Difference between revisions of "Part:BBa K4815007:Experience"
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===Applications of BBa_K4815007=== | ===Applications of BBa_K4815007=== | ||
| + | We utilized the obtained PYPL1 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: | ||
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| + | 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 lower than natural promoters(p = 0.016), and PYPL1-driving expression is 0.89 times of natural promoters (as is shown in the result page of our team). | ||
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| + | We then checked the quantitative gene expression levels using quantitative RT-PCR, and the results indicated that our generated promoters drive a lower transcript accumulation than natural promoters. The result gives a strong vertification that the low exprssions of the synthesized promoters are unaffected with different downstream tondon,and it also proves that it is our synthesized promoters that play a fundamental role in driving lower promoter sequences. | ||
===User Reviews=== | ===User Reviews=== | ||
Latest revision as of 09:17, 12 October 2023
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Applications of BBa_K4815007
We utilized the obtained PYPL1 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 lower than natural promoters(p = 0.016), and PYPL1-driving expression is 0.89 times of 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 lower transcript accumulation than natural promoters. The result gives a strong vertification that the low exprssions of the synthesized promoters are unaffected with different downstream tondon,and it also proves that it is our synthesized promoters that play a fundamental role in driving lower promoter sequences.
User Reviews
UNIQbf4910eb4204fa11-partinfo-00000000-QINU UNIQbf4910eb4204fa11-partinfo-00000001-QINU