Synonymous Codon Usage Affects the Expression of Wild Type and F508del CFTR

Abstract

The cystic fibrosis transmembrane conductance regulator (CFTR) is an anion channel composed of 1480 amino acids. The major mutation responsible for cystic fibrosis results in loss of amino acid residue, F508, (F508del). Loss of F508 in CFTR alters the folding pathway resulting in endoplasmic reticulum associated degradation (ERAD). This study investigates the role of synonymous codon in the expression of CFTR and CFTR F508del in human HEK293 cells. DNA encoding the open reading frame (ORF) for CFTR containing synonymous codon replacements, were expressed using a heterologous vector integrated into the genome. The results indicate that the codon usage greatly affects the expression of CFTR. While the promoter strength driving expression of the ORFs was largely unchanged and the mRNA half-lives were unchanged, the steady state levels of the mRNA varied by as much as 30 fold. Experiments support that this apparent inconsistency is attributed to exon junction complex independent nonsense mediated decay. The ratio of CFTR/mRNA indicates that mRNA containing native codons was more efficient in expressing mature CFTR as compared to mRNA containing synonymous high expression codons. However, when F508del CFTR was expressed after codon optimization, a greater percentage of the protein escaped ERAD resulting in considerable levels of mature F508del CFTR on the plasma membrane, which showed channel activity. These results indicate that for CFTR, codon usage has an effect on mRNA levels, protein expression and likely, for F508del CFTR, chaperone assisted folding pathway.

A synonymous codon change alters the drug sensitivity of ΔF508 cystic fibrosis transmembrane conductance regulator

“…We have reported that the half‐lives of low‐temperature‐rescued I507‐ATT and I507‐ATC ΔF508 CFTR were similar (2 h) when cells are returned to physiologic temperature (37°C). However, the I507‐ATC ΔF508 CFTR variant displays wild‐type CFTR‐like functional characteristics (18), whereas the I507‐ATT (native) ΔF508 CFTR loses its function quickly, much sooner than expected based on cell surface protein levels and stability (25, 65). We report that VX‐809 extended I507‐ATT and I507‐ATC ΔF508 CFTR cell surface protein half‐lives to 4 h. Further, the combination of C4+VX‐809 eliminated the functional differences between the variants after low‐temperature rescue observed in whole‐cell patch clamp experiments performed in identical conditions.…”

“…ca/cftr/app). Shah et al (18) expressed codon-optimized wild-type and DF508 CFTR constructs in human embryonic kidney (HEK)-293 cells and observed that synonymous codon usage influences both wild-type and DF508 CFTR expression. Although wild-type CFTR expression is more efficient from native codons, DF508 CFTR expression is higher with more efficient processing from the codon-optimized gene.…”

Evidence against resveratrol as a viable therapy for the rescue of defective ΔF508 CFTR

“…Given the low level of increased CFTR production of wt CFTR expressing heterologous cells, it is unlikely that we would increase the production of ΔF508 CFTR beyond the capacity of the cell’s quality control machinery. Why we see no increase in ΔF508 CFTR in response to resveratrol is not immediately apparent to us, but may reflect nonsense mediated decay of ΔF508 mRNA during co-translational processing and ERAD of ΔF508-CFTR [55]. …”

Synthetic gene design—The rationale for codon optimization and implications for molecular pharming in plants

“…Of these software packages, citations have been found for JCat and OPTIMIZER for expression systems such as E. coli (Fahimi et al 2016;Guo et al 2016;Karkhah & Amani 2016;Zhao et al 2016), S. cerevisiae (Ask et al 2013;Guadalupe-Medina et al 2013;Li et al 2015;Milne et al 2015;Solis-Escalante et al 2013), N. benthamiana (Binder et al 2014), HEK293 cells (Shah et al 2015), B. subtilis (Reilman et al 2014), C. crescentus (Ko et al 2013), P. putida (Dammeyer et al 2013;Dammeyer et al 2011), S.…”

“…Many of the codon optimization software lack citations. Of these software packages, citations have been found for JCat and OPTIMIZER for expression systems such as E. coli (Fahimi et al, 2016;Guo et al, 2016;Karkhah and Amani, 2016;Zhao et al, 2016), S. cerevisiae (Ask et al, 2013;Guadalupe-Medina et al, 2013;Li et al, 2015;Milne et al, 2015;Solis-Escalante et al, 2013), N. benthamiana (Binder et al, 2014), HEK293 cells (Shah et al, 2015), B. subtilis (Reilman et al, 2014), Caulobacter crescentus (Ko et al, 2013), Pseudomonas putida (Dammeyer et al, 2011(Dammeyer et al, , 2013, Salmonella typhimurium (Manuel et al, 2011), S. lividans (Dubeau et al, 2009), wheat (Mih alik et al, 2015, transplastomic tobacco plants (chloroplast translation system) (Occhialini et al, 2015), Plasmodium berghei (Singer et al, 2015), Spodoptera frugiperda (Geisler et al, 2015), S. pneumoniae (Overkamp et al, 2013), A. marginale (Pierl e et al, 2013), R. pomeroyi (Green et al, 2013), L. acidophilus (Askelson et al, 2014), C. reinhardtir (Erpel et al, 2016), Y. lipolytica (Matthaus et al, 2014), S. elongates (van der Woude et al, 2016), and baculovirus (Maghodia et al, 2016). While it is encouraging that codon optimization software programs are used for a variety of species and purposes, most of the papers do not compare yields of native and codon optimized sequences, so yield comparisons cannot be made.…”