ELM: super-resolution analysis of wide-field images of fluorescent shell structures

James D Manton,Graham Christie,Yao Xiao,Eric J Rees,Robert D Turner

doi:10.1088/2050-6120/aac28e

James D Manton, Graham Christie + Show 3 more

Open Access

https://doi.org/10.1088/2050-6120/aac28e

Copy DOI

Abstract

It is often necessary to precisely quantify the size of specimens in biological studies. When measuring feature size in fluorescence microscopy, significant biases can arise due to blurring of its edges if the feature is smaller than the diffraction limit of resolution. This problem is avoided if an equation describing the feature’s entire image is fitted to its image data. In this paper we present open-source software, ELM, which uses this approach to measure the size of spheroidal or cylindrical fluorescent shells with a precision of around 10 nm. This has been used to measure coat protein locations in bacterial spores and cell wall diameter in vegetative bacilli, and may also be valuable in microbiological studies of algae, fungi and viruses. ELM is available for download at https://github.com/quantitativeimaging/ELM.

Highlights

Any further distribution of this work must maintain feature size in fluorescence microscopy, significant biases can arise due to blurring of its edges if the attribution to the feature is smaller than the diffraction limit of resolution
The ELM software comprises a set of Matlab functions that are called by a graphical user interface. These functions segment a fluorescence microscope image to isolate single specimens and use non-linear least squares methods to iteratively fit a parametric structure to each candidate (figure 1(a))
Physically-realistic image data were simulated using TestSTORM software, with structural parameters set to emulate our experimental microscopy of spore coats containing mCherry on an Olympus BX51 wide-field microscope [7]

Summary

Introduction

Software, ELM, which uses this approach to measure the size of spheroidal or cylindrical fluorescent shells with a precision of around 10 nm. Limited resolution poses a problem when trying to accurately measure small feature sizes using image data, because errors are introduced by diffractive blurring of the specimen’s edges. We present software for such a post-capture analysis of wide-field microscopy images, which produces super-resolution measurements of shell-like fluorescent specimens, such as bacterial spores, without requiring any additional hardware.

Results

Conclusion