Team:SCUT China/Description

What is the meaning of this old saying？ 

This is the ancient wisdom from Chinese cuisin. In the kitchen, when you cook a small fish, the best existence of five tastes means that not to let have some blindly to appear particularly outstanding among them, but the harmony of five tastes and balance. This great wisdom not only is the perfect state that Chinese successive dynasties chefs seeks ceaselessly, but also the ideal state that Chinese people pursue in dealing with people and even governing a great nation.

Inspired by this wisdom, we come up with an idea just like a bite of tomorrow to deal with the problem in regulating genetic system precisely.

The challenge of precise regulation of genetic system

Precise and reliable gene expression is critical in fine regulation of gene or pathway expression. Generally, the optimal expression of one gene often depends on the expression levels of other genes in the system, thus multiple genes have to be regulated simultaneously to achieve an improvement. For the metabolic pathway, the challenge is that the correct expression levels are often not knowna priori. Suboptimal enzyme concentrations could always lead to some problems, such as the low flux of products, accumulation of toxic intermediates or overburdening the host ^[1-3].

Figure1. The challenge of precise regulation of genetic system[2]
（Take a two-enzyme metabolic pathway）

Upon these reasons, precise regulation of genetic system often requires library construction to vary the genetic parts controlling each gene. Typically, libraries of multi-gene systems can be built using guided and unguided approaches. Many variants of a pathway can be constructed by substituting genetic parts controlling each gene; for example, promoters, ribosome binding sites(RBSs), and RNA stability elements^[4-6].
 

For promoters and RBS libraries, due to the complicated gene combination and assembly process, the number of combinations is small, and this simple regulation makes the optimal results often differ greatly from the actual optimal combination. What’s more, each adjustment of a new system requires the reconstruction of the library, which is time-consuming and difficult to be applied in practice. The limitation of sRNA pool is that the genes can only be repressed, as opposed to being up-regulated. This can be problematic if any of the genes are toxic^[5].

It is necessary to explore a universal, efficient and simple promoter comprehensive regulation and optimization technology, and optimize the fitness of multi-factor system in E. coli to obtain the ideal yield.

	Promoters pool	RBS pool	sRNA pool	VerProS pool
Repeatability	No	NO	Universal	Universal
Workload	Tedious	Tedious	Less	Less
Regulation range	Narrow	Large	Large	Large
Control	Active	Active	Repressive	Active

Figure2. Comparison of several simultaneous regulation methods of multi-genes

A bite of tomorrow--what do we create?   

To address the challenge we face now, a method where the expression levels of multiple genes could be simultaneously regulated without the need to rebuild a library for each system is promising. Therefore we propose a novel method to optimize the adaptability of multi-gene system in E. coli, with only one library so-called Versatile Promoter-Toehold Switches(VerProS) pool. This pool is built where four Toehold Switches are placed under one of 10 promoters that yielding about 10⁴ combinations, and it can optimize up to four genes in a system simultaneously. Particularly, this versatile pool can be applied to fast optimization in different systems without having to build ad hoc libraries, which can greatly reduce manpower and costs.

Figure3. Schematic diagram of VerProS pool

Design-Build-Test-Learn cycle

Here, we would like to demonstrate the versatility of this approach by using the pool for fine regulation of four genes to enhance the acid tolerant of E. coli. Follow the classical approach of synthetic biology design-build-test-learn cycle, we suppose that this up-and-coming method can access previously unattainable regions of genetic space, and provide a useful, fast tool for genetic optimization^[7-8].

Figure4. Design-build-test-learn cycle

• 

  Design

• 

  Build

• 

  Test

• 

  Learn

Design

--Toehold switches

To achieve the simultaneous regulation of multi-genes with a separate library, built once, it should contain some regulators expressed at different levels. Each regulator would control a different gene in the system so that changes in regulator expression lead to changes in the target gene. Here, we selected Toehold Switches as their orthogonality are close to 100%; have wide dynamic range；possess excellent universality^[9].

 

Figure5. Structures of Toehold Switch

Figure6. Orthogonality and dynamic range of Toehold Switch^[9]

--T7 promoter

The T7 promoter is recognized by T7 RNA polymerase. Since T7 RNA polymerase is a very powerful RNA polymerase, it can synthesize mRNA several times more efficiently than E. coli RNA polymerase, and stops transcription less frequently, so it is enough to stop the background expression of E. coli. Therefore, T7 promoter plays an important role in the study of the comprehensive regulation and optimization of promoter^[5]. 

--Acid tolerant factors

Global regulators are prone to trigger unnecessary responses and need to be precisely regulated against acid factors. Therefore, we selected 4 structural genes as our parts through a large number of investigations^[10].

 

Figure7. Different strategies of acid tolerant factors

 

Build

--Integration of T7 RNAP by CRISPR-Cas9 into MG1655

A large number of experimental evidence signs that MG1655 has good acid tolerance and always has higher growth rate than BL21 in the acid environment, so it is more suitable for the expression of acid tolerance factors in this project. But because MG1655 does not have the T7 expression system, so it is necessary to use the CRISPR-Cas9to integrate the T7RNAP into the MG1655 genome.

--Construction of VerProS pool

After ten T7 Promoters of different strength screened and forty kinds of promoters + Trigger RNA plasmid vectors were constructed by annealing splicing, forty plasmids and a negative selection ccdB lethal plasmids were randomly combined to build VerProS Pool with a capacity of 10⁴by Golden Gate assembly.

--Construction of acid-tolerant working part

 

In order to better realize the versatility of VerProS pool, we have designed 10 standardized parts to construct the working part by Golden Gate Assembly. Then We would like to demonstrate the versatility of our approach by using the VerProS pool for fine regulation of four genes to enhance the acid tolerant of E. coli. 

Test

The resulting library is screened and the top clone is sequenced to determine the promoter controlling each Trigger, from which the fold-repression of the genes can be inferred. We attempted to provide local blast packetto provide an efficient method for screening promoters from the DNA sequencing result.

Learn

In science, crafting theoretical models can help understand, predict and improve experiments and their interpretation. In our project, combinatorial optimization models based on neural networks create a general framework for precise quantitative control of gene expression.

Design

10000

combinations

in VerProS pool

Demonstrate

∞

versatile application of VerProS pool

Safety

5

aspects of security risk self-assessment

HP

1

The first socialized & marketized system theory of synthetic biology

In our project, we have constructed about 10,000 combinations in VerProS pool. This pool has versatile application which is bite of tomorrow need us to reach into our infinity and imagination. Also our team has concluded 5 aspects of security risk self-assessment. Most importantly, we are the first team who put forward a socialized and marketized system theory of synthetic biology.  We expect that we will see traces of our thinking and the application of this project in the future which is sufficiently simple to be routinely or systematically applied when building constructs for new pathways.

References

1. [1]Lee,M.E.,Dueber,J.E. (2013).Expression-level optimization of a multi-enzyme pathway in the absence of a high-throughput assay.
   
2. [2]Stephanopoulos,G. (1999). Metabolic fluxes and metabolic engineering.
3. [3]San,K.-Y., Bennett,G.N.,et al. (2002). Metabolic engineering through cofactor manipulation and its effectson metabolic flux redistribution in Escherichia coli.
4. [4]Kosuri,S., Goodman,D.B., et al. (2013). Composability ofregulatory sequences controlling transcription and translation in Escherichia coli.
5. [5]Amar Ghodasara and Christopher A. Voigt. (2017). Balancing gene expression without library construction via a reusable sRNA pool.
6. [6]Scott M, Gunderson C W, Mateescu E M, et al.(2010). Interdependence of cell growth and gene expression: origins and consequences.
7. [7]Matthias Heinemann, and Sven Panke. (2006). Synthetic biology—putting engineering into biology.
8. [8]Michael J Smanski, Swapnil Bhatia, et al.(2014). Functional optimization of gene clusters by combinatorial design and assembly.
9. [9]Alexander A. Green, Pamela A. Silver, James J. Collins, Peng Yin.(2014). Toehold switches: de-novo-designed regulators of gene expression.
10. [10]Liu Y, Tang H, Lin Z, Xu P. (2015). Mechanisms of acid tolerance in bacteria and prospects in biotechnology and bioremediation.