Bouvier, G. | bioRxiv Science

bioRxiv2020

Head Movements Control the Activity of Primary Visual Cortex in a Luminance Dependent Manner

The vestibular system broadcasts head-movement related signals to sensory areas throughout the brain, including visual cortex. These signals are crucial for the brains ability to assess whether motion of the visual scene results from the animals head-movements. How head-movements impact visual cortical circuits remains, however, poorly understood. Here, we discover that ambient luminance profoundly transforms how mouse primary visual cortex (V1) processes head-movements. While in darkness, head movements result in an overall suppression of neuronal activity, in ambient light the same head movements trigger excitation across all cortical layers. This light-dependent switch in how V1 processes head-movements is controlled by somatostatin expressing (SOM) inhibitory neurons, which are excited by head movements in dark but not in light. This study thus reveals a light-dependent switch in the response of V1 to head-movements and identifies a circuit in which SOM cells are key integrators of vestibular and luminance signals.

neuroscience↗

bioRxiv2020

Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution

Electron cryo-microscopy (cryo-EM) has emerged as a powerful method to obtain three-dimensional (3D) structures of macromolecular complexes at atomic or near-atomic resolution. However, de novo building of atomic models from near-atomic resolution (3-5 [A]) cryo-EM density maps is a challenging task, in particular since poorly resolved side-chain densities hamper sequence assignment by automatic procedures at a lower resolution. Furthermore, segmentation of EM density maps into individual subunits remains a difficult problem when no three-dimensional structures of these subunits exist, or when significant conformational changes occur between the isolated and complexed form of the subunits. To tackle these issues, we have developed a graph-based method to thread most of the C- trace of the protein backbone into the EM density map. The EM density is described as a weighted graph such that the resulting minimum spanning tree encompasses the high-density regions of the map. A pruning algorithm cleans the tree and finds the most probable positions of the C- atoms, using side-chain density when available, as a collection of C- trace fragments. By complementing experimental EM maps with contact predictions from sequence co-evolutionary information, we demonstrate that our approach can correctly segment EM maps into individual subunits and assign amino acids sequence to backbone traces to generate full-atom models.

bioinformatics↗