Bacteria and Genetic Engineering: A Complex Balance
Exploring the intricate relationship between bacteria and genetic manipulation.
Cameron T. Roots, Alexis M. Hill, Claus O. Wilke, Jeffrey E. Barrick
― 6 min read
Table of Contents
- The Cost of Engineering Bacteria
- The Role of Cellular Resources
- The Impact of Codon Usage
- Tips for Better Protein Production
- Experimental Strategies
- Protein Overexpression Experiments
- Observations from Experiments
- Deoptimization: A Double-Edged Sword
- Challenges in the Laboratory
- Looking to the Future
- Conclusion: The Balancing Act of Bacterial Engineering
- Original Source
Bacteria are tiny living organisms that can be found almost anywhere on Earth. They are important for many processes, from helping us digest food to breaking down waste. Scientists often play with the genes of these bacteria to make them do new tasks, like producing medicines or cleaning up pollution. This process is called genetic engineering.
The Cost of Engineering Bacteria
When scientists change the genes in bacteria, it can make them stronger or help them grow faster. But sometimes, these changes can also make it harder for the bacteria to survive. Think of it like trying to play a video game while your character is wearing too heavy armor. Sure, you're protected, but you can’t run as fast or jump high. The extra genetic material can weigh the bacteria down, which we call "burden." If this burden is too high, the bacteria can become unstable and may even stop multiplying altogether.
The Role of Cellular Resources
Bacteria need various resources to grow. These include tiny machines called Ribosomes, which build Proteins, and other materials like RNA and amino acids. When genes are added to bacteria, the resources must be shared between the old and new functions. If too much attention is given to the new job, it can reduce the bacteria’s ability to do what it used to do well.
For example, ribosomes are often in short supply when bacteria are working hard to produce extra proteins. If all the ribosomes are busy making a new protein, there might not be enough left to make the proteins the bacteria need for their normal survival. This can lead to a decline in overall health.
The Impact of Codon Usage
Bacteria speak their own language using codes called Codons. These codons help determine how well proteins are made. Some codons are more commonly used than others. When a bacterium has to use less common codons, it can struggle because it takes longer to find the right building blocks (called tRNAs) to turn those codes into proteins.
For scientists, this means that if they want to get the most out of their engineered proteins, they need to pay attention to which codons they use. Using the “popular” codons can help get more proteins made quickly and without overloading the bacterial machinery.
Tips for Better Protein Production
To maximize protein production, scientists have come up with strategies to optimize codon usage. They analyze which codons are optimal and try to use more of them in their designs. This is like trying to make a best-seller book by knowing exactly what kinds of plots and characters people love. A few of the tricks include:
- Optimal Codon Frequency: Using the right proportion of popular codons to avoid confusion in the bacteria.
- Codon Adaptation Index (CAI): A system that helps evaluate the effectiveness of codon choices.
- Codon Health Index (CHI): A newer metric that focuses on reducing the burden on the bacteria while still getting good protein production rates.
Experimental Strategies
Scientists have learned that tweaking codon usage can lead to big changes in bacterial behavior. They have conducted experiments by changing the codons in genes responsible for producing fluorescent proteins, which glow under specific lighting. By altering the codon usage, scientists could see how much the bacteria’s growth slowed as they worked harder to produce these proteins.
In their tests, they found that when codons were adjusted to be more optimal, the bacteria would flourish and produce more proteins. However, when less optimal codons were used, the bacteria became sluggish and had a harder time keeping up.
Protein Overexpression Experiments
To further understand how this works, researchers performed tests with two types of fluorescent proteins, sfGFP and mCherry2. They designed different versions of these proteins with varying levels of codon Optimization and then studied how they affected the bacteria.
They used a sneaky trick with colors: scientists measured how brightly the bacteria glowed, as this directly related to how much protein they were producing. The more optimal the codon usage, the brighter the glow, and the less burden the bacteria experienced in terms of growth rate reduction.
Observations from Experiments
In their findings, the team noticed that when the proteins were designed with highly optimal codons, the bacteria could produce more protein without slowing down too much. But they also uncovered a surprising twist: at certain points, going too far with optimization could lead to instability in the bacteria.
It’s like trying to bake a cake; if you add too much frosting, it might look great but fall apart when you cut it. Similarly, too much optimization could lead to a genetic disaster for the bacteria.
Deoptimization: A Double-Edged Sword
To further test their theories, the researchers played around with replacing codons that made specific amino acids with rare ones. This nicely demonstrated how even small changes could have a big impact on performance. Some rare codons didn’t seem to affect the bacteria much, while others made the burden jump dramatically.
This showed that knowing when and how to deoptimize a gene can be just as important as optimizing it. A well-balanced approach is key to achieving the best results in bacterial engineering.
Challenges in the Laboratory
Despite all the clever strategies, researchers faced challenges. Bacteria can be unpredictable. Sometimes, mutants - bacteria that have changed in unintended ways - can arise and spread through a population. These mutants may grow better than the original engineered bacteria but could also produce less or even stop functioning altogether.
This unpredictability can complicate measurements; scientists can find their results altered because some bacteria just don’t behave like they should. Even with a controlled system, some of the engineered proteins sometimes just didn't express well, leading to a frustrating day in the lab.
Looking to the Future
Understanding the relationship between genetic changes and how they impact bacteria is essential for making them work better for us. Researchers believe that further studies will allow for better predictions about how bacteria will respond to genetic engineering. They are hopeful that in time, more reliable tools will emerge to help them design effective systems for bacterial engineering.
Conclusion: The Balancing Act of Bacterial Engineering
In the end, genetic engineering in bacteria is a complex balancing act. Scientists continually tweak and refine their methods, hoping to maximize protein production while minimizing growth Burdens. As they learn more about how these tiny organisms work, they can develop better techniques to make them behave just the way we want-kind of like training a puppy, but with genes instead of treats!
Through understanding and innovation, the world of bacteria holds great promise for future advancements, whether it’s in medicine, environmental cleanup, or other technologies. So, next time you think of bacteria, remember-these little guys are on the front lines of science, and they carry the future in their tiny, well-engineered hands!
Title: Modeling and measuring how codon usage modulates the relationship between burden and yield during protein overexpression in bacteria
Abstract: Excess utilization of translational resources is a critical source of burden on cells engineered to over-express exogenous proteins. To improve protein yields and genetic stability, researchers often use codon optimization strategies that improve translational efficiency by matching an exogenous genes codon usage with that of the host organisms highly expressed genes. Despite empirical data that shows the benefits of codon optimization, little is known quantitatively about the relationship between codon usage bias and the burden imposed by protein overexpression. Here, we develop and experimentally evaluate a stochastic gene expression model that considers the impact of codon usage bias on the availability of ribosomes and different tRNAs in a cell. In agreement with other studies, our model shows that increasing exogenous protein expression decreases production of native cellular proteins in a linear fashion. We also find that the slope of this relationship is modulated by how well the codon usage bias of the exogenous gene and the hosts genes match. Strikingly, we predict that an overoptimization domain exists where further increasing usage of optimal codons worsens yield and burden. We test our model by expressing sfGFP and mCherry2 from constructs that have a wide range of codon optimization levels in Escherichia coli. The results agree with our model, including for an mCherry2 gene sequence that appears to lose expression and genetic stability from codon overoptimization. Our findings can be leveraged by researchers to predict and design more optimal cellular systems through the use of more nuanced codon optimization strategies.
Authors: Cameron T. Roots, Alexis M. Hill, Claus O. Wilke, Jeffrey E. Barrick
Last Update: 2024-11-28 00:00:00
Language: English
Source URL: https://www.biorxiv.org/content/10.1101/2024.11.28.625058
Source PDF: https://www.biorxiv.org/content/10.1101/2024.11.28.625058.full.pdf
Licence: https://creativecommons.org/licenses/by/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.