CN112525806A - Flow cytometry detection device, preparation method and system - Google Patents
Flow cytometry detection device, preparation method and system Download PDFInfo
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Abstract
本发明公开了一种流式细胞检测装置、制备方法及系统，该装置包括：表面等离激元激发芯片，用于在偏振光的照射下激发表面等离激元，包括透明基底，以及基底表面附着的金属膜层；细胞通道，包括流入通道、压缩通道和回收通道，细胞通道与所述芯片的附着有金属膜层的一面键合形成不透水密闭空间。其中，压缩通道的覆盖区域附着有金属膜层。当该装置处于工作状态时，利用溶液搭载的待测细胞从流入通道流入，进入压缩通道，以保持与所述金属膜层接触的状态通过目标检测区域，由回收通道流出。通过该装置能够有效地实现单个待测细胞表面折射率的快速检测。
The invention discloses a flow cytometry detection device, a preparation method and a system. The device comprises: a surface plasmon excitation chip, which is used to excite the surface plasmon under the irradiation of polarized light, including a transparent substrate, and a substrate The metal film layer attached to the surface; the cell channel, including the inflow channel, the compression channel and the recovery channel, and the cell channel is bonded to the side of the chip with the metal film layer attached to form a watertight closed space. Wherein, the covering area of the compression channel is attached with a metal film layer. When the device is in working state, the cells to be tested carried by the solution flow in from the inflow channel, enter the compression channel, pass through the target detection area in a state of contact with the metal film layer, and flow out from the recovery channel. The device can effectively realize the rapid detection of the surface refractive index of a single cell to be measured.
Description
Technical Field
The invention relates to the technical field of photoelectric detection, in particular to a flow cytometry detection device, a preparation method and a system.
Background
As a basic unit of organism structure and function, cell research is of great significance for revealing chemical essence and rules in the life process. Due to the limitation of research means, the past life science research mainly measures the comprehensive characteristics of a large number of cells, however, significant microscopic heterogeneity exists among different individuals of the same cell, the experimental result based on the comprehensive characteristics of a large number of cells is difficult to reflect the life activity rule on the single cell level, and the realization of single cell analysis becomes one of the development directions of measurement technologies. Meanwhile, the heterogeneity of the same kind of cells is important to the nature and regularity of life activities, such as: heterogeneity between tumor cells is a key factor in causing cancer fatality, treatment failure and drug resistance, and thus, a large number of homogeneous single cells need to be analyzed separately.
Based on the need for high throughput single cell analysis, different analytical methods have been developed to analyze various characteristics of cells, such as: genome sequencing, PCR, mass spectrometry, microscopy, etc. The analysis of the characteristics of single cells is a systematic problem, and the development of the analysis of different characteristics of the single cells helps to promote people to further enhance the understanding of the cells and reveal the law of life processes. The refractive index distribution of the cell surface layer is a physical quantity which can characterize the cell characteristics: because the refractive index of the cell surface layer is related to factors such as water content, protein concentration and the like, the refractive index can effectively analyze the components of the cell in different physiological states; meanwhile, the refractive index of the cells changes in the processes of bacterial infection, cell dormancy and the like. However, since the composition of cell surface layer substances in different states is similar, the refractive index change is small, and signals from the cell surface layer are often mixed with signals inside the cell and are difficult to be extracted separately. Therefore, the measurement difficulty of the surface refractive index of the single cell is large.
Disclosure of Invention
The invention provides a flow cytometry detection device, a preparation method and a system, which can quickly and effectively measure the surface refractive index of a single cell.
In a first aspect, embodiments of the present disclosure provide a flow cytometry detection apparatus, including:
the surface plasmon excitation chip is used for exciting surface plasmons under the irradiation of polarized light and comprises a transparent substrate and a metal film layer attached to the surface of the substrate;
the cell channel comprises an inflow channel, a compression channel and a recovery channel, the inflow channel, the compression channel and the recovery channel are sequentially communicated, the cell channel is bonded with one surface, attached with the metal film layer, of the chip to form a waterproof closed space, and the metal film layer is attached to a covering area of the compression channel;
when the device is in a working state, the cell to be detected carried by the solution flows in from the inflow channel, enters the compression channel, passes through the target detection area in a state of keeping contact with the metal film layer, and flows out from the recovery channel, wherein the refractive index of the solution is smaller than that of the substrate.
Further, the flow cytometry detection apparatus further includes: and the driver is connected with the cell channel and is used for driving the cell to be detected to enter from the inflow channel and flow out from the recovery channel through the compression channel.
Further, the height and width of the compression channel are both less than or equal to the size of the cell to be detected.
Further, the difference between the height of the compression channel and the size of the cell to be tested is between 0 and 10 micrometers, and the difference between the width of the compression channel and the size of the cell to be tested is between 0 and 10 micrometers.
In a second aspect, embodiments of the present disclosure provide a method for manufacturing a flow cytometry detection apparatus, the method including: forming a cell channel matched with the transparent substrate, wherein the cell channel comprises an inflow channel, a compression channel and a recovery channel, and the inflow channel, the compression channel and the recovery channel are communicated in sequence; preparing a metal film layer on the surface of the transparent substrate to form a surface plasmon excitation chip, wherein the chip is used for exciting surface plasmons under the irradiation of polarized light; and bonding the cell channel with the surface of the surface plasmon excitation chip, on which the metal film layer is prepared, to form a flow cytometry detection device, wherein the metal film layer is attached to a covering region of the compression channel on the chip, and the compression channel is used for enabling cells to be detected to pass through a target detection region in a state of keeping contact with the metal film layer.
In a third aspect, embodiments of the present disclosure provide a flow cytometry detection system, including: an optical detection device and a flow cytometry detection device according to the first aspect. The flow cytometry detection device is used for driving cells to be detected to pass through a target detection area one by one in a mode of keeping contact with a metal film layer on a surface plasmon excitation chip. The optical detection apparatus includes: the system comprises an illumination subsystem, an objective lens, an imaging subsystem and a data processing device, wherein the illumination subsystem is used for collimating and polarization adjusting light emitted by a light source and generating polarized light to be incident on the objective lens; the objective lens is used for enabling the polarized light to enter a target detection area on the flow cytometry detection device, exciting surface plasmons on the surface of a metal film layer of the target detection area to interact with passing cells to be detected, wherein the target detection area is located in the coverage area of the compression channel; the imaging subsystem is used for imaging the reflected light formed by the polarized light on the detection device to a target surface of a photoelectric detector and acquiring a target image sequence formed by the reflected light at a target position through the photoelectric detector; and the data processing device is used for obtaining the surface refractive index and the morphology information of the cell to be detected based on the target image sequence.
Further, the optical detection apparatus further includes: and the carrying subsystem comprises a clamp and a moving mechanism, the clamp is connected with the moving mechanism, the clamp is used for fixing the flow cytometry detection device, and the moving mechanism is used for carrying the flow cytometry detection device to move so as to adjust the position of the target detection area and focus the objective lens.
Further, the objective lens is used for enabling polarized light generated by the illumination subsystem to be parallelly incident to the target detection area, and the target position is a conjugate imaging plane of a back focal plane of the objective lens. The data processing apparatus is configured to: acquiring brightness distribution data of each target image in the target image sequence; and determining the surface refractive index distribution and the profile information of the cell to be detected based on the brightness distribution data of each target image and a first preset corresponding relation, wherein the first preset corresponding relation is the corresponding relation between the brightness of the reflected light and the refractive index of the sample.
Further, the objective lens is used for focusing the parallel polarized light generated by the illumination subsystem to the target detection area, and the target position is a Fourier plane of a conjugate imaging plane of a back focal plane of the objective lens. The data processing apparatus is configured to: aiming at each target image in the target image sequence, obtaining a target reflection light space frequency domain spectrum corresponding to the cell to be detected; and determining the surface refractive index and the surface fluctuation distribution of the cell to be detected based on the target reflection light space frequency domain spectrum corresponding to each target image in the target image sequence and a second preset corresponding relationship, wherein the second preset corresponding relationship is the corresponding relationship between the reflection light space frequency domain spectrum obtained based on a transmission theory model and the refractive index of the sample and the target thickness.
Further, the data processing apparatus is further configured to: and obtaining an analysis result of the cell to be detected based on the surface refractive index of the cell to be detected and a pre-trained cell analysis model, wherein the cell analysis model is a machine learning model.
In the flow cytometry detection device provided by the embodiment of the present specification, the surface plasmon excitation chip and the cell channel are bonded, so that the cell to be detected flows in the cell channel under solution loading, and passes through the target detection region one by one in a state of keeping contact with the metal film layer in the process of flowing through the compression channel. By matching with an optical detection system, polarized light is incident to a target detection area to excite surface plasmons, and the surface plasmons interact with cells to be detected passing through the target detection area one by one, so that the detection of the surface refractive index of a single cell to be detected is realized. In the detection process, the adherent growth on the measurement chip is not required to be spent for a large amount of time in advance, namely, the longer cell culture time is not required, the switching of different cells is not required to be realized by continuously changing the position of the measurement chip, the detection is favorable for reducing the time consumption, the rapid detection of the surface refractive index of a single cell to be detected is favorable for realizing, and then the high-throughput single cell detection is realized. Moreover, the flow cytometry detection device can be repeatedly used for detecting different types of cells, and different detection chips do not need to be prepared for different cells, so that the detection cost is reduced. In addition, the flow cytometry detection system provided by the embodiment of the present specification can effectively realize the rapid detection of the surface refractive index of a single cell to be detected by using the flow cytometry detection device.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the specification. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a schematic structural diagram of a flow cytometry detection apparatus provided in a first aspect of an embodiment of the present disclosure;
fig. 2 is a process flow chart of a method for manufacturing a flow cytometry detection apparatus according to a second aspect of an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of an exemplary flow cytometry system provided by a third aspect of an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of another exemplary flow cytometry system provided in a third aspect of embodiments of the present disclosure;
FIG. 5 is a schematic diagram of two imaging systems provided in a third aspect of embodiments of the present disclosure;
FIG. 6 is a spatial frequency domain image of reflected light corresponding to an exemplary sample provided in a third aspect of embodiments of the present disclosure;
fig. 7 is a schematic diagram illustrating a detection principle of a dot region detection method provided in the third aspect of the embodiment of the present specification.
Detailed Description
In order to better understand the technical solutions provided by the embodiments of the present specification, the technical solutions of the embodiments of the present specification are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present specification are detailed descriptions of the technical solutions of the embodiments of the present specification, and are not limitations on the technical solutions of the embodiments of the present specification, and the technical features in the embodiments and examples of the present specification may be combined with each other without conflict.
In a first aspect, the present specification provides a flow cytometry detection apparatus, as shown in fig. 1, where the flow cytometry detection apparatus 10 includes: a surface plasmon excitation chip 110, and a cell channel 120.
The surface plasmon excitation chip 110 includes a transparent substrate 101, and a metal film layer 102 attached to a surface of the substrate 101, for exciting surface plasmons under irradiation of polarized light. In a specific implementation process, the surface plasmon excitation chip 110 may be formed by plating a metal thin film with a specified thickness on a high refractive index cover glass substrate.
It is understood that Surface Plasmon Resonance (SPR) is an electromagnetic oscillation formed by the interaction of free electrons and photons at a metal-dielectric interface. The electromagnetic field of SPR attenuates exponentially along the normal direction on both sides of the interface of two materials, has extremely strong field distribution in a spatial range far less than the wavelength, and the local field is very sensitive to the change of the peripheral refractive index, thereby realizing high-sensitivity detection. SPR, on the other hand, is an evanescent field that decays exponentially along a metal interface, has a very high field density, and is very sensitive to the distribution of objects and changes in their refractive indices within its field coverage.
In an alternative embodiment, the metal film layer 102 attached to the surface of the substrate 101 includes an adhesion layer and an excitation layer, and the adhesion layer is attached to the surface of the transparent substrate for adhering the excitation layer. The excitation layer is used to excite SPR at the excitation layer-medium interface. For example, the metal material used for the adhesion layer may be titanium (Ti) or chromium (Cr); the metal material adopted by the excitation layer can be gold (Au) as SPR excitation metal. The thicknesses of the adhesion layer and the excitation layer can be set according to actual needs, for example, the thickness of the adhesion layer can be 2 to 5nm, and the thickness of the excitation layer can be 45 to 55 nm.
It should be noted that the left side of fig. 1 is a front view of the flow cytometry detection apparatus 10, the upper right dotted frame part is a top view of the dotted frame area in the front view, the oval and dot-filled area represents the cell 100 to be detected, and the shape and size of the cell are only schematic. The cell channel 120 includes an inflow channel 121, a compression channel 122, and a recovery channel 123, and the inflow channel 121, the compression channel 122, and the recovery channel 123 are sequentially communicated. The cell channel 120 is bonded to the surface of the surface plasmon excitation chip 110 to which the metal film layer 102 is attached, to form a watertight sealed space. The height and width of the compression channel 122 are both less than or equal to the size of the cell 100 to be detected, and the difference between the height and width of the compression channel 122 and the size of the cell 100 to be detected is within a preset range, so as to ensure that the cell 100 to be detected can be tightly attached to the lower metal film layer 102 in a compressed state one by one to pass through a target detection area in the compression channel 122. For example, the height and width of the compression channels 122 may be in the range of 1 to 50 microns. The size of the cell to be detected refers to the maximum size of the cell to be detected in an uncompressed state, for example, if the cell to be detected is oval, the length of the major axis is obtained; the preset range is a deviation range of the height and the height of the compression channel and the corresponding size of the cell to be detected under the condition that the single cell to be detected can pass through the compression channel in a compression state in an actual application scene. For example, the difference between the height of compression channel 122 and the size of test cell 100 may be between 0 and 10 microns, and the difference between the width of compression channel 122 and the size of test cell 100 may also be between 0 and 10 microns.
The compression channels 122 have a metal film layer attached to the footprint of the chip surface. In this embodiment, the metal film may cover the entire surface of the excitation chip; or, in order to facilitate bonding, only the region range corresponding to the compression channel may be covered, so as to ensure that the target detection region 1221 located in the compression channel 122 is attached with the metal film layer, so as to implement detection of the cell to be detected passing through the target detection region 1221; alternatively, the area range corresponding to the compression path and a partial area in the vicinity of the area range may be covered.
When the flow cytometry detection apparatus 10 is in an operating state, for example, when the flow cytometry detection apparatus is applied to surface refractive index detection of a cell to be detected, the cell to be detected 100 is carried by a solution, so that the cell to be detected flows in from the inflow channel 121, enters the compression channel 122, passes through a target detection region in a state of maintaining contact with the metal film layer in the compression channel, and then flows out from the recovery channel 123. The specific refractive index detection process is detailed below in the flow cytometry system. Of course, in order to drive the direction flow of the cells to be tested in the cell channel, an external driver is required. The refractive index of the solution for carrying the cells is smaller than the refractive index of the chip substrate 101.
In an alternative embodiment, to facilitate the use of the flow cytometry detection apparatus, the flow cytometry detection apparatus 10 may further comprise: and the driver 130, the driver 130 is connected with the cell channel 120, and is used for driving the cell to be tested to enter from the inflow channel 121, pass through the compression channel 122, and flow out from the recovery channel 123.
In this embodiment, the driver 130 may be a pneumatic driver. In one embodiment, the driver may be a positive pressure driver, and the positive pressure driver has a pressure greater than the pressure in the cell channel, is connected to the inflow channel, and drives the cell to be detected to flow directionally in the cell channel by the positive pressure. In another embodiment, the driver may be a negative pressure driver, the negative pressure driver has a pressure lower than the pressure in the cell channel, and is connected to the recovery channel, and the negative pressure drives the cell to be detected to flow directionally in the cell channel.
It should be noted that the flow cytometry detection apparatus 10 may further include other components besides the above components, for example, a connection pipeline 140, such as a pipeline connected to the inflow channel and a pipeline connected to the recovery channel, and specifically, reference may be made to a transfer pipeline of a conventional microfluidic chip, which is not described in detail herein.
In the flow cytometry detection device provided by the embodiment of the present specification, the surface plasmon excitation chip and the cell channel are bonded, so that the cell to be detected flows in the cell channel under solution loading, and passes through the target detection region one by one in a state of keeping contact with the metal film layer in the process of flowing through the compression channel. By matching with an optical detection system, polarized light is incident to a target detection area to excite surface plasmons, and the surface plasmons interact with cells to be detected passing through the target detection area one by one, so that the detection of the surface refractive index of a single cell to be detected is realized. In the detection process, the adherent growth on the measurement chip is not required to be spent for a large amount of time in advance, namely, the longer cell culture time is not required, the switching of different cells is not required to be realized by continuously changing the position of the measurement chip, the detection is favorable for reducing the time consumption, the rapid detection of the surface refractive index of a single cell to be detected is favorable for realizing, and then the high-throughput single cell detection is realized. Moreover, the flow cytometry detection device can be repeatedly used for detecting different types of cells, and different detection chips do not need to be prepared for different cells, so that the detection cost is reduced.
In a second aspect, embodiments of the present disclosure provide a method for preparing a flow cytometry detection apparatus, which is used to prepare the flow cytometry detection apparatus described in the foregoing first aspect.
The preparation method provided by the embodiment can comprise the following steps: forming a cell channel matched with the transparent substrate, wherein the cell channel comprises an inflow channel, a compression channel and a recovery channel, and the inflow channel, the compression channel and the recovery channel are sequentially communicated; preparing a metal film layer on the surface of a transparent substrate to form a surface plasmon excitation chip, wherein the chip is used for exciting surface plasmons under the irradiation of polarized light; bonding the cell channel with the surface of the surface plasmon excitation chip, on which the metal film layer is prepared, to form a flow cytometry detection device, wherein the metal film layer is attached to a covering region of the compression channel on the chip during bonding. Wherein, the compression channel is used for enabling the cells to be detected to pass through the target detection area one by one in a state of keeping contact with the metal film layer. For the specific structure of the flow cytometry detection apparatus, reference may be made to the description of the apparatus embodiment provided in the first aspect, and details are not repeated here.
By way of example, FIG. 2 shows a schematic diagram of an exemplary fabrication process flow. In fig. 2, the left side a-E diagram illustrates a process for preparing a cell channel, the material of the cell channel is PDMS (Polydimethylsiloxane) material, the right side F-I diagram illustrates a process for preparing a surface plasmon excitation chip, and the metal film is a gold film as an example. J represents bonding of the cell channel and the surface plasmon excitation chip.
The preparation process of the cell channel comprises the following steps: a layer of photoresist 1, such as SU-8 photoresist, is coated on the surface of a smooth substrate, such as a silicon wafer, and the thickness of the photoresist determines the height of a cell channel, which is less than or equal to the height of a cell to be detected and can be 1-50 microns. It is understood that a smooth substrate is one intermediate for the formation of PDMS cell channels. An exposure operation is performed based on a Mask (Mask) shown in figure a, and then a layer of photoresist 2, such as SU-8 photoresist, is coated on the exposed photoresist layer, and the photoresist thickness can be between 1 and 200 microns. And (3) carrying out alignment and secondary exposure operation based on the mask shown in the diagram B (arrows in the diagrams A and B represent photoetching exposure), sequentially developing (shown in the diagram C), pouring PDMS (shown in the diagram D), taking down the cell channel formed by the PDMS, and punching to serve as a channel and conveying pipeline interface (shown in the diagram E).
The preparation process of the surface plasmon excitation chip comprises the following steps: coating a layer of photoresist 3 on the surface of a transparent substrate such as a cover glass, carrying out photoetching operation based on a mask plate shown in a figure F, developing (shown in a figure G), removing the photoresist at a position inside a compression channel, plating a gold (Au) film on the surface after the developing operation is finished (shown in a figure H), and further stripping the photoresist to obtain the surface plasmon excitation chip (shown in a figure I).
Further, the formed cell channel is aligned with the surface plasmon excitation chip, mainly the position of the compression channel is aligned with the position of the gold-plated film, and the compression channel is bonded to the gold-plated film side, so that the flow cytometry detection device can be obtained, as shown in fig. 2, J.
In a third aspect, embodiments of the present disclosure provide a flow cytometry detection system, including: an optical detection device and the flow cytometry detection device provided by the embodiment of the first aspect.
The flow cytometry detection device is used for driving cells to be detected to pass through a target detection area one by one in a mode of keeping contact with a metal film layer on a surface plasmon excitation chip. For the specific structure of the flow cytometry detection apparatus, reference may be made to the description of the apparatus embodiment provided in the first aspect, and details are not repeated here.
In this embodiment, the optical detection apparatus includes: an illumination subsystem, an objective lens, and an imaging subsystem.
The illumination subsystem is used for collimating and polarization adjusting light emitted by the light source to generate polarized light to be incident on the objective lens, and preferably, single-wavelength laser or narrow-band light can be used as the light source.
And the objective lens is used for enabling polarized light to enter a target detection area on the flow cytometry detection device, exciting surface plasmons on the surface of a metal film layer of the target detection area to interact with passing cells to be detected, wherein the target detection area is located in a coverage area of the compression channel on the surface plasmon excitation chip. Therefore, when the cells to be detected pass through the compression channel one by one, the cells to be detected cling to the lower metal film layer in a compression state one by one and sequentially pass through the target detection area.
And the imaging subsystem is used for imaging the reflected light formed on the flow cell detection device to the target surface of the photoelectric detector and acquiring a target image sequence formed at the target position by the reflected light through the photoelectric detector. The target image sequence comprises target images of a plurality of moments which are read continuously in a preset time period.
Further, in the embodiments of the present specification, the optical detection apparatus may further include a carrying subsystem for carrying the flow cytometry detection apparatus and achieving high-precision movement, for achieving switching of the target detection region and focusing of the objective lens. Specifically, the mounting subsystem may include a clamp for fixing the flow cytometry detection apparatus and a moving mechanism for mounting the flow cytometry detection apparatus to move to adjust the position of the target detection region and to focus the objective lens. For example, the moving mechanism may employ a motorized three-dimensional translation stage.
In a specific implementation process, the optical detection device can select one of two detection modes according to different measurement ranges and detection amounts of the imaging system.
First, the surface plasmon imaging detection mode. At this time, the objective lens is used for parallelly making the p-polarized light generated by the probe light generating subsystem incident into the target detection area, correspondingly, the target position is a conjugate imaging plane of a back focal plane of the objective lens, and the acquired target image is an image of the electric field distribution of the target detection area.
For example, the system optical path diagram of the above surface plasmon imaging detection method can be as shown in fig. 3, and an exemplary detection process of the detection method is described below.
After the probe light is emitted from the light source 301, the probe light passes through the beam expanding/shaping/converging lens group 302, passes through the polarizing plate 303 and the thin film beam splitter 304, and is focused on the back focal plane of the oil immersion objective lens 305 in a p-polarization state. The detection light may be monochromatic light or narrow-band light, such as monochromatic light output by a laser, super-radiation light emitting diode SLD or LED monochromatic light, the beam expanding and shaping converging lens group 302 may be composed of a plurality of lenses, and the polarizer 303 may be located in the middle of the beam expanding and shaping converging lens group.
Adjusting the illumination subsystem to focus the incident light onto the position of the oil immersion objective 305 back focal plane; the position of the flow cytometry detection device 10 is adjusted through the carrying subsystem 309, so that the upper metal surface of the surface plasmon excitation chip is at the objective lens working height, meanwhile, the incident light illumination position corresponds to the target detection area in the flow cytometry detection device 10, the generated evanescent wave vector of total reflection is matched with the surface plasmon wave vector, and the transmission surface plasmon is excited in the target detection area on the surface of the surface plasmon excitation chip.
And controlling the flow cytometry detection device 10 to start working, namely conveying a solution loaded with the cell to be detected into the flow cytometry detection device 10, driving the cell to be detected to enter from the inflow channel, pass through the compression channel and then flow out from the recovery channel.
The position of the pellicle beam splitter 304 is adjusted left and right in the direction of the arrow by a one-dimensional electric translation stage 306 of the illumination subsystem, and the parallel incident angle of incident light is changed to excite the strongest surface plasmon. The excited surface plasmon interacts with a cell to be detected passing through a target detection region, and reflected light is collected by the same oil immersion objective 305 and then is incident on the photodetector 308 through the thin film beam splitter 304 and the tube mirror 307 in sequence. The focal length and position of the tube lens 307 are reasonably selected, so that the photoelectric detector 308 is located on a conjugate imaging plane of a back focal plane of the oil immersion objective 305, and a signal received by the photoelectric detector 308 is an image of electric field distribution of a target detection area in the flow cytometry detection device 10, and can be further used for calculating refractive index distribution information of the surface of a cell to be detected.
Second, a dot region detection method. The point area detection mode is to adopt a target detection area in the convergent light incident flow type cell detection device, wherein the target detection area is a focusing light spot, reflected light is collected, the spatial frequency domain distribution of the reflected light is imaged by utilizing the Fourier transform function of a lens, and the reflectivity distribution of incident light with different angles is obtained. That is to say, the objective lens is configured to focus parallel polarized light generated by the probe light generation subsystem to a target detection area, and accordingly, the target position is a fourier plane of a conjugate imaging plane of a back focal plane of the objective lens, and the target image is a spatial frequency domain image of reflected light.
For example, the system optical path diagram of the dot area detection method can be as shown in fig. 4, and an exemplary detection process of the detection method is described below.
And controlling the flow cytometry detection device 10 to start working, namely conveying a solution loaded with the cell to be detected into the flow cytometry detection device 10, driving the cell to be detected to enter from the inflow channel, pass through the compression channel and then flow out from the recovery channel.
After being emitted from the light source 401, the probe light is expanded and shaped by the expanded-beam shaping lens group 402, and then passes through the polarization adjusting device 403 and the thin film beam splitter 404 in sequence, so that the incident light vertically enters the oil immersion objective lens 405 in a parallel light state. The detection light may be monochromatic light, such as laser output monochromatic light, super-luminescent diode SLD or LED monochromatic light, and the beam expanding, shaping, and converging lens group 402 may be composed of a plurality of lenses. The polarization adjusting device 403 is used to adjust the polarization state of the incident light, and may adopt various polarization states, such as linearly polarized light and radially polarized light, and this embodiment may preferably adopt radially polarized light. The position of the flow cytometry detection device 10 is adjusted through the carrying subsystem 409, so that the upper surface of the metal of the surface plasmon excitation chip is positioned at the working height of the objective lens, and meanwhile, the illumination position of incident light corresponds to a target detection area in the flow cytometry detection device 10. Parallel incident light is converged to a target detection area in the flow cytometry detection device 10 under the convergence action of the oil immersion objective lens 405 to form an incident light set which is incident at different angles, and the incident light in a specific angle range can excite surface plasmons. The specific angle range is related to the surface medium distribution on the target detection area. In addition to the incident light of this specific angle range, the incident light of other angles is reflected by the surface of the surface plasmon excitation chip in the flow cytometry detection apparatus 10.
The reflected light is collected by the same oil immersion objective 405, and then enters the photodetector 408 through the thin film beam splitter 404, the tube lens 406 and the optical lens 407 in sequence, and the focal lengths and positions of the tube lens 406 and the optical lens 407 are selected reasonably, so that the photodetector 408 is located on the fourier plane of the conjugate imaging plane of the back focal plane of the oil immersion objective 405, and the signal received by the photodetector 408 is a spatial frequency domain image of the reflected light. The spatial frequency domain image can be used for calculating the refractive index information and the morphology information of the surface of the cell to be detected.
Further, in order to obtain the detection data quickly, the optical detection apparatus provided by this embodiment further includes a data processing device. The data processing device is connected with the photoelectric detector and used for reading the photoelectric detector to obtain a target image sequence and obtaining characteristic information of the cell to be detected, such as surface refractive index and morphology information of the cell to be detected, based on the target image sequence.
Specifically, the data processing device may include a chip having a data processing function, such as a single chip, a DSP, or an ARM, and may be, for example, a personal computer, a notebook computer, or the like.
In an alternative embodiment, the optical detection device adopts the above surface plasmon imaging detection mode, and at this time, the target image sequence acquired by the photodetector is an image of the electric field distribution in the target detection region. The data processing device is specifically configured to: acquiring brightness distribution data of each target image in a target image sequence; and determining the surface refractive index distribution and the profile information of the cell to be detected based on the brightness distribution data of each target image and a first preset corresponding relation, wherein the first preset corresponding relation is the corresponding relation between the brightness of the reflected light and the refractive index of the sample.
Specifically, the data processing device reads an imaging image of the photodetector, that is, a target image, first determines whether a target detection region has a cell to be detected at a plurality of different times within a preset time period, and if the cell to be detected exists at the current time, further calculates the surface refractive index of the cell to be detected according to the target image read at the current time, and then counts the surface refractive index information of the cell to be detected. The preset time period and the sampling interval can be set according to actual needs and multiple tests.
It can be understood that if there is no cell to be detected above the target detection region, i.e. a fixed region in the compression channel, the cell-carrying solution, such as PBS buffer or cell culture solution, is mainly above the target detection region, and the refractive index is fixed, and the detection image is the background light distribution. If a cell to be detected flows over the target detection region, the detection image is changed. For example, fig. 5 depicts two target images in the above surface plasmon imaging detection mode, where the left image in fig. 5 is a target image obtained when there is no cell to be detected in the target detection region, and the right image in fig. 5 is a target image obtained when there is one cell to be detected in the target detection region. Obviously, the reflected light intensity of the same detection position is different when cells exist, and the light intensity difference is related to the cell refractive index and the detection system parameters.
Therefore, for the same system, the inventor has proposed through the above research that the first preset correspondence relationship can be determined by performing experimental calibration in advance before the surface plasmon imaging detection method is used. The specific calibration process comprises the following steps: introducing liquid with different known refractive indexes into a cell channel of the flow cytometry detection device, ensuring that other system parameters are the same, detecting brightness data in a read target image to obtain brightness corresponding to the different refractive indexes, and determining the corresponding relation between the reflected light brightness of the system under the fixed parameters and the sample refractive index as a first preset corresponding relation.
Furthermore, after the data processing device acquires the target image at each sampling time within the preset time period, the brightness distribution data can be extracted from the target image, and then the brightness distribution data of the target image acquired at each time can be converted into the refractive index distribution of the cells above the target detection area at the time based on the first preset corresponding relation. Furthermore, the obtained refractive index distribution can be counted, and the surface refractive index distribution of a single cell can be obtained by splicing or averaging the refractive index distributions corresponding to the same cell. In addition, as can be seen from comparing the left and right images in fig. 5, the contour information of the cell to be measured can also be obtained from the luminance distribution data of the target image, and it can be understood that the point of the luminance distribution data which is different from the background, that is, the point corresponds to the contour of the cell to be measured.
In an alternative embodiment, the obtained surface refractive index of the test cell may be further used for cell analysis, for example, cell classification. At this time, the data processing apparatus is further configured to: and obtaining an analysis result of the cell to be detected based on the surface refractive index distribution of the cell to be detected and a cell analysis model trained in advance. The cell analysis model may be a machine learning model, for example, a Support Vector Machine (SVM) or a neural network algorithm may be used. Specifically, the purpose of cell analysis can be various, and model training can be performed according to actual needs.
For example, in an application scenario, the cell analysis model may be a clustering model, the same cell to be detected has different forms, the surface refractive indexes of different forms are distributed differently, one or more of characteristic quantities such as an average value, a maximum difference value, a root-mean-square difference value, and the like of the surface refractive index of each cell may be calculated, the calculated characteristic quantities are input into a cell analysis model trained in advance, and a large number of cells to be detected of the same type are clustered, so that the obtained cell of each type of cluster corresponds to one form of the cell. In another application scenario, the cell analysis model may be a classification model, and at this time, the class to which the cell belongs may be identified by inputting the calculated feature quantity of the certain cell into a cell analysis model trained in advance.
In an alternative embodiment, the optical detection device adopts the above point region detection mode, and the target image collected by the photodetector is a spatial frequency domain image of the reflected light. The detection mode can obtain the surface fluctuation distribution of the cells to be detected, also can be called surface roughness, besides the surface refractive index distribution of the cells to be detected, and is favorable for obtaining richer single cell detection data. At this time, the data processing apparatus is specifically configured to: aiming at each target image in the target image sequence, obtaining a target reflection light space frequency domain spectrum corresponding to the cell to be detected; and determining the surface refractive index and the surface fluctuation distribution of the cell to be detected based on the target reflection light space frequency domain spectrum corresponding to each target image in the target image sequence and a second preset corresponding relation, wherein the second preset corresponding relation is the corresponding relation between the reflection light space frequency domain spectrum obtained based on the transmission theoretical model and the refractive index of the sample and the target thickness.
In the point area detection system, at a single moment, an image formed by the photoelectric detector is a circular bright spot presenting a dark ring (for radial polarized light) or two symmetrical dark arcs (for linear polarized light). Taking linearly polarized light as an example, the distance between the dark arc and the center of the circle and the light intensity distribution near the dark arc represent the spectral distribution of the surface plasmon excitation angle at the moment, and the incident angle corresponding to the dark arc is the excitation angle of the surface plasmon. As shown in fig. 6, the left graph is a reflected light spatial frequency domain image obtained when the medium above the target detection region is air, the middle graph in fig. 6 is a reflected light spatial frequency domain image obtained when the medium above the target detection region is water, and the right graph in fig. 6 is a reflected light spatial frequency domain image obtained when the medium above the target detection region is a glucose solution having a mass fraction of 10%. The measurement is carried out by using three samples with refractive indexes of 1, 1.33 and 1.35 of air, water and a glucose solution with the mass fraction of 10%, and the larger the refractive index of the sample is, the larger the corresponding arc radius is.
Further, in order to obtain a curve of the reflection intensity varying with the incident angle, a circle where the circular arc is located may be determined by using Hough transform, and then a position of a minimum value of the intensity value on the circle may be determined (a point of the dark arc corresponding to the circle may be regarded as the intensity minimum value), and the incident angle corresponding to the center of the circle is zero degree. The intensity value from the center of the circle to the radius of the point, namely the change curve of the reflection intensity along with the incident angle, is taken along the radial direction. Or, because the dark arc can be made to be basically symmetrical left and right by adjusting the light path, the intensity value change curve from the center of the image to the edge can also be extracted along the radial direction of the center of the dark arc. In another embodiment, when the radial polarized light is used for incidence, the intensity value and the corresponding incidence angle can be extracted along the radial direction with the circle center as the starting point, and the variation curve of the reflection intensity along with the incidence angle can be obtained. Further, smoothness of the curve can be increased in a multi-group averaging mode, and noise interference is reduced.
After obtaining a variation curve of the reflected light intensity along with the incident angle, that is, a spatial frequency domain spectrum of the target reflected light corresponding to the cell to be detected, for each target image in the target image sequence, a specific implementation process for determining the surface refractive index distribution and the surface fluctuation distribution of the cell to be detected is described below.
It can be understood that when the cell to be detected passes through the target detection region, i.e. above the detection point, two layers of medium distribution are present above the detection position, assuming that the lowest layer is a buffer solution layer, the refractive index is n1, the thickness is d, the upper layer is a cell layer, the refractive index is n2, and all SPR field regions are covered. Since the refractive index of the solution is uniform and can be a known quantity, the change of the thickness d of the solution layer reflects the morphology information of the cell membrane, and n2 reflects the refractive index distribution information of the cell surface layer. When no cell exists above the detection point, the detection position presents a uniform refractive index medium layer distribution, and d can be approximately equal to the SPR penetration depth, and the SPR excitation angular spectrum distribution is only influenced by the refractive index (n1) of the lower medium.
Theoretically, the relation between the values of n1, d and n2 and the reflection spatial spectrum distribution can be obtained by a transmission theoretical model. That is to say, a second preset corresponding relation can be obtained based on the medium distribution above the detection position and the transmission theoretical model, the sample refractive index is the cell layer refractive index n2, the target thickness is the solution layer thickness d, and the cell membrane morphology information is reflected. It should be noted that the transmission theoretical model is an existing theoretical model, and represents the relationship between transmission and reflection in the multilayer medium and incident light, and is not described in detail herein.
And matching the target reflected light spatial frequency domain spectrum measured by the experiment with the reflected light spatial frequency domain spectrum corresponding to different sample refractive indexes and target thicknesses in the second preset corresponding relation to obtain the surface refractive index n2 of the cell to be measured and the thickness d of the solution layer. For example, a least square method, a residual square sum or a root mean square error method may be used for fitting, so that the objective function value of the theoretical data and the experimental data in the second preset corresponding relationship is the minimum, and the surface refractive index n2 of the cell to be detected and the thickness d of the solution layer may be matched. The objective function value is a function value used for representing the difference degree between theoretical data and experimental data, and the specific function is determined according to the adopted fitting method.
In the specific implementation process, based on continuously reading the target images at a plurality of moments in a preset time period, the refractive index n2 of the cell surface layer and the thickness d of the solution layer at the moments can be respectively measured. Wherein the preset time period is a time period when the cell surface passes above the probe point as shown in fig. 7. Then, the cell surface refractive index n2 and the solution layer thickness d obtained at these consecutive times within the preset time period are sequentially connected, so as to obtain the surface refractive index distribution curve of the cell to be detected and the topography information, i.e. the fluctuation distribution of the cell surface, as shown in fig. 7.
In an alternative embodiment, the obtained surface refractive index profile and morphology information of the cells to be detected can be further used for cell classification. Firstly, feature extraction can be carried out according to the surface refractive index distribution curve and the morphology information of the cells to be detected; and then inputting the extracted characteristic information into a cell analysis model trained in advance, and identifying the category of the cell to be detected. The cell analysis model may employ a machine learning model, for example, a support vector machine or a deep neural network, etc., for identifying the category to which the cell to be detected belongs.
Specifically, classification algorithms can be adopted step by step to study the classification capability:
1) extracting spatial features with different scales from a surface refractive index distribution curve and morphology information of the cell to be detected by using a wavelet analysis feature method, and then performing network training and classification research on the extracted features by combining a support vector machine method.
2) Adopting an end-to-end deep neural network algorithm: and extracting different spatial scale features from the surface refractive index distribution curve and the morphology information of the cell to be detected through a Feature Pyramid Network (FPN) and classifying the features.
3) An attention mechanism is introduced to weight spatial features, and the capability of finding specific detailed structures and high-level features in the cell membrane morphology by an algorithm is improved.
4) The recurrent EfficientDet algorithm is adopted, different spatial scale feature extraction of a depth network EfficientNet and bidirectional feature fusion of a bidirectional feature pyramid (BiFPN) are combined for classification, and the method is applied to feature extraction and classification research based on cell membrane morphology.
Further, the overall statistical parameters corresponding to physical concepts such as "cell membrane surface roughness" and "protein distribution" can be used based on statistical methods, including expectation and variance, and the results can be subjected to classification capability detection by statistical methods such as variance analysis and T test.
To sum up, the flow cytometry detection system provided in the embodiment of the present specification adopts the flow cytometry detection device provided in the first aspect, and drives the cells to be detected to pass through the target detection area in the compression channel one by one in a state of keeping contact with the metal film layer, on this basis, polarized light is provided to be incident into the target detection area to excite SPR at the metal film-medium interface, so that the SPR interacts with the cells to be detected passing through the compression channel one by one, reflected light detected by the photodetector is imaged, thereby obtaining the surface refractive index and morphology information of the cells to be detected, and realizing rapid detection of the surface refractive index of a single cell to be detected, thereby facilitating realization of high-throughput single cell detection.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
While preferred embodiments of the present specification have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all changes and modifications that fall within the scope of the specification.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present specification without departing from the spirit and scope of the specification. Thus, if such modifications and variations of the present specification fall within the scope of the claims of the present specification and their equivalents, the specification is intended to include such modifications and variations.
Claims (10)
1. A flow cytometric assay device, said device comprising:
the surface plasmon excitation chip is used for exciting surface plasmons under the irradiation of polarized light and comprises a transparent substrate and a metal film layer attached to the surface of the substrate;
the cell channel comprises an inflow channel, a compression channel and a recovery channel, the inflow channel, the compression channel and the recovery channel are sequentially communicated, the cell channel is bonded with one surface, attached with the metal film layer, of the chip to form a waterproof closed space, and the metal film layer is attached to a covering area of the compression channel;
when the device is in a working state, the cell to be detected carried by the solution flows in from the inflow channel, enters the compression channel, passes through the target detection area in a state of keeping contact with the metal film layer, and flows out from the recovery channel, wherein the refractive index of the solution is smaller than that of the substrate.
2. The apparatus of claim 1, further comprising:
and the driver is connected with the cell channel and is used for driving the cell to be detected to enter from the inflow channel and flow out from the recovery channel through the compression channel.
3. The device of claim 1, wherein the compression channel has a height and a width that are both less than or equal to the size of the test cell.
4. The device of claim 3, wherein the difference between the height of the compression channel and the size of the test cell is between 0 and 10 microns, and the difference between the width of the compression channel and the size of the test cell is between 0 and 10 microns.
5. A method of making a flow cytometry detection apparatus, said method comprising:
forming a cell channel matched with the transparent substrate, wherein the cell channel comprises an inflow channel, a compression channel and a recovery channel, and the inflow channel, the compression channel and the recovery channel are communicated in sequence;
preparing a metal film layer on the surface of the transparent substrate to form a surface plasmon excitation chip, wherein the chip is used for exciting surface plasmons under the irradiation of polarized light;
and bonding the cell channel with the surface of the surface plasmon excitation chip, on which the metal film layer is prepared, to form a flow cytometry detection device, wherein the metal film layer is attached to a covering region of the compression channel on the chip, and the compression channel is used for enabling cells to be detected to pass through a target detection region in a state of keeping contact with the metal film layer.
6. A flow cytometric assay system, comprising: an optical detection device and the flow cytometry detection apparatus of any one of claims 1-4,
the flow cytometry detection device is used for driving cells to be detected to pass through the target detection area one by one in a mode of keeping contact with the metal film layer on the surface plasmon excitation chip;
the optical detection apparatus includes: an illumination subsystem, an objective lens, an imaging subsystem, and a data processing device, wherein,
the illumination subsystem is used for collimating and polarization adjusting light emitted by the light source to generate polarized light to be incident to the objective lens;
the objective lens is used for enabling the polarized light to enter a target detection area on the flow cytometry detection device, exciting surface plasmons on the surface of a metal film layer of the target detection area to interact with passing cells to be detected, wherein the target detection area is located in the coverage area of the compression channel;
the imaging subsystem is used for imaging the reflected light formed by the polarized light on the detection device to a target surface of a photoelectric detector and acquiring a target image sequence formed by the reflected light at a target position through the photoelectric detector;
and the data processing device is used for obtaining the surface refractive index and the morphology information of the cell to be detected based on the target image sequence.
7. The system of claim 6, wherein the optical detection device further comprises: and the carrying subsystem comprises a clamp and a moving mechanism, the clamp is connected with the moving mechanism, the clamp is used for fixing the flow cytometry detection device, and the moving mechanism is used for carrying the flow cytometry detection device to move so as to adjust the position of the target detection area and focus the objective lens.
8. The system of claim 6, wherein the objective lens is configured to parallel-incident polarized light generated by the illumination subsystem to the target detection area, the target location is a back focal plane conjugate imaging plane of the objective lens, and the data processing device is configured to:
acquiring brightness distribution data of each target image in the target image sequence;
and determining the surface refractive index distribution and the profile information of the cell to be detected based on the brightness distribution data of each target image and a first preset corresponding relation, wherein the first preset corresponding relation is the corresponding relation between the brightness of the reflected light and the refractive index of the sample.
9. The system of claim 6, wherein the objective lens is configured to focus parallel polarized light generated by the illumination subsystem onto the target detection area, the target location being a Fourier plane of a conjugate imaging plane of a back focal plane of the objective lens;
the data processing apparatus is configured to:
aiming at each target image in the target image sequence, obtaining a target reflection light space frequency domain spectrum corresponding to the cell to be detected;
and determining the surface refractive index and the surface fluctuation distribution of the cell to be detected based on the target reflection light space frequency domain spectrum corresponding to each target image in the target image sequence and a second preset corresponding relationship, wherein the second preset corresponding relationship is the corresponding relationship between the reflection light space frequency domain spectrum obtained based on a transmission theory model and the refractive index of the sample and the target thickness.
10. The system of claim 6, wherein the data processing device is further configured to:
and obtaining an analysis result of the cell to be detected based on the surface refractive index of the cell to be detected and a pre-trained cell analysis model, wherein the cell analysis model is a machine learning model.
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