Rapid propagation of membrane tension at retinal bipolar neuron presynaptic terminals

Many cellular activities, such as cell migration, cell division, phagocytosis, and exo-endocytosis, generate and are regulated by membrane tension gradients. Membrane tension gradients drive membrane flows, but there is controversy over how rapidly plasma membrane flow can relax tension gradients. Here, we show that membrane tension can propagate rapidly or slowly, spanning orders of magnitude in speed, depending on the cell type. In a neuronal terminal specialized for rapid synaptic vesicle turnover, membrane tension equilibrates within seconds. By contrast, membrane tension does not propagate in neuroendocrine adrenal chromaffin cells secreting catecholamines. Stimulation of exocytosis causes a rapid, global decrease in the synaptic terminal membrane tension, which recovers slowly due to endocytosis. Thus, membrane flow and tension equilibration may be adapted to distinct membrane recycling requirements.

bpRNA: large-scale automated annotation and analysis of RNA secondary structure

While RNA secondary structure prediction from sequence data has made remarkable progress, there is a need for improved strategies for annotating the features of RNA secondary structures. Here, we present bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature. We also introduce several new informative representations of RNA structure types to improve structure visualization and interpretation. We have further used bpRNA to generate a web-accessible meta-database, ‘bpRNA-1m’, of over 100 000 single-molecule, known secondary structures; this is both more fully and accurately annotated and over 20-times larger than existing databases. We use a subset of the database with highly similar (≥90% identical) sequences filtered out to report on statistical trends in sequence, flanking base pairs, and length. Both the bpRNA method and the bpRNA-1m database will be valuable resources both for specific analysis of individual RNA molecules and large-scale analyses such as are useful for updating RNA energy parameters for computational thermodynamic predictions, improving machine learning models for structure prediction, and for benchmarking structure-prediction algorithms.