Akpinaroglu, D. | Search bioRxiv

bioRxiv2021

Separable mechanisms drive local and global polarity establishment in the C. elegans intestinal epithelium

Apico-basolateral polarization is essential for epithelial cells to function as selective barriers and transporters, and to provide mechanical resiliency to organs. Epithelial polarity is established locally, within individual cells to establish distinct apical, junctional, and basolateral domains, and globally, within a tissue where cells coordinately orient their apico-basolateral axes. Using live imaging of endogenously tagged proteins and tissue specific protein depletion in the C. elegans embryonic intestine, we found that local and global polarity establishment are temporally and genetically separable. Local polarity is initiated prior to global polarity and is robust to perturbation. PAR-3 is required for global polarization across the intestine but is not required for local polarity establishment as small groups of cells are able to correctly establish polarized domains in PAR-3 depleted intestines in an HMR-1/E-cadherin dependent manner. Despite belonging to the same apical protein complex, we additionally find that PAR-3 and PKC-3/aPKC have distinct roles in the establishment and maintenance of local and global polarity. Together, our results indicate that different mechanisms are required for local and global polarity establishment in vivo. SUMMARY STATEMENTLive-imaging and intestine specific protein depletion reveal that apico-basolateral polarity establishment can be temporally and genetically separated at the local level of individual cells and globally, across a tissue.

cell biology↗

bioRxiv2021

Improved antibody structure prediction by deep learning of side chain conformations

Antibody engineering is becoming increasingly popular in medicine for the development of diagnostics and immunotherapies. Antibody function relies largely on the recognition and binding of antigenic epitopes via the loops in the complementarity determining regions. Hence, accurate high-resolution modeling of these loops is essential for effective antibody engineering and design. Deep learning methods have previously been shown to effectively predict antibody backbone structures described as a set of inter-residue distances and orientations. However, antigen binding is also dependent on the specific conformations of surface side chains. To address this shortcoming, we created DeepSCAb: a deep learning method that predicts inter-residue geometries as well as side chain dihedrals of the antibody variable fragment. The network requires only sequence as input, rendering it particularly useful for antibodies without any known backbone conformations. Rotamer predictions use an interpretable self-attention layer, which learns to identify structurally conserved anchor positions across several species. We evaluate the performance of our model for discriminating near-native structures from sets of decoys and find that DeepSCAb outperforms similar methods lacking side chain context. When compared to alternative rotamer repacking methods, which require an input backbone structure, DeepSCAb predicts side chain conformations competitively. Our findings suggest that DeepSCAb improves antibody structure prediction with accurate side chain modeling and is adaptable to applications in docking of antibody-antigen complexes and design of new therapeutic antibody sequences.

biophysics↗