Image-processing software for high-throughput quantification of colony luminescence

Eyal Dafni, Iddo Weiner, Noam Shahar, Tamir Tuller, Iftach Yacoby

Research output: Contribution to journalArticlepeer-review

Abstract

Many microbiological assays include colonies that produce a luminescent or fluorescent (here generalized as "luminescent") signal, often in the form of luminescent halos around the colonies. These signals are used as reporters for a trait of interest; therefore, exact measurements of the luminescence are often desired. However, there is currently a lack of high-throughput methods for analyzing these assays, as common automatic image analysis tools are unsuitable for identifying these halos in the presence of the inherent biological noise. In this work, we have developed CFQuant-automatic, high-throughput software for the analysis of images from colony luminescence assays. CFQuant overcomes the problems of automatic identification by relying on the luminescence halo's expected shape and provides measurements of several features of the colonies and halos. We examined the performance of CFQuant using one such colony luminescence assay, where we achieved a high correlation (R=0.85) between the measurements of CFQuant and known protein expression levels. This demonstrates CFQuant's potential as a fast and reliable tool for analysis of colony luminescence assays.

Original languageEnglish
Article numbere00676-18
JournalmSphere
Volume4
Issue number1
DOIs
StatePublished - 1 Jan 2019

Keywords

  • Fluorescent-image analysis
  • Microbial method
  • Software

Fingerprint

Dive into the research topics of 'Image-processing software for high-throughput quantification of colony luminescence'. Together they form a unique fingerprint.

Cite this