lag time window size is determined based on the half-peak width of the cumulative peak in the frequency distribution histogram, for example, [0, 2s], with an optimization step size of 2ms.

[0072] Step S05: Based on the lag time window size W OM Size of L OM Further confirmation is needed; such as Figure 5 As shown in (e), with L OM ±(W OM / 2) As a lag time window, in t M Search in [m] for whether there is an element belonging to t. Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); If one or more elements belong to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2), then it means that one or more elements may be related to t. Oj Corresponding single-cell signal concurrent mass spectrometry single-cell signal; through L OM The value is taken in the interval [0, -10s], and different values ​​of L are calculated with a step size of, for example, 0.1s. OM t values ​​of possible concurrent mass spectrometry signals O [n] Element count, determining the final L OM Values;

[0073] Step S06: With L OM ±(W OM / 2) As a lag time window, pair them one by one at t M Search in [m] for whether there is an element belonging to t. Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); If there is an element t Mk Belongs to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2), then t Oj The corresponding two-parameter single-cell signal and t Mk These are concurrent single-cell signals; if multiple elements belong to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); After screening and calculation, t is obtained. Oj and t Mk A two-dimensional array;

[0074] Step S07: Combine with t Oj The information in the corresponding two-parameter single-cell list, including "fluorescence peak height – fluorescence peak area – scattering peak height – scattering peak area composition", and its relationship with t Mk The corresponding "peak time – peak height – peak area" data are integrated to form a three-dimensional single-cell signal data list recorded as "peak time – fluorescence peak height – fluorescence peak area – scattering peak height – scattering peak area – mass spectrometry signal peak height – mass spectrometry signal peak area". This completes the integration and unification of the three-dimensional single-cell signals. Statistical analysis of the obtained three-dimensional single-cell signals yields the following results: Figure 6 As shown.

[0075] A three-dimensional flow cytometry method based on optical detection and ICP-MS is presented. Utilizing a three-dimensional flow cytometer based on optical detection and ICP-MS, this method can perform single-cell flow cytometry analysis using only single parameters (fluorescence, scattering, and mass spectrometry) or arbitrary combinations of multiple parameters. The results of fluorescence-scattering dual-parameter flow cytometry analysis of fluorescent microspheres (cell models) are shown below. Figure 7 As shown.

Claims

1. A three-dimensional flow cytometer based on optical detection and ICP-MS, characterized in that, It includes fluid flow systems, optical detection systems, mass spectrometry detection systems, and electronic and software systems; The fluid flow system, optical detection system, and mass spectrometry detection system all operate under the control of the instrument control software in the electronic and software system; the obtained single-cell signals are processed and analyzed by the data processing software in the electronic and software system. The fluid flow system focuses and arranges the chaotically dispersed cells in the cell suspension into a single-cell stream, and then collects the optical detection signal of each cell by passing it one by one through the detection site of the optical detection system at a stable flow rate. The cells are then introduced into the mass spectrometry detection system to obtain the mass spectrometry single-cell signal. The fluid flow system includes an air compressor, a pressure controller, a flow sensor, a sheath bottle, a sample tube, a syringe, a switching valve, an injection capillary, and a quartz flow cell. The air compressor is placed on the ground, the pressure controller is fixed in a support bracket below the optical detection system, the flow sensor is fixed to the top plate of the optical detection system's cassette, the sheath bottle is fixed to the optical plate, and the injection capillary is fixed to the optical plate via a lifting slide. The air compressor is connected to the pressure controller, providing pressure input to it. The pressure controller is equipped with… It has pressure output 1 and pressure output 2, which are connected to the pressure input ports of the sheath fluid bottle and the sample tube, respectively; the inlet end of the sample inlet capillary is inserted into the sample tube, and the outlet end of the sample inlet capillary, the sheath fluid bottle, and the syringe are all connected to the quartz flow cell; the sheath fluid line is connected by a Teflon rigid tube; the pressure lines are all connected by thermoplastic polyurethane tubes; the syringe and the flow cell are connected by a silicone flexible tube and are equipped with a switch valve, and the rinsing fluid is manually driven; the quartz flow cell is transparent on all four sides and has a focusing channel inside; the quartz flow cell is fixed on a three-dimensional translation stage on the top plate of the optical detection system, and the focusing channel of the quartz flow cell is focused with the optical detection system through the three-dimensional translation stage; the cell suspension is squeezed by the sheath fluid inside the focusing channel to form a single cell flow, which is then optically detected, and then transferred to the mass spectrometry detection system by the output capillary; The optical detection system includes a laser, a laser beam reducer, a first reflecting mirror, a first filter, a dichroic mirror, a first objective lens, a second reflecting mirror, a second filter, an aspherical lens, a first pinhole plate, a first detector, a second objective lens, a third reflecting mirror, a third filter, a second pinhole plate, and a second detector. The laser is fixed to the top plate of a dark box constructed from aluminum alloy plates. The dark box is fixed to an optical plate, which in turn is fixed to an aluminum support frame. The first filter, dichroic mirror, second filter, second reflector, lens, first pinhole plate, first detector, third reflector, third filter, second pinhole plate, and second detector are all encapsulated inside the dark box. The laser beam reducer is fixed at the laser beam exit point. The first reflector and objective lens are fixed to the top plate of the dark box. The first, second, and third reflecting mirrors are fixed on an angle-adjustable beam deflector. The laser beam emitted by the laser passes sequentially through a laser beam reducer, the first reflecting mirror, the first filter, a dichroic mirror, and the first objective lens before being focused onto the sample stream, forming the excitation light path. The fluorescence generated by the laser beam excitation of the sample is collected by the first objective lens and then sequentially passes through a dichroic mirror, the second reflecting mirror, the second filter, an aspherical lens, and the first pinhole plate before being detected by the first detector, forming the fluorescence collection light path. The side-scattered light generated by the laser irradiating the sample is collected by the second objective lens in a direction orthogonal to the excitation light path, and then sequentially passes through the third reflecting mirror, the third filter, and the second pinhole plate before being detected by the second detector, forming the side-scattered light path. The mass spectrometry detection system includes a high-efficiency nebulization system and an ICP-MS. The high-efficiency nebulization system consists of a capillary tube, an original nebulizer, an original adapter, and a quartz nebulization chamber. The output capillary of the liquid flow system is connected to the original nebulizer through the capillary tube. The quartz nebulization chamber is equipped with an inlet, an outlet, and a waste outlet. The inlet of the quartz nebulization chamber and the nebulizer are connected and fixed through the original adapter, the outlet is connected to the ICP-MS, and the waste outlet is connected to the waste outlet pipe of the ICP-MS.

2. The three-dimensional flow cytometer based on optical detection and ICP-MS as described in claim 1, characterized in that, The electronic and software system includes an electronic system, instrument control software, and data processing software; the electronic system includes a signal conversion and amplification module, a data acquisition card, and a host computer; the voltage signal generated by the first detector is directly acquired by the data acquisition card; the current signal generated by the second detector is converted into a voltage signal by the conversion and amplification module and amplified, and then acquired by the data acquisition card; The instrument control software and data processing software are both written in LabVIEW and installed on the host computer. The instrument control software controls the pressure controller, the detector gain of the optical detection system, and the data acquisition of the data acquisition card, and controls the synchronous triggering of data acquisition of the optical detection system and the mass spectrometry detection system. The data processing software performs data display, signal recognition, data filtering, integration and unification of fluorescence and scattering single-cell signals, integration and unification of single-cell signals obtained from optical detection systems and mass spectrometry detection systems, and statistical analysis of single-cell signals.

3. A three-dimensional flow cytometry analysis method based on optical detection and ICP-MS, implemented using a three-dimensional flow cytometry analyzer based on optical detection and ICP-MS as described in claim 1, characterized in that... Specifically, the following steps are included: Step 1: First, ignite and preheat the mass spectrometry detection system; Step 2: Before each sample test, the liquid flow system needs to be pre-flushed to remove air bubbles and form a stable sheath flow. First, replace the solution in the sample tube with ultrapure water, turn on the air compressor and pressure controller, set the pressure output of the pressure controller on the instrument control software, let the sheath fluid fill the entire liquid flow channel, and run the instrument control software until the pressure output is stable and the sheath fluid flow rate obtained by the flow meter reaches the preset flow rate and the flow rate is stable before proceeding to the next step. Step 3: Powering on the optical detection system and setting its parameters: Turn on the laser, set the gain voltage of the first and second detectors, and set the acquisition frequency of the data acquisition card; Step 4: Establish the detection method of inductively coupled plasma mass spectrometry: Open the control software MassHunter that comes with ICP-MS, create a new batch in the "Batch Processing" module, and then set the acquisition mode to time-resolved mode, the integration time to 0.1 s, the data acquisition time, and select the element to be detected in the new batch. Step 5: Sample introduction: Pause the pressure output 2 of the pressure controller to the pressure input of the sample tube, replace the ultrapure water in the sample tube with cell suspension, and continue to apply pressure to the sample tube to introduce the cell suspension; Step 6: Collect data; The data acquisition time is set on the instrument control software, and the linkage with MassHunter is realized through the method of calling the attribute node. The data acquisition of fluorescence, scattering and mass spectrometry intensity time-series spectra of the optical detection system and the mass spectrometry detection system is triggered synchronously to obtain fluorescence / side scattering light signal intensity-time spectrum and mass spectrometry signal intensity-time spectrum. Step 7: Process the data collected in the above steps; import the collected fluorescence signal intensity-time spectrum data, side-scattered light signal intensity-time spectrum data, and mass spectrometry signal intensity-time spectrum data into data processing software for processing to obtain the peak height, peak area, and peak width information of the single-cell pulse signal spectrum peak for semi-quantitative analysis of the fluorescence signal, and perform statistical analysis to obtain the frequency distribution results of the peak height, peak area, and peak width information of the single-cell pulse signal spectrum peak; then integrate and unify the fluorescence single-cell signal, side-scattered light single-cell signal, and mass spectrometry single-cell signal to obtain single-cell three-parameter analysis data, and perform statistical analysis on them.

4. The three-dimensional flow cytometry cell analysis method based on optical detection and ICP-MS according to claim 3, characterized in that, The integration and unification of fluorescence single-cell signals, side-scattered light single-cell signals, and mass spectrometry single-cell signals involves the following steps: Step S01: After data processing such as peak identification, obtain a list of fluorescence, side scattering and mass spectrometry single-cell signals recorded in the format of "peak time - peak height - peak area"; after integrating and unifying the fluorescence-side scattering single-cell signals, obtain a list of dual-parameter single-cell signals recorded in the format of "peak time - fluorescence peak height - fluorescence peak area - scattering peak height - scattering peak area". Step S02: Extract the peak times from the dual-parameter single-cell signal list and the mass spectrometry single-cell signal list, and compile them into two separate arrays t. O [n] and t M [m], and according to formula L j,k =t Oj -t Mk Calculate all t O [n] element and t M The difference between each element in the [m] array is used to obtain the lag time array L between optical detection and mass spectrometry detection. j,k [n×m]; Where n is the total number of signals in the two-parameter single-cell signal list, and m is the total number of signals in the mass spectrometry single-cell signal list; t Oj This represents the time of occurrence of the j-th single-particle signal peak in the dual-parameter single-cell signal list, where j = 1, 2, 3, ..., n, n, t. Mk It is the time when the k-th single-particle signal peak appears in the single-cell signal list of mass spectrometry, k=1, 2, 3, ... m; Step S03: Process the obtained lag time array L j,k Statistical analysis was performed on all elements in [n×m], and a frequency distribution histogram was plotted. The results showed that L... j,k Elements in [n×m] will show significant cumulative peaks; Step S04: Adjust the lag time window size W OM Optimize the size; use nested for loops to iterate over L. OM and W OM The size is optimized using two parameters to determine the final W. OM The numerical value; lag time L OM The optimization interval is determined based on the position of the cumulative peak in the frequency distribution histogram; the optimization interval for the lag time window size is determined based on the half-peak width of the cumulative peak in the frequency distribution histogram. Step S05: Based on the lag time window size W OM Size of L OM Further confirmation is needed; with L OM ±(W OM / 2) As a lag time window, in t M Search in [m] for whether there is an element belonging to t. Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); If one or more elements belong to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2), then it means that one or more elements may be related to t. Oj Corresponding single-cell signal concurrent mass spectrometry single-cell signal; through L OM Take values ​​and calculate different L values. OM t of concurrent mass spectrometry signals under different values O [n] Element count, determining the final L OM Values; Step S06: With L OM ±(W OM / 2) As a lag time window, pair them one by one at t M Search in [m] for whether there is an element belonging to t. Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); If there is an element t Mk Belongs to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2), then t Oj The corresponding two-parameter single-cell signal and t Mk These are concurrent single-cell signals; if multiple elements belong to t Oj The corresponding lag time window t Oj +L OM ±(W OM / 2); After screening and calculation, t is obtained. Oj and t Mk A two-dimensional array; Step S07: Combine with t Oj The information in the corresponding two-parameter single-cell list, including "fluorescence peak height – fluorescence peak area – scattering peak height – scattering peak area composition", and its relationship with t Mk The corresponding "peak time - peak height - peak area" are integrated to form a three-dimensional single-cell signal data list recorded as "peak time - fluorescence peak height - fluorescence peak area - scattering peak height - scattering peak area - mass spectrometry signal peak height - mass spectrometry signal peak area", thus completing the integration and unification of three-dimensional single-cell signals.

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