Foodborne pathogens are primarily transmitted via contaminated food and water. Their ingestion can lead to intestinal illness or toxicity. Therefore, rapid real-time detection of foodborne pathogens is crucial for food safety. Colorimetric assays have gained research attention for their simplicity, intuitive interpretation, and field deployability. In this study, we developed smartphone-based colorimetric detection1 of Bacillus cereus (BC) and Vibrio parahaemolyticus (VP) using bacterial binding proteins. Smartphone quantification of color changes enabled the determination of bacterial levels in test samples, meeting the criteria for point-of-care testing (POCT).
Figure 1 Design diagram of this project.Drawing under the guidance of Mr. Hong
Design
In order to study the colorimetric of Bacillus cereus (BC) binding proteins labeled with anti-His-HRP antibody and TMB substrate, we aimed to constructed a His-tagged BC autolysin cell wall binding domain (CBD) with the vector pET-28a.
The target gene fragment CBD sequence comes from the C-terminal cell wall binding domain of Bacillus cereus ATCC 14579 autolysin. Bacillus cereus, also known as cactus bacillus, is a Gram positive bacterium, β Hemolytic rod-shaped bacteria. Often found in soil and food, some strains can cause Fried Rice Syndrome.2 The fragment we used is a characteristic sequence of BC and was synthetic by the company Genscript.
The experimental design of this study is as follows:
1. Construction of plasmids pET28a-His-autolysinCBD
2. Expression and purification of autolysinCBD
3. Detection system optimization
4. Colorimetric detection with autolysinCBD
Build
We designed a plasmid encoding the BC autolysin cell wall binding domain (CBD) i.e., pET28a-His-autolysin CBD. To construct this plasmid, we first amplified the autolysin CBD fragment from the synthetic plasmid and obtained the pET28a vector by enzymatic digestion reaction at NdeI and XhoI sites. Then, we homologous recombined the autolysin CBD with the pET28a vector to generate the pET28a-His-autolysin CBD (Figure 2).
Figure 2 Mapping of pET28a-His-autolysinCBD plasmid.
The constructed plasmid was transformed into E. coli and plated on LB agar containing kanamycin. The plates were incubated at 37°C overnight. On the next day, it was observed that transformants grew on the plate, and we selected the transformants for colony PCR and sequencing. The colony PCR (autolysinCBD: 402 bp) and sequencing results verified the successful construction of the plasmid (Figure 3).
Figure 3 Colony PCR result and sequencing of pET28a-His-autolysinCBD transformants.
Test 1: Expression and purification of autolysinCBD
We inoculated the correctly sequenced transformant and subjected it to an expanded culture. When the cultures grew to OD600 0.6-0.8, they were induced with IPTG for 24 h. We lysed the cells by sonication, obtained the protein supernatant by centrifugation, and purified it by Ni-affinity chromatography. As shown in Figure 4, we successfully obtained purified autolysin CBD (15.3 KDa).
Figure 4 Expression and purification result of autolysinCBD.
Test 2: Detection system optimization
To improve the detection and to obtain optimal reaction conditions, we explored the two most important experimental conditions in the autolysinCBD detection system, i.e., the catalytic reaction time and the TMB substrate concentration. We first diluted the bacterial suspension to 106 CFU/mL and used different concentrations of TMB 0.01-0.05% (w/v) as the colorimetric substrate. The concentration of bacteria was determined at different times (0.5-2 h). The results showed that the optimal assay conditions were at 0.01% TMB for 1 h for autolysinCBD (Figure 5).
Figure 5 Optimal reaction conditions for the detection system.
Test 3: Detection of different concentrations of bacterial fluids
For testing the ability of the system to detect BC. We diluted overnight bacterial cultures of BC to 102-107 CFU/mL using PBS, and then 1 mL of each concentration was taken for the assay. The bacterial solutions were reacted under previously determined optimal conditions (Figure 5).
We performed curve fitting of the detection results, and the experimental results are shown in Figure 6. For BC bacteria, the fitted curve of the detection was y = 0.1922x - 0.1994 (R² = 0.9423), The detection values showed a favorable linear relationship with the concentration of the bacteria. However, it was also seen that when the concentration of the bacterium reached 107 CFU/mL, the detection value decreased instead, which suggested that we should control the concentration of the bacterium between 102-106 CFU/mL to obtain the best detection results when using this detection system.
Figure 6 Testing results of different concentrations of bacteria.
Learn
To detect BC pathogens using a colorimetric assay based on smartphone and bacterial binding proteins, we first recombinantly expressed and purified a bacterial binding protein (His-autolysinCBD). Per the results mentioned above, we can validate our theory as a success of the colorimetric detection by the binding proteins of BC. In order to implement our detection method, we need to conduct more experiments, including investigating the limit concentration of detection and the quantity relationship between RGB values of the test samples and the bacteria concentrations per the app development requirement.
Design
In order to study the colorimetric detection of Vibrio parahaemolyticus (VP) binding proteins labeled with anti-His-HRP antibody and TMB substrate, we aimed to constructed a His-tagged VP bacteriophage tail fiber protein (TFP) with the vector pET-28a.
The gene fragment TFP we used comes from the tail fiber protein (TFP) MS18 of Vibrio parahaemolyticus phage VPMS1. Vibrio parahaemolyticus is a marine bacterium that mainly comes from seafood such as fish, shrimp, crab, shellfish and seaweed. Consumption of food containing this bacterium can lead to food poisoning, also known as halophilic food poisoning. Clinically, acute abdominal pain, vomiting, diarrhea and watery stools are the main symptoms.3 The fragment we used is a characteristic sequence of VP and was synthetic by the company Genscript.
The experimental design of this study is as follows:
1. Construction of plasmids pET28a-His-MS18
2. Expression and purification of MS18
3. Detection system optimization
4. Colorimetric detection with MS18
Build
We designed plasmids encoding the VP phage tail fiber protein (MS18) i.e., pET28a-His- MS18. To construct this plasmid, we first amplified the MS18 fragment from the synthetic plasmid and obtained the pET28a vector by enzymatic digestion reaction at BamHI and XhoI sites. Then, we homologous recombined the MS18 with the pET28a vector to generate the pET28a-His- MS18 (Figure 7).
Figure 7 Mapping of pET28a-His-MS18 plasmid.
The constructed plasmid was transformed into E. coli and plated on LB agar containing kanamycin. The plates were incubated at 37 °C overnight. On the next day, it was observed that transformants grew on the plate, and we selected the transformants for colony PCR and sequencing. The colony PCR (MS18: 495 bp) and sequencing result verified the successful construction of the plasmid (Figure 8).
Figure 8 Colony PCR result and sequencing of pET28a-His-MS18 transformants.
Test
Test 1: Expression and purification of MS18
We inoculated the correctly sequenced transformant and subjected it to an expanded culture. When the cultures grew to OD600 0.6-0.8, they were induced with IPTG for 24 h. We lysed the cells by sonication, obtained the protein supernatant by centrifugation, and purified it by Ni-affinity chromatography. As shown in Figure 9, we successfully obtained purified MS18.
Figure 9 Expression and purification result of MS18.
Test 2: Detection system optimization
To improve the detection and to obtain optimal reaction conditions, we explored the two most important experimental conditions in the MS18 detection system, i.e., the catalytic reaction time and the TMB substrate concentration. We first diluted the bacterial suspension to 106 CFU/mL and used different concentrations of TMB 0.01-0.05% (w/v) as the colorimetric substrate. The concentration of bacteria was determined at different times (0.5-2 h). The results showed that the optimal assay conditions were at 0.04% TMB for 0.5 h for MS18 (Figure 10).
Figure 10 Optimal reaction conditions for detection systems.
Test 3: Detection of different concentrations of bacterial fluids
For testing the ability of the system to VP. We diluted overnight bacterial cultures of VP to 102-107 CFU/mL using PBS, and then 1 mL of each concentration was taken for the assay. The bacterial solutions were reacted under previously determined optimal conditions (Figure 10).
We performed curve fitting of the detection results, and the experimental results are shown in Figure 11. For VP bacteria, the fitted curve of the detection was y = 0. 1797x - 0.1067 (R² = 0.9775), The detection values showed a favorable linear relationship with the concentration of the bacteria. However, it was also seen that when the concentration of the bacterium reached 107 CFU/mL, the detection value decreased instead, which suggested that we should control the concentration of the bacterium between 102-106 CFU/mL to obtain the best detection results when using this detection system.
Figure 11 Testing results of different concentrations of bacteria.
Learn
The same as the cycle 1, it can be seen that this pathogenic bacteria detection system based on smartphone and bacterial binding protein has a good detection effect for both BC and VP pathogenic bacteria. It should not be overlooked that although the results of our experiments have a certain degree of accuracy and reliability, they still cannot be used in products directly based on current progress. In the detection of bacterial concentration, we initially obtained the upper and lower limits of the detection system, but this part of the results still needs to be repeatedly verified by experiments.
In addition, we also had a review of the whole experiment during which we encountered some problems. For example, the concentration of the plasmids we extracted was always very low, which could be caused by not using fresh enough bacteria. Another example is that the recovery rate of DNA fragments is low, to optimize this part of the experiment, we can obtain better and more gene materials for further research use.
1. Hong Bin, Li Yanmei, Wang Wenhai, Ma Yi, Wang Jufang. Separation and colorimetric detection of Escherichia coli by phage tail fiber protein combined with nano-magnetic beads[J]. Microchimica Acta,2023,190(6).
2. Ivanova Natalia, Sorokin Alexei, Anderson Iain, Galleron Nathalie, Candelon Benjamin, KapatralVinayak, Bhattacharyya Anamitra, Reznik Gary, Mikhailova Natalia, Lapidus Alla, Chu Lien, Mazur Michael, Goltsman Eugene, Larsen Niels, D'Souza Mark, Walunas Theresa, Grechkin Yuri, PuschGordon, Haselkorn Robert, Fonstein Michael, Ehrlich S Dusko, Overbeek Ross, KyrpidesNikos. Genome sequence of Bacillus cereus and comparative analysis with Bacillus anthracis. [J]. Nature,2003,423(6935).
3. Ramírez-Orozco Martín, Serrano-Pinto Vania, Ochoa-Álvarez Norma, Makarov Roman, Martínez-Díaz Sergio F. Genome sequence analysis of the Vibrio parahaemolyticus lytic bacteriophage VPMS1. [J]. Archives ofvirology,2013,158(11).