Overview

As our project progressed, we gradually realised that we needed to grow a large number of tomatoes, both wild-type and transgenic, to obtain sufficient data and accurate results. This raised two issues: First, to determine whether the experimental group tomatoes correctly expressed our target genes, we needed to conduct multiple rounds of testing. This resulted in a heavy workload in the laboratory -- our team members had to spend a significant amount of time on traditional and inefficient Western Blot (one day) and ELISA (three hours) experiments, not to mention the time required to purify samples from tomato specimens for testing. Simultaneously, we were very concerned about the sugar content in our tomatoes, but lacked a good method to characterize this indicator, relying only on electronic tongue sweetness results for estimation.

To address the first issue, we developed the HA-tag LFIA -- a Lateral Flow Immunoassay test strip -- using specific antibodies for the HA tag we marked on the Thaumatin. This allows us to quickly and accurately determine whether tomato plants express our target protein and even measure the protein expression levels. This is crucial for the further development of our tomatoes. If we hope for our tomatoes to enter the market, this test strip has the potential to significantly shorten the time from laboratory to market by improving experimental efficiency.

Fig 1a. Ha-tag LFIA Fig 1b. Sweetglow

Regarding the second issue, we recognized that this need for sugar detection is widespread: farmers want to know the sugar content of fruits, and people on diets want to avoid excessive calorie intake by detecting the sugar content in their drinks. Therefore, we aimed to develop a handheld device that can quickly and accurately detect the types and contents of sugars in liquids. Finally, we introduced SweetGlow, a common sugar detector based on lanthanide metal ester fluorescence, that can detect three or more types of sugar and accurately measure their concentrations within ten minutes.

HA-tag LFIA

Introduction

What is HA-tag LFIA ?

HA-tag LFIA is an innovative rapid protein detection method specifically designed to detect target proteins with HA tags. This detection system is based on traditional lateral flow chromatography technology and consists of five main components: sample pad, conjugate pad, nitrocellulose membrane, absorbent pad, and backing card. When a liquid sample containing the target protein is added to the sample pad, it flows along the test strip through capillary action. During this process, the HA-tagged protein in the sample specifically binds with pre-treated detection reagents and forms a detectable complex at the test line position. This method offers advantages such as simple operation, rapid detection (usually completed within minutes), relatively low cost, and no need for specialized equipment or technical personnel. It provides an efficient and convenient solution for the detection of HA-tagged proteins.

Why do we create HA-tag LFIA ?

In this project, we creatively constructed a tomato-based bio-manufacturing platform aimed at efficiently producing thaumatin protein. During the experimental process, we implemented a diversified transgenic strategy to obtain a more comprehensive and in-depth dataset. To verify the successful expression of target proteins in transgenic plants and effectively screen out unsuccessful transgenic plants, we had to rely on time-consuming and costly Western Blot (WB) and Enzyme-Linked Immunosorbent Assay (ELISA). The complexity and time-consuming nature of these detection methods, along with the high cost of reagents used, forced our experimental group to repeat them repeatedly, resulting in significant time costs and economic pressure.

Moreover, as a transgenic crop, the tomato variety in this project must undergo rigorous safety testing and final production trials before being officially marketed to ensure its safety, reliability, and stable yield. Considering that the "planting-testing-planting" cycle will be repeated during the trial process, and the final production trial needs to be conducted in test fields far larger than laboratory plant cultivation rooms, continuing to use the aforementioned cumbersome detection methods for selection and breeding would greatly extend the cycle from product development to commercialization, generate enormous costs, and place a heavy burden on experimental personnel. Therefore, exploring more efficient and simplified detection methods is of great significance for accelerating the commercialization process of this project's transgenic tomato variety.

Fig 2. From plants in the laboratory to large-scale cultivation

To address this issue, we designed the HA-tag LFIA strip. By using common HA tag antibodies to target the HA tag on proteins expressed by engineered plants, we achieved rapid quantitative detection of Thaumatin content in samples. This test strip can also be used for other protein samples that employ HA tags, demonstrating good scalability.

Where can HA-tag LFIA be applied ?

HA-tag LFIA, as an efficient and sensitive protein detection method, has enormous potential in multiple research and application fields. The following are its main application areas:

1. Agricultural Biotechnology: As a widely used tag in transgenic crop development, HA-tag LFIA can be used in multiple experimental projects for rapid screening of plants expressing target proteins. For example, in our project, it can efficiently detect the expression of thaumatin, significantly improving screening efficiency and shortening breeding cycles.

2. Molecular Biology Research: As a rapid alternative to Western Blot and ELISA, HA-tag LFIA can verify the expression of HA-tagged recombinant proteins in a short time. This greatly improves experimental efficiency and accelerates research progress.

3. Agricultural Field Trials: In large-scale field trials, HA-tag LFIA can be used for rapid evaluation of target trait expression in crop lines containing HA-tags. This in-situ detection method provides timely and accurate data, helping to optimize breeding strategies.

4. Medical Diagnostics: By detecting disease markers with HA tags, HA-tag LFIA has the potential to be developed into a rapid diagnostic tool. This is significant for diseases requiring timely diagnosis and treatment.

5. Environmental Monitoring: HA-tag LFIA can be used to detect specific protein contaminants in environmental samples. Its rapid and portable nature makes it a promising tool for on-site environmental monitoring, especially in monitoring HA-tagged biological sample leakage issues.

6. Quality Control in Molecular Biology Experiments: In molecular biology experiments, HA-tag LFIA can be used for rapid detection of target protein expression and purification effects, improving experimental efficiency and accuracy of expression quality control.

HA-tag LFIA combines the simplicity of lateral flow chromatography with the specificity of immunodetection, providing an efficient and economical protein detection solution for multiple fields.

Principle

Fig.3 LFIA test strip^[1]

A typical test strip consists of five parts: sample pad, conjugate pad, nitrocellulose membrane, absorbent pad, and backing card. The liquid sample flows along the test strip, forming detectable complexes at the test line, resulting in visible results. The control line is used to verify the reliability of the test strip^[2].

Sample Pad: The function of the sample pad is to deliver the sample to the lower end of the test strip. It is made of cellulose and/or glass fiber. The sample pad is sometimes used for sample pretreatment, such as separating sample components, removing interferents, adjusting pH, etc.

Conjugate Pad: This is the second pad that biological recognition molecules encounter in the test strip. The pad material is usually glass fiber, cellulose, polyester, and other materials that can immediately release conjugates upon contact with the moving liquid sample. Here, we have fixed colloidal gold-labeled HA-tag antibodies, and when the sample flows through, the HA-tag on the somatin protein will partially bind to the antibody.

Nitrocellulose (NC) Membrane: It is the largest pad in the test strip and has a significant impact on the sensitivity of the strip. The test line and control line are usually drawn on the nitrocellulose membrane. The function of the membrane is to provide support and help the capture probe bind well with the sample, while the sample and detection conjugate are guided through the membrane to the reaction area. To achieve this, the nitrocellulose membrane must have a uniform high adsorption capacity and also have certain pores to ensure capillary flow of aqueous samples. We have pre-fixed HA-tag antibodies on the membrane. Since our somatin protein has 3 HA-tags, the HA-tags that have not bound to the colloidal gold-labeled antibodies will bind to the fixed antibodies, anchoring on the test strip. When the concentration of accumulated protein reaches a certain level, it will appear red on the strip. To achieve quantitative detection, we have set up three test lines on the strip. The number of red test lines and the intensity of their color can achieve a certain degree of semi-quantitative detection.

Absorbent Pad: It is the last pad in the strip. Its function is like blotting paper, maintaining the flow rate of liquid through the membrane and preventing backflow of the sample.

Backing Card: Also known as the backing plate. All the above-mentioned pads are fixed on the backing card. It is used for strip assembly support and result reading.

All these pads are typically laminated to each other in sequence with a 2 mm overlap to ensure the liquid solution migrates through the LFA strip.

Product

Fig 4. HA-tag LFIA test strip

We have designed the HA-tag LFIA test strip with three parallel antibody detection lines fixed on the strip, enabling semi-quantitative detection of samples bound to colloidal gold-labeled antibodies that are dripped onto it. As the sample flows along the test strip with the diluent, it successively encounters the detection lines. As the sample is captured by the detection antibodies, its concentration gradually decreases, causing the colors of the detection lines to become successively lighter. Since the amount of sample that can be captured by a single detection line is relatively fixed, users can infer the approximate concentration of the antibodies based on this. In the future, we will develop a colorimetric application on mobile phones to make the quantitative detection process more accurate and convenient.

User Manual for HA-tag LFIA

Protocol

Sweetglow

Introduction

What is SweetGlow ?

SweetGlow is an innovative portable sugar detector based on the principle of fluorescence reaction between lanthanide metal esters and sugars. The device utilizes a unique combination of 3-nitrophenylboronic acid (3-NPBA) and lanthanide metal ester H(6)L/Tb(3+) to construct a highly sensitive three-dimensional fluorescence sensor array. Under 333 nm excitation light, H(6)L/Tb(3+) emits characteristic fluorescence signals at three eigenwavelength. When sugars in the sample undergo esterification reactions with 3-NPBA, it causes changes in the solution's pH, which in turn affects the fluorescence intensity of H(6)L/Tb(3+). By incorporating Principal Component Analysis (PCA) algorithm, SweetGlow can achieve high-precision detection and quantitative analysis of various sugars such as fructose, glucose, and sucrose in complex liquid environments. This innovative detection method overcomes the limitations of traditional sugar meters and chemical reagent methods, providing users with a fast, accurate, and portable sugar detection solution.

Why do we create SweetGlow ?

When testing tomato fruits, we often wondered about their sugar content: although tomatoes are not high-sugar fruits, we still wanted to know the potential impact of consuming tomatoes on our project's target population. We were curious about the relationship between the taste information obtained in electronic tongue tests, especially sweetness, and its sugar content. We wanted to know whether our target product, thaumatin, would affect the sugar content of tomatoes and what changes might occur. However, we couldn't find a good method to accurately measure the sugar content in tomatoes . Currently, the main measurement methods, apart from the cumbersome use of chemical reagents and expensive laboratory equipment, include relatively simple refractometer-based refractometer. However, the results obtained this way are highly inaccurate: refraction is easily affected by other non-sugar solutes and the properties of the liquid itself.

Fig 5. Refractometer

During our research, we discovered that this need for sugar detection is not unique to us: farmers need to test the sugar content in fruits during harvest (usually more sugar means sweeter); people on diets want to know how much sugar in their drinks might increase calorie intake, avoiding falling into a "calorie trap"; diabetics have an even more urgent need for a device that can help them detect sugar content. Not all sweet substances are harmful, but to avoid consuming the wrong types of sugar, they have to say goodbye to many delicious foods, which greatly reduces their quality of life.

Unfortunately, there is no quick and convenient instrument that can meet all of the above requirements. The dietary assessment function in the most commonly used health management apps in people's daily lives is just a "guess" based on machine vision and big data, which is often far from reality. For ordinary people, it is very difficult to rely on their own experience to avoid excessive sugar intake; moreover, these methods are completely unsuitable for farmers. Is there anything that can solve all of this?

Fig 6. Calorie Counting Applications

Our initial idea was to develop a rapid multi-channel test strip, similar to a glucose test strip, believing this format would effectively address user needs while ensuring ease of use and real-time results. However, we discovered that even by identifying and integrating individual tests for each common sugar, this approach was infeasible. Not all common sugars have readily available testing methods adaptable to a test strip format that are simultaneously fast, convenient, and specific.

Fig 7. Initial idea for carbohydrate testing

After relentless searching and exploration, we finally found a detection method based on the fluorescence reaction between lanthanide metal esters and sugars. Based on this, we designed SweetGlow, a fluorescence sugar detector utilizing lanthanide metal esters.

Where can SweetGlow be applied ?

SweetGlow's versatility and portability offer wide-ranging application prospects in multiple fields:

1. Agricultural Production: Fruit growers can use SweetGlow to quickly detect sugar content in fruits in the field, optimizing harvest times and improving product quality. This is significant for precision agriculture and enhancing the market competitiveness of agricultural products.

2. Food Industry: Food manufacturers can use SweetGlow for sugar content testing in raw materials and finished products, ensuring product consistency, optimizing formulations, and meeting consumer demands for low-sugar, healthy foods.

3. Healthcare: Diabetic patients can use SweetGlow to accurately monitor sugar content in food, better control their diet, and manage blood sugar levels. This will greatly improve patients' quality of life and reduce the risk of inadvertently consuming high-sugar foods.

4. Nutrition Management: Weight loss enthusiasts and health management advocates can use SweetGlow to precisely control sugar intake, avoid "calorie traps," and achieve more scientific dietary management.

5. Scientific Research: In biotechnology research, such as in our project, SweetGlow can be used to rapidly assess the impact of target products (like thaumatin) on the sugar content of tomato fruits, providing accurate and timely data support for research.

6. Beverage Industry: Beverage manufacturers can use SweetGlow for product development and quality control, precisely adjusting the sweetness of drinks to meet the needs of different consumer groups.

7. Education: SweetGlow can serve as a practical tool for science education, helping students understand sugar chemistry and fluorescence detection principles, sparking their interest in science.

8. Food Service: Restaurants and cafes can use SweetGlow to provide customers with more precise nutritional information, especially for customized drinks and desserts, enhancing service quality and customer satisfaction.

These applications of SweetGlow not only meet the need for precise sugar detection in multiple fields but also have the potential to drive technological innovation and service upgrades in related industries, making important contributions to people's healthy living and scientific research.

Principle

3-nitrophenylboronic acid (3-NPBA) interacts with sugars, specifically binding to diol groups^[4]. This interaction triggers an esterification reaction, releasing hydrogen ions and altering the solution's pH. We synthesized a lanthanide complex, H(6)L/Tb(3+), which exhibits pH-sensitive fluorescence. When excited at 333 nm, it emits fluorescence at 398, 490, and 546 nm. By ingeniously combining a gradient concentration of 3-NPBA solution with an H(6)L/Tb(3+) gel, we constructed a three-dimensional fluorescent sensor array. Coupled with principal component analysis (PCA), this array enables highly accurate detection of fructose, glucose, and sucrose in complex solutions^[3][5].

Fig 8. Principle diagram

Design

Insrument

The detection instrument's structure is as follows: The user interacts with the instrument through a screen. Inside, a detection mechanism processes the sample and acquires data. This data is then processed by a chip on the built-in main control circuit board, and the results are displayed to the user.

Fig 9. The structure of Sweetglow Instrument

Detection Mechanism

Fig 10. The structure of the Detection Mechanism

The detection mechanism, illustrated in the accompanying diagram, consists of the following components:

- Ultrasonic Transducer (large top, small bottom cylinder): Sonicates the sample within the sample tube to ensure uniformity and complete reaction.

- 330nm Wavelength LED Light Source (small grayish-green square): Emits the excitation light required for the gel to fluoresce.

- Optical Prism (semi-transparent triangular prism): Disperses the fluorescence emitted by the gel into a spectrum that can be identified through machine vision.

- Miniature Industrial Camera (green square with cylindrical protrusion): Captures the dispersed spectrum and transmits the data to the main control chip.

Operation

When a sample tube is inserted into the instrument, as shown in the diagram, the ultrasonic transducer makes contact with the sample tube to process the sample.

Fig 11. Operation mode

The optical component of the instrument, also illustrated, functions as follows: The light source generates excitation light at a specific wavelength. The fluorescence produced by the sample is dispersed by the prism and then captured by the camera.

Fig 12. The optical path of the Detection Mechanism

Reagent

Component

1. H(6)L/Tb3+ gel: Fluorescent material, indicates detection results

2. 3-NPBA solution in thionyl chloride: Phenylboronic acid solution, reacts with sugars affecting the gel's fluorescence

3. Water and buffer solution: Ensures the correct initial pH for the reaction

Package

To simplify reagent handling for our users, we package a dry gel, along with two separate ampoules — one containing a 3-NPBA solution in thionyl chloride and the other containing water and buffer — inside a translucent polymer tube. After adding their sample, the user can manually mix the reagents within the tube.

Fig 13. Package of reagent

As the instrument requires testing within a gradient of 3-NPBA in thionyl chloride to correctly measure sugar content, we designed a triple sample tube. These three tubes are connected by an extended rod-like structure. This design facilitates user handling while aligning with a groove in the instrument's sample slot. This ensures correct placement and prevents invalid results caused by an incorrect orientation of the concentration gradient.

Fig 14. The triple-chambered sample tube

Workflow

Fig 15. Workflow

Comparison

Physical model

We've created a 3D-printed Sweetglow model to test and demonstrate our ideas in the real world. Further details are available in the user manual.

Fig 16. Sweetglow model

Proof of concept

We attempted to synthesize the gel and obtained small gel particles. In indoor environments, they appear as small white gel beads, and under ultraviolet light, they emit a strong green fluorescence.

Fig 17. H(6)L/Tb3+ Dry gel

We measured the fluorescence spectrum of the synthesized fluorescent substance and found that when dispersed in water at a concentration of 200mg/L, it exhibited high fluorescence intensity with four characteristic peaks. Among these, the peak at 543 nm was the highest.

Fig 18. Fluorescence pattern of 200mg/L gel aqueous solution

We tested the detection capability of this gel for different sugar substances. We conducted three sets of experiments: a blank group, a glucose group, and a sucrose group.

Fig 19a. Fluorescence pattern of the blank sample Fig 19b. Fluorescence patterns of glucose samples

Fig 19c. Fluorescence patterns of sucrose samples Fig 19d. Plot of PCA results of
test results for blank, glucose, and sucrose samples

We performed Principal Component Analysis (PCA) on the obtained data using Origin software. In the processed result graph, it can be observed that the three groups of samples show good differentiation. This indicates that the gel is capable of distinguishing between multiple types of sugars.

User Manual for SweetGlow

Protocol