Particles that bud off from the cell surface, including viruses and microvesicles, typically have a unique membrane protein composition distinct from that of the originating plasma membrane. This selective protein composition enables viruses to evade the immune response and infect other cells. But how membrane proteins sort into budding viruses such as human immunodeficiency virus (HIV) remains unclear. Proteins could passively distribute into HIV-assembly-site membranes producing compositions resembling pre-existing plasma-membrane domains. Here, we demonstrate that proteins instead sort actively into HIV-assembly-site membranes, generating compositions enriched in cholesterol and sphingolipids that undergo continuous remodeling. Proteins are recruited into and removed from the HIV assembly site through lipid-based partitioning, initiated by oligomerization of the HIV structural protein Gag. Changes in membrane curvature at the assembly site further amplify this sorting process. Thus, a lipid-based sorting mechanism, aided by increasing membrane curvature, generates the unique membrane composition of the HIV surface.

Electrophysiology has long been the workhorse of neuroscience, allowing scientists to record with millisecond precision the action potentials generated by neurons in vivo. Recently, calcium imaging of fluorescent indicators has emerged as a powerful alternative. This technique has its own strengths and weaknesses and unique data processing problems and interpretation confounds. Here we review the computational methods that convert raw calcium movies to estimates of single neuron spike times with minimal human supervision. By computationally addressing the weaknesses of calcium imaging, these methods hold the promise of significantly improving data quality. We also introduce a new metric to evaluate the output of these processing pipelines, which is based on the cluster isolation distance routinely used in electrophysiology.

Electrophysiology is the most used approach for the collection of functional data in basic and translational neuroscience, but it is typically limited to either intracellular or extracellular recordings. The integration of multiple physiological modalities for the routine acquisition of multimodal data with microelectrodes could be useful for biomedical applications, yet this has been challenging owing to incompatibilities of fabrication methods. Here, we present a suite of glass pipettes with integrated microelectrodes for the simultaneous acquisition of multimodal intracellular and extracellular information in vivo, electrochemistry assessments, and optogenetic perturbations of neural activity. We used the integrated devices to acquire multimodal signals from the CA1 region of the hippocampus in mice and rats, and show that these data can serve as ground-truth validation for the performance of spike-sorting algorithms. The microdevices are applicable for basic and translational neurobiology, and for the development of next-generation brain-machine interfaces.