Nanoparticles of Block Ionomer Complexes from Double Hydrophilic Poly(acrylic acid)-b-poly(ethylene oxide)-b-poly(acrylic acid) Triblock Copolymer and Oppositely Charged Surfactant

The novel water-dispersible nanoparticles from the double hydrophilic poly(acrylic acid)-b-poly(ethylene oxide)-b-poly(acrylic acid) (PAA-b-PEO-b-PAA) triblock copolymer and oppositely charged surfactant dodecyltrimethyl ammonium bromide (DTAB) were prepared by mixing the individual aqueous solutions. The structure of the nanoparticles was investigated as a function of the degree of neutralization (DN) by turbidimetry, dynamic light scattering (DSL),ζ-potential measurement, and atomic force microscope (AFM). The neutralization of the anionic PAA blocks with cationic DTAB accompanied with the hydrophobic interaction of alkyl tails of DTAB led to formation of core–shell nanoparticles with the core of the DTAB neutralized PAA blocks and the shell of the looped PEO blocks. The water-dispersible nanoparticles with negative ζ-potential were obtained over the DN range from 0.4 to 2.0 and their sizes depended on the DN. The looped PEO blocks hindered the further neutralization of the PAA blocks with cationic DTAB, resulting in existence of some negative charged PAA-b-PEO-b-PAA backbones even when DN > 1.0. The spherical and ellipsoidal nature of these nanoparticles was observed with AFM

Single Molecule Analysis Research Tool (SMART): An Integrated Approach for Analyzing Single Molecule Data

Single molecule studies have expanded rapidly over the past decade and have the ability to provide an unprecedented level of understanding of biological systems. A common challenge upon introduction of novel, data-rich approaches is the management, processing, and analysis of the complex data sets that are generated. We provide a standardized approach for analyzing these data in the freely available software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data

BOBA FRET: Bootstrap-based analysis of single-molecule FRET data

Time-binned single-molecule Förster resonance energy transfer (smFRET) experiments with surface-tethered nucleic acids or proteins permit to follow folding and catalysis of single molecules in real-time. Due to the intrinsically low signal-to-noise ratio (SNR) in smFRET time traces, research over the past years has focused on the development of new methods to extract discrete states (conformations) from noisy data. However, limited observation time typically leads to pronounced cross-sample variability, i.e., single molecules display differences in the relative population of states and the corresponding conversion rates. Quantification of cross-sample variability is necessary to perform statistical testing in order to assess whether changes observed in response to an experimental parameter (metal ion concentration, the presence of a ligand, etc.) are significant. However, such hypothesis testing has been disregarded to date, precluding robust biological interpretation. Here, we address this problem by a bootstrap-based approach to estimate the experimental variability. Simulated time traces are presented to assess the robustness of the algorithm in conjunction with approaches commonly used in thermodynamic and kinetic analysis of time-binned smFRET data. Furthermore, a pair of functionally important sequences derived from the self-cleaving group II intron Sc.ai5γ (d3'EBS1*/IBS1*) is used as a model system. Through statistical hypothesis testing, divalent metal ions are shown to have a statistically significant effect on both thermodynamic and kinetic aspects of their interaction. The Matlab source code used for analysis (bootstrap-based analysis of smFRET data, BOBA FRET), as well as a graphical user interface, is available via http://www.aci.uzh.ch/rna/