Difference between revisions of "Team:William and Mary/RiboJ"

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<div class="title">
 
<div class="title">
 
<h2 style='padding-top: 40px; font-family: "Verlag-Book"; font-size: 50px;'>
 
<h2 style='padding-top: 40px; font-family: "Verlag-Book"; font-size: 50px;'>
RBS Tuning
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RiboJ
 
</h2>
 
</h2>
 
</div>
 
</div>
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<div class="description">
 
<div class="description">
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
One of the more familiar ways of tuning a biological circuit is to change the strength of a Ribosome binding site (RBS).
+
In the past many teams have rigorously characterized parts both new and old, so what separates the Circuit Control Toolbox from being just another characterization project? The answer to that is multifold, but mainly consists of the fact that the Circuit Control Toolbox not only rigorously characterizes novel or useful tools to alter transfer functions, but also allows these tools to be generalizable to any circuit, not just to the specific circuit in which they were characterized.  
Changing the strength of an RBS allows for the alteration of the amplitude of a given transfer function. While this is  
+
a familiar concept to most iGEM teams, it takes on a special importance in the context of the Circuit Control Toolbox.
+
This is because while transfer functions are preserved when shifted, the amplitude of those transfer functions is
+
oftentimes reduced due to increased metabolic load. So we characterized a library of variable strength RBSs for use
+
in amplitude tuning in the Circuit Control Toolbox.
+
 
</p>
 
</p>
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
While it would have been possible to construct brand new RBSs for use in the Circuit Control Toolbox, we thought that  
+
A key problem of generalizing the results of characterizations is that the dynamics of gene expression are influenced by the protein coded for. For our toolbox to be able to to be used orthogonally at the end of an arbitrary genetic circuit, we must be able to use the characterization done in fluorescent proteins on any other protein. That is, we have to be able to insulate a circuit from its genetic context.
it would be more useful to characterize existing commonly used RBSs on the registry. So we chose to characterize the  
+
Community Collection, which is made up of 8 variable strength RBSs, and is commonly used by most iGEM teams.  
+
 
</p>
 
</p>
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
For our characterization we chose to emulate the methods of Lou et al. 2012 (“Ribozyme-based insulator parts buffer  
+
Fortunately, Lou et al. from the Voigt lab at MIT discovered a ribozyme which does just that. RiboJ is ribozyme derived from a hammerhead ribozyme, which self cleaves, removing the upstream region, most importantly the 5’ untranslated region <b>(Figure 1)</b>.
synthetic circuits from genetic context”) and used a super folder Green Fluorescent Protein (sfGFP) with RiboJ under
+
When Lou et al. 2012 (“Ribozyme-based insulator parts buffer synthetic circuits from genetic context”) measured two different variants of GFP (sfGFP and cl-sfGFP fusion), they found that the relative expression for the induction curves was not always the same, likely due to upstream effects. However, when they added RiboJ before the coding region, the relative expression levels for the induction curves collapsed, indicating that the relative expression had been homogenized for a given promoter <b>(Figure 2)</b>. This means that the gene expression dynamics are controlled only by the promoter, and not by the coded for protein, which means as long as the promoter is kept the same and RiboJ is added before all coding regions, our characterizations can be used for different proteins.
the control of pLacO1 (Bba_K2066014). The use of the IPTG inducible promoter pLacO1 allowed us to characterize the
+
 
functions over an induction curve, and the use of RiboJ, a self cleaving ribozyme from Lou et al. 2012 prevented the 5’
+
untranslated region of the promoter from effecting the translational efficiency of the mRNA transcript (Figure 1).  
+
That means that unlike past iGEM characterization, our results are generalizable beyond the promoter pLacO1. <b>(See the  
+
RiboJ section for more details)</b>
+
 
</p>
 
</p>
 
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
 
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
<img src="https://static.igem.org/mediawiki/2016/b/b2/T--William_and_Mary--F1-V1-.png" width="800px">
+
<img src="https://static.igem.org/mediawiki/2016/1/1c/T--William_and_Mary--Ribo1.png" width="600px">
 
</p>
 
</p>
 
<!--FIGURE CAPTION-->
 
<!--FIGURE CAPTION-->
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<b>Figure 1:</b> RiboJ acts to homogenize translational efficiency between promoters by cleaving the 5’ region upstream from
+
<b>Figure 1:</b> Structure of RiboJ, the loop in uppercase is derived from the sTRSV ribozyme, while the additional loop is in lowercase. The catalytic core of the active ribozyme is circled in red and the smaller loop serves to promote translation by exposing the RBS. Figure adapted from Lou et al.  
RiboJ. -35 and -10 boxes are shown in bold, and transcription factor binding sites are underlined. Note how there is  
+
an operator sequence located within the transcribed region of the pTac promoter (BBa_K864400), and that pSal and pBad
+
include transcribed regions. These untranslated regions can change translational efficiency of the downstream protein,
+
leading to inconsistent expression between different combinations of promoters and coding sequences. Figure modified
+
from figure S1 of Lou et al. 2012.
+
</p>
+
<p class='large' style="padding-left:40px; text-indent: 50px;">
+
Characterization was done on 07/26/16 using flow cytometry, which means that our data shows single cell resolution of the  
+
impact of various RBSs. Characterization was done in BL21 E. coli, which is a standard protein expression strain. A high
+
copy plasmid (1C3) containing one of the pLacO1 RiboJ RBS variants (ex. Bba_K206636) was co-transformed with a low copy
+
plasmid (3K3) which contained a constitutively expressed LacI (Bba_K206616) to repress the promoter. Individual colonies
+
were picked from antibiotic selection plates, and colony PCRed to ensure the correct plasmids were contained. For each RBS  
+
variant 3 colonies containing both plasmids were inoculated in M9 and incubated till midlog growth was reached. At that
+
point the cells were induced with various concentrations of IPTG until steady state was reached. Cells were then FACSed
+
and their fluorescence was reported in MEFL calculated using Spherotech calibration beads. <b>(Figure 2)</b>.
+
</p>
+
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
+
<img src="https://static.igem.org/mediawiki/2016/f/f0/T--William_and_Mary--Rbs-plot.svg" width="850px">
+
 
</p>
 
</p>
 
 
<!--FIGURE CAPTION-->
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
 
<b>Figure 2:</b> Average (3 biological replicates) population level fluorescence of RBS library over different induction conditions.
 
Note the wide range of RBS strengths in the library, and that the strongest RBS B0035, is not actually the strongest until
 
induced at a concentration of 1000µM IPTG. This illustrates the importance of evaluating over a transfer function, not just
 
at an arbitrary steady state.
 
</p>
 
 
<p class='large' style="padding-left: 40px; text-indent: 50px; padding-bottom: 50px;">
 
All of the individual RBS plots are available on our <a href='https://2016.igem.org/Teams:William_and_Mary/Measurement'>measurement</a>
 
page, but here are a few examples of individual RBS measurements.
 
</p>
 
 
 
 
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
 
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
<img src="https://static.igem.org/mediawiki/2016/4/42/3a_RBS.png" width="800px">
+
<img src="https://static.igem.org/mediawiki/2016/0/04/T--William_and_Mary--Ribo2.png" width="600px">
</p>
+
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
+
<b>Figure 3A</b>
+
</p>
+
+
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
+
<img src="https://static.igem.org/mediawiki/2016/0/00/T--William_and_Mary--Rbs-3b.png" width="800px">
+
</p>
+
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
+
<b>Figure 3B</b>
+
 
</p>
 
</p>
 
 
 
<!--FIGURE CAPTION-->
 
<!--FIGURE CAPTION-->
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<b>Figure 3A and 3B:</b> Fluorescence measurements of replicate 1 of B0031 (BBa_K2066036) un-induced (A) and induced at [IPTG]
+
<b>Figure 2:</b> Figure from Lou et al. showing that the relative relationship is preserved when RiboJ is used as an insulator.  
100µM (B). Note the relative crispness of peaks, indicating a nearly normal distribution of florescence. The majority
+
of all replicates are similarly unimodel in their distribution.  
+
 
</p>
 
</p>
 
 
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
+
<p class='large' style="padding-left:40px; text-indent: 50px;">
<img src="https://static.igem.org/mediawiki/2016/9/99/T--William_and_Mary--Rbs-4a.png" width="800px">
+
First, we wanted to make sure that RiboJ worked the way Lou et al. had outlined, so we characterized RiboJ in the Biobrick Backbone. We reconstructed some of the characterization parts from Lou et al. in the Biobrick Backbone and then proceeded to characterize the impact of RiboJ <b>(Figure 3)</b>
 +
</p>
 +
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
 +
<img src="https://static.igem.org/mediawiki/2016/0/0c/T--William_and_Mary--pLac_no_RiboJ.png" width="850px">
 
</p>
 
</p>
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<b>Figure 4A</b>
+
<b>Figure 3A</b>
 
</p>
 
</p>
+
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
+
<img src="https://static.igem.org/mediawiki/2016/1/10/T--William_and_Mary--RiboJ-ConvergenceB.svg" width="850px">
<img src="https://static.igem.org/mediawiki/2016/6/66/T--William_and_Mary--Rbs-4b.png" width="800px">
+
 
</p>
 
</p>
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
+
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<b>Figure 4B</b>
+
<b>Figure 3B</b>
 
</p>
 
</p>
 
 
<!--FIGURE CAPTION-->
 
<!--FIGURE CAPTION-->
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<b>Figure 4A and 4B:</b> Fluorescence measurements of replicate 3 of B0031 (BBa_K2066036) un-induced (A) and induced [IPTG] 100µM(B).  
+
<b>Figure 3A and B:</b> Measurements of plLacO-1 sfGFP and cI-GFP with (B) and without (A) RiboJ. Our findings were consistent with Lou et al. Notice how the relative expression curves collapse with RiboJ compared to the ones without RiboJ which do not. Measurements were done in triplicate using FACS. MEFL was calculated using Spherotech beads. The reporters (Bba_K2066014, Bba_K2066015) were located on a high copy 1C3 plasmid while the repressor LacI (Bba_K2066016) was constitutively expressed on a low copy 3K3 plasmid.
Note the bimodal distribution compared to figure. In this case induction occurs, but a subset of the population is maximally
+
 
induced at all induction conditions. All induction conditions of number 3 contained this distribution, while other replicates
+
<p class='large' style="padding-left:40px; text-indent: 50px;">
of this biological circuit had a more normal fluorescence distribution, indicating that something unusual, likely the loss of  
+
While we confirmed the findings of Lou et al. that the relative expression of different proteins under one promoter converges, we also noticed that absolute expression of the same protein is altered by the inclusion of RiboJ. Furthermore, we noticed that the direction of this shift changes based on the promoter used <b>(Fig. 4)</b>.
the repressor is going on in this replicate. Of note, this bimodal distribution would not be noticeable without the use of FACs
+
</p>
to observe at a single cell level.  
+
 
 +
<p class='large' style="padding-left:40px; text-indent: 50px;">
 +
These phenomena led us to initiate a thorough characterization of the impact of RiboJ on the absolute gene expression levels of widely used promoters, including the entire Anderson library of constitutive promoters. We designed a library of promoter characterization constructs with and without RiboJ (Bba_K2066057-K2066108), which consist of the Anderson library as well as additional inducible promoters on a standard superfolder GFP expression cassette. To our knowledge, this will be the first such targeted characterization effort on these promoters in the literature.
 +
</p>
 +
 
 +
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
 +
<img src="https://static.igem.org/mediawiki/2016/0/04/T--William_and_Mary--RiboJ-abs-A.svg" width="850px">
 
</p>
 
</p>
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
 
While teams have measured RBSs in the past <b>(Warsaw 2010)</b>, to our knowledge no team has ever measured the entire community
 
library over a variety of induction conditions. As illustrated by B0035’s variable relative strength at different induction
 
conditions, it is vital to perform characterization at different induction conditions rather than just constitutively.
 
However, our findings have been consistent with the measurements on the registry, and much like Warsaw 2010 we found that
 
B0030 was stronger than reported in previous measurements on the registry. Additionally, measurements on the registry by Kelly
 
and Rubin in 2007 indicate that B0035 is stronger than B0034. Given that their data was recorded from a strong constitutively
 
expressed promoter, their measurement makes sense in the context of our findings that B0035 is a stronger RBS only when expressed
 
at a high level.
 
</p>
 
 
<p class='large' style="padding-left:40px; text-indent: 50px;">
 
While the community RBSs are designed for and most commonly used for expression in E. Coli, we thought that it would be
 
useful to characterize them in a variety of conditions. So as a collaboration we sent a blinded version of the library to
 
University of Pittsburgh’s iGEM team, who then proceeded to characterize the RBSs in the cell free system S30 <b>(Figure 5)</b>.
 
We also sent a blinded library to the high school team Alverno, who characterized them using Richard Murray’s TX-TL cell free system
 
<b>(Figure 6)</b>. In both cases, the majority of RBSs had relative expressions similar to our characterization. However, Team Alverno
 
characterized B0064 as having a significantly higher relative expression than was found in existing registry characterization as
 
well as our characterization. We talked to UPitt iGEM, and they noted that due to technical concerns they were not confident about
 
the validity of their first set of measurements <b>(Figure 7)</b>. When we looked at the unblinded data from the first set of measurements,
 
we noted that they had a similarly high level of B0064 expression. Future experiments are needed to determine whether that is an
 
artifact of a common procedural error in cell free systems, or is representative of a novel result in a cell free system.
 
</p>
 
 
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
 
<img src="https://static.igem.org/mediawiki/2016/5/58/T--William_and_Mary--Rbs-5.png" width="800px">
 
</p>
 
<!--FIGURE CAPTION-->
 
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<b>Figure 5:</b> Unblinded graph of UPitt iGEM’s measurements of our RBS library in the S30 cell free system. Their data
+
<b>Figure 4A</b>   
is in line with both existing measurements, as well as our measurements.  
+
 
</p>
 
</p>
+
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
+
<img src="https://static.igem.org/mediawiki/2016/e/e3/T--William_and_Mary--RiboJ-abs-B.svg" width="850px">
<img src="https://static.igem.org/mediawiki/2016/b/b6/T--William_and_Mary--RBS-F6a-V1-.png" width="800px">
+
 
</p>
 
</p>
<!--FIGURE CAPTION-->
+
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
+
<b>Figure 4B</b>   
<b>Figure 6A:</b> Unblinded graph of Team Alverno’s characterization of our RBS library in the TX-TL cell free system.  
+
</p>
+
+
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
+
<img src="https://static.igem.org/mediawiki/2016/5/58/T--William_and_Mary--RBS_Characterization_Curves.png" width="800px">
+
 
</p>
 
</p>
 
<!--FIGURE CAPTION-->
 
<!--FIGURE CAPTION-->
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
 
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
<b>Figure 6B:</b> Time course measurements of Team Alverno’s characterization of our RBS library in the TX-TL cell free system.
+
<b>Figure 4A and B:</b> Mean levels of sfGFP expression with and without RiboJ using the IPTG inducible promoters pLacO-1 (A) and pTac (B). Plasmid set up is the same as in Figure 3. For the plLacO-1 reporter, RiboJ increases the absolute expression level, while for the pTac reporter, RiboJ has little effect on the absolute expression level.
</p>
+
 
+
<p class='large' style="padding-left:40px; text-indent: 50px;">
<p class='large' style="padding-left:40px; text-indent: 50px;">
+
After validating Lou et al.’s results in the BioBrick standard, we carried out our subsequent <a href= "https://2016.igem.org/Team:William_and_Mary/Results"> RBS </a> characterizations with RiboJ insulation to ensure that our results are applicable and useful to other scientists and iGEM teams in general.
Our RBS characterization highlights the importance of rigorous characterization, especially in the context of our
+
</p>
Circuit Control Toolbox. To be able to use RBSs to tune the amplitude of any given transfer function, you need to be
+
sure that you can apply your characterization to a given situation. For example, using our RBS characterization it
+
becomes clear that it is important to consider both the system you are working in as well as the number of mRNA
+
transcripts created. Someone trying to use B0035 for high expression of a protein under the control of a weak
+
constitutive promoter needs to be aware that B0035 is only the strongest relative RBS when there are a large number
+
of copies of mRNA. Keeping this in mind, it is now possible to use our characterization to tune the amplitude and
+
relative max of various transfer functions. Using RiboJ to remove 5’ untranslated regions, and keeping in mind the
+
various limitations of any set of characterizations, our characterization of this will be of use in the Circuit Control
+
Toolbox, and for teams at large.
+
</p>
+
+
<p style="text-align: center; padding-top: 30px; padding-bottom: 30px;">
+
<img src="https://static.igem.org/mediawiki/2016/6/67/T--William_and_Mary--RBS-F7-V1.png" width="800px">
+
</p>
+
<!--FIGURE CAPTION-->
+
<p class='large' style="padding-left:40px; text-indent: 50px; color:#A9A9A9; font-size: .75em !important;">
+
<b>Figure 7:</b> Team Pitt’s first series of measurements 
+
</p>
+
  
 
 
<div align="center">
 
<div align="center">
 
<h3 style='padding-top: 50px; padding-bottom: 50px;'>References</h3>
 
<h3 style='padding-top: 50px; padding-bottom: 50px;'>References</h3>

Latest revision as of 21:42, 1 December 2016


...

RiboJ

In the past many teams have rigorously characterized parts both new and old, so what separates the Circuit Control Toolbox from being just another characterization project? The answer to that is multifold, but mainly consists of the fact that the Circuit Control Toolbox not only rigorously characterizes novel or useful tools to alter transfer functions, but also allows these tools to be generalizable to any circuit, not just to the specific circuit in which they were characterized.

A key problem of generalizing the results of characterizations is that the dynamics of gene expression are influenced by the protein coded for. For our toolbox to be able to to be used orthogonally at the end of an arbitrary genetic circuit, we must be able to use the characterization done in fluorescent proteins on any other protein. That is, we have to be able to insulate a circuit from its genetic context.

Fortunately, Lou et al. from the Voigt lab at MIT discovered a ribozyme which does just that. RiboJ is ribozyme derived from a hammerhead ribozyme, which self cleaves, removing the upstream region, most importantly the 5’ untranslated region (Figure 1). When Lou et al. 2012 (“Ribozyme-based insulator parts buffer synthetic circuits from genetic context”) measured two different variants of GFP (sfGFP and cl-sfGFP fusion), they found that the relative expression for the induction curves was not always the same, likely due to upstream effects. However, when they added RiboJ before the coding region, the relative expression levels for the induction curves collapsed, indicating that the relative expression had been homogenized for a given promoter (Figure 2). This means that the gene expression dynamics are controlled only by the promoter, and not by the coded for protein, which means as long as the promoter is kept the same and RiboJ is added before all coding regions, our characterizations can be used for different proteins.

Figure 1: Structure of RiboJ, the loop in uppercase is derived from the sTRSV ribozyme, while the additional loop is in lowercase. The catalytic core of the active ribozyme is circled in red and the smaller loop serves to promote translation by exposing the RBS. Figure adapted from Lou et al.

Figure 2: Figure from Lou et al. showing that the relative relationship is preserved when RiboJ is used as an insulator.

First, we wanted to make sure that RiboJ worked the way Lou et al. had outlined, so we characterized RiboJ in the Biobrick Backbone. We reconstructed some of the characterization parts from Lou et al. in the Biobrick Backbone and then proceeded to characterize the impact of RiboJ (Figure 3)

Figure 3A

Figure 3B

Figure 3A and B: Measurements of plLacO-1 sfGFP and cI-GFP with (B) and without (A) RiboJ. Our findings were consistent with Lou et al. Notice how the relative expression curves collapse with RiboJ compared to the ones without RiboJ which do not. Measurements were done in triplicate using FACS. MEFL was calculated using Spherotech beads. The reporters (Bba_K2066014, Bba_K2066015) were located on a high copy 1C3 plasmid while the repressor LacI (Bba_K2066016) was constitutively expressed on a low copy 3K3 plasmid.

While we confirmed the findings of Lou et al. that the relative expression of different proteins under one promoter converges, we also noticed that absolute expression of the same protein is altered by the inclusion of RiboJ. Furthermore, we noticed that the direction of this shift changes based on the promoter used (Fig. 4).

These phenomena led us to initiate a thorough characterization of the impact of RiboJ on the absolute gene expression levels of widely used promoters, including the entire Anderson library of constitutive promoters. We designed a library of promoter characterization constructs with and without RiboJ (Bba_K2066057-K2066108), which consist of the Anderson library as well as additional inducible promoters on a standard superfolder GFP expression cassette. To our knowledge, this will be the first such targeted characterization effort on these promoters in the literature.

Figure 4A

Figure 4B

Figure 4A and B: Mean levels of sfGFP expression with and without RiboJ using the IPTG inducible promoters pLacO-1 (A) and pTac (B). Plasmid set up is the same as in Figure 3. For the plLacO-1 reporter, RiboJ increases the absolute expression level, while for the pTac reporter, RiboJ has little effect on the absolute expression level.

After validating Lou et al.’s results in the BioBrick standard, we carried out our subsequent RBS characterizations with RiboJ insulation to ensure that our results are applicable and useful to other scientists and iGEM teams in general.

References

1. C. Lou, B. Stanton, Y.-J. Chen, B. Munsky, C. A. Voigt, Ribozyme-based insulator parts buffer synthetic circuits from genetic context. Nat. Biotechnol. 30, 1137 (2012). doi:10.1038/nbt.2401 pmid:23034349