Difference between revisions of "Part:BBa K4815008:Experience"
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We utilized the obtained PYPL2 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: | We utilized the obtained PYPL2 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 PYPL2-driving expression is 0. | + | 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 PYPL2-driving expression is 0.86 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. | 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. |
Latest revision as of 15:47, 12 October 2023
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We utilized the obtained PYPL2 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 PYPL2-driving expression is 0.86 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.
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