Applications & Examples

 

The RBS Calculator allows you to control the production rate of any protein in bacteria. Here, we show how to use the RBS Calculator to solve common problems in biotech applications. Feel free to contact Howard Salis with additional applications or examples.

 

Recombinant Protein Expression

 

            Increasing Expression: Emma Haredale cloned a new recombinant protein into her favorite E. coli expression vector, but the protein expression level is poor. She can use the RBS Calculator to see if a low translation rate is the problem. She copies and pastes at least 50 nucleotides before and after the start codon of the recombinant protein’s coding sequence into the Reverse engineering mode of the RBS Calculator. Five minutes later, the email she receives contains a list of start codons and their translation initiation rates. She finds the start codon of her protein coding sequence. It has a translation initiation rate of only 120 au. That is very low, when compared to a maximum of 100,000 au or more. To increase the translation initiation rate, she uses the RBS Calculator to design a new synthetic ribosome binding site. Switching to the Forward engineering mode, she inputs the first 50 nucleotides of the recombinant protein’s coding sequence and a target translation initiation rate of 100,000 au. Ten minutes later, her inbox contains an email with a new synthetic ribosome binding site sequence. She orders a pair of oligonucleotides to clone in the new sequence. A few days later, the new ribosome binding site sequence has increased the recombinant protein’s expression level by a factor of about 800. Emma is quite satisfied.

 

            Emma wonders, “Why do some expression vectors work well for some recombinant proteins and not for others?” One reason is that the translation initiation rate can change when reusing the same ribosome binding site sequence with different proteins. How does that happen? The transcribed mRNA sequence can form strong secondary structures that prevent the ribosome from binding, reducing the translation rate. Both the ribosome binding site sequence and the protein coding sequence can participate in these secondary structures. Thus, changing the protein coding sequence can change the strength of the mRNA secondary structure, altering the translation rate. Is there a way to avoid the problem of low translation rates altogether?

 

            Avoiding Poor Expression: Emma has a new recombinant protein to express. Instead of immediately selecting her favorite E. coli expression vector, she decides to test whether the translation rate will be high enough for her purposes. She copies and pastes the mRNA sequence surrounding the protein’s start codon into the Reverse engineering mode of the RBS Calculator. If the start codon has a high translation rate (on a scale from 1 to 100,000 au) then poor translation will not be a problem. However, if the translation rate is low, then Emma can instead choose a different E. coli expression vector. She repeats the process of copy/pasting the mRNA sequence of her protein in a new expression vector (with a different ribosome binding site) until she finds one that has a high translation rate. When she finds one, she does her cloning as usual. She never has a problem with poor translation rates ever again.

           

Metabolic Engineering

 

            Eliminating Pathway Bottlenecks: Jack Dawkins is optimizing a 9-enzyme metabolic pathway in E. coli that produces a wonderful new biofuel. He is trying to maximize the amount of biofuel, but there is at least one bottleneck in his metabolic pathway. Through many experiments, he has identified that poor expression of one enzyme in the pathway is the cause of the bottleneck. Jack has spent the last few months making dozens of random mutations to the ribosome binding site in front of this enzyme’s protein coding sequence and re-measuring the biofuel’s production rate; however, he still hasn’t improved the pathway's productivity that much.

 

            Jack can use the RBS Calculator to find the enzyme’s optimal expression level and eliminate the bottleneck in his metabolic pathway. He inputs the enzyme’s original mRNA sequence into the Reverse engineering mode. The translation initiation rate of the enzyme’s start codon is 1000 au. He then uses the Forward engineering mode to generate four synthetic ribosome binding site sequences with translation initiation rates of 10, 100, 10000, and 100000 au. These ribosome binding site sequences will express the enzyme at widely different production rates. After inserting these ribosome binding site sequences into his genetic system, Jack tests which one produces the most biofuel. With only a few experiments, he identifies that the RBS sequence with a translation initiation rate of 10000 au produced the most biofuel. Using this number as his baseline, he then generates additional synthetic RBS sequences with rates of 5000, 20000, and 30000 au. Repeating his experiments, he finds that the RBS sequence with a rate of 20000 au produced the most biofuel. He finishes off his experiments by designing two synthetic RBS sequences with rates of 15000 and 25000 au, finding that the 25000 au RBS sequence performed the best. Altogether, Jacks finds that the biofuel production was increased by 500% by optimizing a single enzyme’s expression level and eliminating a pathway bottleneck. Jack continues to increase biofuel production by optimizing the remaining enzyme’s expression levels.

 

            Designing Synthetic Metabolic Pathways: Peter Magnus is creating a synthetic 9-enzyme metabolic pathway, taking enzymes from many different organisms and combining them together into a single pathway to produce a novel chemical product. He is using DNA synthesis to construct the genetic system and would like a way to avoid the problems that Jack Dawkins initially had with poor enzyme expression levels. He uses the Forward engineering mode of the RBS Calculator to generate a synthetic ribosome binding site sequence for each enzyme coding sequence. He initially chooses a translation initiation rate of 10000 au to ensure that each enzyme is sufficiently expressed. He knows that optimization of the enzyme expression levels will then be necessary to maximize the productivity of the pathway. He heard from Howard that techniques for performing this optimization in a systematic way will be available soon.