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Zhou, W.-J.

Publications and source records attributed to Zhou, W.-J..

2 recordsLinked to original sources

Fluorogenic Interacting Protein Stabilization for Orthogonal RNA Imaging

Live imaging of RNAs is crucial to interrogate their cellular functions, and approaches allowing fluorogenic RNA imaging with high orthogonality and contrast remains underexplored. We propose a fluorogenic interacting protein stabilization (FLIPS) strategy that enables orthogonal RNA imaging in live cells with fluorescence-labeled RNA interacting proteins (RIPs) stabilized by cognate RNA motifs. We show that the RNA motif stabilizes the otherwise degraded cognate RIP fused to a poly(arginine)- extended C-terminal degron, and the stabilizing effect is enhanced with circular permutation of the RIP. This design affords a generally applicable strategy for different RNA motifs and RIPs, enabling orthogonal and multi-color fluorescence-activated RNA imaging. Our strategy is broadly demonstrated for multiplexed, high-contrast RNA detection and imaging, single molecule RNA imaging and RNA dynamic translocation tracking in live cells. The versatility of our system highlights its potential for interrogating RNA biology and developing RNA-based imaging tools.

cell biology↗

Open-pFind enables precise, comprehensive and rapid peptide identification in shotgun proteomics

Shotgun proteomics has grown rapidly in recent decades, but a large fraction of tandem mass spectrometry (MS/MS) data in shotgun proteomics are not successfully identified. We have developed a novel database search algorithm, Open-pFind, to efficiently identify peptides even in an ultra-large search space which takes into account unexpected modifications, amino acid mutations, semi- or non-specific digestion and co-eluting peptides. Tested on two metabolically labeled MS/MS datasets, Open-pFind reported 50.5-117.0% more peptide-spectrum matches (PSMs) than the seven other advanced algorithms. More importantly, the Open-pFind results were more credible judged by the verification experiments using stable isotopic labeling. Tested on four additional large-scale datasets, 70-85% of the spectra were confidently identified, and high-quality spectra were nearly completely interpreted by Open-pFind. Further, Open-pFind was over 40 times faster than the other three open search algorithms and 2-3 times faster than three restricted search algorithms. Re-analysis of an entire human proteome dataset consisting of [~]25 million spectra using Open-pFind identified a total of 14,064 proteins encoded by 12,723 genes by requiring at least two uniquely identified peptides. In this search results, Open-pFind also excelled in an independent test for false positives based on the presence or absence of olfactory receptors. Thus, a practical use of the open search strategy has been realized by Open-pFind for the truly global-scale proteomics experiments of today and in the future.

bioinformatics↗