Simple Science

Cutting edge science explained simply

# Biology # Biochemistry

TINGL: The Future of Glucose Monitoring

A new sensor illuminates glucose levels in real time.

Dennis Botman, Annemoon Tielman, Joachim Goedhart, Bas Teusink

― 7 min read


TINGL: A New Glucose TINGL: A New Glucose Sensor changes in real time. Revolutionary sensor tracks glucose
Table of Contents

Glucose is a simple sugar that serves as a primary source of energy for many living organisms. It's the fuel your cells need to perform everything from thinking and running to growing and repairing themselves. Imagine your body as a car engine; glucose is the gasoline that keeps it going. Without adequate glucose levels, energy production slows down, which can lead to various issues.

How Organisms Use Glucose

Most organisms take in glucose from their food and transport it into their cells. Once inside, glucose is broken down through a process called glycolysis, which is like a series of steps that lead to the production of adenosine triphosphate (ATP), the energy currency of the cell. Think of glycolysis as the assembly line at a factory, where each step adds value to the raw material (in this case, glucose) until it becomes something valuable that the cell can use.

In YEAST, a type of fungus often used in baking and brewing, glucose is taken up by specific proteins called hexose transporters. These guys are like delivery trucks, bringing glucose into the cells based on concentration gradients. If there's a lot of glucose outside the cell, these transporters open up and let it in. However, too much glucose inside can slow down this process, a situation known as product inhibition.

The Challenge of Measuring Glucose Levels

For a long time, scientists measured glucose levels in yeast by taking samples and using complex biochemical methods. While this approach gave a rough estimate of glucose concentrations, it didn't allow for quick or real-time observation, like watching a soap opera unfold rather than reading a summary.

To solve this problem, researchers have turned to fluorescent biosensors-special tools that light up in the presence of glucose. These biosensors help visualize glucose levels inside live cells, making it easier to study how cells respond to changes in glucose concentrations over time.

Existing Biosensors: The Good and the Bad

Various glucose biosensors have been developed, each with its own strengths and weaknesses. Some examples include the FLIPglu FRET sensor and the GIP sensor, which use fluorescent proteins to indicate glucose levels. However, many of these Sensors are sensitive to PH changes, meaning they can get confused if the acidity of the surrounding environment shifts. Given that glucose metabolism alters pH levels inside cells, this can render such sensors useless in dynamic situations.

Recently, a new sensor based on a fluorescent protein called mTq2 showed promise for being more stable under changing pH conditions. But it was not fully characterized, meaning scientists were still unsure if it would work well inside living cells.

Enter TINGL, the Glucose Sensor

To tackle these challenges, researchers designed a new glucose sensor called TINGL-short for Turquoise Indicator for Glucose. TINGL is like the superhero of glucose sensors, with a bright glow and a fast response time. TINGL is robust and can withstand pH changes better than its predecessors, making it an excellent tool for monitoring glucose levels in single living cells.

Development of TINGL

Creating TINGL involved several steps. First, researchers used a method known as PCR (polymerase chain reaction) to amplify specific regions of DNA that code for the sensor. They then tested various versions of the sensor in yeast cells to find the one that worked best. This involved growing the yeast, exposing them to glucose, and measuring the changes in Fluorescence.

In essence, the researchers created a small library of sensor variants and then screened them to find the most effective one. After multiple tests, they zeroed in on a version of the sensor that outshined the others in brightness, specificity, and response speed.

Testing TINGL

Once TINGL was developed, it underwent a series of tests to evaluate its performance. Researchers used a technique called fluorescence microscopy to visualize the sensor's response to glucose levels in real-time. By applying glucose to the yeast cells and measuring the fluorescent signals, they could see how quickly and effectively TINGL reacted. Results showed that TINGL could respond to glucose pulses in less than 5 seconds.

Not only that, but TINGL also maintained a consistent performance across different pH levels, opening up its potential use in various biological contexts. This means scientists could study glucose levels without worrying too much about the acidity of the environment.

How TINGL Works

When glucose is present, TINGL lights up, allowing scientists to track glucose dynamics in real time. It's like having a spotlight that helps researchers see how cells react as glucose levels change. This ability to visualize changes offers insights into cellular metabolism, which is crucial for understanding how organisms function.

Also, TINGL can be used to measure glucose concentrations in single cells. This is significant because, traditionally, measuring glucose levels required analyzing a bulk sample of cells, which could mask individual variations. With TINGL, scientists can now see what's happening inside each cell, leading to more accurate data.

TINGL's Specificity

One of the standout features of TINGL is its specificity for glucose. Researchers conducted various tests to ensure that TINGL would only respond to glucose and not to other sugars like fructose or mannose. This specificity is crucial because it means the sensor won't give false readings when other sugars are present, allowing for more accurate measurements.

In practice, when researchers added fructose, TINGL showed no change, proving that it is particularly tuned to detect glucose only. When glucose was added, however, TINGL responded by lighting up, demonstrating its effective performance in determining glucose levels.

Real-Time Glucose Dynamics

Using TINGL, researchers could monitor how glucose levels fluctuate in real time. This helps to answer important questions, such as how quickly cells adjust their glucose uptake in response to changes in their environment.

For example, when cells that had adapted to low glucose levels (glucose-repressed cells) were suddenly given glucose, they exhibited a different response than cells that had been exposed to glucose all along (de-repressed cells). Interestingly, the response was more dynamic in the repressed cells. This suggests that the state of the cells before exposure affects how they manage glucose later on.

TINGL in Action: Real-Life Applications

The implications of TINGL stretch beyond the lab. For instance, researchers can use the sensor to investigate how yeast behaves during baking or fermentation processes, where glucose dynamics play a pivotal role. Shifting focus from yeast, TINGL could potentially serve in medical research to monitor blood sugar levels or metabolic diseases in humans.

Being able to visualize glucose changes in real time can provide valuable information for studying diabetes or other metabolic disorders, guiding researchers toward better treatment options.

Challenges and Future Prospects

While TINGL has proven to be a fantastic tool, there are still challenges to overcome. Many sensors, including TINGL, perform differently in various environments. This means researchers may need to fine-tune TINGL for specific applications.

For the future, researchers might also look into developing sensors for other important metabolites, such as fatty acids or amino acids, which play significant roles in cellular metabolism. Given the success of TINGL, it may pave the way for a new generation of biosensors that can monitor multiple substances simultaneously.

Conclusion

In summary, glucose is a vital fuel for life, and understanding its dynamics in organisms is crucial. TINGL, the innovative glucose sensor, allows scientists to visualize and measure glucose levels in real time. By providing accurate, specific, and rapid readings of glucose concentrations, TINGL opens the door to new research avenues in metabolism, fermentation processes, and even medical applications.

So, the next time you enjoy a slice of cake or a glass of juice, think about TINGL working away in the background, illuminating the sugar levels in every tasty bite!

Original Source

Title: An mTurquoise2-based glucose biosensor

Abstract: Glucose is an important substrate for organisms to acquire energy needed for cellular growth. Despite the importance of this metabolite, single-cell information at a fast time-scale about the dynamics of intracellular glucose levels is difficult to obtain as the current available sensors have drawbacks in terms of pH sensitivity or glucose affinity. To address this, we developed a convenient method to make and screen biosensor libraries using yeast as workhorse. This resulted in TINGL (Turquoise INdicator for GLucose), a robust and specific biosensor for intracellular glucose detection. We calibrated the sensor in vivo through equilibration of internal and external glucose in a yeast mutant unable to phosphorylate glucose. Using this method, we measured dynamic glucose levels in budding yeast during transitions to glucose. We found that glucose concentrations reached levels up to 1 mM as previously determined biochemically. Furthermore, the sensor showed that intracellular glucose dynamics differ based on whether cells are glucose-repressed or not. We believe that this sensor can aid researchers interested in cellular carbohydrate metabolism.

Authors: Dennis Botman, Annemoon Tielman, Joachim Goedhart, Bas Teusink

Last Update: 2024-11-29 00:00:00

Language: English

Source URL: https://www.biorxiv.org/content/10.1101/2024.11.29.626064

Source PDF: https://www.biorxiv.org/content/10.1101/2024.11.29.626064.full.pdf

Licence: https://creativecommons.org/licenses/by-nc/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to biorxiv for use of its open access interoperability.

More from authors

Similar Articles