CN117654656A - Liquid drop generation method and device - Google Patents
Liquid drop generation method and device Download PDFInfo
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Abstract
The invention discloses a method and a device for generating liquid drops, wherein the method comprises the following steps: s1, preparing a sample; s2, chip sample adding; s3, starting a test, starting a droplet generation device, enabling droplets required by reaction to be generated in the microfluidic chip, and collecting and providing the droplets generated in the microfluidic chip to a control unit in real time through an image collection unit in the device; the control unit can analyze and calculate parameters about the sizes, the number, the proportions and the like of the liquid drops of different types according to the image acquisition information in the liquid drop generation process; s4, collecting reaction liquid and generating a quality control result in an experimental process; the invention can simultaneously control various droplet morphological parameters such as droplet size, droplet blank package, droplet single package, droplet multi-package, droplet total amount and the like. The droplets wrapping the different types of cells can be controlled in quality without affecting the experimental process or the reaction collection after the completion of the experiment. High identification accuracy and good stability. The quality control statistics may be real-time statistics.
Description
Technical Field
The invention relates to the technical field of microfluidic chips, in particular to a liquid drop generation method and a liquid drop generation device.
Background
In the fields of biochemistry and medical detection, the droplet microfluidic technology has the advantages of simple and convenient fluid operation, miniaturization, low cost, high sensitivity, high flux and the like, so that the droplet generation technology based on the microfluidic chip is widely applied in recent years.
The micro-fluidic chip is driven by external force to make cell suspension, reaction reagent, microbeads, separation oil and the like directionally flow in the corresponding micro-flow channel, so as to generate liquid drops. The generation of microdroplets is based on coupling effects due to surface tension and fluid shear forces between the different phases, requiring precise control of the parameters of the fluid of each phase. The physical and chemical properties of each phase of fluid, the surface roughness and surface treatment process of the fluid channel, the geometric structure design of the flow channel, the accurate control of driving pressure in the experimental process and the like can influence the quality of liquid drop generation, and further influence the quality of reaction collection products. In the traditional microfluidic experiments, the quality of droplet generation is generally judged by means of the manual experience of experimenters, so that time and labor are wasted, and quality result judgment is seriously dependent on the experience of operators and subjective judgment standards and has hysteresis. Therefore, there is a need to develop new droplet generation systems and quality control methods to solve the above-mentioned problems.
Prior art fig. 1, for example, is a microfluidic channel structure for generating droplets, which is common in microfluidic chips. Wherein fig. 1a is a cross-shaped microfluidic channel, fig. 1b is a T-shaped microfluidic channel, and fig. 1c is a concentric focusing microfluidic channel. In the figure, 1 is a continuous phase fluid, 2 is a discrete phase fluid, and 3 is a droplet formed in a microfluidic channel. The direction indicated by the arrows is the flow direction of the fluid of each phase. In scientific research and detection technology, micro-droplets serve as basic units for reaction, and provide carriers for biochemical actions of various reactants in a micro space. Typically, the droplets contain various reactants required for biochemical reactions. For example, in the digital PCR technique, the microdroplet contains the nucleic acid templates, primers, masterMix, etc. reactants necessary for performing the PCR reaction; in single-cell sequencing technology, the microdroplet contains the cell or nucleus, the reactant, the encoded microbead and other reactants required for the reaction. Since various reactants are randomly distributed into each micro-droplet during the droplet formation process, the basic principle of poisson distribution is followed, and thus, in the reaction collection obtained in the microfluidic chip, a plurality of different types of droplets are also contained according to different types of reactants contained in the droplets and components thereof. FIG. 2 is a schematic representation of different droplet types obtained in single cell sequencing experiments. In fig. 2, 10 is a schematic diagram of a microfluidic channel structure for single cell analysis, wherein 1, 2, and 3 are respectively continuous phase fluid, discrete phase fluid, and micro-droplets generated by reaction. The continuous phase fluid 1 comprises at least one continuous phase reactant 11 and the discrete phase fluid 2 comprises a plurality of discrete phases, namely a first reactant 21, a second reactant 22, a third reactant 23, for example in a single cell sequencing analysis, discrete phase reactants such as a sample to be tested, coded microspheres, reagents, etc. Since each reactant is randomly distributed into the interior of the droplet during the droplet generation process, the droplets generated by the reaction are of different types depending on the composition and the amount of the reactant liquid contained in each droplet. 31-36 in FIG. 2 are schematic representations of different droplet types containing different reactive species.
The quantity and proportion of various liquid drops are accurately counted and analyzed, the quality of the reaction collection can be evaluated and controlled, and accurate quality control information is provided for experimental operators. Because the formation and generation of droplets in a microfluidic chip are a fast-running dynamic process, in conventional experimental methods, the above information is usually obtained by sampling a reaction collection material, and performing microscopic analysis on a small portion of the sampled droplet sets under a microscope by an experimenter, thereby obtaining quality control results. The disadvantages are:
1) The method can not carry out real-time quality analysis on the generation of liquid drops in the experimental process, can only be carried out after the experiment is completed, has hysteresis in analysis results, and can only discard the reaction collector once the reaction collector does not accord with the quality standard;
2) Because the reaction collector is subjected to sampling microscopic examination, the detection result has a certain deviation from the actual situation, and often the liquid drop generation quality situation in the sampling detection cannot completely represent the actual situation in the reaction collector;
3) Sampling microscopy after the end of the reaction requires one or more extractions of a portion of the reaction collection, thus resulting in a reduction of the expected reaction collection, while too little sampling can have a significant impact on the accuracy of the results. This is particularly pronounced for some of the more scarce or precious starting reactants;
4) In order to ensure the accuracy of sampling quality detection in part of experiments, the reaction collecting objects in the reaction collecting cavity are subjected to multi-point sampling, and the original normal liquid drops in the reaction collecting cavity can be damaged in the process of sampling the reactants by using the liquid transfer device for multiple times, so that the experimental result is influenced;
5) The method for carrying out manual sampling microscopic examination after the experiment is finished adds additional manual operation, and increases the workload;
6) The traditional method based on manual sampling microscopic examination is completed by completely depending on experimental operators, and the detection result depends on the experience of manual interpretation and cannot ensure the uniformity of the interpretation result;
to solve the above problems, the present invention proposes a new droplet generation apparatus and method.
Disclosure of Invention
The invention aims to solve the technical problem of providing a simple and reliable liquid drop generation quality control system and method, and solves the problems that the existing liquid drop generation working medium is unstable to control and wastes time and labor.
The invention firstly provides a method for generating liquid drops, which comprises the step of generating liquid drops in a microfluidic chip and simultaneously controlling the quality,
in one embodiment according to the invention, the quality control is the acquisition and calculation of droplet parameters;
In one embodiment according to the invention, the droplet parameters include one or more of the size, number, ratio, etc. parameters of different types of droplet generation.
In one embodiment according to the invention, the method comprises the steps of:
s1, preparing a sample;
s2, chip sample adding;
s3, starting a test;
s4, collecting reaction liquid and generating a quality control result in an experimental process;
in one embodiment according to the invention, the sample preparation includes preparation of a cell suspension, preparation of reagents required for a reaction, preparation of a microfluidic chip for droplet generation, and the like;
in one embodiment according to the invention, the chip loading comprises adding a sample and various reagents required for the reaction into a microfluidic chip, and adding the microfluidic chip into a droplet generation device with image acquisition and recognition functions;
in one embodiment according to the invention, the starting test comprises starting a droplet generation device so that droplets required for a reaction are generated in the microfluidic chip, and collecting and providing a droplet generation process in the microfluidic chip to a control unit in real time through an image collection unit in the droplet generation device; the control unit can analyze and calculate parameters about the sizes, the number, the proportions and the like of the liquid drops of different types according to the image acquisition information in the liquid drop generation process;
In one embodiment according to the invention, the reaction liquid collection and experimental process quality control result generation comprises collecting the reaction liquid containing liquid drops from the reaction collection cavity of the microfluidic chip after the reaction is completed, and generating the overall experimental process quality control parameters for reference of experimental staff.
In one embodiment according to the invention, the droplet parameters include droplet size, droplet generation rate, droplet volume, number of droplets, number of different types of droplets distinguished by the inclusion of different reactants, and proportions thereof, etc., or statistical distribution of one or more of the foregoing parameters, and combinations thereof;
in one embodiment according to the invention, the presentation of the parameter-bearing data includes one or more of tables, arrays, text, charts, videos, or combinations thereof.
In one embodiment according to the invention, the control unit may accurately calculate the rate of real-time droplet generation from a sequence of characteristic droplets during droplet generation within a microfluidic chip.
In one embodiment according to the invention, the image acquisition information for the droplet production process may be used for quality control of the reaction collection or as a real-time feedback basis, the driving pressure of each reactant is regulated by the control unit, so as to optimize the experimental process and achieve the desired experimental result.
The present invention also provides a droplet generation device comprising: the system comprises a precision pressure controller, an image acquisition unit, an image recognition and processing unit and a processor.
In one embodiment according to the invention, the image acquisition unit focuses on an image acquisition area on the microfluidic chip and acquires and analyzes experimental phenomena in the area during the experiment;
in one embodiment according to the present invention, the image acquisition region is a flow channel for generating droplets on a microfluidic chip and a peripheral region thereof.
In one embodiment according to the invention, the device further comprises a switching device arranged at the collection end of the reactant;
in one embodiment of the present invention, the image recognition and processing unit analyzes the data obtained by the image acquisition unit to obtain the morphological data of the micro-droplets;
in one embodiment according to the present invention, the recognition algorithm adopted by the image recognition and processing unit is any one of machine learning target detection algorithms;
in one embodiment according to the present invention, the micro-droplet morphology identifiable by the image recognition and processing unit comprises at least micro-droplet size, droplet number, droplet volume, number of different droplet types and proportion thereof;
In one embodiment according to the present invention, the image recognition and processing unit may recognize three main stages of initial, stable, and final micro-droplet generation;
in one embodiment according to the present invention, the image recognition and processing unit may recognize the number of species of different reactants contained within a single microdroplet;
in one embodiment according to the present invention, the image recognition and processing unit may precisely adjust the driving pressure of the pressure controller to each phase reactant according to the calculation result of the image acquisition information.
In one embodiment according to the present invention, the camera frame rate of the image acquisition unit may be estimated and set before the experiment starts, and adjusted according to the real-time droplet generation rate calculated by the control unit after the experiment starts, and the droplet generation rate is matched, so that the image acquisition unit may complete capturing each newly generated droplet in the internal experimental process of the microfluidic chip; and the matching relation can be adjusted in real time by the control unit in the whole experimental process and always kept to be matched.
In one embodiment of the present invention, the control unit may reduce the acquisition frame rate of the camera according to a certain relationship, and reduce the memory space and the computing resources.
The invention finally provides a droplet generation method or application of a droplet generation device, the application comprising one or more of the following applications: a, generating liquid drops; b, detecting liquid drops; c, guiding the preparation of the microfluidic chip; d detection, optionally said detection being a medical detection for non-diagnostic purposes.
In order to facilitate the accurate identification of each reactant within the droplet by the image acquisition unit and the image processor, the reactants may be pre-processed. For example, the cells or nuclei involved in the reaction may be stained or pre-treated with chemical agents to increase their contrast under the camera view without affecting downstream reactions and mathematical analysis. For the reactant, one or more additives can be added according to the type of the light source of the image acquisition unit, so that the reactants such as cells, cell nuclei, microbeads and the like in the liquid drop have better identification effect.
The technical scheme of the invention has the following beneficial effects:
the invention relates to a droplet generation quality control system and a droplet generation quality control method, which can simultaneously control various droplet morphological parameters such as droplet size, droplet empty package, droplet single package, droplet multi-package, droplet total amount and the like.
(2) The droplets wrapping the different types of cells can be controlled in quality without affecting the experimental process or the reaction collection after the completion of the experiment.
(3) The data is classified mainly through an image AI recognition method, no processing is required for the liquid drops, and no physical damage is caused to the liquid drops.
(4) The identification accuracy is high and the stability is good.
(5) The quality control statistical data is completely and automatically generated without manual operation.
(6) The quality control statistical data can be real-time statistical data.
(7) The quality control statistical data are presented in an interactive mode such as a chart, a dynamic diagram and the like, and are simple and clear.
(8) The quality control data can be saved, archived and downloaded, and is convenient for subsequent research.
Drawings
FIG. 1 is a schematic diagram of a microfluidic channel structure for droplet generation commonly found in microfluidic chips; wherein fig. 1 (a) is a cross-shaped microfluidic channel, fig. 1 (b) is a T-shaped microfluidic channel, and fig. 1 (c) is a concentric focusing microfluidic channel. In the figure, 1 is a continuous phase fluid, 2 is a discrete phase fluid, and 3 is a droplet formed in a microfluidic channel. The direction indicated by the arrows is the flow direction of the fluid of each phase.
FIG. 2 is a schematic representation of different droplet types obtained in single cell sequencing experiments; 10 is a schematic diagram of a microfluidic channel structure for single cell analysis, wherein 1, 2 and 3 are respectively continuous phase fluid, discrete phase fluid and micro-droplets generated by reaction. The continuous phase fluid 1 comprises at least one continuous phase reactant 11 and the discrete phase fluid 2 comprises a plurality of discrete phases, i.e. the first reactant 21, the second reactant 22, the third reactant 23, 31-36 are schematic diagrams of different droplet types comprising different reactive species.
FIG. 3 is a schematic illustration of a droplet generator according to the present invention; drawing reference 20, generating means; 40. a microfluidic chip; 50. a control unit 50; 41. 42a and 42b are liquid adding cavities; 43. a reaction collection chamber; 45. an image acquisition unit; 44. an image acquisition region.
Fig. 4 (a) - (c) are schematic diagrams of different stages of droplet generation during the whole experiment of the image acquisition area within the microfluidic chip in one embodiment.
Fig. 5 is a photograph of a micro-droplet generation stabilization phase taken by a camera and its labeling schematic diagram in an embodiment of the invention.
Fig. 6 (a) to (e) are schematic diagrams showing dynamic descriptions of the droplet generation process in one droplet production cycle in the steady phase.
Fig. 7 (a) to (c) are schematic droplet sequences at the transition point from the unstable state to the stable state.
Fig. 8 (a) to (c) are schematic diagrams of determination of characteristic droplet sequences based on different reactants in a droplet.
Fig. 9 (a) to (c) are schematic diagrams of a characteristic droplet sequence when the capture frame rate of the camera is 1/2 of the droplet generation rate.
Fig. 10 shows a droplet generator with a switching device.
Fig. 11 is a report of quality control of droplet generation after completion of the experimental procedure.
Detailed Description
In order to make the technical problems, technical solutions and advantages to be solved more apparent, the following detailed description will be given with reference to the accompanying drawings and specific embodiments. Whatever the microfluidic channel structure, its basic principle is based on the physical phenomenon formed by interfacial tension between mobile phase and discrete phase liquid and shear force interactions generated during fluid flow. Therefore, the cross-shaped microfluidic channel is described herein and hereinafter as a main embodiment, and is intended to clearly express the technical features of the present invention and not to limit the scope of the present invention in any way.
Example 1 droplet generation apparatus
The device can generate micro liquid drops in a microfluidic chip, and integrates an image acquisition unit, an image recognition unit and a processor aiming at a liquid drop generation area on the chip, so that the device can analyze and count the liquid drop generation result in real time while generating the liquid drops, and automatically generate quality control output information after the experiment is completed for an experiment operator to read and refer.
Fig. 3 shows a droplet generator according to the present invention. A droplet generation device 20 includes a microfluidic chip 40 for preparing droplets, and a control unit 50 that controls the microfluidic chip to perform experiments. The microfluidic chip 40 is provided with a plurality of reaction liquid adding cavities 41, 42a and 42b, which are respectively used for adding reactants required for generating liquid drops before the experiment starts. And 43 is a reaction collection chamber of the microfluidic chip. 45 is an image acquisition unit including elements for image acquisition functions such as a camera, an optical element, a magnifying lens, a light source, and the like. The image acquisition unit may capture a section of microfluidic channels and its surrounding area on the microfluidic chip for generating micro-droplets, as shown by the image acquisition area in dashed box 44. The control unit 50 includes a pressure controller for driving the flow of liquid in each liquid filling chamber in the microfluidic chip, an image recognition processor and a system processor.
Fig. 4 is a schematic diagram of various stages of droplet generation throughout an experiment of the image acquisition region 44 within a microfluidic chip. Fig. 4 (a) is a schematic diagram of droplet generation in the microfluidic channel in the image acquisition region at the initial stage of the experiment, where no stable droplet sequence is formed in the microfluidic chip. Before the experiment starts, each reactant is added into the reactant liquid adding cavity by an experimenter, then the microfluidic chip is placed into the liquid drop generating device, the experimenter inputs an instruction and starts the device, and then the pressure controller is started to push each reactant to flow into the microfluidic channel from the liquid adding cavity. Because reactants do not exist in the microfluidic channel in the initial state, and the time sequence is arranged for each reactant to reach the liquid drop generation area, the steady experimental state can be reached after a certain time. This time is affected by factors such as the flow channel structure of the microfluidic chip, the physicochemical properties of the reactants, the surface treatment process of the microfluidic chip, the magnitude of the liquid driving pressure, etc., and is typically several seconds to several tens of seconds or more. Fig. 4 (b) is a schematic diagram showing droplet generation at steady state during the experimental process. At this point, a stable sequence of droplets is formed within the microfluidic channel and each reactant is entrapped within the resulting microdroplet. Fig. 4 (c) is the end of the reaction, where the droplets in the microfluidic channel begin to be unstable as each reactant in the feed chamber tends to be depleted, with depletion of one or all of the several reactants, and the experimental procedure ends. In some cases, to avoid unstable droplet sequences in the collected product that introduce the end of the reaction, the experimenter may terminate the experiment before reaching the end of the reaction, thereby providing a quality of the reaction collected product. In some cases, such as where the number of reaction collectors is itself relatively small, or where the samples used in the experiment are rare or precious, the experimenter may allow the reaction to proceed as fully as possible to obtain more reaction collectors.
Example 2 automatic identification of droplet generation device
The liquid drop generating device and the liquid drop generating method can automatically identify the initial stage, the stable stage and the final stage in the liquid drop generating process, and detect and calculate the total liquid drop quantity, the quantity of each reactant in the liquid drop and the statistical proportion of the reactant in the liquid drop in the stable liquid drop generating stage in the experimental process.
Fig. 5 is a photograph of the steady-state generation of micro-droplets within the image acquisition area 44 taken by the camera during the course of the experiment. The above information is passed through an image recognition processor of the control unit 50 to form a real-time recognition labeling chart, where the image recognition processor includes a micro-droplet morphology data model and a real-time recognition labeling algorithm, where the micro-droplet morphology model is obtained by training a pre-collected micro-droplet morphology image information set through a deep learning algorithm, and the real-time recognition labeling algorithm is an algorithm for calculating the micro-droplet morphology by combining the real-time image information with the micro-droplet morphology model. The real-time label of FIG. 5 includes the number of one reactant and its confidence.
In microfluidic chips, the process of generating micro-droplets is a periodic physical process, the basic principle of which is based on interfacial tension between mobile phase and discrete phase liquids and shear force interactions generated during fluid flow. Fig. 6 (a) to (e) are schematic diagrams showing dynamic descriptions of the droplet generation process in one droplet production cycle in the image pickup region 44 at the steady-state. Since the droplet generation process is a continuously variable process, each droplet generation node described in (a) to (e) in fig. 6 selects only a few representative droplet generation dynamic feature nodes for illustration purposes. According to different factors such as reactant components, structural parameters of microfluidic channels, driving pressure of each phase, target droplet size and the like, the period of droplet generation in the experimental process is also different. Taking a cross microfluidic channel as an example, in a typical experimental procedure, the period for completing one droplet generation is typically on the order of sub-milliseconds, tens or hundreds of milliseconds, or even seconds.
The image acquisition unit 45 selects a camera to detect the generation condition of the liquid drops in the image acquisition area 44 in the microfluidic chip and calculate and analyze the related information. Because the camera shoots based on a certain frame rate setting in the image capturing process, if the frame rate setting of the camera is consistent with the frequency of droplet generation, namely, the time between two adjacent frames of the camera in the shooting process is consistent with the time for completing one droplet generation period, each frame of the camera can just capture one newly generated droplet in sequence, so that the accurate and effective detection result in the droplet generation process is ensured.
For example, assuming that the frequency of droplet generation is 200 droplets per second, i.e., one new droplet is generated every 5 milliseconds in the microfluidic channel, and the frame rate of the camera is set to 800 frames, i.e., 800 shots per second, the first four frames of pictures of the camera capture information sequentially as shown in (a) to (d) in fig. 6 (assuming that (a) to (d) in fig. 6 correspond to 0, 1/4, 1/2, 3/4 cycles, respectively, of one droplet generation). The information captured by the 5 th frame of the camera is shown in fig. 6 (e), where 301-305 are the sequence of droplets that have been generated prior to the current droplet generation period, and 310 are the droplets that have been newly generated during the current droplet generation period. Therefore, when the stable phase of drip generation starts, a new drip is just generated at the position of the cross-shaped channel port in the picture corresponding to every 4n+1 frames (n is an integer greater than or equal to 1) of the camera. If the frame rate of the camera is set to 200 frames in the above case, the shooting frame rate of the camera is consistent with the frequency of droplet generation, and the next frame shot after each acquisition can just correspond to one newly generated droplet 310. In the latter case, it can be seen that not only the generation of each new droplet can be completely captured, but also the computing resources and the storage space of the image processing unit are saved. In addition, when the same industrial camera is used for setting different frame rates, the common situation is that the high frame rate corresponds to relatively poor imaging resolution, and the selection of the frame rate of the camera consistent with the liquid drop production frequency can improve the imaging quality while completely capturing the liquid drop production situation, so that the reactant in the liquid drop can be analyzed more accurately, and the quantity of the reactant is sufficient.
If the camera frame rate is not set to an integer multiple of the droplet production frequency, for example, it is assumed that the droplet production frequency is 200 droplets per second, and the camera frame rate is set to 330 frames, i.e., a new droplet is produced every 5 milliseconds in the microfluidic channel, and the time interval between each camera shot is about 3.03 milliseconds. At this time, if the camera is used to record the experimental process, the number of qualified droplets actually generated cannot be truly and accurately calculated. Assuming that the drop generation situation captured by the n-th frame of the camera is as shown in fig. 6 (a), the drop generation situation captured by the n+1-th frame is close to the situation shown in fig. 6 (c), no new drop is generated at this time, and at this time, the number of generated drops observable in the camera window is reduced because the discrete phase liquid at the cross-shaped channel position is elongated (new drops have not been cut off). In this case, the final counted number of qualified droplets deviates from the number of droplets actually produced in the experiment to some extent.
In some applications, this will not occur if the time between two adjacent frames of the camera is much less than the period for which one droplet generation is completed, for example, taking a picture with a specific high speed camera. However, the price of the high-speed camera is far higher than that of the common industrial camera, and more advanced hardware equipment is needed to support and analyze and calculate the shot information, and the volume and the weight of the high-speed camera are far higher than those of the common industrial camera, so that the cost and the complexity of the system are greatly improved.
Example 3 correction of acquisition frame Rate of Camera
1) In the sample adding stage before the experiment starts, the sample adding amount of each reactant is estimated, the total volume of the liquid drops required to be collected in the experiment process is calculated according to the expected reaction volume of the discrete phase reactant, and then the speed of the liquid drops in the experiment process is estimated according to the expected liquid drop size and the reaction time in the experiment process. For example, in one experiment, the total amount of droplets to be collected was 150. Mu.L, the diameter of the microdroplet produced in the reaction was 90. Mu.m, and the reaction was continued for 15 minutes, so that it was possible to calculate the theoretical total amount of microdroplets produced by the reaction of about 3937000, and the average amount of microdroplets produced per second was about 438.
2) If the settable frame rate of the camera is not less than the droplet generation frequency while ensuring satisfactory image capturing range and sharpness within the image capturing area 44, the camera frame rate is set to n times (n is an integer equal to or greater than 1) the calculated droplet generation frequency; if the settable frame rate of the camera is less than the frequency of droplet generation, the frame rate setting of the camera is set such that the droplet generation frequency is n times the camera frame rate (n is an integer greater than 1). For example, taking the above experimental estimation as an example, if the settable maximum frame rate of the camera in the above case is 1000, the frame rate of the camera is set to 438 or 876, and if the settable maximum frame rate of the camera is 300, the frame rate of the camera may be set to 219, that is, the droplet generation frequency at this time is 2 times the frame rate setting of the camera.
3) And starting an experiment, wherein reactants in each phase in the microfluidic chip are pushed into the microfluidic channel under the action of the pressure controller, and enter a stable droplet generation stage after an initial stage of the experiment. The image acquisition unit 45 and the control unit 50 acquire and analyze the droplet generation process in the microfluidic chip in real time after the experiment starts, and the real droplet generation speed is calculated according to the characteristic droplet sequence and the preliminarily set camera frame number;
4) According to the actual droplet generation speed obtained by the calculation and analysis, the frame rate setting of the camera is adjusted, and at the same time, the control unit 50 can also finely adjust the driving pressure of each phase of reactant through the pressure controller, so that the droplet generation speed is completely matched with the frame rate of the camera under the condition that the experimental result meets the requirement, that is, the droplet generation frequency is n times, 1 times or 1/n (n is an integer greater than 1) of the frame rate setting of the camera. For example, according to the above analysis, the control unit calculates that the real droplet generation rate in the microfluidic chip is 411 per second at this time, and the frame rate setting of the camera can be adjusted to 411 by the controller at this time, so as to completely coincide with the droplet generation rate; alternatively, if the initial camera settable frame rate is 300, the camera frame rate setting may be adjusted to 205 while the pressure controller fine-tunes the reactant drive pressure for each phase so that the rate of droplet generation is adjusted to 410, i.e., the camera frame rate is just 1/2 of the droplet generation rate.
5) The setting of the camera frame rate and the adjustment of the droplet generation rate in the experimental process can be dynamically completed by the control unit 50 according to the real-time droplet generation condition, so that the setting of the camera frame rate always maintains a certain relation with the real-time droplet generation rate in the whole experimental process;
6) When the generation of the liquid drops reaches a stable state, the control unit can reduce the real-time acquisition frame rate of the camera, so that the purposes of saving the memory and the computing resources of the controller are achieved;
in the stable phase of droplet generation, the frequency of the size of the generated droplets in the microfluidic channel is stable and unchanged, so that the image information captured by two adjacent frames of the image acquisition unit 45 almost overlap, and therefore, the control unit needs to judge different positions of the droplets at the front and rear moments according to the characteristic droplet sequence, so that the real-time droplet generation rate is accurately calculated. The characteristic droplet sequence is a sequence formed by one or more droplets, and can provide judgment basis for the control unit to calculate the generation rate of the real-time droplets. All sequences of droplet compositions having the above characteristics can be regarded as characteristic droplet sequences.
The characteristic droplet sequence is a droplet sequence at the transition time from the unstable state to the stable state, as shown in fig. 7. In fig. 7, (a) to (c) are n, n+1, and n+2 frames of images captured by the image capturing unit, where 401 is a droplet generated in an unstable stage, a stable droplet sequence is not formed in the image captured by the n frame, and stable droplet 310 starts to be formed in the microfluidic chip from the n+1 frame, and at this time, the unstable droplet 401 and the droplet 310 may be combined as a characteristic droplet sequence. The control unit can test the characteristic liquid drop sequence from the n+2 frame, if each frame has new liquid drop generation which can be stable from the n+2 frame, the characteristic liquid drop sequence is established, and the liquid drop generation rate can be accurately calculated according to the time relation between different positions of the characteristic liquid drop sequence in the microfluidic channel and the frame rate. On the other hand, if no new droplet is generated after the n+3 frame, the above-mentioned characteristic droplet sequence is not established, and the control unit needs to re-determine the characteristic droplet sequence.
If the set capturing frame rate of the camera is n times of the estimated droplet generation rate, one or more droplets closest to the droplet generation area, i.e. at the cross-shaped microfluidic channel structure, in the microfluidic chip can be used as the characteristic droplet sequence. For example, if the capturing frame rate of the camera is set to 2 times the experimentally estimated droplet generation rate, the image information captured in the n+1th frame is shown in fig. 6 (c) if the image information captured in the n-th frame is shown in fig. 6 (a). At this time, since the time interval between two adjacent frames of the camera is smaller than the period of one droplet generation, there is no newly generated droplet in the n+1th frame image, and then the generated droplets 301, 302, etc. in fig. 6 can be used as the characteristic droplet sequence, and the droplet generation rate at this time can be accurately calculated from the interval time of the two frames and the droplet positions at different times.
The number and type of different reactants contained within a droplet can be used to determine a characteristic droplet sequence. For example, in a single-cell histology experiment, droplets typically contain different reactive species, such as cells, nuclei, encoded microspheres, etc., and if one droplet type is labeled with an array (0, 1), the droplet contains zero first reactive species and one second reactive species within the droplet. Assume that the frame rate of the camera is set to be the same as the experimentally estimated droplet generation rate. As shown in fig. 8, fig. 8 (a) to (c) are n, n+1, n+2 frame images captured by the image capturing unit, respectively. Then in fig. 8a there are three consecutive drops 501, 502, 503 of drop type { (1, 1), (0, 2), (0, 1) }, where 511 and 512 are new drops generated by the n+1st and n+2nd frames, respectively. Since the kinds and the amounts of different reactive substances contained inside the droplets are based on random distribution, in the image information captured by the adjacent frames, the probability that the types of the consecutive several droplets are completely identical and reappear is almost zero, i.e., three consecutive droplets reappear in the consecutive several frames of images thereafter from the nth frame of image, and the probability that the types thereof are { (1, 1), (0, 2), (0, 1) } is almost zero. Thus, a droplet sequence consisting of three consecutive droplets 501, 502, 503 at this time can be used as a characteristic droplet sequence to calculate the real-time droplet generation rate.
The calculation process is completed by the image processor and the controller of the control unit, so that the current liquid drop generation rate can be calculated in real time according to the characteristic liquid drop sequence, and the capturing frame rate and the liquid drop generation rate of the camera are adjusted to be completely matched. After the calculation is completed, the control unit can verify the calculation result according to the image information acquired at the next moment. If the calculation result is accurate and effective, the new droplet position obtained in each next droplet generation cycle should completely coincide with the new droplet position produced in the previous cycle, so that the accuracy of the control unit for the above adjustment result can be verified.
The above method of determining the characteristic drop sequence is equally applicable to situations where the camera capture frame rate is less than the drop generation rate. For example, the capturing frame rate of the camera is 1/2 of the generation rate of the droplet, and the above-described method of calculating the generation rate of the droplet from the characteristic droplet sequence is still effective. The difference is that at this time, 2 newly generated droplets appear in the image information acquired in the n+1th frame compared with the image information acquired in the n-th frame. Fig. 9 (a) to (c) are n, n+1, n+2 frame images captured by the image capturing unit, respectively. Since the droplet generation rate is 2 times the camera capturing frame rate at this time, 2 new droplets 511 and 512 appear in the image acquired in the n+1 frame compared to the n frame, and 2 new droplets 513 and 514 appear in the image acquired in the n+2 frame compared to the n+1 frame, so that the droplet position shift at this time is also larger when the droplet generation rate is calculated, and as a result, the accuracy of the droplet generation rate calculation is not affected.
It should be noted that, due to the limited capture area of the camera, when the droplet generation image collection is performed at a low frame rate (as in the above example, the camera is set to 1/2 of the droplet generation rate), the capture range of the camera, that is, the size parameter of the image collection area 44 shown in fig. 9, needs to be considered. Otherwise, if the camera frame rate is set too low, the information collected in the nth frame containing the sequence of characteristic droplets may be partially or completely lost in the image collected in the n+1 frame, resulting in inaccurate calculation. In addition, the method for acquiring and identifying the image with low frame rate can obtain the liquid drop rate calculation result with the same precision, and occupies less memory space and operation resources. Therefore, if the frame rate of the camera in the initial stage is set to be higher, for example, n times of the droplet generation rate, correction calculation and adjustment of the real-time droplet velocity are performed, after the frame rate of the camera after the adjustment is completed and the droplet generation rate are matched, the frame rate of the camera can be reduced to 1/n of the real-time droplet generation rate, so that more storage space and calculation resources can be saved while the concentration of the calculation result is ensured.
The selective switching device is added at the downstream of the microfluidic chip, so that the system can selectively discard the unqualified liquid drop sequence according to the information captured by the image acquisition unit, and the proportion of the qualified liquid drops in the reaction collection can be further improved. As shown in fig. 10, 60 is a droplet generator with a switching device. Reference numeral 61 denotes a reaction product collecting pipe, which may be connected downstream to a reactant collecting vessel 63 or a waste liquid collecting vessel 64, and is switched by a switching device 62. The control unit may control the switching device 62 based on the information collected from the image to determine the reaction product collection or discarding. For example, the control unit may discard the unstable droplet sequence to the waste collection vessel 64 during the initial phase of the reaction, and switch the collection vessel 61 to the reactant collection vessel 63 after droplet formation has entered the stable phase. In this way, the effective droplet ratio within the reactant collection vessel can be increased.
After the experimental process is finished, the control unit can summarize the results according to the results obtained by analysis and calculation in the experimental process and generate an experimental result quality control report, and the experimental result is interpreted by an experimental operator. The experimental quality control report includes, but is not limited to, the total amount of droplets generated during the experiment, the total amount of effective droplets, the total amount of various droplet types containing different reactive substances, and the ratio of various droplet types and the statistical result of the ratio of the effective reactive substances. FIG. 11 is an example of an experimental process quality control report generated after completion of the experimental process. Wherein the first reactant is a cell or a cell nucleus and the second reactant is a coded microbead, and a droplet containing one cell/cell nucleus and one coded microbead is considered to be an effective droplet, i.e., a droplet of type (1, 1), according to the expected outcome of the experiment. A single reactant droplet is a droplet containing only one cell/nucleus or a droplet containing only one encoded microbead or empty droplet, i.e., a droplet of type (0, 0), (0, 1), (1, 0). The droplets produced during other experiments were multi-reactant droplets, i.e., droplets containing two different reactants and having a number greater than one.
The liquid drop generation method can capture the image information generated by each liquid drop in real time and analyze and calculate the result in real time, and in the traditional experiment method, the liquid drop generation quality can only be checked by laboratory staff after the experiment is completed, and the hysteresis is provided. Therefore, the liquid drop generating device and the liquid drop generating method not only can carry out quality control analysis on liquid drop generation in the experimental process, but also can be used for feedback control on the experimental process, so that the quality of the collected materials obtained by the experiment is optimized. For example, the experimentally expected reaction collection needs to ensure that the number of (1, 1) and (2, 1) type droplets and their duty cycle are within a range of expected intervals. When the experiment is carried out for a period of time, the generation process of the liquid drops reaches a stable stage, the frame rate setting of the camera is matched with the generation rate of the liquid drops after calculation and debugging by the processor, at the moment, the control unit can analyze different types and proportions of the liquid drops which are generated at present according to real-time experiment data, if the liquid drops of (0, 1), (0, 0), (0, 2) and the like generated in the experiment process are too many, but the liquid drops of (1, 1) and (2, 1) do not reach the expected ratio of the experiment, the control unit can finely adjust the driving pressure of each phase of the corresponding substances, change the output flow (the reactants added before the experiment is supposed to be sufficient), namely, properly increase the driving pressure of the first reactant of the discrete phase, so that the volume flow of the first reactant output in unit time is increased. In this way, during the droplet generation process, the probability of the first reactant being contained in the droplet is correspondingly increased, so that the reaction process is optimally increased towards the direction expected by the experiment. Otherwise, if the control unit in the beginning stage calculates that the number of the liquid drops containing the first reactant is too large according to the image acquisition information, the control unit can properly reduce the driving pressure of the first reactant by adjusting experimental parameters so as to meet experimental expectations. After the control unit adjusts the driving pressure of each phase, the droplet generation rate can also change slightly, the real-time droplet generation rate is recalculated by utilizing the characteristic droplet sequence and matched with the corresponding camera capturing frame rate, and new experiment output parameters can be formed by calculation of the control unit so as to ensure the accuracy of experiment results.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.
Claims (10)
1. A method for generating liquid drops is characterized by comprising the step of generating liquid drops inside a microfluidic chip and simultaneously performing quality control,
optionally, the quality control is to collect and calculate droplet parameters;
optionally, the drop parameters include one or more of size, number, ratio parameters of different types of drop generation.
2. The method of droplet generation of claim 1, comprising the steps of:
s1, preparing a sample;
s2, chip sample adding;
s3, starting a test;
s4, collecting reaction liquid and generating a quality control result in an experimental process;
optionally, the sample preparation includes preparing a cell suspension, preparing reagents required for a reaction, and preparing a microfluidic chip for droplet generation;
optionally, the chip sample adding comprises adding a sample and various reagents required by the reaction into a microfluidic chip, and adding the microfluidic chip into a liquid drop generating device with image acquisition and recognition functions; optionally, the starting test comprises starting a droplet generation device, so that droplets required by the reaction are generated in the microfluidic chip, and collecting and providing the droplet generation process in the microfluidic chip to a control unit in real time through an image collection unit in the droplet generation device; the control unit can analyze and calculate parameters related to the sizes, the number and the proportions of the liquid drops of different types according to the image acquisition information in the liquid drop generation process; optionally, the control unit reduces the acquisition frame rate of the camera according to the parameter relation, and reduces the memory space and the calculation resources;
Optionally, the reaction liquid collection and experimental process quality control result generation comprises collecting the reaction liquid containing liquid drops from the reaction collection cavity of the microfluidic chip after the reaction is completed, and generating the overall experimental process quality control parameters for reference of experimental staff.
3. The method of claim 1 or 2, wherein the droplet parameters include droplet size, droplet generation rate, droplet volume, number of droplets, number of different types of droplets and their proportions, distinguished by the inclusion of different reactants, or statistical distribution of one or more of the foregoing parameters and combinations thereof;
optionally, the presentation of the parameter-bearing data includes one or more of a table, an array, text, a chart, video, or a combination thereof.
4. The method of droplet generation according to claim 2, wherein the control unit can precisely calculate the rate of real-time droplet generation from a sequence of characteristic droplets during droplet generation within a microfluidic chip.
5. A method of droplet generation according to claim 2, wherein the image acquisition information during droplet generation can be used for quality control of the reaction collection or as a real-time feedback basis, the driving pressure of each reactant is regulated by the control unit to optimize the experimental process and bring it to the desired experimental result.
6. A droplet generation device comprising a microfluidic chip having a reaction collection chamber; characterized by further comprising: the device comprises a precision pressure controller, an image acquisition unit, an image recognition and processing unit and a processor; optionally, the image acquisition unit focuses on an image acquisition area on the microfluidic chip and acquires and analyzes experimental phenomena in the area in the experimental process;
optionally, the image acquisition area is a flow channel for generating liquid drops on the microfluidic chip and a peripheral area thereof.
7. The liquid droplet generator of claim 6, further comprising a switching device disposed at the reaction collection chamber end.
8. The liquid drop generating device according to claim 6, wherein the image recognition and processing unit is configured to analyze the data obtained by the image acquisition unit to obtain morphological data of the micro liquid drops; optionally, the recognition algorithm adopted by the image recognition and processing unit is any one of machine learning target detection algorithms;
optionally, the micro-droplet morphology identifiable by the image recognition and processing unit comprises at least micro-droplet size, droplet number, droplet volume, number of different droplet types, and proportion thereof;
Optionally, the image recognition and processing unit may recognize three main stages of initial, stable, and final micro-droplet generation;
optionally, the image recognition and processing unit may recognize the number of species of different reactants contained within a single microdroplet;
optionally, the image recognition and processing unit can accurately adjust the driving pressure of the pressure controller on each phase of reactant according to the calculation result of the image acquisition information.
9. The droplet generation method or droplet generation apparatus according to claim 2 or 6, wherein the camera frame rate of the image acquisition unit is estimated and set before the start of the experiment, and is adjusted according to the real-time droplet generation rate calculated by the control unit after the start of the experiment, and the droplet generation rate is matched so that the image acquisition unit can complete capturing each newly generated droplet in the internal experimental process of the microfluidic chip; and the matching relation can be adjusted in real time by the control unit in the whole experimental process and always kept to be matched.
10. Use of a droplet generation method according to any one of claims 1-5 or a droplet generation device according to any one of claims 6-9, wherein the use comprises one or more of the following: a, generating liquid drops; b, detecting liquid drops; c, guiding the preparation of the microfluidic chip; d detection, optionally said detection being a medical detection for non-diagnostic purposes.
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