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Single molecule analysis reveals reversible and irreversible steps during spliceosome activation.

ABSTRACT: The spliceosome is a complex machine composed of small nuclear ribonucleoproteins (snRNPs) and accessory proteins that excises introns from pre-mRNAs. After assembly the spliceosome is activated for catalysis by rearrangement of subunits to form an active site. How this rearrangement is coordinated is not well-understood. During activation, U4 must be released to allow U6 conformational change, while Prp19 complex (NTC) recruitment is essential for stabilizing the active site. We used multi-wavelength colocalization single molecule spectroscopy to directly observe the key events in Saccharomyces cerevisiae spliceosome activation. Following binding of the U4/U6.U5 tri-snRNP, the spliceosome either reverses assembly by discarding tri-snRNP or proceeds to activation by irreversible U4 loss. The major pathway for NTC recruitment occurs after U4 release. ATP stimulates both the competing U4 release and tri-snRNP discard processes. The data reveal the activation mechanism and show that overall splicing efficiency may be maintained through repeated rounds of disassembly and tri-snRNP reassociation.

SUBMITTER: Hoskins AA

PROVIDER: S-EPMC4922858 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Single molecule analysis reveals reversible and irreversible steps during spliceosome activation.

Hoskins Aaron A AA Rodgers Margaret L ML Friedman Larry J LJ Gelles Jeff J Moore Melissa J MJ

eLife 20160531

The spliceosome is a complex machine composed of small nuclear ribonucleoproteins (snRNPs) and accessory proteins that excises introns from pre-mRNAs. After assembly the spliceosome is activated for catalysis by rearrangement of subunits to form an active site. How this rearrangement is coordinated is not well-understood. During activation, U4 must be released to allow U6 conformational change, while Prp19 complex (NTC) recruitment is essential for stabilizing the active site. We used multi-wave ...[more]

PMID: 27244240

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Project description:Over the past few decades, single molecule investigations employing optical tweezers, AFM and TIRF microscopy have revealed that molecular behaviors are typically characterized by discrete steps or events that follow changes in protein conformation. These events, that manifest as steps or jumps, are short-lived transitions between otherwise more stable molecular states. A major limiting factor in determining the size and timing of the steps is the noise introduced by the measurement system. To address this impediment to the analysis of single molecule behaviors, step detection algorithms incorporate large records of data and provide objective analysis. However, existing algorithms are mostly based on heuristics that are not reliable and lack objectivity. Most of these step detection methods require the user to supply parameters that inform the search for steps. They work well, only when the signal to noise ratio (SNR) is high and stepping speed is low. In this report, we have developed a novel step detection method that performs an objective analysis on the data without input parameters, and based only on the noise statistics. The noise levels and characteristics can be estimated from the data providing reliable results for much smaller SNR and higher stepping speeds. An iterative learning process drives the optimization of step-size distributions for data that has unimodal step-size distribution, and produces extremely low false positive outcomes and high accuracy in finding true steps. Our novel methodology, also uniquely incorporates compensation for the smoothing affects of probe dynamics. A mechanical measurement probe typically takes a finite time to respond to step changes, and when steps occur faster than the probe response time, the sharp step transitions are smoothed out and can obscure the step events. To address probe dynamics we accept a model for the dynamic behavior of the probe and invert it to reveal the steps. No other existing method addresses the impact of probe dynamics on step detection. Importantly, we have also developed a comprehensive set of tools to evaluate various existing step detection techniques. We quantify the performance and limitations of various step detection methods using novel evaluation scales. We show that under these scales, our method provides much better overall performance. The method is validated on different simulated test cases, as well as experimental data.

Dataset Information

Single molecule analysis reveals reversible and irreversible steps during spliceosome activation.

Publications

Single molecule analysis reveals reversible and irreversible steps during spliceosome activation.

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