Difference between revisions of "Part:BBa K4815005:Experience"
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===Applications of BBa_K4815005=== | ===Applications of BBa_K4815005=== | ||
+ | We utilized the obtained PYPH6 to drive the expression of the mucosal vaccine adjuvant LTB downstream in yeast, resulting in the fusion protein of LTB and GFP. The expression level of this fusion protein was quantitatively analyzed using flow cytometry, and expression analysis was conducted at both the transcriptional and translational levels. The results are as follows: | ||
+ | |||
+ | Using GAPDH as an internal control ,we quantify the expression intensity of LTB-eGFP as Intensity[LTB-eGFP]/intensity[GAPDH]. The above figure illustrates that expression driven by our Pymaker generated promoter is significantly higher than natural promoters(p = 0.016), and PYPH6-driving expression is 5.18 times higher than natural promoters (as is shown in the result page of our team). | ||
+ | |||
+ | We then checked the quantitative gene expression levels using quantitative RT-PCR, and the results indicated that our generated promoters drive a much higher transcript accumulation than natural promoters. The result gives a strong validation that it is our generated promoters that play a fundamental role in driving a extremely high promoter sequences. | ||
===User Reviews=== | ===User Reviews=== |
Revision as of 13:19, 12 October 2023
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Applications of BBa_K4815005
We utilized the obtained PYPH6 to drive the expression of the mucosal vaccine adjuvant LTB downstream in yeast, resulting in the fusion protein of LTB and GFP. The expression level of this fusion protein was quantitatively analyzed using flow cytometry, and expression analysis was conducted at both the transcriptional and translational levels. The results are as follows:
Using GAPDH as an internal control ,we quantify the expression intensity of LTB-eGFP as Intensity[LTB-eGFP]/intensity[GAPDH]. The above figure illustrates that expression driven by our Pymaker generated promoter is significantly higher than natural promoters(p = 0.016), and PYPH6-driving expression is 5.18 times higher than natural promoters (as is shown in the result page of our team).
We then checked the quantitative gene expression levels using quantitative RT-PCR, and the results indicated that our generated promoters drive a much higher transcript accumulation than natural promoters. The result gives a strong validation that it is our generated promoters that play a fundamental role in driving a extremely high promoter sequences.
User Reviews
UNIQcc64ed232a979259-partinfo-00000000-QINU UNIQcc64ed232a979259-partinfo-00000001-QINU