DNEMO: a tool for quantification of mRNA and punctate structures in time-lapse images of single cells.

Gabriel J Kowalczyk,Robin E C Lee,Yue Guo,J Agustin Cruz,Natalie Sauerwald,Qiuhong Zhang,Alfonso Valencia

doi:10.1093/bioinformatics/btaa874

Abstract

Many biological processes are regulated by single molecules and molecular assemblies within cells that are visible by microscopy as punctate features, often diffraction limited. Here, we present detecting-NEMO (dNEMO), a computational tool optimized for accurate and rapid measurement of fluorescent puncta in fixed-cell and time-lapse images. The spot detection algorithm uses the à trous wavelet transform, a computationally inexpensive method that is robust to imaging noise. By combining automated with manual spot curation in the user interface, fluorescent puncta can be carefully selected and measured against their local background to extract high-quality single-cell data. Integrated into the workflow are segmentation and spot-inspection tools that enable almost real-time interaction with images without time consuming pre-processing steps. Although the software is agnostic to the type of puncta imaged, we demonstrate dNEMO using smFISH to measure transcript numbers in single cells in addition to the transient formation of IKK/NEMO puncta from time-lapse images of cells exposed to inflammatory stimuli. We conclude that dNEMO is an ideal user interface for rapid and accurate measurement of fluorescent molecular assemblies in biological imaging data. The data and software are freely available online at https://github.com/recleelab. Supplementary data are available at Bioinformatics online.

Highlights

Quantitative imaging of single cells enables measurement with subcellular resolution of dynamic biological processes that regulate critical cellular behaviors
RESULTS: dNEMO identifies near diffraction-limited fluorescent puncta in 2D and 3D images Wavelet-based approaches are used in image analysis for de-noising, compression, and feature extraction with low computational cost [19, 20]
With ground truth information for the position and number of puncta in simulated data, we found that both applications have almost negligible localization error in low noise, but error rates for dNEMO remained lower for images with greater noise (Supplemental Figure 4b)

Summary

Introduction

Quantitative imaging of single cells enables measurement with subcellular resolution of dynamic biological processes that regulate critical cellular behaviors. Most live-cell imaging approaches use fluorescent biosensors and fusion proteins that report within large subcellular compartments, such as the cytoplasm or nucleus, and quantification of punctate structures is often limited to fixed-cell and low-throughput applications. Upstream kinase activation by the NF-κB essential modulator protein (NEMO, known as IKKɣ) is a necessary step in regulation of the classical NF-κB signaling cascade [11]. NEMO is recruited to polyubiquitin scaffolds associated with cytokine-ligated receptor complexes where NEMO-interacting IκB kinases (IKKs) are activated through induced proximity with other signaling mediators [12,13,14,15,16]. The number and timescales of EGFP-NEMO-enriched puncta reveal quantitative properties of receptor-associated protein complexes that transmit information from the inflammatory milieu into the NF-κB transcriptional system

Methods

Results

Conclusion