Quantitative tests of a reconstitution model for RNA folding thermodynamics and kinetics.

Decades of study of the architecture and function of structured RNAs have led to the perspective that RNA tertiary structure is modular, made of locally stable domains that retain their structure across RNAs. We formalize a hypothesis inspired by this modularity-that RNA folding thermodynamics and kinetics can be quantitatively predicted from separable energetic contributions of the individual components of a complex RNA. This reconstitution hypothesis considers RNA tertiary folding in terms of ΔG, the probability of aligning tertiary contact partners, and ΔG, the favorable energetic contribution from the formation of tertiary contacts in an aligned state.

Kinetic and thermodynamic framework for P4-P6 RNA reveals tertiary motif modularity and modulation of the folding preferred pathway.

The past decade has seen a wealth of 3D structural information about complex structured RNAs and identification of functional intermediates. Nevertheless, developing a complete and predictive understanding of the folding and function of these RNAs in biology will require connection of individual rate and equilibrium constants to structural changes that occur in individual folding steps and further relating these steps to the properties and behavior of isolated, simplified systems. To accomplish these goals we used the considerable structural knowledge of the folded, unfolded, and intermediate states of P4-P6 RNA.

Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data.

Background: Single-molecule techniques have emerged as incisive approaches for addressing a wide range of questions arising in contemporary biological research [Trends Biochem Sci 38:30-37, 2013; Nat Rev Genet 14:9-22, 2013; Curr Opin Struct Biol 2014, 28C:112-121; Annu Rev Biophys 43:19-39, 2014]. The analysis and interpretation of raw single-molecule data benefits greatly from the ongoing development of sophisticated statistical analysis tools that enable accurate inference at the low signal-to-noise ratios frequently associated with these measurements. While a number of groups have released analysis toolkits as open source software [J Phys Chem B 114:5386-5403, 2010; Biophys J 79:1915-1927, 2000; Biophys J 91:1941-1951, 2006; Biophys J 79:1928-1944, 2000; Biophys J 86:4015-4029, 2004; Biophys J 97:3196-3205, 2009; PLoS One 7:e30024, 2012; BMC Bioinformatics 288 11(8):S2, 2010; Biophys J 106:1327-1337, 2014; Proc Int Conf Mach Learn 28:361-369, 2013], it remains difficult to compare analysis for experiments performed in different labs due to a lack of standardization.

Fluorescently labeling synthetic RNAs.

This protocol covers the steps required to incorporate N-hydroxysuccinamide (NHS) functionalized fluorophores into synthetic RNAs containing a residue derivatized with a primary amine. This method has been widely used to label RNA oligonucleotides that are used directly, targeted to a complementary RNA using base pairing rules, or covalently ligated to a RNA of interest (Ha et al., 1999; Hodak et al.

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.

Implications of molecular heterogeneity for the cooperativity of biological macromolecules.

Cooperativity, a universal property of biological macromolecules, is typically characterized by a Hill slope, which can provide fundamental information about binding sites and interactions. We demonstrate, through simulations and single-molecule FRET (smFRET) experiments, that molecular heterogeneity lowers bulk cooperativity from the intrinsic value for the individual molecules. As heterogeneity is common in smFRET experiments, appreciation of its influence on fundamental measures of cooperativity is critical for deriving accurate molecular models.

Removal of covalent heterogeneity reveals simple folding behavior for P4-P6 RNA.

RNA folding landscapes have been described alternately as simple and as complex. The limited diversity of RNA residues and the ability of RNA to form stable secondary structures prior to adoption of a tertiary structure would appear to simplify folding relative to proteins. Nevertheless, there is considerable evidence for long-lived misfolded RNA states, and these observations have suggested rugged energy landscapes.

Measuring the energetic coupling of tertiary contacts in RNA folding using single molecule fluorescence resonance energy transfer.

Tertiary contacts are critical to stabilizing the folded conformations of structured RNAs. In some cases, these contacts have been shown to interact with positive cooperativity. Measuring the energetic coupling of tertiary contact formation is among the most basic physical characterizations of a structured RNA.

Multiple native states reveal persistent ruggedness of an RNA folding landscape.

According to the 'thermodynamic hypothesis', the sequence of a biological macromolecule defines its folded, active (or 'native') structure as a global energy minimum in the folding landscape. However, the enormous complexity of folding landscapes of large macromolecules raises the question of whether there is in fact a unique global minimum corresponding to a unique native conformation or whether there are deep local minima corresponding to alternative active conformations. The folding of many proteins is well described by two-state models, leading to highly simplified representations of protein folding landscapes with a single native conformation.

Probing nucleic acid-ion interactions with buffer exchange-atomic emission spectroscopy.

The ion atmosphere of nucleic acids directly affects measured biochemical and biophysical properties. However, study of the ion atmosphere is difficult due to its diffuse and dynamic nature. Standard techniques available have significant limitations in sensitivity, specificity, and directness of the assays.

Quantitative and comprehensive decomposition of the ion atmosphere around nucleic acids.

The ion atmosphere around nucleic acids critically affects biological and physical processes such as chromosome packing, RNA folding, and molecular recognition. However, the dynamic nature of the ion atmosphere renders it difficult to characterize. The basic thermodynamic description of this atmosphere, a full accounting of the type and number of associated ions, has remained elusive.