4.8 Article

KERA: analysis tool for multi-process, multi-state single-molecule data

Journal

NUCLEIC ACIDS RESEARCH
Volume 49, Issue 9, Pages -

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab087

Keywords

-

Funding

  1. NIH/NIGMS [R35GM131704, GM081433]
  2. University of Iowa, FUTURE in Biomedicine Program
  3. Iowa Space Grant Consortium, Collaborative Grant
  4. Iowa Science Foundation [ISF 20-17]
  5. University of Northern Iowa, Office of Research and Sponsored Programs' Capacity Building Grant
  6. UNI, Physics Undergraduate Summer Research Fellowship
  7. NIH, T32 Pharmacological Sciences Training Grant [T32 GM067795]

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Molecular machines within cells exhibit dynamic assembly, disassembly, and reorganization, with molecular interactions between components being observed and quantified through single-molecule level studies and fluorescence microscopy techniques. Analyzing sequences of molecular interactions can reveal the structure and dynamic organization of complexes, providing important insights into complex biological systems.
Molecular machines within cells dynamically assemble, disassemble and reorganize. Molecular interactions between their components can be observed at the single-molecule level and quantified using colocalization single-molecule spectroscopy, in which individual labeled molecules are seen transiently associating with a surface-tethered partner, or other total internal reflection fluorescence microscopy approaches in which the interactions elicit changes in fluorescence in the labeled surface-tethered partner. When multiple interacting partners can form ternary, quaternary and higher order complexes, the types of spatial and temporal organization of these complexes can be deduced from the order of appearance and reorganization of the components. Time evolution of complex architectures can be followed by changes in the fluorescence behavior in multiple channels. Here, we describe the kinetic event resolving algorithm (KERA), a software tool for organizing and sorting the discretized fluorescent trajectories from a range of single-molecule experiments. KERA organizes the data in groups by transition patterns, and displays exhaustive dwell time data for each interaction sequence. Enumerating and quantifying sequences of molecular interactions provides important information regarding the underlying mechanism of the assembly, dynamics and architecture of the macromolecular complexes. We demonstrate KERA's utility by analyzing conformational dynamics of two DNA binding proteins: replication protein A and xeroderma pigmentosum complementation group D helicase.

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