Microfluidic biomimetic method and system for evaluating the ability of microorganisms to penetrate mucus-containing barriers

Abstract

The application discloses a kind of microfluidic biomimetic method and system for evaluating the ability of microorganism to penetrate mucus-containing barrier, belongs to the technical field of microfluidic biomimetic evaluation. In view of the problem that the dynamic penetration process of microorganism on the surface of mucus-containing barrier is difficult to be quantitatively evaluated by the prior art, the method of the application constructs a microfluidic biomimetic environment including an external aqueous phase region, a surface mucus simulation region and a deep mucus simulation region; obtain the motion process data of the microorganism to be evaluated in the environment; establish a penetration behavior evaluation model including a flow field module, an equivalent shear module, a trapping release module and an interface crossing module, and calibrate the model parameters using the data; finally output the quantitative evaluation results such as penetration rate, trapping rate and target area arrival rate. The system of the application includes a microfluidic chip, a data acquisition module and a data processing module for implementing the above method. The application can quantitatively evaluate the ability of different microorganisms to penetrate the mucus barrier in a standardized, high-throughput and process-based manner.

Description

Technical Field

[0001] This invention belongs to the field of microfluidic biomimetic evaluation, biological motion modeling and microbial behavior analysis technology, specifically relating to a microfluidic biomimetic method and system for evaluating the ability of microorganisms to penetrate mucus-containing barriers. Background Technology

[0002] Mucus-barrier biological surfaces are widely found on the surfaces of aquatic animals, mucosal tissues, and other biological interfaces with stratified mucus coverage. These biological surfaces typically possess characteristics such as external fluid transport, surface mucus retention, and deep mucus retardation. The migration, residence, and traversal processes of the microorganisms being evaluated within these surfaces are influenced by multiple factors, including flow velocity, shear, mucus density, mucus rheological properties, and the microorganisms' own movement behavior.

[0003] Existing studies primarily employ endpoint detection, co-incubation with ex vivo mucus or tissue, and microscopic or microfluidic observation under simplified conditions to analyze the adhesion, survival, retention, or local entry of microorganisms into mucus. While these methods can obtain some qualitative or quantitative endpoint information, they remain limited in their ability to coupled characterize external aqueous transport, stratified mucus blockage, interfacial shear trapping, and continuous traversal processes, making it difficult to simultaneously acquire process data, conduct quantitative evaluation, and calibrate models.

[0004] Existing evaluation methods, which mainly rely on microscopic observation, in vitro co-incubation, or endpoint detection, typically depend on long experimental cycles, numerous manual observations, and post-processing analysis steps. When there are many evaluation subjects, many combinations of experimental conditions, or when repeated comparisons are required, they often suffer from insufficient throughput, low efficiency, and inconvenience in cross-sectional comparison of results, making it difficult to achieve rapid, convenient, and batch evaluation of the penetration behavior of different microorganisms or under different conditions.

[0005] Furthermore, if only an abstract mathematical model is established without combining it with specific microfluidic chip configurations, motion process data acquisition methods, and parameter calibration processes, it is difficult to form a penetration evaluation scheme that can be directly implemented by those skilled in the art. Therefore, it is necessary to provide a microfluidic biomimetic method and system that can simulate the external fluid environment and stratified mucus environment of a biological surface containing a mucus barrier under in vitro conditions, and perform process-oriented and quantitative evaluation of the penetration behavior of the microorganisms to be evaluated. Summary of the Invention

[0006] The purpose of this invention is to provide a microfluidic biomimetic method and system for evaluating the ability of microorganisms to penetrate mucus barriers, so as to solve the problem in the prior art that it is difficult to simultaneously characterize external aqueous phase transport, stratified mucus blockage, interface residence and crossing processes, and difficult to form a unified evaluation result.

[0007] To address the aforementioned technical problems, this invention provides a microfluidic biomimetic method for evaluating the ability of microorganisms to penetrate mucus-containing barriers, comprising the following steps: Step 1: Construct a microfluidic biomimetic environment, which includes an external aqueous phase region, a surface mucus simulation region, and a deep mucus simulation region arranged sequentially along the predetermined penetration direction of microorganisms; Step 2: Introduce the microorganism to be evaluated into the microfluidic biomimetic environment and obtain its motion process data in it. The motion process data includes at least position, velocity, interface dwell events and interface crossing events. Step 3: Establish an evaluation model for the penetration behavior of the microorganism to be evaluated. The model includes at least a flow field module, an equivalent shearing module, a trapping and release module, and an interface crossing module. The model parameters are calibrated using the motion process data. The flow field module is used to construct a partitioned advection velocity field in the microfluidic biomimetic environment. The equivalent shear module is used to calculate the local equivalent shear strength based on the velocity field. The trapping and release module is used to determine the probability that the microorganism to be evaluated is trapped in the current region based on the equivalent shear strength. The interface crossing module is used to determine the probability that the microorganism to be evaluated will cross from the current area to the adjacent area based on the equivalent shear strength and the preset continuous straight running time threshold. Step 4: Based on the calibrated penetration behavior evaluation model, output the penetration evaluation results of the microorganism to be evaluated. The penetration evaluation results include at least the penetration rate, the trapping rate, and the target area reach rate.

[0008] The core of this invention lies in the deep coupling of a specific partitioned microfluidic structure with a data-driven penetration behavior evaluation model. The model includes the following functional modules: Flow field module: Used to construct partitioned advection velocity fields within the "external aqueous phase region - surface mucus region - deep mucus region" of the microfluidic chip. Advection velocity along the microbial penetration direction (x-axis). The smooth transition of flow velocities between regions and the wall shear effect are characterized by the following formula: , in, and These represent the characteristic flow velocities in the external aqueous phase region and the mucus simulation region, respectively. For the location of the regional interface, For the transition width, Let σ(z) = 1 / (1 + e^(-z)) be the wall shear coefficient, and let σ(z) = 1 / (1 + e^(-z)) be the Sigmoid function.

[0009] Equivalent shear module: Based on the above velocity field, define the local equivalent shear strength. As a proxy for quantifying the mechanical effects of local fluids on microorganisms: .

[0010] Trapped and Release Module: This module simulates the stochastic process of microorganisms being trapped and released in a slime layer. Microorganisms in the region... The base probability of being trapped is Actual probability of being trapped With equivalent shear strength It exhibits a single-peak variation:

[0011] in, For the region The base probability of being trapped. The critical shear strength. This is the gain coefficient. The trapped microorganisms will be released randomly at a specific rate.

[0012] Interface Traversal Module: This module employs dual gating rules. First, microorganisms must meet the condition that their "continuous straight-running time" exceeds a preset threshold; second, the traversal probability... Subjected to local shear resistance and external stimuli (such as light) Enhanced joint regulation:

[0013] in, Based on the probability of crossing, This is the shear resistance coefficient. For the stimulus enhancement coefficient, Regarding stimulus intensity The Hill function.

[0014] The above modules together constitute a penetration behavior evaluation model that can be calibrated by motion process data.

[0015] Preferably, the penetration evaluation results in step 4 also include indicators such as directionality and interface event throughput. Among these, directionality... Target area reach rate and penetration rate They can be calculated using the following expressions respectively: .

[0016] in, The total number of microorganisms, For the first The direction of movement of each individual, For the target direction, For indicator functions, Location of the target area For export location, For evaluation duration.

[0017] Preferably, the microfluidic biomimetic method further includes a model parameter calibration step, which uses the motion process data to invert or fit at least a portion of the velocity parameters, tumble rate parameters, trapping parameters, interface crossing parameters, and mucus rheological parameters. Step 3 may also introduce external stimulus input to modulate the tumble rate, motion speed, or equivalent internal state of the microorganism to be evaluated; the external stimulus input includes at least one of light stimulation, chemical stimulation, or mechanical stimulation, and can be applied in at least one form of continuous stimulation, pulsed stimulation, gradient stimulation, or closed-loop gated stimulation.

[0018] This invention also provides a system for implementing the above-described microfluidic biomimetic method, comprising a microfluidic chip, a data acquisition module, and a data processing module. The microfluidic chip is used to construct an external aqueous phase region, a surface mucus simulation region, and a deep mucus simulation region sequentially arranged along the penetration direction; the data acquisition module is used to acquire motion data of the microorganism to be evaluated within the microfluidic chip; the data processing module is used to establish or calibrate an evaluation model of the penetration behavior of the microorganism to be evaluated and output the penetration evaluation results of the microorganism to be evaluated. Preferably, the data acquisition module includes an imaging acquisition module and a trajectory analysis module. The imaging acquisition module is used to acquire time-series images of the microorganism to be evaluated within the microfluidic chip, and the trajectory analysis module is used to extract one or more data from the time-series images, including the trajectory, velocity, movement orientation, interface dwell events, and interface crossing events of the microorganism to be evaluated. Preferably, the system further includes a control module, which is used to provide at least one of light stimulation, chemical stimulation, or mechanical stimulation to the microfluidic chip.

[0019] Preferably, the surface mucus simulation zone and the deep mucus simulation zone are filled with a mucus mimicry containing at least one of mucin, hyaluronic acid, methylcellulose, collagen, and agarose.

[0020] Compared with existing technologies, this invention has at least the following advantages: First, by constructing a microfluidic biomimetic environment composed of an external aqueous phase region, a surface mucus simulation region, and a deep mucus simulation region, it can more realistically characterize the layered blockage and transport characteristics of biological surfaces containing mucus barriers; second, by acquiring motion process data and combining it with a penetration behavior evaluation model, it can simultaneously characterize different penetration states of the microorganisms under evaluation, such as interfacial residence, interfacial crossing, and deep region arrival; third, this invention does not rely on a single mathematical expression, but achieves a unified evaluation of the residence, crossing, and deep region arrival behaviors of the microorganisms under evaluation through a combination of partitioned flow field characterization, equivalent shear characterization, trapping and release rules, interfacial crossing rules, motion process data-driven parameter calibration, and evaluation index calculation, thereby improving the interpretability and comparability of the evaluation results; fourth, this invention can be used not only in scenarios related to mucus barriers on fish surfaces, but also for the evaluation of penetration of other biological surfaces containing mucus barriers. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the partitioning of the microfluidic chip described in this invention.

[0022] Figure 2 This is a flowchart of the evaluation process for the penetration behavior of the microorganism to be evaluated as described in this invention.

[0023] Figure 3 This is a flowchart illustrating the data acquisition, model calibration, and evaluation output process described in this invention.

[0024] In the attached diagram: 1-External aqueous phase zone, 2-Surface mucus simulation zone, 3-Deep mucus simulation zone Detailed Implementation

[0025] The following embodiments will further illustrate the present invention, but are not intended to limit the invention.

[0026] The following are the optimal implementation methods for three typical scenarios, all based on the core system and method design of this invention: Example 1: Construction and Flow Field Setting of Microfluidic Bionic Environment This embodiment provides a microfluidic biomimetic method and system for evaluating penetration of biological surfaces containing mucus barriers. First, a multi-layered biomimetic environment is constructed within a microfluidic chip. The observation window of the microfluidic chip is positioned along the direction of microbial penetration (i.e.,...). x The axis is divided into three main regions. The external aqueous phase zone is set at... x Within a range of <200μm, the fluid transport environment outside the mucus barrier is simulated, with the surface mucus simulation zone set at ≤200μm. x Within a range of < 400 μm, shallow mucus is used to simulate biological surfaces, while the deep mucus simulation zone is set at... xWithin a range of ≥ 400 μm, it is used to simulate deep and highly dense mucus on the surface of organisms. Interfacial barrier bands of limited thickness are set between adjacent regions, such as the half-width of the interface layer between the outer aqueous phase region and the surface mucus simulation region, which is set to 12 μm.

[0027] After spatial region partitioning, the system establishes a partitioned advection velocity field along the non-penetrating direction within the microfluidic environment. To realistically simulate the strong scouring effect of the external aqueous phase and the weak flow characteristics of the internal viscous layer, the external aqueous phase region is endowed with a high transport velocity (e.g., ), while the mucus simulation region is given a lower transport velocity (e.g. The velocity transition between regions is smoothly achieved near the interface using the Sigmoid function. The advection velocity along the y-axis... The calculation model is shown below:

[0028] Among them, intermediate variables The smoothing function is expressed as follows: ,in, This is the adjustable shear ratio constant of the system.

[0029] Example 2: Establishment of an evaluation model for the penetration behavior of the microorganism to be evaluated This embodiment details how to establish a microbial penetration behavior evaluation model based on the biomimetic environment constructed above. This model, for each introduced microbial individual to be evaluated, evaluates the penetration behavior at discrete time steps. The motion state is iteratively updated within the system.

[0030] First, the system recalibrates the movement parameters of the microorganisms based on the physicochemical properties of the mucus at their location. The system also establishes a mucosal density field that smoothly increases with penetration depth. As density increases, the basic swimming speed of microorganisms also increases. It will decay exponentially, as expressed by:

[0031] Simultaneously, the system incorporates the Carreau-Yasuda generalized Newtonian fluid model to characterize the shear thinning effect of the viscous fluid. The system is based on the local equivalent shear strength... Calculate the local relative effective viscosity. Based on this, the actual swimming speed of microorganisms is nonlinearly adjusted to satisfy... This allows for a realistic simulation of the changes in penetration resistance of microorganisms in non-Newtonian fluids.

[0032] Furthermore, the system sets interface trapping and release rules in the model. Microorganisms have a probability of being trapped by mucus or the interface during penetration, and this trapping probability exhibits a unimodal variation with the equivalent shear strength, simulating the physical phenomenon of near-interface adhesion most likely to occur under moderate shear. Actual trapping probability. The calculation model is as follows:

[0033] Once a microorganism is determined to be trapped, it will be randomly released at a constant rate following an exponential distribution in subsequent time steps.

[0034] A dual-gating rule is set for the interface crossing mechanism. When microorganisms attempt to enter the surface slime simulation zone from the external aqueous phase zone, or from the surface slime simulation zone to the deep slime simulation zone, they must first meet the continuous straight-line running time threshold, that is, the continuous straight-line movement time since the last tumbling behavior is greater than a preset threshold. Based on meeting the time threshold, the system further calculates the probability crossing threshold. The probability of crossing is weakened by local shear resistance and simultaneously affected by favorable external stimuli (such as effective light intensity). Enhancement, its expression is:

[0035] If the microorganisms meet the above probability and successfully cross the boundary, their coordinates are updated to the next region; if the crossing fails, the model forces a small position of 1~5μm to retreat in order to avoid the simulation getting stuck in the interface deadlock.

[0036] Finally, the system also incorporates a phototactic dynamics module to regulate the tumbling and redirection behavior of microorganisms. The system determines the direction of movement by extracting the time derivative signal of light intensity sensed by the microorganisms and generates a bias intensity by combining it with absolute light intensity weights. When microorganisms undergo tumbling redirection, the direction of movement is resampled using a von Mises distribution. Bias strength The larger the value, the higher the concentration parameter k of the von Mises distribution, which makes the new orientation of microorganisms more significantly biased towards the penetration direction of deep mucus (i.e., the +x direction).

[0037] Example 3: Output of Penetration Evaluation Results and Calculation of Quantitative Indicators After a preset duration of iterative movement, the system's data processing module outputs quantitative indicators for evaluating penetration effectiveness based on the acquired global temporal trajectory data of individual microorganisms. The main output indicators include penetration rate, target area reach rate, and directionality. Specifically, the penetration rate is defined as the proportion of microorganisms that ultimately touch or cross the right boundary of the deep mucus zone out of the initial total number introduced; the target area reach rate is defined as the percentage of microorganisms whose movement trajectory crosses a set target line (e.g., [missing information]). xThe proportion of individuals (500μm). Directionality D ( t The formula for calculating ) is:

[0038] in, This represents the number of microorganisms currently surviving within the observation domain. For the first i The instantaneous direction of movement of each individual. The reference angle corresponds to the target penetration direction. By combining the above calculation indicators, this invention can simultaneously and quantitatively characterize the coupled effects of external fluid scouring, interfacial physical resistance, and the microbial's own tendency behavior on the final penetration process.

[0039] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A microfluidic biomimetic method for evaluating the ability of microorganisms to penetrate mucus-containing barriers, characterized in that, include: Step 1: Construct a microfluidic biomimetic environment, which includes an external aqueous phase region, a surface mucus simulation region, and a deep mucus simulation region arranged sequentially along the predetermined penetration direction of microorganisms; Step 2: Introduce the microorganism to be evaluated into the microfluidic biomimetic environment and obtain its motion process data in it. The motion process data includes at least position, velocity, interface dwell events and interface crossing events. Step 3: Establish an evaluation model for the penetration behavior of the microorganism to be evaluated. The model includes at least a flow field module, an equivalent shearing module, a trapping and release module, and an interface crossing module. The model parameters are calibrated using the motion process data. The flow field module is used to construct a partitioned advection velocity field in the microfluidic biomimetic environment. The equivalent shear module is used to calculate the local equivalent shear strength based on the velocity field. The trapping and release module is used to determine the probability that the microorganism to be evaluated is trapped in the current region based on the equivalent shear strength. The interface crossing module is used to determine the probability that the microorganism to be evaluated will cross from the current area to the adjacent area based on the equivalent shear strength and the preset continuous straight running time threshold. Step 4: Based on the calibrated penetration behavior evaluation model, output the penetration evaluation results of the microorganism to be evaluated. The penetration evaluation results include at least the penetration rate, the trapping rate, and the target area reach rate.

2. The method according to claim 1, characterized in that, The trapping release module is configured to: set a baseline trapping probability based on the region where the microorganism to be evaluated is located, and introduce a trapping enhancement factor that varies with the equivalent shear strength in a single peak, so as to determine the probability that it will eventually be trapped.

3. The method according to claim 1, characterized in that, The interface crossing module is configured to use at least one of the following criteria to determine crossing: (1) Criterion for continuous straight running: The continuous straight running time of the microorganism to be evaluated before crossing the interface of the adjacent region is not less than a preset threshold; (2) Crossing probability criterion: The crossing probability is determined based on the local equivalent shear strength and the external stimulus input, wherein the crossing probability decreases as the equivalent shear strength increases.

4. The method according to claim 1, characterized in that, The flow field module is configured to: construct a partitioned advection velocity field along the penetration direction, and determine the local equivalent shear strength based on the spatial gradient of the velocity field and the wall shear term.

5. The method according to claim 1, characterized in that, The penetration behavior of the microorganism to be evaluated is characterized by an intelligent agent model. The motion state update methods of the intelligent agent model include at least swimming and tumbling motion update, advection transport update based on the advection velocity field of the partition, rotational diffusion update, trap release update controlled by the trap release module, and interface crossing determination controlled by the interface crossing module.

6. The method according to claim 1, characterized in that, The penetration evaluation results also include directionality and interface event throughput.

7. The method according to claim 1, characterized in that, Step 3 also includes using the motion process data obtained in step 2 to invert or fit at least some of the flow parameters, tumble rate parameters, trapping parameters, interface crossing parameters, and viscous rheological parameters.

8. The method according to claim 1, characterized in that, It also includes adjusting at least one of the stimulation parameters, flow parameters, microfluidic structure parameters, or mucus parameters based on the penetration evaluation results of the microorganism to be evaluated.

9. The method according to claim 8, characterized in that, The stimulation parameters include at least one of light stimulation parameters, chemical stimulation parameters, or mechanical stimulation parameters.

10. The method according to claim 1, characterized in that, The method is used to compare and evaluate the ability of different microorganisms to penetrate mucus-containing barriers.

11. A microfluidic biomimetic system for evaluating the ability of microorganisms to penetrate mucus-containing barriers, characterized in that, include: Microfluidic chips are used to construct an external aqueous phase region, a surface mucus simulation region, and a deep mucus simulation region arranged sequentially along a predetermined microbial penetration direction. The data acquisition module is used to acquire data on the movement process of the microorganism to be evaluated in the microfluidic chip; The data processing module is used to extract the movement process data of the microorganism to be evaluated, establish or calibrate its penetration behavior evaluation model, and output the penetration evaluation results.

12. The microfluidic biomimetic system according to claim 11, characterized in that, It also includes a control module, which is used to apply light stimulation, chemical stimulation or mechanical stimulation to the microfluidic chip.

13. The microfluidic biomimetic system according to claim 11, characterized in that, The main chamber of the microfluidic chip has a height of 20~80μm; the surface mucus simulation region and the deep mucus simulation region are filled with a mucus mimicry containing at least one of mucin, hyaluronic acid, methylcellulose, collagen, and agarose.

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