
Detective Engineering Bacteria: Let Pseudomonas aeruginosa Have No Place to Hide in Water
Abstract
This project aims to develop an efficient, specific, and low-cost tool for detecting pathogenic bacteria in water. Using synthetic biology approaches, we engineered Escherichia coli to construct a biosensor capable of specifically detecting Pseudomonas aeruginosa. The sensor detects the presence of the target bacterium through triple verification—by sensing the quorum-sensing signal molecule PQS, the virulence factor pyocyanin (PYO), and the resistance to triclosan—thereby greatly improving the accuracy of detection. We designed the system based on a mature enzyme-substrate platform, enabling on-site, rapid, and quantitative detection of water samples.
1. Background
1.1 Pseudomonas aeruginosa and its hazardsPseudomonas aeruginosa is a common Gram-negative opportunistic pathogen widely distributed in soil, water, and hospital environments. It exhibits strong environmental adaptability and intrinsic resistance and is one of the main pathogens causing nosocomial infections. Especially in burn patients, cystic fibrosis (CF) patients, and immunocompromised individuals, it can cause severe or even fatal infections such as pneumonia, sepsis, and soft tissue infections [1]. In addition, its presence in food and drinking water poses a major public health concern. According to the China National Food Safety Standard for Drinking Natural Mineral Water (GB 8538-2016), five samples should be collected from the same batch of products, and Pseudomonas aeruginosa must not be detected in any 250 mL sample. However, existing conventional detection methods still have limitations in sensitivity, timeliness, or complexity, which pose challenges for comprehensive and efficient monitoring.
1.2 Current detection methods and their shortcomingsThe mainstream methods for detecting Pseudomonas aeruginosa currently on the market include:
Traditional culture method:
The China National Food Safety Standard for Drinking Natural Mineral Water uses selective media (such as CN agar) for isolation and identification. This method is regarded as the "gold standard" and can achieve accurate quantification through colony counting, but it is time-consuming, usually requiring 48–72 hours to obtain results, and thus cannot meet the needs for rapid detection.
Molecular biology methods (e.g., PCR):
These detect specific gene fragments (such as lasR, oprL). They have high sensitivity and speed but are mainly used for qualitative or semi-quantitative detection and are difficult to use for precise quantification; they also require expensive instruments, professional operators, and complex DNA extraction steps, making them difficult to apply on-site in resource-limited settings.
Immunological methods (e.g., ELISA):
These use antibodies to detect specific antigens. They also require professional equipment, and the preparation and preservation of antibodies are costly, with a risk of cross-reactivity. Like molecular methods, they can only perform qualitative or semi-quantitative detection.
Enzyme substrate method:
A rapid detection technology based on specific bacterial enzymatic reactions. It can achieve quantitative detection through the most probable number (MPN) method, and the operation is relatively simple and rapid. However, the cost of dedicated enzyme-substrate culture bottles, pre-prepared media, or quantification plates is much higher than that of traditional methods.
The common shortcomings of these methods are: complex operation, long time consumption, high cost, or dependence on large-scale laboratory equipment, making them unsuitable for on-site, real-time, high-throughput screening of water pollution. Therefore, the development of a rapid, simple, low-cost, and reliable detection technology is urgently needed.
2. Design concept
We drew on the mature enzyme-substrate method currently used for the quantitative detection of Escherichia coli. The principle of this technology is: the target bacterium contains the lacZ and gus (also known as uidA) genes, which can express β-galactosidase and β-glucuronidase. These two enzymes can decompose the colorless substrates o-nitrophenyl-β-D-galactopyranoside (ONPG) and 4-methylumbelliferyl-β-D-glucuronide (MUG) [4] to produce a yellow observable signal and a fluorescent reaction under 365 nm ultraviolet light, respectively. We plan to transform this system from "constitutive expression" to "inducible expression", i.e., reporter gene expression is initiated only when our engineered bacteria sense the characteristic signals of Pseudomonas aeruginosa. Our core design concept is to use synthetic biology to engineer Escherichia coli so that it can recognize the unique biological characteristics of Pseudomonas aeruginosa, and to use the lacZ and gus genes as reporter genes to convert the recognition signals into easily detectable colorimetric and fluorescent reactions. In addition, we utilize the difference in triclosan sensitivity between Pseudomonas aeruginosa and wild-type Escherichia coli to use triclosan to eliminate the influence of other strains, especially wild-type E. coli, thereby achieving specific and quantitative detection of the target bacterium.
2.1 Selection and modification of the chassis strain
If the engineered vector escapes accidentally, it may cause gene pollution and the spread of antibiotic resistance through horizontal transfer of foreign genes or resistance genes.
To prevent this, we adopted a physical containment strategy based on a conditionally replicating plasmid. The specific scheme is to construct the gene circuit using the replication origin of the pORI280 plasmid, which is a conditionally replicating plasmid whose replication strictly depends on the RepA protein encoded by the repA gene from the Lactococcus lactis (L. lactis) pWV01 plasmid. However, pORI280 itself does not carry the repA gene, so it cannot replicate or persist in ordinary E. coli. The host strain we chose is Escherichia coli EC1000, whose genome has been integrated with a helper plasmid providing the RepA protein, making it the only host in which pORI280 can replicate. This "lock-and-key" pairing design, relying on the conditional replication property of the plasmid, ensures that any vector escaping into the natural environment cannot replicate due to using the replication origin of pORI280, fundamentally eliminating the risks caused by plasmid escape.
In the design of the gene circuit for this project, we chose the lacZ and gus genes as reporter genes. This requires that the host strain itself does not express these two endogenous genes to avoid background interference. The engineered strain we selected—Escherichia coli EC1000—has been artificially modified to delete the lacZ gene (ΔlacZ), which fully meets the requirement for using lacZ as a reporter gene. However, its gus gene is still retained. Therefore, before using gus as a reporter gene, we deleted the gus gene of Escherichia coli EC1000 (Δgus) through homologous recombination to ensure that the detection signal originates from the reporter gene on the plasmid rather than from the genomic background.
2.2 Target selection: Three specific characteristics of Pseudomonas aeruginosa
To construct a biosensing platform for highly specific and sensitive identification of Pseudomonas aeruginosa in complex microbial communities, our target selection is based on an in-depth analysis of the molecular signatures and intrinsic physiological characteristics of Pseudomonas aeruginosa. We abandoned universal markers and instead focused on three key features that are highly exclusive in terms of phylogeny and pathological biology, using them as the core criteria for multiple verification:
Specific signal molecule PQS:
PQS (Pseudomonas Quinolone Signal) is a key signal molecule in the quorum-sensing system of Pseudomonas aeruginosa and is extremely rare in other common aquatic bacteria.
Specific virulence factor PYO:
Pyocyanin (PYO) is a unique blue phenazine toxin produced by Pseudomonas aeruginosa and is both a key virulence factor and a biomarker.
Specific resistance:
Pseudomonas aeruginosa has high natural tolerance to the antibacterial agent triclosan [8], while most other bacteria that can express lacZ and gus genes (including E. coli) do not.
2.3 Genetic circuit design
The core of this system is the construction of an integrated genetic circuit, which ensures extremely high specificity for Pseudomonas aeruginosa recognition through multi-level logic gating. The circuit consists of three functional modules, integrated into the engineered Escherichia coli chassis cell.
Module 1: PQS-responsive transcriptional activation circuit
This module is designed to specifically sense the characteristic signal molecule PQS of Pseudomonas aeruginosa. We heterologously express the transcriptional regulatory protein PqsR from Pseudomonas aeruginosa in the chassis cell. When PQS in the environment diffuses into the cell, it specifically binds to the PqsR protein to form an active transcriptional complex. This complex can efficiently activate the downstream artificially designed PpqsA promoter. We place the lacZ reporter gene under the control of this promoter. Therefore, the presence of PQS will directly trigger the expression of lacZ, whose encoded β-galactosidase can catalyze the decomposition of the colorless substrate ONPG to produce an observable yellow product, thereby achieve signal detection by colorimetry.
Module 2: PYO-responsive multiple transcriptional activation circuit
To specifically detect the signature virulence factor PYO of Pseudomonas aeruginosa, we constructed three independent candidate sensing circuits in parallel for optimization and screening. Each circuit is based on a unique PYO-sensing protein—SoxR, MexL, and BrlR—which can specifically recognize and bind PYO molecules. The binding event between PYO and the protein is converted into a conformational change, which then activates their respective specific promoters—PmexG, PphzA1, and PbrlR. We connected each of these three promoters to the universal gus reporter gene. The gus gene encodes β-glucuronidase, which can catalyze the hydrolysis of MUG to produce a strong blue fluorescent signal. Through parallel evaluation, we will select the single circuit with the best response performance as the final PYO detection module. This "multiple candidates, one selection" design strategy aims to ensure the system has the highest detection sensitivity and reliability.
Module 3: Triclosan resistance-based conditional survival and background elimination module
To ensure that the entire detection system is not interfered with by other microorganisms in the environment, especially E. coli, we introduced strict selective pressure. On the sensor plasmid, in addition to the sensing circuits, we also integrated a resistance gene (fabV) that confers triclosan resistance. Adding triclosan to the detection system can achieve two purposes:
1. Selective enrichment: Only Pseudomonas aeruginosa, which is naturally tolerant to triclosan, and our engineered bacteria carrying the resistance gene can grow, while other strains in the sample are effectively inhibited.
2. Background elimination: This step can exclude other coliform bacteria that may exist in the environment and carry their own lacZ or gus genes, ensuring that the reporter signal originates solely from the engineered bacteria's response to the markers of Pseudomonas aeruginosa, thereby greatly reducing false positives.
Logical integration and output:
We designed the PQS and PYO sensing circuits as a dual-verification system, which requires both circuits to produce positive signals to confirm the presence of Pseudomonas aeruginosa, ensuring higher specificity. Ultimately, these two sensing signals will respectively trigger the expression of β-galactosidase and β-glucuronidase, which can decompose specific substrates to produce a yellow observable signal and a blue fluorescent reaction under 365 nm ultraviolet light, facilitating visual interpretation and quantitative analysis of Pseudomonas aeruginosa.
2.4 Detection process and quantification principle: MPN method based on 97-well quantification plate
To achieve accurate quantification of Pseudomonas aeruginosa in water samples, we adopted the principle of the most probable number (MPN) method and designed a matching 97-well quantification plate (Figure 1), which contains several large wells and small wells.
The specific detection process is as follows:
Sample mixing and inoculation: Mix the water sample to be tested with detection reagents (PB medium, lyophilized engineered bacteria, substrates (ONPG and MUG), and triclosan), and then evenly add the mixture to each well of the quantification plate.
Cultivation and reaction: Incubate the quantification plate at 37 °C for 6–12 hours. During this process, if the water sample contains Pseudomonas aeruginosa, it will release PQS and PYO.
Dual signal activation: After sensing these specific signals, the engineered bacteria will activate the genetic circuit, express β-galactosidase and β-glucuronidase, and further decompose the substrates.
Result interpretation: After cultivation, interpret the results with the naked eye. Positive wells will show two signals simultaneously: a yellow color change (ONPG decomposition) and blue fluorescence under 365 nm ultraviolet light (MUG decomposition). Only wells showing both signals are counted as valid positive wells.
Quantitative calculation: Count the number of dual-signal positive wells among the large wells and small wells respectively and based on a pre-established most probable number lookup table, calculate the original concentration of Pseudomonas aeruginosa in the water sample.
This method combines the high specificity of biosensing with the reliability of MPN statistics, enabling low-cost, high-throughput on-site quantitative detection without the need for expensive equipment.
3. (Expected) Results
Through the above design, we expect to obtain the following results:
3.1 High specificityThrough the above design, we expect to obtain the following results:
3.1 High specificityThrough triple verification (PQS + PYO + triclosan screening), our system can effectively distinguish Pseudomonas aeruginosa from other common aquatic bacteria (such as Escherichia coli, Legionella pneumophila, etc.), minimizing false positive results.
3.2 High sensitivityBased on the principle of quorum-sensing signal amplification, our engineered bacteria can sense low concentrations of PQS and PYO, meeting the needs of actual water sample detection.
3.3 Rapid and convenientThe entire detection process does not require complex instruments. After adding the sample to the detection reagent containing PB medium, engineered bacteria, substrates, and triclosan, results can be directly read through color changes within 6–12 hours, significantly shortening the time compared with traditional culture methods.
3.4 Quantitative capabilityThe quantitative capability of this detection system is based on the principle of the most probable number method. By using a 97-well quantification plate, positive results are represented by the simultaneous appearance of yellow coloration and blue fluorescence in specific wells. After detection, count the number of dual-signal positive wells among the large and small wells respectively, and based on a pre-calibrated most probable number lookup table, accurately calculate the concentration of Pseudomonas aeruginosa in the water sample.
3.5 Application prospectsThe biosensor kit developed in this project is low-cost and simple to operate, making it highly suitable for on-site rapid screening and monitoring in water treatment plants, food processing plants, hospital environments, and field water sources, and has great market application potential and public health value.
4. Conclusion
We propose an innovative, reliable, and practical solution for the detection of Pseudomonas aeruginosa. By cleverly using synthetic biology design, we convert the specific biological characteristics of pathogenic bacteria into intuitive detection signals, providing a unique iGEM-style approach to solving real-world microbial contamination problems.
References
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