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- Title
Targeted quantitation of CFTR protein expression in vivo using immunoprecipitation & parallel reaction monitoring tandem mass spectrometry.
- Authors
Wang, Hui; Dai, Yunxiang; Clark, Nicholas; Boeglin, Lianne; Woo, Caroline; Wooster, Richard; Sun, Gang; Sullivan, James C.
- Abstract
Background: The cystic fibrosis transmembrane conductance regulator (CFTR) protein is a low-abundance membrane protein. The dysfunction of CFTR protein is the fundamental cause of cystic fibrosis (CF), a fatal genetic disease. In recent years, the novel messenger RNA (mRNA)-based therapy shows high potential to treat CF disease, by delivering CFTR mRNA into lung epithelial cells to generate fully functional CFTR replacement protein. To evaluate mRNA drug efficacy, a targeted quantitative proteomics method is needed to estimate the expression level of mRNA encoded CFTR protein. Methods: In this paper, a method combining membrane protein extraction, immunoprecipitation (IP), and nanoLC-MS/MS for quantifying CFTR in lung tissue samples was reported for the first time. Absolute quantification was performed by constructing a standard curve by spiking recombinant human CFTR protein in mouse lung tissue matrix. Results: This method was qualified, with good linearity of standard curve and lower limit of quantification of human CFTR at 1.4 pg per mg tissue. The coefficient of variation of back calculated concentration of all standards and their back-calculation errors were < 20%. The CFTR expression level in mouse lungs dosed with mRNA encapsulated lipid nanoparticle (LNP), and the endogenous level in wild type human lungs were measured successfully. Conclusions: The result demonstrated high sensitivity, precision and accuracy of this proteomics method for quantifying low-abundance CFTR protein in lung tissue sample.
- Subjects
CYSTIC fibrosis treatment; IN vivo studies; LIQUID chromatography; LUNGS; ANIMAL experimentation; PRECIPITIN tests; PROTEOMICS; MASS spectrometry; MESSENGER RNA; HUMAN error; MEMBRANE proteins; SENSITIVITY &; specificity (Statistics); GENETIC techniques; MICE; NANOPARTICLES
- Publication
Translational Medicine Communications, 2022, Vol 7, Issue 1, p1
- ISSN
2396-832X
- Publication type
Article
- DOI
10.1186/s41231-022-00117-5