Microbial interactions are closely related to human health, and secreted signal molecules from bacteria determine the gene expression of bacteria following bacterial cell density and signal molecule density. However, the conventional quantitative analysis of the number of bacteria requires several days using standard cultivation methods, and the detection of molecules secreted via microbial interactions is difficult since they are in extremely small amounts. In this study, we performed local fluorescence spectroscopy to quantitatively evaluate the density of the assembly of dispersoids (fluorescent microparticles and bacteria) under optical condensation at a solid–liquid interface on our developed bubble-mimetic substrate, which exhibits extremely low thermal damage after a few minutes of laser irradiation. The obtained results showed that the fluorescence intensity spectrum was positively correlated with the concentration of dispersoids even when only several tens of assembled microparticles were observed. Furthermore, a calibration curve was obtained by plotting the integrated fluorescence intensity by integrating the fluorescence intensity spectrum over the observed wavelength, and the concentration of living bacteria was quantitatively analyzed. The clarified mechanism of local fluorescence spectroscopy under optical condensation will pave the way for rapid and precise analysis of bacteria and their secreted biomolecules labeled with fluorescent dye.

Detection and analysis of microbes are important subjects in the field of biophotonics; for example, adenosine triphosphate (ATP) bioluminescence with an enzymatic reaction is a simple popular method for detecting bacteria,1,2 and a precise analysis of bacterial cells was performed using a super-resolution microscope.3,4 There are not only harmful bacteria but also beneficial bacteria in the biological system, where bacterial activity and microbial interactions are closely related to human health.5,6 One of the microbial interactions is called quorum sensing, which causes squid luminescence, determines gene expression based on bacterial cell densities, and is involved in biofilm production and pathogenic expression of opportunistic bacteria.7 However, because the signal molecules of quorum sensing are usually diluted to the nM level, these molecules cannot be easily analyzed using standard analytical methods, such as nuclear magnetic resonance. Therefore, a more common approach is to use a reporter strain that can detect the signal molecule, for the cultivation process requires ∼24 h, followed by visualization and detection.8 

Since the development of optical tweezers, light-induced force, an electromagnetic interaction between light and matter, has been used to manipulate nano/micrometer-scale substances in a nondestructive and noncontact manner.9 The target of optical manipulation is not only limited to inorganic substances but also extends to biological samples, such as cells and bacteria. Plasmon tweezers using an electric field enhanced by the localized surface plasmons have also been recently developed and used to successfully trap cells.10 However, in general, the photothermal effect cannot be ignored in optical trapping. Inside the irradiated samples or metallic nanostructures, the electrons can be excited optically, and non-radiative decay occurs arising from Coulomb interaction between the excited electron and phonons, which leads to lattice vibration and generation of light-induced heat.11 This effect is an obstacle that must be overcome in the conventional type of optical manipulation.

On the other hand, optical condensation has recently been proposed to achieve rapid, high-density assembly of dispersoids in dispersion liquid via light-induced force and light-induced convection derived from the photothermal effect.12–20 For example, by using light-induced force and convection under laser irradiation, a submillimeter assembled structure was formed via DNA hybridization with DNA-modified gold nanoparticles,13 and an assembled structure of metallic nanoparticles via protein was formed,12 where the assembling phenomenon can be enhanced by the pressure-driven flow.14,15 In addition, bubbles are generated by local heating owing to photothermal effects, and light-induced convection is driven around the bubbles. In addition, the generated bubbles can be used for the formation of microscale assembly of nanoparticles,16,17 poly-crystallization of organic molecules,18 and electrical detection of metallic nanoparticles.19 In addition, this method can be used for the measurement of bacterial cell densities,20,21 but the light-induced heat that generates bubbles causes thermal damage to bacteria, which limited the analysis of microbial interactions. In order to avoid such thermal damage, a honeycomb substrate with a microstructure was developed and was found to reduce thermal damage.22 In addition, a bubble-mimetic substrate with a solid sphere similar to the bubbles on optical condensation could be used to avoid thermal damage to assembled samples by separating the heat source and the assembly site.23 However, when these substrates are used, fluorescence images obtained with large microscopes are needed to analyze the number of assembled bacteria and to determine whether substances smaller than the diffraction limit are assembled.

In this contribution, we performed optical condensation on a bubble-mimetic substrate consisting of a spherical sub-millimeter particle imitation bubble (Fig. 1) and then quantitatively evaluated the number of dispersoids from the locally measured fluorescence spectrum from an optically assembled structure. After optical condensation was performed with a high numerical aperture (NA) lens, a fluorescence spectrum was obtained for the entire assembled dispersoids using a low NA lens. The degree of assembly was evaluated from the integrated intensity obtained by integrating the fluorescence spectrum over the wavelength region around the main peak. Then, after the experiment with polystyrene particles with high fluorescence intensity, we performed optical condensation and quantitative evaluation of lactic acid bacteria (Lactobacillus casei) as an example of living microbes (Fig. S1).

FIG. 1.

Schematic diagram of the optical condensation of bacteria on a bubble-mimetic substrate and local fluorescence spectroscopy. The fixed polystyrene particle (diameter: 100 µm) was used as an imitation bubble. The orange dashed line shows the assembly region of bacteria, and their fluorescence spectrum corresponds to the orange line in the lower graph. The blue dashed line shows the dispersion region of bacteria, and their fluorescence spectrum corresponds to the blue line in the lower graph.

FIG. 1.

Schematic diagram of the optical condensation of bacteria on a bubble-mimetic substrate and local fluorescence spectroscopy. The fixed polystyrene particle (diameter: 100 µm) was used as an imitation bubble. The orange dashed line shows the assembly region of bacteria, and their fluorescence spectrum corresponds to the orange line in the lower graph. The blue dashed line shows the dispersion region of bacteria, and their fluorescence spectrum corresponds to the blue line in the lower graph.

Close modal

The bubble-mimetic substrate (Fig. 1) was prepared for optical condensation and local fluorescence spectroscopy. The method for preparing the bubble-mimetic substrate is as follows.19 First, a glass-bottom dish (cat. no. 3911-035; IKWAKI, Japan) was immersed in ethanol (cat. no. 360678-5G, Sigma-Aldrich, USA), and ultrasonic cleaning was performed using an ultrasonic cleaner (cat. no. MCD-2; ASONE, Japan) for 10 min at 33 and 44 kHz. The residual ethanol was then dried using an air duster. Next, 10 µl of the dispersion liquid for COOH-modified polystyrene beads (cat. No. MPT-01-02-105-10; Micromod Partikeltechnologie GmbH, Germany, diameter: 100 µm, concentration: 25 mg/ml) and 3 µl of the ten-fold diluted silane coupling agent 3-(trimethoxysilyl) propylmethacrylate (cat. no. 440159-500ML; Sigma-Aldrich, USA) were mixed with 287 µl ultrapure water. The mixture was dropped onto a washed glass-bottom dish, allowed to rest for at least 6 h, and naturally dried. After drying, 100 μl ultrapure water was added dropwise, and the ultrapure water was allowed to rest for 5 min. The water was then removed using a Kimwipe, and the sample was allowed to dry naturally. Finally, a thin platinum film (10 nm thick) was formed using an ion sputtering device (cat. no. MC1000; Hitachi, Japan). The polystyrene particles fixed on the substrate were called imitation bubbles.

COOH-modified polystyrene particles (diameter: 1 µm; cat. no. 15702; Fluoresbrite carboxylate microspheres (2.5% solid latex), 1.0 μm-YG; Polysciences, USA) and Lactobacillus casei were used as dispersoids. Here, we obtained Lactobacillus casei from the Biological Resource Center (NBRC), National Institute of Technology and Evaluation, in Japan. The code of Lactobacillus casei is NBRC 15883. Fluorescence staining of bacteria was performed using SYTO9 (cat. no. L7012; LIVE/DEAD BacLight Bacterial Viability Kit for Microscopy; Invitrogen, Carlsbad, CA, USA) for fluorescence spectrum measurement. Bacterial concentrations were determined by culturing for 72 h. The size of Lactobacillus casei was determined from the scanning electron microscopy image recorded using a scanning electron microscope (cat no. JSM-IT100; JEOL Ltd., Japan).

In this work, an inverted microscope (cat. no. Eclipse Ti-U; Nikon, Japan) was used for optical condensation and local fluorescence spectroscopy with laser and mercury lamp irradiation using a backport adapter (cat. no. MMS-2L-800/1064; Sigma Koki, Japan), as shown in Fig. S2. One hundred microliters of the sample dispersion liquid was dropped onto a bubble-mimetic substrate, and the substrate was then placed on the microscope stage. Optical condensation and local fluorescence spectrum measurement were performed. A near-infrared continuous laser (wavelength: 1064 nm; cat. no. FLS-1064-2000F; Sigma Koki, Japan) focused on the imitation bubble/glass interface using a CFI S Plan Fluor ELWD 40XC objective (0.6 NA) was irradiated at the center of the imitation bubbles (27 mW, 300 s). During laser irradiation, the halogen lamp for sample illumination was turned off to avoid affecting the fluorescence signal. After laser irradiation, the objective was replaced with a CFI Plan Fluor 10× (0.3 NA) to cover the overall assembly site, and the local fluorescence spectra were measured at the assembly site and dispersion region far from the imitation bubbles using a spectrometer (cat. no. USB4000; Ocean Optics, USA). Here, the integration time was 300 ms for polystyrene particles and 500 ms for bacteria, and results of 3 measurements were averaged in each experiment. The experiment was repeated three times using respective bubble-mimetic substrates.

Fluorescent polystyrene particles (diameter: 1 µm) with high fluorescence intensity were assembled around imitation bubbles (non-fluorescent polystyrene particle of a diameter of 100 µm) by optical condensation with 300 s laser irradiation on the bubble-mimetic substrate. The concentration of polystyrene particles was decreased from 9.10 × 107 to 4.55 × 105 particles/ml, and fluorescence images and local fluorescence spectra of the assembly region around the imitation bubble and the dispersion region far from the imitation bubbles were recorded. The green fluorescent dye doped in polystyrene particles used in this study show a spectrum similar to that of fluorescein isothiocyanate (FITC). For example, fluorescence images and local fluorescence spectra of 2.28 × 106 particles/ml are shown in Fig. 2 (fluorescence images and local fluorescence spectrum of other concentrations are shown in Figs. S3–S7), where FITC fluorescence filter was used for the observation of green fluorescence. Figure 2(a) shows the fluorescence image of the assembly region recorded with a high NA objective. Figures 2(b) and 2(c) show the fluorescence image of the assembly region and dispersion region recorded with a low NA objective. The white circles in Figs. 2(b) and 2(c) show the measurement areas of local fluorescence spectroscopy. Polystyrene particles were assembled around the imitation bubbles for each concentration. From our previous research,19 we found that the assembly mechanism was as follows: First, the platinum thin film on the top of the imitation bubbles was heated by laser irradiation. Subsequently, light-induced convection toward the imitation bubble was driven. Then, an assembly site was formed between the imitation bubbles and glass substrate, enabling polystyrene particles to be assembled around the imitation bubbles. The number of assembled particles decreased depending on the particle concentration, reaching several tens of particles at a concentration of 2.28 × 106 particles/ml, as shown in Fig. 2(a).

FIG. 2.

Fluorescence images and local fluorescence spectra after optical condensation of polystyrene particles (concentration: 2.28 × 106 particles/ml). (a) Fluorescence image around the imitation bubble after optical condensation of polystyrene particles. (b) and (c) Fluorescence images after optical condensation of polystyrene particles in assembly (b) and dispersion regions (c). Here, white circles show the measurement area of local fluorescence spectroscopy. (d) Local fluorescence spectra of the assembly and dispersion regions.

FIG. 2.

Fluorescence images and local fluorescence spectra after optical condensation of polystyrene particles (concentration: 2.28 × 106 particles/ml). (a) Fluorescence image around the imitation bubble after optical condensation of polystyrene particles. (b) and (c) Fluorescence images after optical condensation of polystyrene particles in assembly (b) and dispersion regions (c). Here, white circles show the measurement area of local fluorescence spectroscopy. (d) Local fluorescence spectra of the assembly and dispersion regions.

Close modal

The fluorescence intensity spectra of the assembly region [Fig. 2(b)] and dispersion region [Fig. 2(c)] showed different intensities [Fig. 2(d)]. The peak intensity of the assembly region was higher than that of the dispersion region. This result reflected that the number of particles present in the measurement area of the local fluorescence spectrum varied for the assembly and dispersion regions. Therefore, the local fluorescence spectrum depended on the spatial distribution of the polystyrene particles. When the concentration of polystyrene particles was high, the peak intensities of the fluorescence spectra differed in the assembly and dispersion regions [eg., Fig. 2(d) or Fig. S3(d)]. However, for a low concentration of polystyrene particles, it was difficult to distinguish the peaks of the fluorescence spectra for the assembly site and dispersion region [Fig. S7(d)]. In order to solve this problem, the fluorescence intensity spectrum was integrated with the wavelength region (508.5-551.5 nm) to obtain the integrated fluorescence intensity, and the evaluation was performed using the integrated intensity. The integrated intensity was calculated for each concentration, and the graphs at assembly region and at dispersion region plotted against the concentration are shown in Fig. 3(a) (the calibration curves were obtained from Figs. 2 and S3–S7). Notably, the integrated fluorescence intensities also differed between the assembly and dispersion regions, similar to the local fluorescence spectra. Each graph excluding the high concentration of Fig. 3(a) is shown in Fig. 3(b). It demonstrated that the integrated fluorescence intensity could be distinguished even if the concentration of polystyrene particles was low. This result indicated that a small amount of assembled particles could be detected based on the integrated fluorescence intensity. In addition, the integrated fluorescence intensity showed a linear correlation with the particle concentration. Figure 3 also shows a calibration curve for the polystyrene particles. Especially, in the low concentration region (from 2.28 × 107 to 4.55 × 105 particles/ml) excluding a very high concentration [Fig. 3(b)], the integrated fluorescence intensity showed good linear fitting. Therefore, by calculating the integrated fluorescence intensity based on the local fluorescence intensity after optical condensation, the concentration of the assembled dispersoids could be measured from the integrated fluorescence intensity.

FIG. 3.

Dependence of the integrated fluorescence spectrum intensity on the particle concentration. (a) All concentrations. (b) Replotted graph in the low-concentration region.

FIG. 3.

Dependence of the integrated fluorescence spectrum intensity on the particle concentration. (a) All concentrations. (b) Replotted graph in the low-concentration region.

Close modal

For quantitative evaluation of bacteria, the optical condensation of Lactobacillus casei was performed, and the local fluorescence spectrum was measured. The concentration of Lactobacillus casei was changed from 2.36 × 108 to 1.18 × 107 cells/ml. In addition, Lactobacillus casei was stained with SYTO9, yielding a green fluorescence signal. However, the fluorescence quantum yield of SYTO9 was 0.43, which was lower than that of the FITC (0.92) similar to fluorescent dye doped in the polystyrene particles. Therefore, the fluorescence intensity of bacteria was much weaker compared with that of polystyrene particles, and it was difficult to measure the local fluorescence spectrum using the same measurement conditions as used for polystyrene particles. To overcome this issue, we changed the integration time from 300 to 500 ms.

For example, Fig. 4 shows fluorescence images and local fluorescence spectra with 1.18 × 108 cells/ml (fluorescence images and local fluorescence spectra with other concentrations are shown in Figs. S8–S11). From the fluorescence images, it can be seen that bacteria were assembled around the imitation bubbles at all concentrations. Similar to the polystyrene particles, light-induced convection was driven by laser irradiation, and an assembly site was formed between the imitation bubbles and the glass substrate. However, the number of assembled bacteria seems to be decreased in comparison with the case of the polystyrene particles depending on the bacterial cell concentration. Therefore, the limit of detectable concentration of assembled bacteria was higher than that for the polystyrene particles. This result was related to the physical properties of the surface, e.g., the shape, surface conditions, and chemotaxis.

FIG. 4.

Fluorescence images and local fluorescence spectra after optical condensation of Lactobacillus casei (concentration: 1.18 × 108 cells/ml). (a) Fluorescence image around the imitation bubbles after optical condensation of Lactobacillus casei. (b) and (c) Fluorescence images after optical condensation of Lactobacillus casei in the assembly (b) and dispersion regions (c). White circles show the measurement area of local fluorescence spectroscopy. (d) Local fluorescence spectra of the assembly and dispersion regions.

FIG. 4.

Fluorescence images and local fluorescence spectra after optical condensation of Lactobacillus casei (concentration: 1.18 × 108 cells/ml). (a) Fluorescence image around the imitation bubbles after optical condensation of Lactobacillus casei. (b) and (c) Fluorescence images after optical condensation of Lactobacillus casei in the assembly (b) and dispersion regions (c). White circles show the measurement area of local fluorescence spectroscopy. (d) Local fluorescence spectra of the assembly and dispersion regions.

Close modal

Similar to polystyrene particles, the local fluorescence intensity was evaluated for quantitative analysis of the number of bacteria. The local fluorescence spectrum [Fig. 4(d)] was similar to that of SYTO9, indicating that the origin of the spectrum was bacteria. In the high concentration region, the peak intensity could be distinguished between the assembly region [Fig. 4(b)] and dispersion region [Fig. 4(c)]. On the other hand, in the low concentration region, fluorescence intensity was much lower in comparison with the that of polystyrene particles as the above-mentioned reason, making it difficult to distinguish the peak intensity of the local fluorescence spectrum between the assembly and dispersion regions. To overcome this issue, we calculated the integrated intensity of the local fluorescence intensity and plotted this value according to the bacterial cell concentration (Fig. 5). The calibration curve was obtained as shown in Figs. 4 and S8–S11. The difference between the assembly and dispersion regions was obvious at high concentrations (∼108 cells/ml) [Fig. 5(a)] but unclear at low concentrations (1.18 × 107 cells/ml). The fluorescence intensity of the bacterium was lower than that of polystyrene particles. Therefore, we concluded that a fluorescent dye showing a higher fluorescence quantum yield rather than SYTO9 was needed to detect lower concentrations of bacteria.

FIG. 5.

Dependence of the integrated fluorescence spectrum intensity on the bacterial cell concentration. (a) All concentrations. (b) Replotted graph of in the middle-concentration region.

FIG. 5.

Dependence of the integrated fluorescence spectrum intensity on the bacterial cell concentration. (a) All concentrations. (b) Replotted graph of in the middle-concentration region.

Close modal

The approximate curve for the integrated fluorescence intensity was a quadratic function [Fig. 5(a)], suggesting that the integrated fluorescence intensity and bacterial cell concentration showed a nonlinear relationship. However, the integrated fluorescence intensity has a linear relationship under the cell concentration condition from 1.18 × 107 to 2.36 × 107 cells/ml [Fig. 5(b)]. This result indicated that quantitative evaluation using integrated fluorescence intensity was helpful for bacterial cell densities of the order of 107 cells/ml. As reasons for the nonlinear relationship, some types of interactions among bacteria or effects of high-density fluorescence dyes may exist. In addition, bacteria were assembled as stacks around the imitation bubbles. As discussed in the previous literature,21 there is a possibility that a number of optically assembled particles exhibit nonlinear behavior since the light-induced convection was affected by the assembled particles and the assembly site around the imitation bubble was occupied with them. Although the number of assembled particles would be saturated beyond the limit of the space, the number of assembled particles was linearly increased in the low concentration.

In conclusion, we successfully measured the local fluorescence spectrum of the assembled dispersoids (polystyrene microparticles and bacteria) around the solid–liquid interface of a bubble-mimetic substrate after optical condensation, and the amount of assembled dispersoids was quantitatively determined based on the integrated local fluorescence intensity. The results showed that only several tens of assembled polystyrene particles were successfully detected by measuring the integrated local fluorescence intensity. By contrast, when the bacterial cell concentration was ∼107 cells/ml, bacteria could be detected by measuring the integrated fluorescence intensity. Since the fluorescence quantum yield of the used dye molecule (SYTO9) for staining bacteria was lower than that of green dye doped in polystyrene particles, fluorescence dyes with higher fluorescence quantum yields could enable more sensitive detection. In addition, integrated fluorescence intensity was found to be positively associated with the dispersion concentration. Therefore, the assembled dispersion could be evaluated by measuring the integrated fluorescence spectrum with a reflected spatial configuration. The advanced study using the results here will be applied in the quantitative analysis of very small molecules, such as bacterial metabolites or fluorescent molecules, and will open the way to innovative biological analysis methods under the optically created high density condition avoiding thermal damage.

Additional supplementary material containing materials and methods and supplementary figures is available in the online version of the paper.

This work was supported by the JST-Mirai Program (Grant Nos. JPMJMI18GA and JPMJMI21G1), the Grant-in-Aid for Scientific Research (A) (Grant Nos. JP17H00856 and JP21H04964), the Grant-in-Aid for Scientific Research (B) (Grant No. JP18H03522), the JST FOREST Program (Grant No. JPMJFR201O), NEDO Intensive Support for Young Promising Researchers (Grant No. JPNP20004), the Scientific Research on Innovative Areas (Grant No. JP16H06507), the Grant-in-Aid for Early-Career Scientists (Grant No. JP20K15196), the Grant-in-Aid for JSPS Fellows (Grant No. JP21J21304) from JSPS KAKENHI, and the Key Project Grant Program of the Osaka Prefecture University.

The authors have no conflicts to disclose.

T.I. and S.T. initiated the research and contributed equally to the study design. K.H., T.I., and S.T. performed the production of the bubble-mimetic substrate and the light-induced assembly of bacteria. K.H., M.T., and T.I. carried out theoretical calculations. K.H., T.I., and S.T. prepared the figures and manuscript. All the authors discussed the results and commented on the manuscript.

Kota Hayashi: Data curation (equal); Formal analysis (equal); Funding acquisition (equal); Investigation (equal); Methodology (equal); Validation (equal); Visualization (equal); Writing – original draft (equal). Mamoru Tamura: Formal analysis (equal); Funding acquisition (equal); Methodology (equal); Software (equal); Validation (equal); Writing – original draft (equal). Shiho Tokonami: Conceptualization (equal); Funding acquisition (equal); Project administration (equal); Supervision (equal); Validation (equal); Writing – original draft (equal). Takuya Iida: Conceptualization (equal); Funding acquisition (equal); Investigation (equal); Methodology (equal); Project administration (equal); Supervision (equal); Validation (equal); Writing – original draft (equal); Writing – review & editing (equal).

The data that support the findings of this study are available within the article and its supplementary material.

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Supplementary Material