Production and characterization of neurosecretory protein GM using Escherichia coli and Chinese Hamster Ovary cells

AbstractNeurosecretory protein GL (NPGL) and neurosecretory protein GM (NPGM) are paralogs recently discovered in birds and in mammals. The post-translational products of NPGL and of NPGM genes include a signal peptide sequence, a glycine amidation signal, and a dibasic amino acid cleavage site. This suggests that the mature forms of NPGL and of NPGM are small proteins secreted in the hypothalamus and containing an amidated C-terminus. However, endogenous NPGL and NPGM have not yet been identified. Chicken NPGL and NPGM have two highly conserved Cys residues that are likely to form a disulfide bond, while mammalian NPGM has one additional Cys residue located between the two conserved Cys residues and the correct disulfide bond pattern is unclear. In this study, we prepared rat NPGM to elucidate the structure of its mature form. We first expressed the predicted mature NPGM, containing an extra C-terminal Gly, in Escherichia coli SHuffle cells, which are engineered to promote the formation of native disulfide bridges in recombinant proteins. We observed the presence of a disulfide bond between the N-terminal Cys residue and the second Cys residue, while the C-terminal Cys residue was free. Secondly, we transfected a construct containing the entire NPGM open reading frame into Chinese Hamster Ovary cells, and observed that NPGM was cleaved immediately after the signal peptide and that it was secreted into the medium. Furthermore, the protein presented a disulfide bond at the same location observed in recombinant NPGM

Spatial Motion Doodles: Sketching Animation in VR Using Hand Gestures and Laban Motion Analysis

International audienceWe present a method for easily drafting expressive character animation by playing with instrumented rigid objects. We parse the input 6D trajectories (position and orientation over time)-called spatial motion doodles-into sequences of actions and convert them into detailed character animations using a dataset of parameterized motion clips which are automatically fitted to the doodles in terms of global trajectory and timing. Moreover, we capture the expres-siveness of user-manipulation by analyzing Laban effort qualities in the input spatial motion doodles and transferring them to the synthetic motions we generate. We validate the ease of use of our system and the expressiveness of the resulting animations through a series of user studies, showing the interest of our approach for interactive digital storytelling applications dedicated to children and non-expert users, as well as for providing fast drafting tools for animators