The delivery of tracers into populations of neurons is essential to visualize their anatomy and analyze their function. In some model systems genetically-targeted expression of fluorescent proteins is the method of choice; however, these genetic tools are not available for most organisms and alternative labeling methods are very limited. Here we describe a new method for neuronal labelling by electrophoretic dye delivery from a suction electrode directly through the neuronal sheath of nerves and ganglia in insects. Polar tracer molecules were delivered into the locust auditory nerve without destroying its function, simultaneously staining peripheral sensory structures and central axonal projections. Local neuron populations could be labelled directly through the surface of the brain, and in-vivo optical imaging of sound-evoked activity was achieved through the electrophoretic delivery of calcium indicators. The method provides a new tool for studying how stimuli are processed in peripheral and central sensory pathways and is a significant advance for the study of nervous systems in non-model organisms.

Regions of genomic DNA called enhancers encode binding sites for transcription factor proteins. Binding of activators and repressors increase and reduce transcription, respectively, but it is not understood how combinations of activators and repressors generate precise patterns of transcription during development. Here, we explore this problem using a fully synthetic transcriptional platform in Drosophila consisting of engineered transcription factor gradients and artificial enhancers. We found that binding sites for a transcription factor that makes DNA accessible are required together with binding sites for transcriptional activators to produce a functional enhancer. Only in this context can changes in the number of activator binding sites mediate quantitative control of transcription. Using an engineered transcriptional repressor gradient, we demonstrate that overlapping repressor and activator binding sites provide more robust repression and sharper expression boundaries than non-overlapping sites. This may explain why this common motif is observed in many developmental enhancers.

hIAPP fibrils are associated with Type-II Diabetes, but the link of hIAPP structure to islet cell death remains elusive. Here we observe that hIAPP fibrils are cytotoxic to cultured pancreatic β-cells, leading us to determine the structure and cytotoxicity of protein segments composing the amyloid spine of hIAPP. Using the cryoEM method MicroED, we discover that one segment, 19-29 S20G, forms pairs of β-sheets mated by a dry interface that share structural features with and are similarly cytotoxic to full-length hIAPP fibrils. In contrast, a second segment, 15-25 WT, forms non-toxic labile β-sheets. These segments possess different structures and cytotoxic effects, however, both can seed full-length hIAPP, and cause hIAPP to take on the cytotoxic and structural features of that segment. These results suggest that protein segment structures represent polymorphs of their parent protein and that segment 19-29 S20G may serve as a model for the toxic spine of hIAPP.

Many functional RNAs have an evolutionarily conserved secondary structure. Conservation of RNA base pairing induces pairwise covariations in sequence alignments. We developed a computational method, R-scape (RNA Structural Covariation Above Phylogenetic Expectation), that quantitatively tests whether covariation analysis supports the presence of a conserved RNA secondary structure. R-scape analysis finds no statistically significant support for proposed secondary structures of the long noncoding RNAs HOTAIR, SRA, and Xist.

Recent developments in machine vision methods for automatic, quantitative analysis of social behavior have immensely improved both the scale and level of resolution with which we can dissect interactions between members of the same species. In this paper, we review these methods, with a particular focus on how biologists can apply them to their own work. We discuss several components of machine vision-based analyses: methods to record high-quality video for automated analyses, video-based tracking algorithms for estimating the positions of interacting animals, and machine learning methods for recognizing patterns of interactions. These methods are extremely general in their applicability, and we review a subset of successful applications of them to biological questions in several model systems with very different types of social behaviors.

Structure determination of conformationally variable proteins can prove challenging even when many possible molecular-replacement (MR) search models of high sequence similarity are available. Calmodulin (CaM) is perhaps the best-studied archetype of these flexible proteins: while there are currently ∼450 structures of significant sequence similarity available in the Protein Data Bank (PDB), novel conformations of CaM and complexes thereof continue to be reported. Here, the details of the solution of a novel peptide-CaM complex structure by MR are presented, in which only one MR solution of marginal quality was found despite the use of 120 different search models, an exclusivity enhanced by the presence of a high degree of hemihedral twinning (overall refined twin fraction = 0.43). Ambiguities in the initial MR electron-density maps were overcome by using MR-SAD: phases from the MR partial model were used to identify weak anomalous scatterers (calcium, sulfur and chloride), which were in turn used to improve the phases, automatically rebuild the structure and resolve sequence ambiguities. Retrospective analysis of consecutive wedges of the original data sets showed twin fractions ranging from 0.32 to 0.55, suggesting that the data sets were variably twinned. Despite these idiosyncrasies and obstacles, the data themselves and the final model were of high quality and indeed showed a novel, nearly right-angled conformation of the bound peptide.