Part:BBa_K4167000
toehold switch-amilCP
Toehold switch-amilCP was inserted into pSB1C3 which is designed to express amilCP protein triggered by miRNA 34a-5p. It is used to detect the amount of miRNA 34a-5p in samples.
Sequence and Features
- 10COMPATIBLE WITH RFC[10]
- 12COMPATIBLE WITH RFC[12]
- 21COMPATIBLE WITH RFC[21]
- 23COMPATIBLE WITH RFC[23]
- 25COMPATIBLE WITH RFC[25]
- 1000COMPATIBLE WITH RFC[1000]
To construct the standard part, toehold switch-amilCP was synthesized and checked the restriction enzyme information, which is shown as follows:
Fig.1 The map of toehold switch-amilCP described with SnapGene Viewer, showing the restriction enzyme information (no EcoRI and PstI sites).
After detecting the restriction enzyme information of toehold switch-amilCP using SnapGene software, it was inserted into the pSB1C3 plasmid to construct the standard part pSB1C3-toehold switch-amilCP with PCR method. Then it was identified as follows:
Fig.2 Identification of standard part pSB1C3-toehold switch-amilCP using PCR and digestion with EcoRI and PstI.
M: Marker; 1: PCR result; Digestion result.
Toehold switch-amilCP plasmid is designed to express the amilCP protein controlled by the toehold switch and miRNA 34a-5p. It comprises the antisense sequence of miRNA 34a-5p, RBS, Linker and part sequence of miRNA 34a-5p, which form a toehold switch, as well as the gene of marker protein amilCP. At the presence of miRNA 34a-5p, it binds to its antisense sequence, opening the toehold switch to trigger the expression of amilCP, which is easily measured. The mechanism is shown as Fig.3.
Fig.3 The mechanism of toehold switch-amilCP.
Toehold switch-amilCP was also cloned into pET-28a expression vector, constructing the recombined plasmid pET-28a-toehold switch-amilCP. After it was transfected into BL21 strain, no amilCP protein (purple color) could be observed with naked eyes, indicating that the toehold switch was effective. However, after transfection with miRNA 34a-5p into the BL21 strain transfected with pET-28a-toehold switch-amilCP, some transfected clones appeared purple color, which were shown in Fig.4.
Fig.4 The effectiveness of toehold switch-amilCP.
Bacteria clones only transfected with toehold switch-amilCP appeared white color, while bacteria clones transfected with both toehold switch-amilCP and miRNA 34a-5p appeared purple color (miRNA 34a-5p switched on the expression of amilCP).
To increase the yielding of marker protein amilCP, some different culture conditions were optimized, including the pH value, temperature, fermentation time, and the concentration of transfected miRNA. BL21 strain containing toehold switch plasmid were cultured under different conditions. Since reporter protein amilCP has color, we can easily intuitively find the optimal conditions through the change of color. The optimization experiment results indicated that pH7.2, 37°C, fermentation 18h, and 1.5uM miRNA are the best culture conditions for higher reporter protein production in E. coli.
Fig.5 Optimization of culture conditions of BL21 strain with toehold switch-amilCP plasmid and miRNA 34a-5p.
References
1. Wan Y, Liu Y, Wang X, Wu J, Liu K, Zhou J, Liu L, Zhang C. Identification of differential microRNAs in cerebrospinal fluid and serum of patients with major depressive disorder. PLoS One, 2015 Mar 12;10(3): e0121975. doi: 10.1371/journal.pone.0121975
2. Zhou L, Zhu Y, Chen W, Tang Y. Emerging role of microRNAs in major depressive disorder and its implication on diagnosis and therapeutic response. J Affect Disord. 2021 May 1;286: 80-86. doi: 10.1016/j.jad.2021.02.063
3. Green AA, Silver PA, Collins JJ, Yin P. Toehold switches: de-novo-designed regulators of gene expression. Cell. 2014 Nov 6;159(4):925-39. doi: 10.1016/j.cell.2014.10.002
Contribution
According to Al-Rawaf et al. [2] and Kuang et al. [3], miRNA 34a-5p was upregulated in the serum of MDD patients, as shown in Figure 1A. According to Feng et al. [4] and Kuang et al. [3], miRNA 221-3p was upregulated in the serum of MDD patients, as shown in Figure 1B. Meanwhile, Bahi et al. [5] and Mendes-Silva et al. [6] reported increased miRNA let-7d-3p concentrations in MDD patient serum as shown in Figure 1C. The above findings all support the 2022 ICJFLS team and their project.
Figure 1. (A) miR-34a-5p expression in normal and MDD cells. (B) miR-34a-5p expression in MDD cells before and after treatment
However, we also noticed that miRNA 34a-5p was downregulated in some other MDD patient tissues, including the anterior cingulate cortex (ACC) [7] and the Brodmann area [8]. This implies major differences in cellular activity and metabolism among cells of different tissues in MDD patients, leaving room for future research.
Furthermore, many other researchers have reported findings of other miRNAs in MDD patient tissues, including miR-363-5p [9], miRNA 218-5p [10], and miRNA 320a-5p [10], as shown in Figure 2. Therefore, new parts can be designed to target the above biomarkers and support MDD diagnosis.
Figure 2. Additional mRNAs that unnormally expressed in MDD
In addition to miRNAs, several types of long non-coding RNA (lncRNA) are also expressed at abnormal levels in MDD patient tissue cells and can serve as biomarkers for the disease. Examples include TCONS_l2_00001212, NONHSAT102891, and TCONS_00019174 were downregulated, while ENST00000517573 was upregulated [11].
Additionally, many other types of molecules also exist at abnormal levels in MDD patient tissues, making them potential biomarkers for MDD. Examples include Immunoglobulin A, estrogen, serotonin, Plasma C-reactive protein, g-aminobutyric acid, and cortisol [12, 13].
This year, our YiYe-China team is utilizing the secondary structure of mRNA to diagnose gastric cancer. Through our process, we used the RNAfold website to predict mRNA secondary structures. Many research topics involve RNA secondary structures, but currently, programs such as RNAfold are not used very frequently as it is relatively new. Here, we suggest that such computer programs will provide substantial help to RNA-related research in the future.
Reference
[1] ICJFLS team. “Project Description.” IGEM, 2022.igem.wiki/icjfls/description.
[2] Al-Rawaf, Hadeel A., et al. “Circulating MicroRNAs and Molecular Oxidative Stress in Older Adults with Neuroprogression Disorders.” Disease Markers, vol. 2021, 22 Oct. 2021, pp. 1–10, https://doi.org/10.1155/2021/4409212
[3] Kuang, Wei-Hong, et al. “MicroRNA-451a, MicroRNA-34a-5p, and MicroRNA-221-3p as Predictors of Response to Antidepressant Treatment.” Brazilian Journal of Medical and Biological Research, vol. 51, no. 7, 2018, https://doi.org/10.1590/1414-431x20187212
[4] Feng, Jianguo, et al. “Serum MiR-221-3p as a New Potential Biomarker for Depressed Mood in Perioperative Patients.” Brain Research, vol. 1720, Oct. 2019, p. 146296, https://doi.org/10.1016/j.brainres.2019.06.015
[5] Amine Bahi, and Jean-Luc Dreyer. “Lentiviral-Mediated Let-7d MicroRNA Overexpression Induced Anxiolytic- and Anti-Depressant-like Behaviors and Impaired Dopamine D3 Receptor Expression.” European Neuropsychopharmacology, vol. 28, no. 12, 20 Sept. 2018, pp. 1394–1404, https://doi.org/10.1016/j.euroneuro.2018.09.004
[6] Mendes-Silva, Ana Paula, et al. “Shared Biologic Pathways between Alzheimer Disease and Major Depression: A Systematic Review of MicroRNA Expression Studies.” The American Journal of Geriatric Psychiatry, vol. 24, no. 10, Oct. 2016, pp. 903–912, https://doi.org/10.1016/j.jagp.2016.07.017
[7] Azevedo, Joshua A., et al. “The MicroRNA Network Is Altered in Anterior Cingulate Cortex of Patients with Unipolar and Bipolar Depression.” Journal of Psychiatric Research, vol. 82, 1 Nov. 2016, pp. 58–67, www.sciencedirect.com/science/article/pii/S0022395616301431, https://doi.org/10.1016/j.jpsychires.2016.07.012
[8] Smalheiser, Neil R., et al. “MicroRNA Expression Is Down-Regulated and Reorganized in Prefrontal Cortex of Depressed Suicide Subjects.” PLoS ONE, vol. 7, no. 3, 9 Mar. 2012, p. e33201, https://doi.org/10.1371/journal.pone.0033201
[9] Wang, Haiyang, et al. “MicroRNA–Messenger RNA Regulatory Network Mediates Disrupted TH17 Cell Differentiation in Depression.” Frontiers in Psychiatry, vol. 13, 5 Apr. 2022, https://doi.org/10.3389/fpsyt.2022.824209
[10] Wan, Zhirong, et al. “MiR-218-5p and MiR-320a-5p as Biomarkers for Brain Disorders: Focus on the Major Depressive Disorder and Parkinson’s Disease.” Molecular Neurobiology, vol. 60, no. 10, 17 June 2023, pp. 5642–5654, https://doi.org/10.1007/s12035-023-03391-y
[11] Zhang, Xin, et al. “Early-Diagnosis of Major Depressive Disorder: From Biomarkers to Point-of-Care Testing.” TrAC Trends in Analytical Chemistry, vol. 159, Feb. 2023, p. 116904, https://doi.org/10.1016/j.trac.2022.116904.
[12] Kennis, Mitzy, et al. "Prospective Biomarkers of Major Depressive Disorder: A Systematic Review and Meta-Analysis." Molecular Psychiatry, vol. 25, 2020, pp. 321–338. https://doi.org/10.1038/s41380-019-0585-z
[13] Cui, Xuelian, et al. “Long Non-Coding RNA: Potential Diagnostic and Therapeutic Biomarker for Major Depressive Disorder.” Medical Science Monitor, vol. 22, 31 Dec. 2016, pp. 5240–5248, https://doi.org/10.12659/msm.899372.
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