Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

Overview

Journal J Vis Exp

Specialties Biology
General Medicine

Date 2017 Sep 21

PMID 28930980

Citations 1

Authors

Ashley H Ramsawhook

Lara C Lewis

Maria Eleftheriou

Abdulkadir Abakir

Paulina Durczak

Robert Markus

Seema Rajani

Nicholas R F Hannan

Beth Coyle

Alexey Ruzov

Affiliations

Soon will be listed here.

Abstract

For several decades, 5-methylcytosine (5mC) has been thought to be the only DNA modification with a functional significance in metazoans. The discovery of enzymatic oxidation of 5mC to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC) as well as detection of N6-methyladenine (6mA) in the DNA of multicellular organisms provided additional degrees of complexity to the epigenetic research. According to a growing body of experimental evidence, these novel DNA modifications may play specific roles in different cellular and developmental processes. Importantly, as some of these marks (e. g. 5hmC, 5fC and 5caC) exhibit tissue- and developmental stage-specific occurrence in vertebrates, immunochemistry represents an important tool allowing assessment of spatial distribution of DNA modifications in different biological contexts. Here the methods for computational analysis of DNA modifications visualized by immunostaining followed by confocal microscopy are described. Specifically, the generation of 2.5 dimension (2.5D) signal intensity plots, signal intensity profiles, quantification of staining intensity in multiple cells and determination of signal colocalization coefficients are shown. Collectively, these techniques may be operational in evaluating the levels and localization of these DNA modifications in the nucleus, contributing to elucidating their biological roles in metazoans.

Citing Articles

MultiScale-CNN-4mCPred: a multi-scale CNN and adaptive embedding-based method for mouse genome DNA N4-methylcytosine prediction.

Zheng P, Zhang G, Liu Y, Huang G BMC Bioinformatics. 2023; 24(1):21.

PMID: 36653789 PMC: 9847203. DOI: 10.1186/s12859-023-05135-0.

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