Latest revision as of 11:56, 1 October 2024

Thiosulfate biosensor-B

Similar to thiosulfate biosensor-A, this biosensor detects thiosulfate and triggers a specific response, such as the expression of a fluorescent reporter or therapeutic protein. Thiosulfate Biosensor-B (BBa_K5084013) is an optimized version of Thiosulfate Biosensor-A(BBa_K5084012), designed to detect thiosulfate in environmental or biological samples.

Description

ThsS and ThsR are two key proteins that form a two-component system, widely used in bacteria to sense and respond to external environmental signals. ThsS is a membrane-bound sensor kinase that detects thiosulfate (S2O3²⁻). When ThsS binds to thiosulfate via its sensing domain, it undergoes a conformational change and initiates an autophosphorylation process, which occurs on its intracellular kinase domain. The phosphorylated ThsS then transfers the phosphate group to ThsR, which is located in the cytoplasm.ThsR is the response regulator in this system, acting as a transcription factor to control gene expression. Once ThsR is phosphorylated by ThsS, it becomes activated and binds to specific DNA sequences, typically located in the promoter regions of target genes. This binding can either activate or repress the transcription of downstream genes, triggering a cellular response. This mechanism allows the cell to rapidly react to changes in thiosulfate concentrations in the environment(Zou et al., 2023).

Figure 1. Sensing System Schematic.

We engineered the promoter and ribosome binding site (RBS) to optimize the performance of the biosensor. The replacement of the promoter allowed for precise regulation of gene transcription levels, while RBS optimization enhanced translation efficiency, leading to increased protein expression. In relevant studies, Yang et al. (2022) regulated the expression ratio of DcuS and DcuR using a panel of promoter-5’ UTR complexes with gradient strength, discovering that an optimal expression ratio of 46:54 was most effective. Similarly, Ding et al. designed an RBS library to fine-tune the translation of transcription factors and reporter proteins, significantly influencing the dynamic range, and used a deep learning platform (CLM-RDR) to achieve a 72.2% prediction accuracy. Based on these findings, we replaced the promoter of ThsR in our project and optimized the RBS sequences of both ThsS and ThsR to enhance their translation efficiency. These adjustments resulted in an improved thiosulfate biosensor that displayed higher sensitivity in detecting changes in thiosulfate concentration, outperforming the original version.

Figure 2. Comparison of the key differences between Thiosulfate biosensor-A and Thiosulfate biosensor-B.

Usage and Biology

Thiosulfate Biosensor-B (BBa_K5084013) is an optimized version of Thiosulfate Biosensor-A(BBa_K5084012), designed to detect thiosulfate in environmental or biological samples. This biosensor is based on a two-component signal transduction system, consisting of the membrane-bound sensor kinase ThsS and the response regulator ThsR. When ThsS senses thiosulfate, it undergoes autophosphorylation and transfers the phosphate group to ThsR, activating it. The activated ThsR then triggers the expression of downstream reporter genes, producing a fluorescent signal for quantitative detection. In Thiosulfate Biosensor-A, standard promoters and ribosome binding sites (RBS) were used, and the expression levels of ThsS and ThsR showed a certain degree of sensitivity when detecting thiosulfate in the environment. However, the dynamic range and response speed were relatively low, limiting the sensor’s accuracy under low concentration conditions. To improve the sensitivity and response speed of the sensor, we designed and constructed Thiosulfate Biosensor-B with the following optimizations: 1. Promoter optimization: We replaced the ThsR promoter with the strong promoter BBa_J23100, ensuring high expression of ThsR and enhancing its ability to respond to signals. 2. RBS optimization: We adjusted the ribosome binding sites for both ThsS and ThsR, using BBa_K5084008 and BBa_K5084007, respectively. This allowed us to fine-tune the translation efficiency of both proteins and balance their expression levels, ensuring optimal sensor performance.

Figure 3. The gene circuit of thiosulfate biosensor-B.

These optimizations enabled Thiosulfate Biosensor-B to exhibit significantly higher sensitivity and faster response to thiosulfate. The improved biosensor B was constructed into the pSB1A3 plasmid and transformed into Escherichia coli BL21(DE3) via electroporation for expression. BL21 was chosen due to its efficient protein expression capability, making it an ideal host strain.

Characterization

Thiosulfate Biosensor Optimization and Evaluation

To evaluate the performance of Thiosulfate biosensor-B, we conducted multiple rounds of screening and functional tests. The testing method was identical to that used for Thiosulfate biosensor-A: the engineered bacteria were inoculated into LB medium containing varying concentrations of sodium thiosulfate (0 mM and 1 mM) and incubated at 37℃ for 8 hours. After incubation, fluorescence intensity (excitation at 584 nm, emission at 607 nm) and OD600 were measured using a microplate reader, and the normalized fluorescence ratio (Fluorescence/OD600) was calculated. As shown in Figure 4, by optimizing the promoter and RBS, we developed Thiosulfate biosensor-B with improved sensitivity. Further testing will assess its performance in more complex environments and conditions.

Figure 4. Comparison of normalized fluorescence ratios before and after the optimization of the thiosulfate biosensor.The results demonstrated that both biosensors, A and B, exhibited low and comparable fluorescence signals in the absence of thiosulfate, indicating minimal background noise without the target molecule. However, Thiosulfate biosensor-B showed a significantly higher response to 1 mM sodium thiosulfate compared to Thiosulfate biosensor-A, with markedly increased fluorescence intensity. This indicates that the adjustments to the promoter and RBS sequences successfully enhanced the sensitivity of Thiosulfate biosensor-B.

Dose-Dependence Analysis of Thiosulfate Biosensor-B

To evaluate the dose-dependent response of Thiosulfate Biosensor-B, we tested its fluorescence output at varying concentrations of sodium thiosulfate (0, 0.125, 0.25, 0.5, and 1 mM). Engineered E. coli strains were inoculated into LB medium with different sodium thiosulfate concentrations and incubated at 37°C for 8 hours. Fluorescence intensity and OD600 were measured, and the normalized fluorescence ratio (Fluorescence/OD600) was calculated for each condition. As shown in Figure 5, the fluorescence signal increased with the concentration of thiosulfate. At 0 mM thiosulfate, the fluorescence signal was low, indicating minimal background activity. At higher thiosulfate concentrations (0.125 mM to 1 mM), the normalized fluorescence ratio increased significantly, demonstrating a strong dose-dependent response. This indicates that Thiosulfate Biosensor-B can accurately detect a wide range of thiosulfate concentrations with improved sensitivity.

Figure 5. Fluorescence response of Thiosulfate Biosensor-B at different thiosulfate concentrations. As shown in the Figure 5, the normalized fluorescence ratio increased as the concentration of thiosulfate increased. At 0 mM thiosulfate, the fluorescence signal is very low, with an average of 15.79, indicating that the sensor is not activated. At a concentration of 0.125 mM, the fluorescence ratio increases sharply to 3449.43, showing a clear response to low concentrations of thiosulfate. At 0.25 mM, the fluorescence signal continues to increase, reaching an average of 4900.49, demonstrating a stronger dose-dependence. At 0.5 mM, the fluorescence signal nears saturation, with an average of 6079.88, indicating that the sensor’s response is close to its maximum. At 1 mM thiosulfate, the fluorescence signal is 6236.64, and the curve begins to plateau, suggesting that the sensor’s response has stabilized at high concentrations.

Specificity Analysis of Thiosulfate Biosensor-B

To ensure the specificity of Thiosulfate Biosensor-B, we tested its response to other sulfate-based compounds, including sodium sulfate, sodium sulfite, and sodium tetrathionate, to determine if the biosensor is selective for thiosulfate. The engineered E. coli strains were inoculated into LB medium containing 1 mM of each compound and incubated at 37°C for 8 hours. Fluorescence intensity and OD600 were measured, and the normalized fluorescence ratio (Fluorescence/OD600) was calculated. As shown in Figure 6, Thiosulfate Biosensor-B exhibited a strong fluorescent response only to sodium thiosulfate, while the response to other sulfate-based compounds was minimal. This demonstrates that Thiosulfate Biosensor-B is highly specific for thiosulfate, with negligible cross-reactivity to similar compounds, making it a reliable tool for thiosulfate detection in complex environments.

Figure 6. Specificity analysis of Thiosulfate Biosensor-B.The specificity analysis shows distinct differences in the biosensor’s response to various sulfate-based compounds: The biosensor exhibited very low responses to sulfate and sulfite, with average normalized fluorescence ratios of 22.23 ± 3.61 and 25.08 ± 7.28, respectively. These results confirm that the biosensor is not activated by these compounds, demonstrating high specificity and minimal false-positive potential. The biosensor showed a moderate response to tetrathionate, with an average fluorescence ratio of 1027.88 ± 96.92. This response indicates some cross-reactivity, but given that tetrathionate is also an important biomarker for inflammatory conditions, this level of response is acceptable. The biosensor exhibited a strong response to thiosulfate, with an average normalized fluorescence ratio of 5853.38 ± 360.09, significantly higher than the responses to other compounds. This confirms that the biosensor is highly sensitive and specific to thiosulfate, with minimal interference from structurally similar compounds.

β-Galactosidase Activity in Engineered Strains Using the ONPG Method

In order to colourise human stool, we added LacZ downstream of the sensory system (BBa_K5084024). We first synthesized the thiosulfate operon, including the ThsS and ThsR genes, and coupled them with the LacZ gene (encoding β-galactosidase) using the PphsA promoter. These gene fragments were cloned into the pSB1A3 plasmid. The plasmid construction was verified through sequencing (Qingke, China). After successful validation, the plasmid was transformed into E. coli DH5α. Appropriate amount of overnight cultured bacterial solution was inoculated into fresh LB medium at 1:100 ratio, and different concentrations of thiosulfate were added. β-galactosidase activity was measured using a β-galactosidase reporter gene assay kit (AKSU042M, boxbio).The yellow product (ortho-nitrophenol, ONP) from the hydrolysis of ONPG was used to measure the fluorescence value (OD400), allowing the calculation of enzyme activity. A standard curve (3 repetitions) was established using a standard material, and the unit of enzyme activity was defined as OD600=1 1 nM ONPG produced by bacteria per hour. The results show that we successfully expressed β-galactosidase in engineered E. coli DH5α and confirmed its ability to degrade X-gal. Future work will focus on expressing it in E. coli Nissle 1917 to optimize its use as an oral product.

Figure 7. The β-galactosidase activity of PphsA-LacZα. (A) ONPG standard curve. (B) The OD400 values at different concentrations of thiosulfate. (C)The enzyme activity under different concentration of thiosulfate. (D) Generation of o-Nitrophenol in ONPG Assay for β-Galactosidase. (E) X-gal reaction: blue product intensity as an indicator of enzyme activity. The Figure 7A shows a positive correlation between OD400 and the amount of ONPG substrate hydrolyzed. The linear regression equation is Y=0.004543X-0.06551, which means we can caculate the concentration of ONPG by mesure the OD400. The Figure 7B shows the OD400 values at different concentrations of thiosulfate. By bringing it into the linear regression equation, we can get the ONPG concentration corresponding to each sample. According to the formula of enzyme activity unit, the enzyme activity under different concentration of thiosulfate was calculated(Figure 11C).With the increase of thiosulfate concentration, the enzyme activity also increased.Through the addition of X-gal, we successfully observed the blue color reaction produced by β-galactosidase.(Figure 7E).

Potential application directions

Thiosulfate Biosensor-B has several potential applications due to its high sensitivity and specificity. It can be used for environmental monitoring, particularly in detecting thiosulfate pollution in wastewater and industrial effluents. In medical diagnostics, it could help detect abnormal sulfur compound levels related to metabolic disorders. Additionally, it has applications in industrial process control, optimizing thiosulfate levels in bioreactors, and improving agricultural practices by monitoring soil health. Thiosulfate Biosensor-B also holds promise in synthetic biology research, serving as a valuable tool for developing biosensors for sulfur-containing compounds.

Sequence and Features

Reference

Zou Z P, Du Y, Fang T T, et al. Biomarker-responsive engineered probiotic diagnoses, records, and ameliorates inflammatory bowel disease in mice[J]. Cell Host & Microbe, 2023, 31(2): 199-212. e5.

Yu W, Xu X, Jin K, et al. Genetically encoded biosensors for microbial synthetic biology: from conceptual frameworks to practical applications[J]. Biotechnology Advances, 2023, 62: 108077.

Yang H, Yang X, Lu Y, et al. Engineering a fumaric acid-responsive two-component biosensor for dynamic range improvement in Escherichia coli[J]. Systems Microbiology and Biomanufacturing, 2022, 2(3): 533-541.

Ding N, Yuan Z, Zhang X, et al. Programmable cross-ribosome-binding sites to fine-tune the dynamic range of transcription factor-based biosensor[J]. Nucleic Acids Research, 2020, 48(18): 10602-10613.