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. 2024 May 6;18(3):034103. doi: 10.1063/5.0203061

The mechanism of biofilm detachment in porous medium under flow field

Yangyang Tang 1,a), Zheng Zhang 1,b), Cong Tao 1,c), Xiaoling Wang 1,2,1,2,d)
PMCID: PMC11080962  PMID: 38737754

Abstract

Biofilms are communities formed by bacteria adhering to surfaces, widely present in porous medium, and their growth can lead to clogging. Our experiment finds that under certain flow conditions, biofilms detach in pores and form a dynamically changing flow path. We define detachment that occurs far from the boundary of the flow path (with a distance greater than 200 μm) as internal detachment and detachment that occurs at the boundary of the flow path as external detachment. To understand the mechanism of biofilm detachment, we study the detachment behaviors of the Bacillus subtilis biofilm in a porous medium in a microfluidic device, where Bacillus subtilis strain is triple fluorescent labeled, which can represent three main phenotypes during the biofilm formation: motile cells, matrix-producing cells, and spores. We find that slow small-scale internal detachment occurs in regions with very few motile cells and matrix-producing cells, and bacterial movement in these areas is disordered. The increase in the number of matrix-producing cells induces clogging, and after clogging, the rapid detachment of the bulk internal biofilm occurs due to the increased pressure difference at the inlet and outlet. When both internal and external detachments occur simultaneously, the number of matrix-producing cells in the internal detachment area is 2.5 times that in the external detachment area. The results indicate that biofilm detachment occurs in areas with fewer matrix-producing cells, as matrix-producing cells can help resist detachment by secreting extracellular polymeric substances (EPSs).

I. INTRODUCTION

Bacteria adhere to surfaces by secreting a polymer matrix, such as polysaccharides, secreted proteins, and extracellular DNA, forming biofilms (Muhammad et al., 2020). This matrix creates a protective layer that allows bacteria to resist adverse environmental factors, such as antibiotics (Van Acker et al., 2014), predators (Li et al., 2022), and fluid shear forces (Hou et al., 2018). Biofilms are widely presenting in the natural and engineered porous medium, such as soil, rocks, and filters. The formation of biofilms in a porous medium often causes serious damage, such as clogging, which reduces the permeability of the porous medium (Charbonneau et al., 2006; and Ye et al., 2009), medical device infections (Jamal et al., 2018), and corrosion of cast iron pipelines (Xing et al., 2018). However, biofilms in the porous medium also have some applications, such as biodegradation (Gröesbacher et al., 2018), phosphorus removal (Pan et al., 2017), gas adsorption and conversion (Gan et al., 2023), enhanced oil recovery (Yao et al., 2022), and building materials (Ertelt et al., 2022). Therefore, studying the mechanisms of biofilm detachment in the porous medium is of great significance for promoting the transport and distribution of resources.

In the porous medium, flow conditions play a crucial role in the formation and growth of biofilms. Bacteria rapidly aggregate at high velocity gradients in the pore throats (Lee et al., 2023). Additionally, regular vortices induce oscillatory wall shear that promotes an increase in the biofilm thickness (Tsagkari et al., 2022). Biofilms exhibit different morphologies in flow fields. For instance, bacteria lacking the EPS form chains in flow fields (Aufrecht et al., 2019), while biofilms attach to microcolumn surfaces transition from a circular to a streamer-like shape under the influence of critical shear forces (Lee et al., 2023). These streamers capture free bacteria and induce clogging in the porous medium (Drescher et al., 2013). Under certain flow velocities, pores are unclogged to form a flow path without biofilm (Stewart and Fogler, 2002). In addition, the flow path is dynamically changing. The opening and closing of preferential flow paths exhibit intermittency under the competing influences of fluid shear stress and growth stress (Kurz et al., 2022). Bottero et al. (2013) proposed a model showing that repeated events of pore clogging and clearance result in changes in the position of flow paths. So far, the reason for the changes in the position of the flow path is attributed to changes in the external environment (nutrients and flow rate) (Stewart and Fogler, 2002; and Bottero et al., 2013). We still need to know if the bacteria themselves contribute to flow path variation, such as the differentiation of cells and distribution of different phenotypes.

The biofilm detachment is influenced by multiple factors, such as the age of the biofilm and EPS. Older Streptococcus mutans biofilms require higher shear forces compared to younger biofilms (Hwang et al., 2014). Wang et al. (2014) indicate that the flow velocity influences the distribution of the EPS, with biofilms grown at high flow velocities exhibiting a more uniform EPS distribution and stronger cohesion compared to those grown at lower velocities. Jang et al. (2017) find that the heterogeneity of EPS distribution in biofilms significantly affects the local adhesion strength of biofilm cells. Furthermore, theoretical studies suggest that biofilms with higher EPS content exhibit greater resistance to fluid shear forces (Xia et al., 2022). Although previous theoretical research has highlighted the important role of the EPS in the biofilm detachment process, experimental support has been lacking.

In this article, we study the detachment behaviors of the Bacillus subtilis biofilm in the porous medium by using microfluidic technology, including internal biofilm detachment and external biofilm detachment. To make the research effect clearer, we adopt a simplified model of a uniform microcolumn array to simulate the soil porous medium environment. By employing triple fluorescent labeled Bacillus subtilis strain, we obtain the spatial and temporal resolution of the distribution of phenotypes in the porous medium, revealing the impact of matrix-producing cell distribution and biofilm age on biofilm detachment. The aim of this study is to elucidate the mechanisms of biofilm detachment in order to better predict and simulate the formation and position variation of flow paths in the porous medium. It also provides new insights and methods for further research on biofilm behavior in porous media, which is crucial for exploring biofilm stability and controlling detachment processes.

II. MATERIALS AND METHODS

A. Biofilm culture

Bacillus subtilis is a model bacterium that exhibits a clear differentiation pattern and biofilm formation process (Vlamakis et al., 2013; and Qin et al., 2022). It is widely found in soil environments (Hashem et al., 2019; and Saxena et al., 2020) and can be collected from plant roots (Beauregard et al., 2013), crude oil (Pereira et al., 2013), and deep-sea sediments (Yan et al., 2016). Therefore, we select Bacillus subtilis 3610 as the research subject. We take out the stored bacteria from the −80 °C refrigerator, inoculate them proportionally into pre-sterilized flasks containing culture medium, and place the flasks in a shaking incubator for 4 h at 30 °C and 150 rpm. After that, we mix the bacterial solution with the culture medium to dilute the bacteria as evenly as possible in the solution. We adjust the wavelength of transmitted light to 600 nm and dilute the solution to the desired optical density OD600 = 0.4. We inject minimal-salts-glutamate-glycerol (MSgg) solution with OD600 = 0.4 and variable flow rate into the microfluidic channel to cultivate the biofilm. The flow rate changes over time, initially cultured at 10 ul/h for 25 h, then at 20 ul/h for 28.5 h, followed by 25 ul/h for 7.5 h, then 30 ul/h for 12 h, 35 ul/h for 11 h, and finally 5 ul/h for 12 h, with the entire cultivation process lasting for 96 h, as shown in Fig. 1. MSgg is composed of 5 mM potassium phosphate (pH 7), 100 mM MOPS (pH 7), 2 mM MgCl2, 700 μm CaCl2, 50 μm MnCl2, 50 μm FeCl2, 1 μm ZnCl2, 2 μm thiamine, 0.5% glycerol, 0.5% glutamate, 50 μg/ml tryptophan, 50 μg/ml phenylalanine, and 50 μg/ml threonine. All experiments are repeated five times.

FIG. 1.

FIG. 1.

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Schematic diagram of the microfluidic device and the flow rate variation over time.

B. Microfluidic device

Microfluidic devices can precisely control fluid flow velocity by changing the structure and size of channels and are typically used to observe biofilm formation at the microscale (Yuan et al., 2023). In the experiment, the microfluidic channels are made of polydimethylsiloxane (PDMS), with a cross-sectional width of 600 μm and a height of 20 μm, as shown in Fig. 1. The porous medium model consists of uniformly arranged microcolumns with a diameter of 32 μm, and the model has a length of 1420 μm and a width of 600 μm, with an initial porosity of 59.5%, which is used to simulate soil environments.

The mother mold of the microfluidic channel is obtained by evenly spinning photoresist (SU-8) on a silicon wafer and then etching it. After treating the mother mold with trichloromethylsilane (TCMS) for silicification, PDMS is poured onto the mother mold. After curing, the PDMS is bonded to a glass slide.

C. Image capture and processing

We use the Zeiss Axio Zoom V16 wide-field fluorescence stereomicroscope to observe biofilms. This microscope allows imaging in both the transmitted light channel and three fluorescence channels simultaneously, enabling real-time monitoring of the growth and phenotypic changes in biofilms in a fluid environment.

We use PIVlab in the MATLAB plugin to process the image sequence captured in the experiment. After obtaining velocity field data, we analyze the average velocity and correlation coefficients of the velocity direction in the small-scale internal detachment region. The correlation coefficient is a measure of the orderliness of the bacterial movement direction. The range of values for the correlation coefficient is between 0 and 1, where 1 indicates the consistent bacterial movement direction and 0 indicates the opposite bacterial movement directions. In addition, we conduct Particle Image Velocimetry (PIV) analysis on the deformation area of the external biofilm, first obtaining velocity field data and then obtaining the strain rate field by calculating the gradient of the velocity field.

To demonstrate the distribution of phenotypes in the porous medium, we convert the images of three fluorescent channels into 8-bit images in ImageJ, then use macros to display the pixel values on the images, and save them as a table. First, the image is composed of individual pixels, each with a corresponding value (gray value), and at the same time, each pixel corresponds to a two-dimensional coordinate. We use the getPixel (x, y) function to traverse the entire image and assign pixel values for each coordinate to the value variable. Then, using the setResult (i, j, value) function, display each value after pixel traversal in the Result table. Finally, we import the data into Origin and convert it into matrices to plot 3D colormap surface with projections. The heatmaps in Figs. 5–7, 9, and 10 are projection images, with color bars representing grayscale values and also representing the number of phenotypes.

FIG. 5.

FIG. 5.

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(a)–(c) The time-lapse microscopic images of the biofilm at three different time points in the porous medium. Green boxes represent the entrance of the porous medium, orange boxes represent the detachment region, and yellow boxes represent the non-detachment region. At 53.5, 56.17, and 56.25 h, heatmaps of the distribution of matrix-producing cells (d)–(f) and motile cells (g)–(i) at the entrance of the porous medium are displayed, with colors representing gray values. The mean fluorescence intensity of matrix-producing cells (j) and motile cells (k) in the detachment region (orange curve) and non-detachment region (yellow curve) over time.

FIG. 6.

FIG. 6.

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(a)–(c) The time-lapse microscopic images of the biofilm in the porous medium at three different time points. Green boxes represent the outlet of the porous medium, white outline represents the region without biofilm, orange boxes represent the detachment region, and yellow boxes represent the non-detachment region. At 60.7, 61.5, and 61.58 h, heatmaps of the distribution of matrix-producing cells (d)–(f) and motile cells (g)–(i) are shown at the outlet of the porous medium, with colors representing gray values. (j) and (k) The average fluorescence intensity of matrix-producing cells and motile cells in the detachment region (orange curve) and non-detachment region (yellow curve) over time.

FIG. 7.

FIG. 7.

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External biofilm detachment at a fluid flow rate of 30 μl/h. (a)–(c) Local images of the biofilm in the porous medium at three different time points, with the orange boxes indicating the external detachment region. At 61.58, 62.83, and 62.92 h, heatmaps of the distribution of matrix-producing cells (d)–(f) and motile cells (g)–(i) are shown at the outlet of the porous medium, with colors representing gray values. (j) Biofilm coverage area as a function of time. (k) The mean fluorescence intensity of matrix-producing cells (blue curve) and motile cells (red curve) as a function of time.

FIG. 9.

FIG. 9.

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(a)–(c) The time-lapse microscopic images of the biofilm in the porous medium at three time points. Orange boxes represent the internal detachment region, yellow boxes represent the internal non-detachment region, and blue boxes represent the external detachment region. Heatmaps of the distribution of matrix-producing cells (d)–(f) and motile cells (g)–(i) in the porous medium at 66.75, 69.25, and 70.75 h, with colors representing gray values. (j)–(l) The changes in the biofilm coverage area, mean fluorescence intensity of matrix-producing cells, and mean fluorescence intensity of motile cells over time. The regions of internal detachment, internal non-detachment, and external detachment are represented by the orange curve, yellow curve, and blue curve, respectively.

FIG. 10.

FIG. 10.

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(a) The variation in the mean fluorescence intensity of phenotypes in the porous medium over time, with matrix-producing cells, motile cells, and spores represented by the blue curve, red curve, and yellow curve, respectively. (b)–(e) The time-lapse microscopy images of the biofilm at 61.58, 73, 84, and 96 h, as well as the distribution heatmap of matrix-producing cells, motile cells, and spores, with colors representing gray values.

D. Statistical analysis

To obtain data on the coverage area of biofilms and the average fluorescence intensity of phenotypes, we adjust the grayscale threshold to a suitable level in ImageJ and sequentially segment the images with an interval of 2 grayscale values. We collect three sets of data, calculate their means, and standard deviations. In the velocity field obtained from PIV analysis, we remove some oversized outliers by selecting velocity limits and then calculate the average velocity and correlation coefficient within the selected area.

III. RESULTS AND DISCUSSIONS

A. Different forms of biofilm detachment

We create a schematic diagram to better understand the internal and external detachment, as shown in Fig. 2. The internal detachment of the biofilm occurring far from the boundary of the flow path leads to the formation of the new flow path, while the external detachment occurring at the boundary of the flow path leads to the widening of the flow path. We calculate the distances h between the areas where internal detachment occurs at different times and the boundary of the previous flow path, which are 270(44.17 h), 380 (61.58 h), and 430 μm (56.25 h), respectively. Obviously, this is not a fixed value.

FIG. 2.

FIG. 2.

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Schematic diagram of internal and external detachments. The distance between the internal detachment area and the boundary of the flow path is h.

B. Internal biofilm detachment

From 25 to 53.5 h, we inject the MSgg solution into the microfluidic platform at a flow rate of 20 μl/h to observe the growth and detachment of the Bacillus subtilis biofilm in the porous medium, as shown in Fig. 3. At 38.75 h, a flow path is formed inside the channel, as shown in Fig. 3(a). About 2 h later, biofilm detachment occurs away from the flow path, as shown in the orange box in Fig. 3, the detachment continues 2 h, then in the following about 2 h, the channel is re-clogged again, as shown in Fig. 3(g); due to a bulk biofilm detachment, a new flow path is formed, which goes through the biofilm detachment region (orange box), as shown in Fig. 3(h).

FIG. 3.

FIG. 3.

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The experimental setup includes a microcolumn array with dimensions of 1420 × 600 μm2, where the microcolumns have a diameter of 32 μm and a height of 20 μm. The orange box represents the internal detachment region, and the yellow box represents the non-detachment region. Fluid flow rate, Q = 20 μl/h. (a) and (b), (g) and (h) Time-lapse microscopic images of the biofilm at four time points within the porous medium. (c)–(f) The velocity field distribution within the selected region, obtained through PIV analysis, shows green arrows representing bacterial motion and red arrows indicating the velocity vector interpolated and fitted after velocity filtering, with larger arrows indicating higher movement speeds. (i) Variation in the biofilm coverage area in the internal detachment region (orange curve) and the non-detachment region (yellow curve) over time. The average velocity (j) and correlation coefficient (k) of bacterial movement in the internal detachment region and non-detachment region are functions of time. The closer the value of the correlation coefficient is to 1, the more consistent the direction of velocity.

To characterize the process of the internal detachment, we delineate the internal detachment region [orange boxes in Figs. 3(a), 3(b), and 3(g) and 3(h)] and the non-detachment region [yellow boxes in Figs. 3(a), 3(b), 3(g), and 3(h)], and statistically analyze the biofilm coverage area within these regions. As shown in Fig. 3(i), from 40.5 to 42.5 h, and from 44.08 to 44.17 h, detachment occurs in the internal detachment region. The difference is that the former experiences continuous detachment in a small area, while the latter experiences bulk detachment, with a detachment rate 652 times faster than the former.

To further understand the internal detachment behavior of biofilms, we employ the PIVlab plugin in MATLAB to analyze the internal detachment region (orange boxes) and the non-detachment region (yellow boxes), to obtain the velocity distribution in selected regions, as shown in Figs. 3(c)–3(f). To quantitatively analyze the motion of bacteria in the internal detachment region and the non-detachment region, we obtain the average velocity of bacterial motion within the regions, as shown in Fig. 3(j), and the correlation coefficient, as shown in Fig. 3(k). The results indicate that bacteria within the internal detachment region exhibited higher velocity and more disordered motion direction, compared with bacteria in the non-detachment region. Previous studies have shown that there is heterogeneity in the permeability of biofilms in the porous medium (Kurz et al., 2023), and the internal flow is related to the permeability of biofilms (Deng et al., 2013; Jung and Meile, 2021; and Karimifard et al., 2021). This means that when the permeability of the biofilm in the non-detachment region is sufficiently high, the motile bacteria are completely shielded by the flow.

To investigate the effect of bacterial differentiation on the internal detachment, we quantitatively analyze the average fluorescence intensity of phenotypes in the 10 internal detachment regions [orange boxes in Figs. 4(a) and 4(b) and the 10 non-detachment regions (yellow boxes in Figs. 4(a) and 4(b)]. The results show that the number of matrix-producing cells and motile cells in the non-detachment regions increases with time and are both higher than those in the detachment regions, as shown in Figs. 4(c) and 4(d). Interestingly, from 40.5 to 42.5 h, there are fewer matrix-producing cells and small areas of biofilm detachment in the internal detachment regions. However, the sharp increase in the number of matrix-producing cells leads to an enhanced resistance of the biofilm to detachment, resulting in clogging. After clogging, due to the increased pressure difference between the inlet and outlet, the biofilm in the internal detachment regions undergoes bulk detachment, and the number of matrix-producing cells and motile cells also decreases. Small-scale internal detachment can cause the biofilm in the detachment regions to become incomplete, disrupting the stability of the biofilm. This slow detachment method is similar to microcracks. After the porous medium is completely clogged, bulk internal biofilms detach, directly causing a change in the position of the flow path. This rapid detachment method is similar to destructive failure.

FIG. 4.

FIG. 4.

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Mark the internal detachment region (orange box) and non-detachment region (yellow box) in the images of matrix-producing cells (a) and motile cells (b). The green lines divide the detachment and non-detachment region into 10 rectangular small areas of equal area. The average fluorescence intensity within each area is calculated after image segmentation. (c) The mean fluorescence intensity of matrix-producing cells (c) and motile cells (d) as a function of time, with the orange curve representing the 10 internal detachment regions and the yellow curve representing the 10 non-detachment regions. Error bars represent the standard deviation.

As time progresses, the internal biofilm detachment always happens instantly and companying large biofilm area detaching, which results in the position of the flow path undergoes dramatic changes (Movie S1 in the supplementary material). At the inlet, we observe the appearance of a flow path in the porous medium at 53.58 h, as shown in Fig. 5(a), with a fluid flow rate of 25 μl/h. At 56.17 h, clogging occurs, as shown in Fig. 5(b). After 5 min, internal biofilm detachment occurs at the inlet, forming a new flow path, as shown in the green box in Fig. 5(c). To explore the phenotypic effects, we obtain heatmaps of matrix-producing cells and motile cell distribution at three time points from the gray values, as shown in Figs. 5(d)–5(i). We find that prior to clogging, there is a higher number of matrix-producing cells, as shown in Fig. 5(d), and a lower number of motile cells around the flow path, as shown in Fig. 5(g), indicating a strong ability of the biofilm to resist fluid shear and maintain a relatively stable flow path. After the flow path is clogged, there is an increased number of matrix-producing cells but a decreased number of motile cells at the site of clogging, as shown in Figs. 5(e) and 5(h).

To further compare the heterogeneity of phenotype distribution at the site of biofilm detachment, we quantitatively analyze the mean fluorescence intensity of phenotypes in the detachment region [orange boxes in Figs. 5(a)–5(c)] and non-detachment region [yellow boxes in Figs. 5(a)–5(c)]. The results show that the number of matrix-producing cells in the detachment region is lower, as shown in Fig. 5(j), and the number of motile cells is higher, as shown in Fig. 5(k), compared to the non-detachment region.

Similarly (Movie S2 in the supplementary material), at the outlet, from 61 to 73 h, the fluid flow rate increases to 30 ul/h. At 61.67 h, a small area without biofilm forms within the detachment region (orange box), as shown in the white outline in Fig. 6(a). At 61.58 h, the flow path at the outlet (green box) passes through the region without biofilm, as shown in Fig. 6(c). Similarly, we obtain heatmaps of the distribution of phenotypes at the outlet, as shown in Figs. 6(d)–6(i). We find that there are fewer matrix-producing cells around the region without biofilm, with matrix-producing cells mainly concentrating at the lower end of the outlet, as shown in Figs. 6(d)–6(f), while motile cells mainly concentrate at the upper end, as shown in Figs. 6(g)–6(i).

We quantitatively analyze the average fluorescence intensity of phenotypes in the detachment region [orange boxes in Figs. 6(a)–6(c)] and the non-detachment region [yellow boxes in Figs. 6(a)–6(c)]. The results indicate that there are fewer matrix-producing cells and more motile cells in the detachment region, compared to the non-detachment region. As time progresses, both the number of matrix-producing cells and motile cells in the detachment region decrease, as shown in Figs. 6(j) and 6(k), which suggests a potential decrease in the biofilm's ability to attach and spread.

C. External biofilm detachment or deformation

We find that the external detachment happens at the outlet, causing the flow path shift from closed to open, as shown in orange boxes in Figs. 7(a)–7(c). To quantify the external detachment process, we delineate the external detachment region, as shown in the orange boxes in Figs. 7(a)–7(c), and characterize the detachment by the coverage area of the biofilm. The biofilm coverage area gradually increases and reaches its maximum value at 62.83 h, as shown in Fig. 7(j). At 62.92 h, the biofilm coverage area has a sudden drop, indicating the opening of the flow path, as shown in Fig. 7(c).

To explore the phenotypic effect, we obtain heatmaps of matrix-producing cells and motile cells distribution from the gray values (details in Materials and Methods section), as shown in Figs. 7(d)–7(i). The results indicate that matrix-producing cells are mainly distributed at the lower end of the outlet, while motile cells are mainly distributed at the upper end of the outlet. For quantitative analysis of the cell populations, we obtain the average fluorescence intensity of the two cell types within the detachment region, as shown in Fig. 7(k). The results indicate that the number of motile cells is approximately 1.6 times that of matrix-producing cells.

Under the loading of normal stress at the boundary of the flow path, the biofilm is compressed and deforms, resulting in the enlargement of the flow path (Kurz et al., 2022). This phenomenon is also observed in our experiment, where biofilm deformation occurs at local clogging in the flow path, as shown in the red boxes in Figs. 8(a) and 8(b). To analyze the biofilm deformation, we perform PIV analysis based on the experimental images in Figs. 8(a) and 8(b) and obtain the velocity field distribution of bacterial movement, as shown in Fig. 8(c). Within the biofilm deformation region, bacteria exhibit a tendency to move toward a specific point. We also analyze the strain rate of the biofilm, as shown in Fig. 8(d). The results indicate that the maximum strain rate occurs at the boundary of the biofilm deformation region.

FIG. 8.

FIG. 8.

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(a) and (b) The images of the biofilm before and after deformation, respectively. Red boxes indicate the region of biofilm deformation. (c) The velocity field distribution, where green arrows indicate the bacterial movement and larger arrows represent higher velocities. (d) The strain rate heatmap of the biofilm.

D. Combination of internal and external biofilm detachment

We observe the simultaneous detachment of internal and external biofilms in our experiment. To indicate the location of biofilm detachment, we mark the internal detachment region [orange boxes in Figs. 9(a)–9(c)], the internal non-detachment region [yellow boxes in Figs. 9(a)–9(c)], and the external detachment region [blue boxes in Figs. 9(a)–9(c)] in the time-lapse microscopic images. Our starting point is at 66.75 h, as shown in Fig. 9(a); at 69.25 h, the inlet of the porous medium is clogged and the flow path at the outlet becomes narrow, as shown in Fig. 9(b); at 70.75 h, internal biofilm detachment occurs at the inlet, causing the front section of the flow path relocate, while external biofilm detachment occurs at the outlet, widening the latter part of the flow path, as shown in Fig. 9(c). To quantify the biofilm detachment process, we characterize it using the biofilm coverage area, as shown in Fig. 9(j). The biofilm coverage area in both internal and external detachment regions begins to decrease after 69.25 h, forming a new flow path, but residual biofilm remains upstream in the flow path, leading to fluctuations in the biofilm coverage area.

Similarly, we obtain heatmaps of matrix-producing cells and motile cells in the porous medium at three time points, as shown in Figs. 9(d)–9(i). The results show that matrix-producing cells are mainly distributed at the inlet, while motile cells are mainly distributed at the outlet. This means that the biofilm phenotype near the inlet to the nutrient source mainly differentiates into matrix-producing cells, while the biofilm phenotype at the outlet with poor nutritional conditions mainly differentiates into motile cells. We also quantitatively analyze the distribution of matrix-producing cells and motile cells in the selected region, as shown in Figs. 9(k) and 9(l). The results indicate that compared to the internal detachment region, the internal non-detachment region has more matrix-producing cells and less motile cells, exhibiting higher resistance to fluid shear. Although both internal detachment events shown in Figs. 9 and 5 occur at the inlet, with the increase in the flow rate, the pressure drop between the inlet and outlet of the porous medium also increases, leading to an increase in the detachment threshold (i.e., the mean fluorescence intensity of matrix-producing cells, 25 in Fig. 5, 35 in Fig. 9). In the external detachment region, there are more motile cells than matrix-producing cells. Before detachment, the number of matrix-producing cells and motile cells decreases over time. When the fluorescence intensity of the matrix-producing cells decreases to 13, the biofilm begins to undergo external detachment. In addition, the detachment threshold for internal detachment is 2.5 times that of external detachment, which also means that the stability of the internal biofilm structure is stronger and more difficult to detach.

E. No detachment in the old biofilm

During the later stage (73–96 h) of biofilm cultivation, we did not observe any change in the flow path. To investigate the influence of biofilm age on detachment, we obtain the average fluorescence intensity of matrix-producing cells and motile cells in the porous medium, as shown in Fig. 10(a). The results demonstrate that the number of matrix-producing cells exhibits a trend of initially increasing and then decreasing, with a peak at 76 h. On the other hand, the number of motile cells decreases with biofilm age and stabilizes after 64.75 h. We obtain the heatmaps of biofilm phenotype distribution at four time points in the porous medium, as shown in Figs. 10(b)–10(e). The results indicate that the distribution of matrix-producing cells becomes more uniform in the later stages, while motile cells tend to concentrate in a specific region. Spores exhibit extremely low fluorescence expression at 73 h. However, at 84 h and 96 h, the spore distribution appears scattered, showing significant spatial heterogeneity. In particular, the point-like regions display prominent fluorescence expression, while areas outside these regions have nearly no spore distribution. Before 73 h, we observe dynamic changes in the flow path. From 73 to 84 h, although the flow rate increases to 35 ul/h, there is no significant change in the flow path. To observe the changes in the flow path, we reduce the flow rate to 5 ul/h from 84 to 96 h. At this time, the number of matrix-producing cells decreases, but no clogging of the flow path is observed.

IV. CONCLUSIONS

During the experiment, we observe the dynamic changes in the flow path caused by different detachment behaviors of the biofilm in the porous medium. We attribute the observed biofilm detachment behavior in the experiment to small-scale and bulk internal biofilm detachment, as well as external biofilm detachment and deformation. We use PIV analysis to examine the small-scale internal detachment and external biofilm deformation. Combining the fluorescence images of the biofilm phenotypes, we obtain the distribution and evolution of the phenotypes in the porous medium, elucidating the mechanism of biofilm detachment and deformation. We draw the following conclusions:

  • 1.

    The width and position of the flow path are dynamically changing in the porous medium with bacteria MSgg suspension flow.

  • 2.

    Small-scale internal biofilm detachment serves as a trigger for the change in the flow path position, while bulk internal biofilm detachment directly leads to the change in flow path position; external biofilm detachment and deformation result in an increase in the flow path width.

  • 3.

    The detachment of the biofilm is mainly dominated by the distribution of matrix-producing cells and occurs preferentially in areas with less distribution of matrix-producing cells.

SUPPLEMENTARY MATERIAL

See the supplementary material for the video of positional changes in the flow path from 53.58 to 56.25 h, fluid flow rate, Q = 25 μl/h (Movie S1), and the video of positional changes in the flow path from 60.67 to 61.58 h, 60.67–61 h fluid flow rate is 25 μl/h, and 60.67–61 h fluid flow rate is 30 μl/h (Movie S2).

ACKNOWLEDGMENTS

The authors would like to thank Professor David A. Weitz and Professor Shmuel Rubinstein from Harvard University for their experimental support. The authors would like to thank the National Natural Science Foundation of China (NNSFC) for funding support (Nos. 12372321, 11972074, 11772047, and 11620101001).

Contributor Information

Yangyang Tang, Email: mailto:tyyfor@163.com.

Zheng Zhang, Email: mailto:zz113994@163.com.

Cong Tao, Email: mailto:taocongxy@163.com.

Xiaoling Wang, Email: mailto:xiaoling@me.ustb.edu.cn.

AUTHOR DECLARATIONS

Conflict of Interest

The authors have no conflicts to disclose.

Author Contributions

Yangyang Tang: Conceptualization (equal); Investigation (equal); Visualization (equal); Writing – original draft (equal); Writing – review & editing (equal). Zheng Zhang: Data curation (equal); Visualization (equal). Cong Tao: Investigation (equal); Visualization (equal). Xiaoling Wang: Conceptualization (equal); Data curation (equal); Validation (equal); Writing – review & editing (equal).

DATA AVAILABILITY

The data that support the findings of this study are available from the corresponding author upon reasonable request.

REFERENCES

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Associated Data

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Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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