Local kinetic measures of macromolecular structure reveal partitioning among multiple parallel pathways from the earliest steps in the folding of a large RNA molecule.
At the heart of the RNA folding problem is the number, structures, and relationships among the intermediates that populate the folding pathways of most large RNA molecules. Unique insight into the structural dynamics of these intermediates can be gleaned from the time-dependent changes in local probes of macromolecular conformation (e.g. reports on individual nucleotide solvent accessibility offered by hydroxyl radical (()OH) footprinting). Local measures distributed around a macromolecule individually illuminate the ensemble of separate changes that constitute a folding reaction. Folding pathway reconstruction from a multitude of these individual measures is daunting due to the combinatorial explosion of possible kinetic models as the number of independent local measures increases. Fortunately, clustering of time progress curves sufficiently reduces the dimensionality of the data so as to make reconstruction computationally tractable. The most likely folding topology and intermediates can then be identified by exhaustively enumerating all possible kinetic models on a super-computer grid. The folding pathways and measures of the relative flux through them were determined for Mg(2+) and Na(+)-mediated folding of the Tetrahymena thermophila group I intron using this combined experimental and computational approach. The flux during Mg(2+)-mediated folding is divided among numerous parallel pathways. In contrast, the flux during the Na(+)-mediated reaction is predominantly restricted through three pathways, one of which is without detectable passage through intermediates. Under both conditions, the folding reaction is highly parallel with no single pathway accounting for more than 50% of the molecular flux. This suggests that RNA folding is non-sequential under a variety of different experimental conditions even at the earliest stages of folding. This study provides a template for the systematic analysis of the time-evolution of RNA structure from ensembles of local measures that will illuminate the chemical and physical characteristics of each step in the process. The applicability of this analysis approach to other macromolecules is discussed.
Department of Genetics, Stanford University, 300 Pasteur Dr. Stanford, CA 94305, USA.
Alain
A
Laederach
Inna
I
Shcherbakova
Mike P
MP
Liang
Michael
M
Brenowitz
Russ B
RB
Altman
D000818:Animals; D007438:Introns; D007700:Kinetics; D046911:Macromolecular Substances; D008954:Models, Biological; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry*; D016337:RNA, Catalytic / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D016053:RNA, Protozoan / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D016808:Tetrahymena thermophila / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D013816:Thermodynamics
D046911:Macromolecular Substances; D016337:RNA, Catalytic; D016053:RNA, Protozoan; D012313:RNA