Difference between revisions of "Team:IISER-Tirupati India/Parts"

Overview

Due to the novel approaches taken while pursuing this project, we found ourselves using new parts that had not been given in the iGEM registry. In total, we developed 37 new basic parts (either entirely new or by modifying previously existing ones). We strongly believe that these two collections can be exploited to their full potential by the subsequent iGEM generations.

Furthermore, we have designed and used multiple combinations of basic parts as given in the composite part section.These composite parts can be used in multiple settings depending on the requirements of the projects.

The parts used in our project are as follows:

Previous Parts used:

Basic Parts: 

Composite Parts: 

Improvement:

Introduction:

While engineering any new circuit, there is always a need for well-characterized and predictable parts. Not only should the circuit function as expected, but it should also be orthogonal to irrelevant cell processes, thereby increasing the need to have efficient production and, in some cases, more importantly, efficient termination. While there are several well-studied and efficient terminators for E. coli, we found no specific efficient single terminator on the iGEM registry that could stand out for B. subtilis chassis. Hence, we decided to improvise a terminator which might fulfil this gap.

Measuring efficiency:

The experiment is divided into two cassettes: one reference and the other is a test cassette containing a terminator whose efficiency needs to be determined as shown by Gale et al.[1].

The device/reference (Fig 1.) and the test cassette (Fig 2 and 3.) provide us the expression levels of both the fluorescent proteins which could be compared to tell us how efficiently the terminator is working.

Formulae for terminator efficiency [1]

\begin{equation}\tag{1}TE_{Device}=\frac{mCherry_{0}}{sfGFP_{0}}\end{equation}
where,

$mCherry_{0}\rightarrow$ mCherry produced by device without terminator

$sfGFP_{0}\rightarrow$ sfGFP produced by device without terminator

Using the device without any changes, $TE_{Device}$ can be calculated which gives the expression of
$mCherry$ in absence of a terminator.



where,

$mCherry$ $\rightarrow$ mCherry produced by device with the terminator that needs to checked

$sfGFP$ $\rightarrow$ sfGFP produced by device with the terminator that needs to checked

d-score:

For E. coli terminators d'Aubenton Carafa [3] gave a scoring system as shown below:

$d=96.59 \times \frac{-\Delta G/(kcal/mol)}{n_{SL}} + 18.16 \times T_{score} -116.87$

Where 

d is the d-score

$-\Delta G$ is the Gibbs free energy of stem-loop formation in kcal/mole

n_SL is the length of the stem loop

T_Score is the score for T-stretch of the terminators

Coefficients are according to fitting the d'Aubenton Carafa’s model 

The T_Score is calculated as follows:

$T_{score}= \sum\limits_{i=0}^{\ 14} x _i$

Where

$x_0 = 0.9$

$x_i = 0.9$ if $i^{th}$ nucleotide is thymine

$x_i = 0.6 \times x_{i-1}$ if $i^{th}$ nucleotide is not thymine

This scoring system was modified by de Hoon et al. [2] for Bacillus subtilis as per their model which is as follows:

$d=7.90 \times \frac{-\Delta G/(kcal/mol)}{n_{SL}} + 2.67 \times T_{score} -14.91$

Where 

d is the d-score

$-\Delta$ G is the Gibbs free energy of stem-loop formation in kcal/mole

n _SL is the length of the stem loop

T_Score is the score for T-stretch of the terminators

Coefficients are according to fitting the model 

Here the T_Score is calculated as follows:

$T= \sum\limits_{i=0}^{\ 14} e^{- \lambda _i} \delta_i$

Where

$\lambda _i = 0.144$ as per the fitting of the model

$\delta_i = 0$ if $i^{th}$ nucleotide is not thymine 

$\delta_i = 1$ if $i^{th}$ nucleotide is thymine

As the d-score takes into account the Gibbs free energy, length of the stem-loop and the richness of thymine in the T-stretch which are essential for a rho independent terminator. Hence, the d-score can provide a rough idea about how good a terminator is. In other words, the higher the d-score higher will be the terminator efficiency.[3]

Improvement:

We decided to improve BBa_B0010 in order to make a strong terminator which can be used for primarily the B. subtilis chassis while still retaining its efficiency in E. coli. For doing this we modified the tail of BBa_B0010 and fused another rho-independent terminator from the B. subtilis genome on the basis of its d-Score. 

From a list of 425 native B.subtilis terminators taken from the study conducted by de Hoon et al [2], we calculated the d-score of each terminator to get a rough idea of their efficiency which is in the Data file containing both data as well as T-stretch calculator python file. Based on the results the highest d-score= 5.666126119 was of the terminator belonging to the gene nagP. Both BBa_B0010 and nagP terminators were ligated to form a double terminator.

Based on our calculations, we decided to go with nagP terminator. We modified the end regions of BBa_B0010 and ligated to it the nagP terminator to create an improved version(BBa_K3889070). Using the server RNAFold we calculated the minimum energy to show in silico that the improved terminator will have more negative Minimum Free energy as shown. 

	BBa_B0010	BBa_B0010+nagP
Minimum Free Energy (kcal/mol)	-40	-64.6

The predicted structure for these two terminators as given by RnaFold server is:

1. BBa_B0010:

   

2. BBa_B0010+nagP:

   

References:

1. Gale, G. A. R., Wang, B., & McCormick, A. J. (2021). Evaluation and Comparison of the Efficiency of Transcription Terminators in Different Cyanobacterial Species. Frontiers in Microbiology, 11. https://doi.org/10.3389/fmicb.2020.624011 : 
2. de Hoon, M. J. L., Makita, Y., Nakai, K., & Miyano, S. (2005). Prediction of Transcriptional Terminators in Bacillus subtilis and Related Species. PLoS Computational Biology, 1(3), e25. https://doi.org/10.1371/journal.pcbi.0010025 
3. Carafa, Y. d’Aubenton, Brody, E., & Thermes, C. (1990). Prediction of rho-independent Escherichia coli transcription terminators. Journal of Molecular Biology, 216(4), 835–858. https://doi.org/10.1016/s0022-2836(99)80005-9