Biology subjects

Seidel, C. A. M.

Publications and source records attributed to Seidel, C. A. M..

3 recordsLinked to original sources

bioRxiv2022

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins

Single-molecule FRET (smFRET) has become an established tool to study biomolecular structure and dynamics in vitro and in live cells. We performed a worldwide blind study involving 19 labs to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems that undergo distinct conformational changes, we obtained an uncertainty of the FRET efficiency of less than {+/-} 0.06, corresponding to an interdye distance precision of [≤] 0.2 nm and accuracy of [≤] 0.5 nm. We further discuss the limits for detecting distance fluctuations with sensitivity down to [lsim] 10% of the Forster distance and provide guidelines on how to detect potential dye perturbations. The ability of smFRET experiments to simultaneously measure distances and avoid averaging of conformational dynamics slower than the fluorescence lifetime is unique for dynamic structural biology.

biophysics↗

bioRxiv2022

Phase separating RNA binding proteins form heterogeneous distributions of clusters in subsaturated solutions

Macromolecular phase separation is thought to be one of the processes that drives the formation of membraneless biomolecular condensates in cells. The dynamics of phase separation, especially at low endogenous concentrations found in cells, are thought to follow the tenets of classical nucleation theory describing a sharp transition between a dense phase and a dilute phase characterized by dispersed monomers. Here, we used in vitro biophysical studies to study subsaturated solutions of phase separating RNA binding proteins with intrinsically disordered prion like domains (PLDs) and RNA binding domains (RBDs). Surprisingly, we find that subsaturated solutions are characterized by heterogeneous distributions of clusters comprising tens to hundreds of molecules. These clusters also include low abundance mesoscale species that are several hundreds of nanometers in diameter. Our results show that cluster formation in subsaturated solutions and phase separation in supersaturated solutions are strongly coupled via sequence-encoded interactions. Interestingly, however, cluster formation and phase separation can be decoupled from one another using solutes that impact the solubilities of phase separating proteins. They can also be decoupled by specific types of mutations. Overall, our findings implicate the presence of distinct, sequence-specific energy scales that contribute to the overall phase behaviors of RNA binding proteins. We discuss our findings in the context of theories of associative polymers. Significance StatementMembraneless biomolecular condensates are molecular communities with distinct compositional preferences and functions. Considerable attention has focused on phase separation as the process that gives rise to condensates. Here, we show that subsaturated solutions of RNA binding proteins form heterogeneous distributions of clusters in subsaturated solutions. The formation of clusters in subsaturated solutions and condensates in supersaturated solution are coupled through sequence-specific interactions. Given the low endogenous concentrations of phase separating proteins, our findings suggest that clusters in subsaturated conditions might be of functional relevance in cells.

biophysics↗

bioRxiv2021

Inferring kinetic rate constants from single-molecule FRET trajectories - a blind benchmark of kinetic analysis tools

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We tested them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

biophysics↗