Coding

Part:BBa_K3924011

Designed by: Yiyuan Huang   Group: iGEM21_Tsinghua   (2021-09-30)


csgA


Sequence and Features


Assembly Compatibility:
  • 10
    INCOMPATIBLE WITH RFC[10]
    Illegal PstI site found at 371
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal PstI site found at 371
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    INCOMPATIBLE WITH RFC[23]
    Illegal PstI site found at 371
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal PstI site found at 371
  • 1000
    COMPATIBLE WITH RFC[1000]

Profile

Name: CsgA
Base Pairs: 453
Origin: Escherichia coli
Properties: Major subunit of Escherichia coli curlin

Usage and Biology

In order to heal the intestinal tract damage, one of notable symptoms of IBD, we adopted a special therapy expressing the therapeutic proteins controllably by E.coli Nissle 1917 (EcN) in situ. The design is based on a ternary system: sensor - secretion peptide - therapeutic proteins.

Figure 1: General design of the treatment ternary system

CsgA is one of candidate secretion peptides we screened out, which is a most essential element that help our therapeutic protein secrete outside the engineered bacteria and diffuse inside the patient's intestinal tract. It is the major unit of Escherichia coli curlin[2]. The sequence is mainly based on NCBI Gene ID: 949055 and modified by our condon preference system.

Design and Construction

According to literature research we chose 7 candidate secretion peptides and did codon analysis with our own software tool.
Table 1. List of candidate therapeutic proteins

Part Name Element Name Origin Reference
BBa_K3924010 DsbA E. coli periplasmic space [1]
BBa_K3924011 CsgA E. coli biofilm matrix [2]
BBa_K3924012 OmpA E. coli outer membrane [3]
BBa_K3924013 PelB Erwinia carotovora periplasmic space [4]
BBa_K3924014 PhoA E. coli periplasmic space [5]
BBa_K3924015 STⅡ E. coli extracellular peptide toxin [6]
BBa_K3924016 TorA E. coli periplasmic space [7]

After getting the codon-optimized sequence for E. coli, we synthesized the sequence by company, and linked them to a GFP element by using HiFi Assembly.

Functional Verification

For all candidate secretion peptides, we did codon analysis with our own software tool.(Figure 2)

Figure 2.Codon preference confidence analysis for secretion peptide, in theroy, the total GC% of EcN is 49.13%, 1st letter GC% is 55.38%, 2nd letter GC% is 42.34%, and 3rd letter GC% is 50.58%. We compare P2N and GenScript® online codon preference tool (GenSmart) analysis results for the bias from theoretical values. The lighter the squares are, the better for the codon optimization. (DNA sequence of each protein is detailed in the part page)

As for csgA, the result of codon preference is shown in Figure 3.

Figure 3.Codon preference confident analysis of csgA

The workflow of the verification of the secretion peptides' function is shown in Figure 4

Figure 4: Secretion peptide flowchart

The functional verification of secretion peptides was conducted by checking the fluorescence of the bacteria supernatant after centrifuging at 8000 rpm for 1 minute. The fluorescence is measured by microplate reader. The results are shown in Figure 5.

Figure 5: Fluorescence intensity

With RGP-GFP group (RGP is the plasmid backbone in our design) as a negative control, which doesn’t have any secretion peptide to diffuse GFP out of the protein, RGP-DsbA-GFP, however, does not show a significant difference. The fluorescence is slightly higher, but maybe due to the volatile lab environment, the significance cannot be shown. Nevertheless, we evaluate this part as a success.
With RGP-GFP group (RGP is the plasmid backbone in our design) as a negative control, which doesn’t have any secretion peptide to diffuse GFP out of the protein, RGP-CsgA-GFP shows a significant difference. Therefore, we evaluate this part as a success.
Usage and Biology

Contribution made by iGEM24_SMU-GDMU-CHINA

We have optimized the codon of the original components,you can click on the part to see details.BBa_K5378011

For the safety module,we referred to a study published in Nature Communications And the PATCH system was used for plasmid design. We first linked the gene fragments responsible for expressing curli fibers to the PBbB8k plasmid, then introduced a 6xHis-tagged linker to connect curli fibers with TFF3, and finally incorporated the TFF3 gene fragment. This configuration allows EcN to secrete and self-assemble curli fibers, linkers, and TFF3 upon reaching the intestine, forming an active domain layer on the intestinal surface. This promotes epithelial cell migration, reduces inflammatory factor levels, supports intestinal barrier repair, and alleviates hepatic encephalopathy complications.

example
Figure 1.our safety module design section CAPTION_HERE

Functional Verification

From the figure below, the size of each band of agarose gel electrophoresis is basically the same as the size of the target gene, indicating that the plasmid has been successfully transformed into EcN.

example
Figure 2.Transfer to bacterial pcr results with TFF3 plasmids

In order to confirm that curli fibers decorated with TFFs could be produced by EcN, as they can in laboratory strains of E. coli, we transformed EcN with the panel of synthetic curli plasmid constructs (Fig.3-a), in addition to a vector in place of the curli genes as a negative control. The transformed cells were cultured at 37 °C and induced with L-(+)-arabinose.

The secretion of TFF3 can be detected by Mouse trefoil factor 3(TFF3) enzyme-linked immunosorbent Assay kit. Results show that the engineered EcN was strongly induced by L-(+)-arabinose with twice as much TFF3 is produced comparing to no induction (Fig3-b).

The secretion of TFF3-fused curli was proved successful (Fig.3-c), however, In some cases, basal expression of the csgA genes was observed without induction.

A quantitative Congo Red-binding (CR) assay, normally used for curli fiber detection, indicated that CsgA-TFF3 fusions could be expressed and assembled into curli fibers under these conditions, while EcN control vector showed no CR binding(Fig3-d).

example
Figure 3.Functionality verification of the PEA-sensing NH3-metabolizing system.(a)Schematic representation of the process of sensing and metabolic module. EcN was co-transformed with plasmid Pcon-FeaR-Pcon-TynA and plasmid PTynA-GS via electroporation. (b)NH3 concentration after coculturing different concentration of PEA and NH4Cl with engineered EcN for 12 hours. Data shows mean±SD, n=3 independent experiments.(c)NH3 concentration after coculturing 100ng/ml PEA and 50μM NH4Cl engineered EcN for 0, 4, 8,12 and 24 hours. EcN-FeaR-TynA was transformed with only plasmid Pcon-FeaR-Pcon-TynA as the control group. Data shows mean±SD, n=3 independent experiments.
==Reference== [1] Zhou Y Z, Liu P, Gan Y T, et al.Enhancing full-length antibody production by signal peptide engineering.Microbial Cell Factories, 2016,15(1):1-11.
[2] Van Gerven, N., Klein, R. D., Hultgren, S. J., & Remaut, H. (2015). Bacterial amyloid formation: structural insights into curli biogensis. Trends in microbiology, 23(11), 693–706.
[3] Zhao F K, Song Q Z, Wang B B, et al.Secretion of the recombination α-amylase in Escherichia coli and purification by the gram-positive enhancer matrix (GEM) particlesInternational Journal of Biological Macromolecules, 2019,123:91-96.
[4] Sriwidodo S, Subroto T, Maksum I, et al.Optimization of secreted recombinant human epidermal growth factor production using pectate lyase B from Escherichia coli BL21(DE3) by central composite design and its production in high cell density culture
[5] Mohajeri A, Abdolalizadeh J, Pilehvar-Soltanahmadi Y, et al.Expression and secretion of endostar protein by Escherichia coli: optimization of culture conditions using the response surface methodology Molecular Biotechnology, 2016,58(10):634-647.
[6] Lu C, Zhao H, Zou W Y, et al.Secretion expression of recombinate human interferon α-2b by Escherichia coli Journal of Biology, 2011,28(3):58-62.
[7] Guerrero Montero I, Richards K L, Jawara C, et al.Escherichia coli “TatExpress” strains export several g/L human growth hormone to the periplasm by the Tat pathway Biotechnology and Bioengineering, 2019,116(12):3282-3291.

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