scholarly journals Author response: Live-cell single particle imaging reveals the role of RNA polymerase II in histone H2A.Z eviction

2020 ◽  
Author(s):  
Anand Ranjan ◽  
Vu Q Nguyen ◽  
Sheng Liu ◽  
Jan Wisniewski ◽  
Jee Min Kim ◽  
...  
Keyword(s):  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Single Particle ◽  
Live Cell ◽  
Author Response ◽  
Particle Imaging ◽  
Single Particle Imaging

scholarly journals The Role of Surface Chemistry in the Efficacy of Protein and DNA Microarrays for Label-Free Detection: An Overview

Polymers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1026
Author(s):  
Elisa Chiodi ◽  
Allison M. Marn ◽  
Matthew T. Geib ◽  
M. Selim Ünlü
Keyword(s):  
Surface Chemistry ◽  
Surface Functionalization ◽  
Dna Microarrays ◽  
Label Free ◽  
Polymeric Coatings ◽  
Label Free Detection ◽  
Particle Imaging ◽  
Single Particle Imaging ◽  
The Impact

The importance of microarrays in diagnostics and medicine has drastically increased in the last few years. Nevertheless, the efficiency of a microarray-based assay intrinsically depends on the density and functionality of the biorecognition elements immobilized onto each sensor spot. Recently, researchers have put effort into developing new functionalization strategies and technologies which provide efficient immobilization and stability of any sort of molecule. Here, we present an overview of the most widely used methods of surface functionalization of microarray substrates, as well as the most recent advances in the field, and compare their performance in terms of optimal immobilization of the bioreceptor molecules. We focus on label-free microarrays and, in particular, we aim to describe the impact of surface chemistry on two types of microarray-based sensors: microarrays for single particle imaging and for label-free measurements of binding kinetics. Both protein and DNA microarrays are taken into consideration, and the effect of different polymeric coatings on the molecules’ functionalities is critically analyzed.

scholarly journals An encryption–decryption framework to validating single-particle imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhou Shen ◽  
Colin Zhi Wei Teo ◽  
Kartik Ayyer ◽  
N. Duane Loh
Keyword(s):  
Conceptual Framework ◽  
Single Particle ◽  
Latent Variables ◽  
Ground Truth ◽  
Resolving Power ◽  
Validation Measure ◽  
Encryption Decryption ◽  
Diffraction Patterns ◽  
Particle Imaging ◽  
Single Particle Imaging

AbstractWe propose an encryption–decryption framework for validating diffraction intensity volumes reconstructed using single-particle imaging (SPI) with X-ray free-electron lasers (XFELs) when the ground truth volume is absent. This conceptual framework exploits each reconstructed volumes’ ability to decipher latent variables (e.g. orientations) of unseen sentinel diffraction patterns. Using this framework, we quantify novel measures of orientation disconcurrence, inconsistency, and disagreement between the decryptions by two independently reconstructed volumes. We also study how these measures can be used to define data sufficiency and its relation to spatial resolution, and the practical consequences of focusing XFEL pulses to smaller foci. This conceptual framework overcomes critical ambiguities in using Fourier Shell Correlation (FSC) as a validation measure for SPI. Finally, we show how this encryption-decryption framework naturally leads to an information-theoretic reformulation of the resolving power of XFEL-SPI, which we hope will lead to principled frameworks for experiment and instrument design.

scholarly journals Live-cell imaging reveals the spatiotemporal organization of endogenous RNA polymerase II phosphorylation at a single gene

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Linda S. Forero-Quintero ◽  
William Raymond ◽  
Tetsuya Handa ◽  
Matthew N. Saxton ◽  
Tatsuya Morisaki ◽  
...  
Keyword(s):  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Single Molecule ◽  
Computational Models ◽  
Spatial Organization ◽  
Fluorescent Antibody ◽  
Single Gene ◽  
Single Copy ◽  
Living Cells ◽  
Live Cell

AbstractThe carboxyl-terminal domain of RNA polymerase II (RNAP2) is phosphorylated during transcription in eukaryotic cells. While residue-specific phosphorylation has been mapped with exquisite spatial resolution along the 1D genome in a population of fixed cells using immunoprecipitation-based assays, the timing, kinetics, and spatial organization of phosphorylation along a single-copy gene have not yet been measured in living cells. Here, we achieve this by combining multi-color, single-molecule microscopy with fluorescent antibody-based probes that specifically bind to different phosphorylated forms of endogenous RNAP2 in living cells. Applying this methodology to a single-copy HIV-1 reporter gene provides live-cell evidence for heterogeneity in the distribution of RNAP2 along the length of the gene as well as Serine 5 phosphorylated RNAP2 clusters that remain separated in both space and time from nascent mRNA synthesis. Computational models determine that 5 to 40 RNAP2 cluster around the promoter during a typical transcriptional burst, with most phosphorylated at Serine 5 within 6 seconds of arrival and roughly half escaping the promoter in ~1.5 minutes. Taken together, our data provide live-cell support for the notion of efficient transcription clusters that transiently form around promoters and contain high concentrations of RNAP2 phosphorylated at Serine 5.

scholarly journals Loss of Ubp3 increases silencing, decreases unequal recombination in rDNA, and shortens the replicative life span in Saccharomyces cerevisiae

2014 ◽  
Vol 25 (12) ◽  
pp. 1916-1924 ◽  
Author(s):  
David Öling ◽  
Rehan Masoom ◽  
Kristian Kvint
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Rna Polymerase ◽  
Life Span ◽  
Rna Polymerase Ii ◽  
Ribosomal Dna ◽  
Genetic Evidence ◽  
Wild Type ◽  
Replicative Life Span ◽  
Unequal Recombination

Ubp3 is a conserved ubiquitin protease that acts as an antisilencing factor in MAT and telomeric regions. Here we show that ubp3∆ mutants also display increased silencing in ribosomal DNA (rDNA). Consistent with this, RNA polymerase II occupancy is lower in cells lacking Ubp3 than in wild-type cells in all heterochromatic regions. Moreover, in a ubp3∆ mutant, unequal recombination in rDNA is highly suppressed. We present genetic evidence that this effect on rDNA recombination, but not silencing, is entirely dependent on the silencing factor Sir2. Further, ubp3∆ sir2∆ mutants age prematurely at the same rate as sir2∆ mutants. Thus our data suggest that recombination negatively influences replicative life span more so than silencing. However, in ubp3∆ mutants, recombination is not a prerequisite for aging, since cells lacking Ubp3 have a shorter life span than isogenic wild-type cells. We discuss the data in view of different models on how silencing and unequal recombination affect replicative life span and the role of Ubp3 in these processes.

scholarly journals Comparison of EMC and CM methods for orienting diffraction images in single-particle imaging experiments

IUCrJ ◽  
2021 ◽  
Vol 8 (6) ◽  
Author(s):  
Miklós Tegze ◽  
Gábor Bortel
Keyword(s):  
Intensity Distribution ◽  
Single Particle ◽  
Free Electron ◽  
Free Electron Laser ◽  
Biological Molecules ◽  
Crucial Step ◽  
X Ray ◽  
Diffraction Patterns ◽  
Particle Imaging ◽  
Single Particle Imaging

In single-particle imaging (SPI) experiments, diffraction patterns of identical particles are recorded. The particles are injected into the X-ray free-electron laser (XFEL) beam in random orientations. The crucial step of the data processing of SPI is finding the orientations of the recorded diffraction patterns in reciprocal space and reconstructing the 3D intensity distribution. Here, two orientation methods are compared: the expansion maximization compression (EMC) algorithm and the correlation maximization (CM) algorithm. To investigate the efficiency, reliability and accuracy of the methods at various XFEL pulse fluences, simulated diffraction patterns of biological molecules are used.

scholarly journals Virus detection and identification in minutes using single-particle imaging and deep learning

2020 ◽  
Author(s):  
Nicolas Shiaelis ◽  
Alexander Tometzki ◽  
Leon Peto ◽  
Andrew McMahon ◽  
Christof Hepp ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Single Particle ◽  
Virus Detection ◽  
Diagnostic Methods ◽  
Clinical Samples ◽  
Promising Alternative ◽  
Detection And Identification ◽  
Particle Imaging ◽  
Single Particle Imaging

AbstractThe increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the current COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive viral diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of single intact particles of different viruses. Our assay achieves labeling, imaging and virus identification in less than five minutes and does not require any lysis, purification or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses, with high accuracy. Single-particle imaging combined with deep learning offers a promising alternative to traditional viral diagnostic methods, and has the potential for significant impact.

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