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Abstract Protein assembly plays an important role throughout all phyla of life, both physiologically and pathologically. In particular, aggregation and polymerization of proteins are key-strategies that regulate cellular function. In recent years, methods to experimentally study the assembly process on a single-molecule level have been developed. This progress concomitantly has triggered the question of how to analyze this type of single-filament data adequately and what experimental conditions are necessary to allow a meaningful interpretation of the analysis. Here, we developed two analysis methods for single-filament data: the visitation analysis and the average-rate analysis. We benchmarked and compared both approaches with the classic dwell-time-analysis frequently used to study microscopic association and dissociation rates. In particular, we tested the limitations of each analysis method along the lines of the signal-to-noise ratio, the sampling rate, and the labeling efficiency and bleaching rate of the fluorescent dyes used in single-molecule fluorescence experiments. Finally, we applied our newly developed methods to study the monomer assembly of actin at the single-molecule-level in the presence of the class II nucleator Cappuccino and the WH2 repeats of Spire. For Cappuccino, our data indicated fast elongation circumventing a nucleation phase whereas, for Spire, we found that the four WH2 motifs are not sufficient to promote de novo nucleation of actin.

Direct and real-time identification of nucleobases in DNA strands is still limited by the sensitivity and spatial resolution of the established solid-state nanopore devices. Here, the authors use CMOS compatible, plasmonic nanoslits to locally enable SERS for identifying nucleobases, both individual and incorporated in DNA strands.

Biological nanopore–based protein sequencing and recognition is challenging due to the folded structure or non-uniform charge of peptides. Here the authors show that engineered FraC nanopores can overcome these problems and recognize biomarkers in the form of oligopeptides, polypeptides and folded proteins.