An automated approach for single-cell tracking in epifluorescence microscopy applied to E. coli growth analysis on microfluidics biochips

Catalin Fetita; Boris Kirov; Alfonso Jaramillo; Christophe Lefevre

doi:10.1117/12.911371

14 April 2012 An automated approach for single-cell tracking in epifluorescence microscopy applied to E. coli growth analysis on microfluidics biochips

Catalin Fetita, Boris Kirov, Alfonso Jaramillo, Christophe Lefevre

Author Affiliations +

Proceedings Volume 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging; 83170Z (2012) https://doi.org/10.1117/12.911371
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

With the accumulation of knowledge for the intimate molecular mechanisms governing the processes inside the living cells in the later years, the ability to characterize the performance of elementary genetic circuits and parts at the single-cell level is becoming of crucial importance. Biological science is arriving to the point where it can develop hypothesis for the action of each molecule participating in the biochemical reactions and need proper techniques to test those hypothesis. Microfluidics is emerging as the technology that combined with high-magnification microscopy will allow for the long-term single-cell level observation of bacterial physiology. In this study we design, build and characterize the gene dynamics of genetic circuits as one of the basic parts governing programmed cell behavior. We use E. coli as model organism and grow it in microfluidics chips, which we observe with epifluorescence microscopy. One of the most invaluable segments of this technology is the consequent image processing, since it allows for the automated analysis of vast amount of single-cell observation and the fast and easy derivation of conclusions based on that data. Specifically, we are interested in promoter activity as function of time. We expect it to be oscillatory and for that we use GFP (green fluorescent protein) as a reporter in our genetic circuits. In this paper, an automated framework for single-cell tracking in phase-contrast microscopy is developed, combining 2D segmentation of cell time frames and graph-based reconstruction of their spatiotemporal evolution with fast tracking of the associated fluorescence signal. The results obtained on the investigated biological database are presented and discussed.

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Catalin Fetita, Boris Kirov, Alfonso Jaramillo, and Christophe Lefevre "An automated approach for single-cell tracking in epifluorescence microscopy applied to E. coli growth analysis on microfluidics biochips", Proc. SPIE 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging, 83170Z (14 April 2012); https://doi.org/10.1117/12.911371

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KEYWORDS

Image segmentation

Microscopy

Luminescence

Genetics

Microfluidics

Biological research

Image filtering

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