[Materials]

Reagent	Equipment
ddH2O	round-bottomed flask
HAuCl4	magnetic stirrer
sodium citrate	pH meter
Phosphate Buffered Saline (pH 8.0)	high-speed centrifuge
purified PBP (TFP and TSP)	shaker
potassium carbonate	spectrophotometer
1% BSA solution	smartphone with camera
E. coli	Incubator
Salmonella	near-infrared light (808 nm)
LB liquid medium	thermal imaging camera (TIC)
LB solid medium	biological safety cabinet

[Procedures]
1.AuNP preparation by sodium citrate reduction
a. Add 100 mL of ultra-pure water to a round-bottom flask.
b. Add 1 mL of 10 mg/mL HAuCl4 solution to the flask. Place the flask on a magnetic stirrer and heat the mixture to boiling, allowing it to reflux.
c. After the mixture reaches boiling, add 1 mL of 10 mg/mL sodium citrate solution to the flask.
d. Continue stirring and heating until the solution turns a deep purple-red color, indicating the formation of gold nanoparticles.
e. Continue heating and stirring for an additional 10 min to ensure complete reaction.
f. Remove the flask from the heat and allow the solution to cool to room temperature. Store the solution at 4°C in the dark for future use.

2.Preparation of AuNP@PBP
a. Adjusting pH of AuNPs Solution: Take 1 mL of the AuNPs solution prepared in the previous steps. Then gradually add 7-8 μL of 100 mM potassium carbonate solution to adjust the pH to 8.0. Monitor pH carefully.
b. Add 100 μg of PBP protein to the pH-adjusted AuNPs solution. Incubate the mixture in a shaker at room temperature for 30 min to allow protein binding.
c. Centrifuge the mixture at 12,000 rpm for 5 min at 4°C. Then carefully discard the supernatant to remove unbound protein.
d. Add 1% BSA solution to resuspend the pellet and incubate at room temperature for 30 min to block any remaining binding sites on the AuNPs.
e. Centrifuge again at 12,000 rpm for 5 min at 4°C and discard the supernatant.
f. Resuspend the AuNPs@PBP pellet in 333 μL of PBS buffer.
g. Scan the full wavelength range to determine the maximum absorption peak of the AuNPs@PBP solution using a spectrophotometer.
h. Note that AuNPs typically have a maximum absorption peak at 530 nm. Successful conjugation with PBP protein should result in a red shift of 2-3 nm in the absorption peak.
i. Store the conjugated AuNPs@PBP solution at 4°C for future use.
3.Bacteria detection of AuNP@PBP
1) Preparation of Bacterial Suspension
a. Cultivate the target bacteria to achieve an OD600 of 1 (approximately 10^9 CFU/mL).
b. Collect the bacterial cells by centrifuging the culture and discard the supernatant.
c. Resuspend the bacterial pellet in PBS and adjust the suspension to an OD600 of 1 (approximately 10^9 CFU/mL).
d. Perform serial dilutions in PBS to achieve concentrations ranging from 10^3 to 10^9 CFU/mL.
2) Add 200 μL of each bacterial dilution to 100 μL of AuNPs@PBP solution and incubate the mixtures at room temperature for 30 min. Include appropriate controls, such as pET28a empty vector controls, to validate the assay specificity and accuracy.
3) After incubation, Transfer 200 μL of the supernatant into new 1.5 mL centrifuge tubes for imaging.
4) Imaging and Data Collection:
a. Assemble the smartphone and lightbox setup. Ensure the lightbox is equipped with a white LED light tube and black curtains to minimize external light interference.
b. Place the centrifuge tubes containing the supernatant in the lightbox. Capture images of the samples using the smartphone camera.
5) Data Analysis
a. Extract the RGB values from the captured images using the RGB analysis software or app.
b. Generate a standard curve based on the RGB values corresponding to known bacterial concentrations.
c. Import the standard curve into the app for subsequent analysis.

As shown in Figure 3, the negative control AuNP@pET28a bound to E. coli and Salmonella, both with no color change, while AuNP@TFP and AuNP@TSP incubated with different concentrations of E. coli and Salmonella, respectively, and the reaction supernatant changed from purple-red to colorless as the concentration of the bacteria increased, illustrating the specificity of AuNP in detecting bacteria.

Subsequently, we performed an RGB color analysis of the results of AuNPs@TFP and AuNPs@TSP (Table 1, 2). There is a correspondence between the increase in bacterial concentration and the corresponding B/R values. As a result, we obtained a standard curve between the logarithmic values of bacterial concentration and B/R. (Figure 4) For AuNP@TFP, the standard curve was y=0.0125x+1.0404 (R2=0.9583), and for AuNP@TSP, the standard curve was y=0.00098x+1.0684 (R2=0.9804).

To detect bacterial concentration by smartphone, we built the standard curve obtained from the experiment into the smartphone APP. After taking a picture to record the incubation supernatant of bacteria with AuNP@TFP or AuNP@TSP, we uploaded the picture to the APP, which will automatically read the RGB value of the picture and calculate the B/R value, and finally show the corresponding bacterial concentration according to the standard curve (Figure 5). The main code of the Bacteria Detection App can be found in the appendix material at the end of the document.

4.Photothermal sterilization of AuNP@PBP
a. The bacterial solution was diluted to a concentration of 10^6 CFU/mL and reacted with the above AuNP@PBP detection method for bacteria.
b. After the above detection part was reacted for 30 min at room temperature, the sample tube was irradiated under near-infrared light (NIR) with a wavelength of 808 nm and a power of 2 W for 10 min (at a distance of 8 cm).
c. The temperature rise of the samples after NIR treatment was monitored using a photothermal camera.
d. Plates were coated with the irradiated samples and incubated at 37°C overnight.
e. Bacterial survival was determined by plate counting method.

The experimental results showed that the temperatures of AuNPs@TFP and AuNPs@TSP gradually increased (28℃-45℃) with the increase in irradiation time (0-10 min). The treated samples were subjected to plate-coating operation and after incubation overnight, we found that the number of bacteria decreased, indicating the effectiveness of photothermal sterilization (Figure 6).

1. Detection Sensitivity:

Our project demonstrates high sensitivity in detecting bacteria by using the colorimetric change of AuNP@TFP and AuNP@TSP. The clear correlation between bacterial concentration and B/R values, as shown in the standard curves (R² > 0.95), supports the precision of this method. The ability to detect varying concentrations of E. coli and Salmonella via visual color shifts is particularly valuable for early detection of pathogens, making it a promising tool for food safety monitoring.

2. Detection Reproducibility:

The smartphone app, by automating RGB analysis, enhances repeatability by reducing human error in interpreting results. In future plans, we intend to integrate a standard curve calibration module that will further improve reproducibility, especially under different environmental conditions, thus ensuring reliable bacterial detection.

3. Detection Versatility:

This biosensor system based on AuNP successfully targeted two major foodborne pathogens. This approach is adaptable and can be extended to other bacteria or even different molecular interactions by selecting the appropriate binding proteins. It provides a modular assay that can interact with other bacteria or even different molecules by selecting appropriate binding proteins. For example, rapid colorimetric detection can be achieved by linking AuNPs to specific aptamers that bind to viral proteins.

4. Safety Considerations:

Most current methods focus primarily on the identification of bacteria but often neglect the critical aspect of bactericidal efficacy. This can leave detected pathogens untreated, posing a continuing risk to food safety and public health. Therefore, the development of a dual-function method that both detects and kills pathogens is essential. The AuNP-based biosensor we use enables photothermal sterilization, effectively reducing the bacterial population. This integrated approach both recognizes and inactivates pathogens, thus ensuring safer results for food industry applications.

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