Advanced microscopy methods allow obtaining information on (dynamic) conformational changes in biomolecules via measuring a single molecular distance in the structure. It is, however, extremely challenging to capture the full depth of a three-dimensional biochemical state, binding-related structural changes or conformational cross-talk in multi-protein complexes using one-dimensional assays. In this paper we address this fundamental problem by extending the standard molecular ruler based on Förster resonance energy transfer (FRET) into a two-dimensional assay via its combination with protein-induced fluorescence enhancement (PIFE). We show that donor brightness (via PIFE) and energy transfer efficiency (via FRET) can simultaneously report on e.g., the conformational state of double stranded DNA (dsDNA) following its interaction with unlabelled proteins (BamHI, EcoRV, and T7 DNA polymerase gp5/trx). The PIFE-FRET assay uses established labelling protocols and single molecule fluorescence detection schemes (alternating-laser excitation, ALEX). Besides quantitative studies of PIFE and FRET ruler characteristics, we outline possible applications of ALEX-based PIFE-FRET for single-molecule studies with diffusing and immobilized molecules. Finally, we study transcription initiation and scrunching of E. coli RNA-polymerase with PIFE-FRET and provide direct evidence for the physical presence and vicinity of the polymerase that causes structural changes and scrunching of the transcriptional DNA bubble.
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http://dx.doi.org/10.1038/srep33257 | DOI Listing |
J Colloid Interface Sci
January 2025
College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, China. Electronic address:
Rational regulation of interface structure in photocatalysts is a promising strategy to improve the photocatalytic performance of carbon dioxide (CO) reduction. However, it remains a challenge to modulate the interface structure of multi-component heterojunctions. Herein, a strategy integrating heterojunction with facet engineering is developed to modulate the interface structure of metal-organic frameworks (MOF)-based heterojunctions.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Department of Civil, Environmental and Architectural Engineering, University of Padova, Via Marzolo 9, 35131, Padova, Italy.
The materials removed in the oil separation units of wastewater treatment plants can be referred to as fat, oil and grease (FOG) waste. FOG waste accumulation in treatment plants can cause clogging of pipes, production of excessive scums and foams, and negatively affect air/liquid oxygen transfer. While conventional disposal routes of this material can be limited by its water and organic content, FOG can represent a source of bio-energy other than bio-diesel production.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, PR China; Faculty of Architecture, The University of Hong Kong, Hong Kong, PR China. Electronic address:
Infectious microbes can spread rapidly from fomites (contaminated surfaces) via hand touch, with prolonged residence time on surfaces increasing transmission risk by extending exposure periods and/or involving more susceptible individuals. Existing studies have focused on decreasing microbial contamination, but not on the need for rapid removal from surface systems. This study introduces residence time as the time that a microbe spends within the surface system.
View Article and Find Full Text PDFACS Nano
January 2025
Institute of Flexible Electronics, Xi'an Key Laboratory of Flexible Electronics, Northwestern Polytechnical University, Xi'an 710072, China.
Photoassisted lithium-sulfur (Li-S) batteries offer a promising approach to enhance the catalytic transformation kinetics of polysulfide. However, the development is greatly hindered by inadequate photo absorption and severe photoexcited carriers recombination. Herein, a photonic crystal sulfide heterojunction structure is designed as a bifunctional electrode scaffold for photoassisted Li-S batteries.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data.
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