Perceptual experiences may arise from neuronal activity patterns in mammalian neocortex. We probed mouse neocortex during visual discrimination using a red-shifted channelrhodopsin (ChRmine, discovered through structure-guided genome mining) alongside multiplexed multiphoton-holography (MultiSLM), achieving control of individually specified neurons spanning large cortical volumes with millisecond precision. Stimulating a critical number of stimulus-orientation-selective neurons drove widespread recruitment of functionally related neurons, a process enhanced by (but not requiring) orientation-discrimination task learning. Optogenetic targeting of orientation-selective ensembles elicited correct behavioral discrimination. Cortical layer–specific dynamics were apparent, as emergent neuronal activity asymmetrically propagated from layer 2/3 to layer 5, and smaller layer 5 ensembles were as effective as larger layer 2/3 ensembles in eliciting orientation discrimination behavior. Population dynamics emerging after optogenetic stimulation both correctly predicted behavior and resembled natural internal representations of visual stimuli at cellular resolution over volumes of cortex.

The structural and functional complexity of multicellular biological systems, such as the brain, are beyond the reach of human design or assembly capabilities. Cells in living organisms may be recruited to construct synthetic materials or structures if treated as anatomically defined compartments for specific chemistry, harnessing biology for the assembly of complex functional structures. By integrating engineered-enzyme targeting and polymer chemistry, we genetically instructed specific living neurons to guide chemical synthesis of electrically functional (conductive or insulating) polymers at the plasma membrane. Electrophysiological and behavioral analyses confirmed that rationally designed, genetically targeted assembly of functional polymers not only preserved neuronal viability but also achieved remodeling of membrane properties and modulated cell type–specific behaviors in freely moving animals. This approach may enable the creation of diverse, complex, and functional structures and materials within living systems.

The KCR channelrhodopsins are recently-discovered light-gated ion channels with high K+selectivity, a property that has attracted broad attention among biologists – due to intense interest in creating novel inhibitory tools for optogenetics leveraging this K+selectivity, and due to the mystery of how this selectivity is achieved in the first place. Indeed, the molecular and structural mechanism for K+selectivity in KCRs has remained especially puzzling since these 7-transmembrane retinal-binding proteins completely lack structural similarity with known K+channels, which generally coordinate K+in a precisely symmetric conduction pathway formed by a tight interface among multiple small monomeric channel subunits (presumably not an accessible mechanism for the large KCR rhodopsin proteins). Here we present the cryo-electron microscopy structures of two KCRs from Hyphochytrium catenoides with distinct spectral properties for light absorption and channel actuation, HcKCR1, and HcKCR2, at resolutions of 2.6 and 2.5 Å, respectively. Structural comparison revealed first an unusually-shaped retinal binding pocket which induces rotation of the retinal in HcKCR2, explaining the large spectral difference between HcKCR1 and 2. Next, our combined structural, electrophysiological, computational, and spectroscopic analyses revealed a new solution to the challenging problem of K+-selective transport. KCRs indeed do not exhibit the canonical tetrameric K+selectivity filter that specifically coordinates dehydrated K+; instead, single KCR monomers form a size exclusion filter using aromatic residues at the extracellular side of the pore which inhibits passage of bulky hydrated ions. This unique feature allows KCRs to function as K+channels under relevant physiological conditions, providing not only a novel mechanism for achieving high K+permeability ratios in biological ion channels, but also a framework for designing the next generation of inhibitory optogenetic tools.

ChRmine, a recently-discovered bacteriorhodopsin-like cation-conducting channelrhodopsin, exhibits puzzling properties (unusually-large photocurrents, exceptional red-shift in action spectrum, and extreme light-sensitivity) that have opened up new opportunities in optogenetics. ChRmine and its homologs function as light-gated ion channels, but by primary sequence more closely resemble ion pump rhodopsins; the molecular mechanisms for passive channel conduction in this family of proteins, as well as the unusual properties of ChRmine itself, have remained mysterious. Here we present the cryo-electron microscopy structure of ChRmine at 2.0 Å resolution. The structure reveals striking architectural features never seen before in channelrhodopsins including trimeric assembly, a short transmembrane-helix 3 unwound in the middle of the membrane, a prominently-twisting extracellular-loop 1, remarkably-large intracellular cavities and extracellular vestibule, and an unprecedented hydrophilic pore that extends through the center of the trimer, separate from the three individual monomer pores. Electrophysiological, spectroscopic, and computational analyses provide insight into conduction and gating of light-gated channels with these distinct design features, and point the way toward structure-guided creation of novel channelrhodopsins for optogenetic applications in biology.

Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain–affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. The integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.