High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

Intercellular communication via gap junction channels can be quantified by several methods based on diffusion of fluorescent dyes or metabolites. Given the variation in intercellular coupling of cells, even under untreated control conditions, it is of essence to quantify the coupling between numerous cells to obtain reliable estimates of metabolic coupling. Quantification is often based on manual counting of fluorescent cells, which is time consuming and may include some degree of subjectivity. In this report, we introduce a technique based on digital image analysis, and the software for the analysis is presented together with a detailed protocol in the online supplemental material ( http://bmi.ku.dk/matlab_program/ ). Fluorescent dye was introduced in connexin 43-expressing C6 glioma cells by in situ electroporation, and fluorescence intensity was measured in the electroporated cells and in cells receiving dye by intercellular diffusion. The analysis performed is semiautomatic, and comparison with traditional cell counting shows that this method reliably determines the effect of uncoupling by several interventions. This new method of analysis yields a rapid and objective quantification process with a high degree of reproducibility.

Download Full-text

Measuring Quantitative Virulence in the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis

Phytopathology ◽

10.1094/phyto-11-13-0328-r ◽

2014 ◽

Vol 104 (9) ◽

pp. 985-992 ◽

Cited By ~ 57

Author(s):

Ethan L. Stewart ◽

Bruce A. McDonald

Keyword(s):

Image Analysis ◽

High Throughput ◽

Digital Image ◽

Digital Image Analysis ◽

Continuous Distribution ◽

Automated Image Analysis ◽

Host Specialization ◽

Septoria Tritici Blotch ◽

Septoria Tritici ◽

Zymoseptoria Tritici

Zymoseptoria tritici, causal agent of Septoria tritici blotch on wheat, produces pycnidia in chlorotic and necrotic lesions on infected leaves. A high-throughput phenotyping method was developed based on automated digital image analysis that accurately measures the percentage of leaf area covered by lesions (PLACL) as well as pycnidia size and number. A seedling inoculation assay was conducted using 361 Z. tritici isolates originating from a controlled cross and two different winter wheat cultivars. Pycnidia size and density were found to be quantitative traits that showed a continuous distribution in the progeny. There was a weak correlation between pycnidia density and size (r = −0.27) and between pycnidia density and PLACL (r = 0.37). There were significant differences in PLACL and pycnidia density on resistant and susceptible cultivars. In all, >20% of the offspring exhibited significantly different pycnidia density on the two cultivars, consistent with host specialization. Automated image analysis provided greater accuracy and precision compared with traditional visual estimates of virulence. These results show that digital image analysis provides a powerful tool for measuring differences in quantitative virulence among strains of Z. tritici.

Download Full-text