In silico algorithms have been the common approach for transmembrane (TM) protein topology prediction. However, computational tools may produce questionable results and experimental validation has proven difficult. Although biochemical strategies are available to determine the C-terminal orientation of TM proteins, experimental strategies to determine the N-terminal orientation are still limited but needed because the N-terminal end is essential for membrane targeting. Here, we describe a new and easy method to effectively determine the N-terminal orientation of the target TM proteins in Escherichia coli plasma membrane environment. D94N, the mutant of bacteriorhodopsin from Haloarcula marismortui, can be a fus... More
In silico algorithms have been the common approach for transmembrane (TM) protein topology prediction. However, computational tools may produce questionable results and experimental validation has proven difficult. Although biochemical strategies are available to determine the C-terminal orientation of TM proteins, experimental strategies to determine the N-terminal orientation are still limited but needed because the N-terminal end is essential for membrane targeting. Here, we describe a new and easy method to effectively determine the N-terminal orientation of the target TM proteins in Escherichia coli plasma membrane environment. D94N, the mutant of bacteriorhodopsin from Haloarcula marismortui, can be a fusion partner to increase the production of the target TM proteins if their N-termini are in cytoplasm (Nin orientation). To create a suitable linker for orientating the target TM proteins with the periplasmic N-termini (Nout orientation) correctly, we designed a three-TM-helix linker fused at the C-terminus of D94N fusion partner (termed D94N-3TM) and found that D94N-3TM can specifically improve the production of the Nout target TM proteins. In conclusion, D94N and D94N-3TM fusion partners can be applied to determine the N-terminal end of the target TM proteins oriented either Nin or Nout by evaluating the net expression of the fusion proteins.
