A novel data-driven algorithm to reveal and track the ribosome heterogeneity in single molecule studies

Abstract

The unique advantage of the single molecule approach is to reveal the inhomogeneous subpopulations in an ensemble. For example, smFRET (single molecule fluorescence resonance energy transfer) can identify multiple subpopulations based on the FRET efficiency histograms. However, identifying multiple FRET states with overlapping average values remains challenging. Here, we report a new concept and method to analyze the single molecule FRET data of a ribosome system. The main results are as follows: 1. based on a hierarchic concept, multiple ribosome subpopulations are identified. 2. The subpopulations are self-identified via the cross-correlation analysis of the FRET histogram profiles. The dynamic heterogeneity is tracked after 2 min intervals on the same ribosomes individually. 3. The major ribosome subpopulations exchange with each other with a certain pattern, indicating some correlations among the motions of the tRNAs and the ribosomal components. Experiments under the conditions of 20% glycerol or 1mM viomycin supported this conclusion.

Keywords: Data-driven algorithm; Dynamic heterogeneity; Ribosome conformational dynamics; Single molecule FRET.