CN117405649B - Cell Raman flow spectrum imaging analysis system and analysis method - Google Patents
Cell Raman flow spectrum imaging analysis system and analysis method Download PDFInfo
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Abstract
The invention relates to the technical field of cell Raman recognition and analysis, in particular to a cell Raman flow spectrum imaging analysis system and an analysis method. Comprising the following steps: the femtosecond laser outputs two femtosecond laser signals with different frequencies, the beams are combined by the beam combining unit, one-dimensional scanning is carried out by the laser scanning unit, and the laser fills the entrance pupil of the focusing unit in the process; focusing the laser on a certain fault section in a micro-flow channel of the micro-flow channel chip by a focusing unit to enable laser spots to reciprocate or scan along the same direction; the micro-channel chip is arranged on the objective table; and injecting a cell sample to be tested into the microfluidic channel through the cell sample injection unit, sequentially exciting scattering Raman signals at each point of the cell through a laser focusing light spot after the cell passes through a scanning section, collecting the scattered Raman signals through a collecting lens, filtering out laser with a certain frequency through an optical filter, obtaining the stimulated Raman signals, and transmitting the stimulated Raman signals to a computer. The advantages are that: high-flux, high-spectrum and high-spatial resolution single-cell Raman flow spectrum imaging is realized through single-dimension scanning.
Description
Technical Field
The invention relates to the technical field of cell Raman recognition and analysis, in particular to a cell Raman flow spectrum imaging analysis system and an analysis method.
Background
The cell is a basic unit for life, and mainly comprises protein, lipid, nucleic acid and other molecules, wherein the molecular components and contents of different cells and different development stages of the same cells are different, for example, metabolic differences usually exist in the process of canceration of the cells, the cell development stages are different, and the types of the cell surface expressed proteins are different, so that the differentiation and separation of different types of cells can be realized. Single cell analysis has important application value in the related fields of life sciences, medicine and the like such as current cancer diagnosis, accurate medical treatment and the like, and the premise of the application is to identify and sort special cells in a near lossless manner. In the current cell analysis field, the most widely applied is a flow cytometer based on fluorescent markers, different fluorescent molecules are marked on cell surface proteins, and the expression condition of the cell surface proteins is obtained by rapidly detecting fluorescent signals with different wavelengths, so that cell identification is realized, and meanwhile, a high-speed camera is added in the current flow cytometer for obtaining cell image information, and cell classification is assisted according to the external contour form of cells. After accurate cell classification is realized, specific cell separation is realized by combining related technologies such as micro-fluidic control and the like, and target cells are obtained for subsequent culture and research.
The current flow cytometry analysis method based on fluorescent markers is limited by the types of marker molecules, only information of limited dimensions of cells can be obtained, such as the expression condition of antigen proteins on the surfaces of the cells, the current general flow cytometry analysis based on fluorescent markers can not obtain image information of molecular distribution inside the cells, as for the increase of the acquisition of cell images based on a high-speed camera in a flow cytometry, the information obtained based on the high-speed camera is only information of the outline of the cells under the condition that the cells are transparent and marker molecules are not added, the information of fine structures inside the cells and the information of the molecules of the cells can not be provided, and the detection flux is limited by the shooting speed of the high-speed camera. Furthermore, the use of fluorescent-labeled antibodies increases the cost of detection and complexity of pretreatment of the detection, and the introduction of fluorescent labels may interfere with the subsequent analysis process. Finally, whether the method is an imaging method or a surface antigen immune labeling-based method, the inherent molecular mechanism of the cell phenotype difference source can not be reflected while the cell phenotype information is obtained, and it is difficult to accurately obtain key information required by accurate treatment such as whether cancer cells have chemotherapy resistance or not while diagnosis is carried out, so that the subsequent treatment effect is influenced.
The Raman spectrum is a molecular scattering spectrum, is derived from inelastic collision of molecules and photons, is a molecular information carrier, has the advantages of no label and nondestructive detection, and can realize different cell characterization based on the chemical bond vibration spectrum of biomolecules and the spatial distribution of the chemical bond vibration spectrum. Raman spectroscopy is thus a potential technique to replace fluorescence analysis as a flow cytometry to achieve label-free analysis. Raman flow, which is currently combined with flow cytometry by raman spectroscopy, generally focuses raman excitation light at a point in a microfluidic channel, and when a cell N passes the point, raman scattering of molecules inside the cell is excited, and the raman spectral information of the cell is obtained by performing spectral analysis on the scattered light. However, the method can only acquire the integral raman spectrum information of single cells, can not combine the microscopic morphology and the molecular vibration spectrum information in the cells, and can not acquire the molecular metabolism information of the internal structure of the cells due to the fact that the cells have high heterogeneity and large differences among cell individuals, and therefore the discrimination accuracy is reduced. At present, a single-frequency laser signal is focused on a microfluidic channel by a microscope or a probe to fix a point, and when a cell passes through the point, a Raman spectrum signal is excited, and a spectrometer collects a scattered light signal to realize Raman spectrum analysis. The raman flow type research based on raman spectrum analysis is carried out at home and abroad, and the document Optical guiding-based cell focusing for Raman flow cell cytometer reports a homodromous scattering spontaneous raman flow type cell analyzer developed in india, wherein excitation light is focused on one point in a chip, a spectrometer is positioned on the other side of the chip to collect raman scattering signals, and cells are guided by laser forceps to pass through the excitation light focusing position to obtain single cell raman spectrum information. Document Robust Spontaneous Raman flow cytometry for single-cell metabolic phenome profiling via pDep-DLD-RFC reports that the back scattering type Raman flow cytometry analyzer developed by the national Qingdao energy source is used for collecting and analyzing the reflected Raman signals by the spectrometer, wherein the excitation light and the spectrum analyzer are positioned on the same side of the micro-channel. The method can only acquire one piece of spectral information for a single cell, can not acquire high-resolution cell Raman spectrum image information, and needs to acquire the spectral information through a spectrometer, so that the detection speed and the detection flux are low.
Disclosure of Invention
The invention provides a cell Raman flow spectrum imaging analysis system and an analysis method for solving the problems.
A first object of the present invention is to provide a cell raman flow type spectral imaging analysis system, comprising: the system comprises a femtosecond laser, a beam combining unit, a laser scanning unit, a focusing unit, an objective table, a cell sample injection unit, a micro-channel chip, a cell collecting unit, a collecting lens, an optical filter, a Raman signal detection unit and a computer;
the femtosecond laser is used for outputting two femtosecond laser signals with different frequencies;
the beam combining unit is used for combining two femtosecond laser signals with different frequencies and transmitting the combined femtosecond laser signals to the laser scanning unit;
the laser scanning unit is used for one-dimensional scanning of the laser after beam combination and ensuring that the laser always fills the entrance pupil of the focusing unit in the scanning process;
the focusing unit is used for focusing laser on a certain fault section in a micro-flow channel of the micro-flow channel chip, so that laser spots reciprocate on the fault section or scan along the same direction;
the micro-channel chip is arranged on the objective table; injecting a cell sample to be detected into a microfluidic channel of the microfluidic channel chip through the cell sample injection unit, and sequentially exciting scattering Raman signals at each point of the cell by a laser focusing light spot after the cell passes through a scanning section; the cell collection unit is used for collecting the detected cells;
and after the scattered Raman signals are collected by the collecting lens, filtering out laser with a certain frequency by the optical filter, detecting the intensity change of the rest laser signals by the Raman signal detection unit, acquiring stimulated Raman signals, and transmitting the stimulated Raman signals to the computer for signal processing to acquire a cell image.
Preferably, the beam combining unit comprises a reflecting mirror and a dichroic mirror, and two femtosecond laser signals with different frequencies are combined into one beam through the dichroic mirror and then transmitted to the laser scanning unit through the reflecting mirror.
Preferably, the laser scanning unit comprises a one-dimensional scanning galvanometer and a 4-f system; transmitting the laser after beam combination to the one-dimensional scanning galvanometer, and rapidly deflecting a reflecting mirror of the one-dimensional scanning galvanometer under the drive of a motor to realize laser scanning; after deflection, the laser passes through the 4-f system, so that the laser is ensured to always fill the entrance pupil of the focusing unit in the scanning process.
Preferably, the focusing unit is a microscope objective, and the laser always fills the entrance pupil of the microscope objective in the scanning process, and is focused on a certain fault section in the microfluidic channel of the microfluidic chip by the microscope objective.
Preferably, the cell sample injection unit is formed by sequentially connecting a sample cell, a sample inlet tube, an injection pump and an injection tube in series, wherein the injection tube is connected with the micro-channel chip; the cell sample to be detected is placed in the sample cell, and after the cell sample is sucked from the sample cell through the sample injection pipe by the injection pump, the cell sample is injected into the microfluidic channel through the injection pipe.
Preferably, the raman signal detection unit is a photodiode, and the photodiode is connected with the computer through a data line; the photodiode is used for detecting the intensity change of the rest laser signals, acquiring stimulated Raman signals and converting the stimulated Raman signals into electric signals, and transmitting the electric signals to the computer through the data line.
The second object of the present invention is to provide a cell raman flow type spectrum imaging analysis method, which adopts a cell raman flow type spectrum imaging analysis system for analysis, and specifically comprises the following steps:
s1, acquiring cells of a target type by using a cell Raman flow spectrum imaging analysis system, and acquiring a cell spectrum image database of the type; establishing a Raman spectrum image database of different cell molecular distributions;
s2, training an analysis model based on a statistical method;
s3, inputting the cell image information into an analysis model, and acquiring cell type information according to a discrimination result;
s4, analyzing and recovering the cells according to different cell types.
Preferably, the step S1 specifically includes the following sub-steps:
s101, setting the injection speed of an injection pump, the laser scanning speed and the frequency difference of femtosecond laser of a cell Raman flow spectrum imaging analysis system;
s102, placing a cell sample to be detected in a sample cell, sucking the cell sample from the sample cell through a sample inlet pipe by a syringe pump, and injecting the cell sample into a microfluidic channel through the syringe;
s103, after the cells pass through the scanning section, sequentially exciting scattering Raman signals at each point of the cells by using a laser focusing light spot;
s104, after the scattered Raman signals are collected by the collecting lens, laser with a certain frequency is filtered by the optical filter, the intensity change of the rest laser signals is detected by the Raman signal detection unit, stimulated Raman signals are obtained and transmitted to the computer for signal processing, and a cell image is obtained;
s105, establishing a Raman spectrum image database of different types of cell molecular distributions.
Preferably, the injection speed of the injection pump is matched with the laser scanning speed, and the laser scanning speed is determined by the scanning frequency of the one-dimensional scanning galvanometer; the matching relation is as follows:
；
wherein V is the injection speed of the injection pump, mu L/s, P is the scanning frequency of the one-dimensional scanning galvanometer, and the unit is Hz; a is a constant, a=1 when the one-dimensional scanning galvanometer scans unidirectionally, and a=2 when the one-dimensional scanning galvanometer scans reciprocally; w, H the width and height of the section of the microfluidic channel are respectively in mm; n is the number of data points in a scan line of data.
Preferably, the statistical method is a principal component analysis method.
Compared with the prior art, the invention has the following beneficial effects:
the invention combines Raman spectrum unidirectional scanning with micro-fluid technology, and can realize single-cell Raman flow spectrum imaging with high flux, high spectrum and high spatial resolution by single-dimensional scanning.
Drawings
Fig. 1 is a schematic diagram of a cellular raman flow spectroscopy analysis system provided according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a method for collecting laser scanning and spectral data in a microfluidic channel according to an embodiment of the present invention.
Fig. 3 is a flowchart of a method for analyzing raman flow spectroscopy of cells according to an embodiment of the present invention.
Fig. 4 is a cell bright field imaging result.
Fig. 5 is a nuclear image of cells detected by a raman flow spectroscopy analysis system for cells according to an embodiment of the present invention.
FIG. 6 is a cell image of a prior art Siamese fly imaging flow cytometer (Attune CytPix).
Reference numerals:
1. a femtosecond laser; 2. a first mirror; 3. a dichroic mirror; 4. a second mirror; 5. a one-dimensional scanning galvanometer; 6. a first lens; 7. a second lens; 8. a microobjective; 9. an objective table; 10. a microfluidic channel; 11. a micro flow channel chip; 12. a sample cell; 13. a sample inlet tube; 14. a syringe pump; 15. a syringe; 16. a collection pipe; 17. a cell collection container; 18. a collection lens; 19. a light filter; 20. a photodiode; 21. a data line; 22. a computer; 23. and (3) cells.
Detailed Description
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, like modules are denoted by like reference numerals. In the case of the same reference numerals, their names and functions are also the same. Therefore, a detailed description thereof will not be repeated.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limiting the invention.
The invention provides a cell Raman flow spectrum imaging analysis system, which comprises:
the system comprises a femtosecond laser, a beam combining unit, a laser scanning unit, a focusing unit, an objective table, a cell sample injection unit, a micro-channel chip, a cell collecting unit, a collecting lens, an optical filter, a Raman signal detection unit and a computer;
the femtosecond laser is used for outputting two femtosecond laser signals with different frequencies;
the beam combining unit is used for combining two femtosecond laser signals with different frequencies and transmitting the combined femtosecond laser signals to the laser scanning unit;
the laser scanning unit is used for one-dimensional scanning of the laser after beam combination and ensuring that the laser always fills the entrance pupil of the focusing unit in the scanning process;
the focusing unit is used for focusing laser on a certain fault section in a micro-flow channel of the micro-flow channel chip, so that laser spots reciprocate on the fault section or scan along the same direction;
the micro-channel chip is arranged on the objective table; injecting a cell sample to be detected into a microfluidic channel of the microfluidic channel chip through the cell sample injection unit, and sequentially exciting scattering Raman signals at each point of the cell by a laser focusing light spot after the cell passes through a scanning section; the cell collection unit is used for collecting the detected cells;
and after the scattered Raman signals are collected by the collecting lens, filtering out laser with a certain frequency by the optical filter, detecting the intensity change of the rest laser signals by the Raman signal detection unit, acquiring stimulated Raman signals, and transmitting the stimulated Raman signals to the computer for signal processing to acquire a cell image.
Specifically, the beam combining unit comprises a reflecting mirror and a dichroic mirror, and two femtosecond laser signals with different frequencies are combined into one beam through the dichroic mirror and then transmitted to the laser scanning unit through the reflecting mirror.
Specifically, the laser scanning unit comprises a one-dimensional scanning galvanometer and a 4-f system; the laser after beam combination is transmitted to a one-dimensional scanning galvanometer, and a reflecting mirror of the one-dimensional scanning galvanometer is rapidly deflected under the drive of a motor, so that laser scanning is realized; the deflected laser passes through a 4-f system consisting of two lenses, so that the laser is ensured to always fill the entrance pupil of the focusing unit in the scanning process.
Specifically, the focusing unit comprises a microscope objective, the laser always fills the entrance pupil of the microscope objective in the scanning process, and the microscope objective focuses on a certain fault section in a microfluidic channel of the microfluidic chip.
Specifically, the cell sample injection unit is formed by sequentially connecting a sample cell, a sample inlet tube, an injection pump and an injection tube in series, wherein the injection tube is connected with the micro-channel chip; the cell sample to be detected is placed in the sample cell, and after the cell sample is sucked from the sample cell through the sample injection pipe by the injection pump, the cell sample is injected into the microfluidic channel through the injection pipe.
Specifically, the cell collection unit comprises a collecting pipe and a cell collection container, wherein the collecting pipe is connected with the micro-channel chip, and the detected cells are collected through the collecting pipe and flow into the cell collection container.
Specifically, the raman signal detection unit comprises a photodiode, and the photodiode is connected with the computer through a data line; the photodiode is used for detecting the intensity change of the rest laser signals, acquiring stimulated Raman signals and converting the stimulated Raman signals into electric signals, and transmitting the electric signals to the computer through the data line.
Example 1
Referring to fig. 1, a cellular raman flow spectroscopy imaging analysis system comprising:
a femtosecond laser 1, a first reflecting mirror 2, a dichroic mirror 3, a second reflecting mirror 4, a laser scanning unit, a microscope objective 8, a stage 9, a micro flow channel chip 11, a cell collecting unit, a collecting lens 18, a filter 19, a raman signal detecting unit, and a computer 22;
the femtosecond laser 1 is used for outputting two femtosecond laser signals with different frequencies;
the beam combining unit comprises a first reflecting mirror 2, a dichroic mirror 3 and a second reflecting mirror 4, wherein two femtosecond laser signals with different frequencies are combined into one beam through the first reflecting mirror 2 and the dichroic mirror 3, and then transmitted to the laser scanning unit through the second reflecting mirror 4;
the laser scanning unit comprises a one-dimensional scanning galvanometer 5 and a 4-f system; the laser after beam combination is transmitted to a one-dimensional scanning galvanometer 5, and a reflector of the one-dimensional scanning galvanometer 5 is rapidly deflected under the drive of a motor, so that laser scanning is realized; the deflected laser passes through a 4-f system formed by a first lens 6 and a second lens 7, so that the laser is always full of the entrance pupil of a microscope objective 8 in the scanning process;
the focusing unit comprises a micro objective 8, the laser is always full of an entrance pupil of the micro objective 8 in the scanning process, and is focused on a certain fault section in a micro-flow channel 10 of a micro-flow channel chip 11 by the micro objective 8, so that laser spots reciprocate on the fault section or scan along the same direction;
the micro-channel chip 11 is arranged on the objective table 9; the cell sample injection unit is formed by sequentially connecting a sample cell 12, a sample injection pipe 13, an injection pump 14 and an injection pipe 15 in series, wherein the injection pipe 15 is connected with the micro-channel chip 11; placing a cell sample to be detected in a sample cell 12, sucking the cell sample from the sample cell 12 through a sample inlet tube 13 by an injection pump 14, injecting the cell sample into a microfluidic channel 10 through an injection tube 15, and sequentially exciting scattering Raman signals at each point of the cell by a laser focusing light spot after the cell passes through a scanning section;
the Raman signal detection unit comprises a photodiode 20, and the photodiode 20 is connected with a computer 22 through a data line 21; the photodiode 20 is used for detecting the intensity change of the rest laser signal, acquiring stimulated raman signal and converting the stimulated raman signal into an electrical signal, transmitting the electrical signal to the computer 22 through a data line, and performing signal processing by the computer 22 to acquire a cell image.
Example 2
In this embodiment, a femtosecond laser (InSight X3, spectra-Physics) is used to synchronously output two Gaussian-phase-locked femtosecond laser pulses, wherein one path of laser pulses has a central wavelength fixed to 1045nm, and the laser pulses are used as Stokes light (ω) of the SRS system s ) Stokes light is modulated by an acousto-optic modulator, has intensity change of 2Mhz, and the other beam has center wavelength tunable between 680 and 1300nm, and is used as Pump light (omega) of SRS system p ) Their initial pulse widths are 200fs and 120fs, respectively. Tuning PumpThe center wavelength of light is 802nm, and the corresponding center wave number is located in a high wave number region of 2900cm < -1 >.
After two laser beams are combined, the two laser beams pass through a one-dimensional scanning vibrating mirror and are focused on a micro-flow channel by a micro-objective lens, the micro-flow channel is a one-way channel with the width of 300 mu m and the depth of 100 mu m, the one-dimensional scanning vibrating mirror deflects at a high speed of 100khz to realize the rapid scanning of a combined laser spot on a detection section of the micro-flow channel, after the laser beams are injected into cells at a set speed, the cells flow through the scanning section to excite stimulated Raman scattering at a corresponding position of the cells, so that the intensity of Stokes is increased, the intensity of the Pump is weakened, stokes light is filtered through a low-pass filter, the change of the intensity of the Pump is detected, raman spectrum information at the corresponding position can be obtained, and stimulated Raman signals obtained by rearranging according to a scanning path of the one-dimensional scanning vibrating mirror can form stimulated Raman spectrum images of the cells, and rapid flow cytometry Raman spectrum imaging detection is realized.
Principle of: the specific process of realizing two-dimensional cell spectrum imaging by flow cell feeding and laser scanning is shown in figure 2, the laser is focused at a certain point in a micro-flow channel by an objective lens, the laser direction is gradually deflected by a one-dimensional scanning galvanometer, so that a laser gathering facula on a certain plane in a cell gradually moves along a specific direction, as shown in figure 2 (a), the gradual scanning is realized along the positions 1, 2, 3 and 4 … n of the channel, the Raman signal in the cell is excited point by point, and a line of signal a in a cell spectrum image is formed after the corresponding signal is collected by a detector 1 、a 2 、a 3 、a 4 …a n As the cells flow along the microfluidic channel at a certain speed under the drive of the microfluid, as shown in FIG. 2 (b), when the position of the cells 23 passing through the scanning section of the microfluidic channel changes, the scanning of different positions of the cells is realized, and the signals b at the corresponding positions of one row are obtained 1 、b 2 、b 3 、b 4 …b n The cell Raman spectrum image information can be constructed according to the laser scanning sequence and the acquired signals through the flow feeding and the laser scanning in sequence. To achieve accurate image acquisition, obtaining image information of sufficient resolution, streaming feedThe speed needs to be matched with the laser scanning speed, the flow feeding speed is determined by the injection speed V of the injection pump, the laser scanning speed is determined by the scanning frequency P of the one-dimensional scanning galvanometer, and the matching relation between the two is as follows:
；
wherein V is the injection speed of the injection pump, mu L/s, P is the scanning frequency of the one-dimensional scanning galvanometer, and the unit is Hz; a is a constant, a=1 when the one-dimensional scanning galvanometer scans unidirectionally, and a=2 when the one-dimensional scanning galvanometer scans reciprocally; w, H the width and height of the section of the microfluidic channel are respectively in mm; n is the number of data points in a scan line of data.
Example 3
A cell Raman flow spectrum imaging analysis method adopts a cell Raman flow spectrum imaging analysis system to analyze, and specifically comprises the following steps:
s1, acquiring cells of a target type by using a cell Raman flow spectrum imaging analysis system, and acquiring a cell spectrum image database of the type; establishing a Raman spectrum image database of different cell molecular distributions; the method specifically comprises the following substeps:
s101, setting the injection speed of an injection pump, the laser scanning speed and the frequency difference of femtosecond laser of a cell Raman flow spectrum imaging analysis system;
s102, placing a cell sample to be detected in a sample cell, sucking the cell sample from the sample cell through a sample inlet pipe by a syringe pump, and injecting the cell sample into a microfluidic channel through the syringe;
s103, after the cells pass through the scanning section, sequentially exciting scattering Raman signals at each point of the cells by using a laser focusing light spot;
s104, after the scattered Raman signals are collected by the collecting lens, laser with a certain frequency is filtered by the optical filter, the intensity change of the rest laser signals is detected by the Raman signal detection unit, stimulated Raman signals are obtained and transmitted to the computer for signal processing, and a cell image is obtained;
s105, establishing a Raman spectrum image database of different cell molecular distributions;
s2, training an analysis model based on statistical methods such as principal component analysis and the like;
s3, inputting the cell image information into an analysis model, and acquiring cell type information according to a discrimination result;
s4, analyzing and recovering the cells according to different cell types.
Principle of: before cell analysis, a Raman spectrum image database of molecular distribution of different types of cells needs to be established in advance, a system is adopted to collect the cells of the target type, the cell spectrum image database of the type is obtained, an analysis model is trained based on a statistical method such as principal component analysis, and in the actual analysis process, the collected cell Raman spectrum image data is input into the analysis model, so that a cell analysis result can be obtained.
Imaging the leukemia cancer cells cultured in the laboratory by injecting them into the system, and observing the micro-channel under the microscope Bai Guangming field imaging, fig. 4 shows that almost no cells are seen and only the outline of the cells is hidden and visible; FIG. 5 is an image of our detection of cells at 60 x objective, showing that the cell nuclei are dividing, a cancer cell in the process of proliferation.
The traditional flow cytometry generally depends on fluorescent markers, meanwhile, cell image information cannot be obtained, a high-speed camera is added on the basis of the traditional flow cytometry to realize microscopic bright field imaging, information such as cell morphology and the like is observed in a bright field, the contrast ratio of cells is generally extremely low, the information such as the outline, the size and the like of the cells is mainly observed under the bright field observation, spectral imaging cannot be realized, and the cell molecular distribution condition (shown in fig. 6) is obtained. FIG. 6 shows the results of imaging cells of 30-100 μm in size, the instrument is used to shoot cells in the open field with a high-speed camera, and the imaging function of the spectrum is not provided, but the invention can give the results of imaging the spectrum of the cells.
The invention can realize high-flux cell Raman flow spectrum imaging analysis, and can obtain the distribution of molecules such as proteins, nucleic acids, lipids and the like in the cells by rapidly obtaining Raman scattering signals at each point in the flowing cells, and can realize analysis such as cancer cell identification and the like by combining a statistical analysis method according to the image information of the molecular distribution.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (7)
1. A method of cellular raman flow spectroscopy analysis, characterized in that a cellular raman flow spectroscopy analysis system is employed for analysis, the system comprising: the system comprises a femtosecond laser, a beam combining unit, a laser scanning unit, a focusing unit, an objective table, a cell sample injection unit, a micro-channel chip, a cell collecting unit, a collecting lens, an optical filter, a Raman signal detection unit and a computer;
the femtosecond laser is used for outputting two femtosecond laser signals with different frequencies;
the beam combining unit is used for combining two femtosecond laser signals with different frequencies and transmitting the combined femtosecond laser signals to the laser scanning unit;
the laser scanning unit is used for one-dimensional scanning of the laser after beam combination and ensuring that the laser always fills the entrance pupil of the focusing unit in the scanning process;
the focusing unit is used for focusing laser on a certain fault section in a micro-flow channel of the micro-flow channel chip, so that laser spots reciprocate on the fault section or scan along the same direction;
the micro-channel chip is arranged on the objective table; injecting a cell sample to be detected into a microfluidic channel of the microfluidic channel chip through the cell sample injection unit, and sequentially exciting scattering Raman signals at each point of the cell by a laser focusing light spot after the cell passes through a scanning section; the cell collection unit is used for collecting the detected cells;
the cell sample injection unit is formed by sequentially connecting a sample cell, a sample inlet tube, an injection pump and an injection tube in series, and the injection tube is connected with the micro-channel chip; placing a cell sample to be detected in the sample cell, sucking the cell sample from the sample cell by the injection pump through the sample injection pipe, and injecting the cell sample into the microfluidic channel through the injection pipe; the injection speed of the injection pump is matched with the laser scanning speed, and the laser scanning speed is determined by the scanning frequency of the one-dimensional scanning galvanometer; the matching relation is as follows:
；
wherein V is the injection speed of the injection pump, mu L/s, P is the scanning frequency of the one-dimensional scanning galvanometer, and the unit is Hz; a is a constant, a=1 when the one-dimensional scanning galvanometer scans unidirectionally, and a=2 when the one-dimensional scanning galvanometer scans reciprocally; w, H the width and height of the section of the microfluidic channel are respectively in mm; n is the number of data points in a line of data scanned;
after the scattered Raman signals are collected by the collecting lens, laser with a certain frequency is filtered by the optical filter, the intensity change of the rest laser signals is detected by the Raman signal detection unit, stimulated Raman signals are obtained and transmitted to the computer for signal processing, and a cell image is obtained;
the method specifically comprises the following steps:
s1, acquiring cells of a target type by using a cell Raman flow spectrum imaging analysis system, and acquiring a cell spectrum image database of the type; establishing a Raman spectrum image database of different cell molecular distributions;
s2, training an analysis model based on a statistical method;
s3, inputting the cell image information into an analysis model, and acquiring cell type information according to a discrimination result;
s4, analyzing and recovering the cells according to different cell types.
2. The method for raman flow spectroscopy imaging analysis of cells according to claim 1, wherein: the beam combining unit comprises a reflecting mirror and a dichroic mirror, and two femtosecond laser signals with different frequencies are combined into one beam through the dichroic mirror and then transmitted to the laser scanning unit through the reflecting mirror.
3. A method of cellular raman flow spectroscopy according to claim 2, wherein: the laser scanning unit comprises a one-dimensional scanning galvanometer and a 4-f system; transmitting the laser after beam combination to the one-dimensional scanning galvanometer, and rapidly deflecting a reflecting mirror of the one-dimensional scanning galvanometer under the drive of a motor to realize laser scanning; after deflection, the laser passes through the 4-f system, so that the laser is ensured to always fill the entrance pupil of the focusing unit in the scanning process.
4. A method of cellular raman flow spectroscopy according to claim 3 wherein: the focusing unit is a microscope objective, and laser always fills the entrance pupil of the microscope objective in the scanning process, and the microscope objective focuses on a certain fault section in a microfluidic channel of the microfluidic chip.
5. The method for raman flow spectroscopy imaging analysis of cells according to claim 4, wherein: the Raman signal detection unit is a photodiode, and the photodiode is connected with the computer through a data line; the photodiode is used for detecting the intensity change of the rest laser signals, acquiring stimulated Raman signals and converting the stimulated Raman signals into electric signals, and transmitting the electric signals to the computer through the data line.
6. The method for raman flow spectroscopy of cells according to claim 5, wherein: the step S1 specifically comprises the following sub-steps:
s101, setting the injection speed of an injection pump, the laser scanning speed and the frequency difference of femtosecond laser of a cell Raman flow spectrum imaging analysis system;
s102, placing a cell sample to be detected in a sample cell, sucking the cell sample from the sample cell through a sample inlet pipe by a syringe pump, and injecting the cell sample into a microfluidic channel through the syringe;
s103, after the cells pass through the scanning section, sequentially exciting scattering Raman signals at each point of the cells by using a laser focusing light spot;
s104, after the scattered Raman signals are collected by the collecting lens, laser with a certain frequency is filtered by the optical filter, the intensity change of the rest laser signals is detected by the Raman signal detection unit, stimulated Raman signals are obtained and transmitted to the computer for signal processing, and a cell image is obtained;
s105, establishing a Raman spectrum image database of different types of cell molecular distributions.
7. The method for raman flow spectroscopy of cells according to claim 6, wherein: the statistical method is a principal component analysis method.
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