Computer image analysis of microbial colonies

Puchkov, E. O.

doi:10.1134/s0026261710020025

Cited by 8 publications

(7 citation statements)

References 17 publications

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“…Using an automated system of scanners and image analysis capable of simultaneously monitoring thousands of bacterial colonies for several weeks, we performed a large-scale study of the diversity of growth patterns of bacteria from a natural soil community. This method, previously applied to single species (21,35,38,49,64), significantly increases the number of colonies that can be followed compared to manual tracking (8,23) or tracking using microscopy (12,40), allowing a broader view of the microbial community. To capitalize on the strengths of this approach, we focus on exploring how it can shed light on microbial diversity directly at the community level without working explicitly with individual strains.…”

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confidence: 99%

Distinct Growth Strategies of Soil Bacteria as Revealed by Large-Scale Colony Tracking

Ernebjerg

Kishony

2012

Appl Environ Microbiol

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Our understanding of microbial ecology has been significantly furthered in recent years by advances in sequencing techniques, but comprehensive surveys of the phenotypic characteristics of environmental bacteria remain rare. Such phenotypic data are crucial for understanding the microbial strategies for growth and the diversity of microbial ecosystems. Here, we describe a high-throughput measurement of the growth of thousands of bacterial colonies using an array of flat-bed scanners coupled with automated image analysis. We used this system to investigate the growth properties of members of a microbial community from untreated soil. The system provides high-quality measurements of the number of CFU, colony growth rates, and appearance times, allowing us to directly study the distribution of these properties in mixed environmental samples. We find that soil bacteria display a wide range of growth strategies which can be grouped into several clusters that cannot be reduced to any of the classical dichotomous divisions of soil bacteria, e.g., into copiotophs and oligotrophs. We also find that, at early times, cells are most likely to form colonies when other, nearby colonies are present but not too dense. This maximization of culturability at intermediate plating densities suggests that the previously observed tendency for high density to lead to fewer colonies is partly offset by the induction of colony formation caused by interactions between microbes. These results suggest new types of growth classification of soil bacteria and potential effects of species interactions on colony growth.

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confidence: 99%

Distinct Growth Strategies of Soil Bacteria as Revealed by Large-Scale Colony Tracking

Ernebjerg

Kishony

2012

Appl Environ Microbiol

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“…The principal parts of this type of colony counters are trans-and epi-illumination system, a CCD camera to capture digital images of the Petri dishes and a computer with an appropriate software (schematically presented in [11]). Several CDIA based computer colony counters (CCC) are presently available on the market (reviewed in [12]) including CCC specially designed for counting mammalian cell colonies (GelCount™, Oxford Optronix Ltd., UK, http://www.oxford-optronix.com/). Also, a number of "homemade" CDIA based systems for automated colony counting have been reported from several laboratories [13]- [18].…”

Section: Colony Countingmentioning

confidence: 99%

“…The major problem of using the automatic mode is the presence of confluent colonies. Although many commercial [12] and "home-made" [19] [20] CCC provide an option to discriminate between individual colonies within a conglomerate, this is actually realized only in case of rather small conglomerates. Anyhow, automatic colony counting of the samples with the confluent colonies is prone to an error.…”

Section: Colony Countingmentioning

confidence: 99%

Image Analysis in Microbiology: A Review

Pushchino¹

2016

JCC

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This review is focused on using computer image analysis as a means of objective and quantitative characterizing optical images of the macroscopic (e.g. microbial colonies) and the microscopic (e.g. single cell) objects in the microbiological research. This is the way of making many visual inspection assays more objective and less time and labor consuming. Also, it can provide new visually inaccessible information on relation between some optical parameters and various biological features of the microbial cultures. Of special interest is application of image analysis in fluorescence microscopy as it opens new ways of using fluorescence based methodology for single microbial cell studies. Examples of using image analysis in the studies of both the macroscopic and the microscopic microbiological objects obtained by various imaging techniques are presented and discussed.

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“…The colony shape and its edge have been morphological features used traditionally in the identification process of microbial strains, including yeasts (Kurtzman et al ., ). This purely descriptive methodology has been improved lately by the incorporation of new techniques of image analysis that automatically produce quick and quantitative results (Robinson et al ., ; Dorge et al ., ; Yang et al ., ; Hansen et al ., ; Banada et al ., ; Clemmensen et al ., ; den Hertog et al ., ; Puchkov, ).…”

Section: Introductionmentioning

confidence: 98%

Quantitative analysis of morphological changes in yeast colonies growing on solid medium: the eccentricity and Fourier indices

Prado

Rivas

Silóniz

et al. 2014

Yeast

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The colony shape of four yeast species growing on agar medium was measured for 116 days by image analysis. Initially, all the colonies are circular, with regular edges. The loss of circularity can be quantitatively estimated by the eccentricity index, E i , calculated as the ratio between their orthogonal vertical and horizontal diameters. E i can increase from 1 (complete circularity) to a maximum of 1.17-1.30, depending on the species. One colony inhibits its neighbour only when it has reached a threshold area. Then, E i of the inhibited colony increases proportionally to the area of the inhibitory colony. The initial distance between colonies affects those threshold values but not the proportionality, E i /area; this inhibition affects the shape but not the total surface of the colony. The appearance of irregularities in the edges is associated, in all the species, not with age but with nutrient exhaustion. The edge irregularity can be quantified by the Fourier index, F i , calculated by the minimum number of Fourier coefficients that are needed to describe the colony contour with 99% fitness. An ad hoc function has been developed in Matlab v. 7.0 to automate the computation of the Fourier coefficients. In young colonies, F i has a value between 2 (circumference) and 3 (ellipse). These values are maintained in mature colonies of Debaryomyces, but can reach values up to 14 in Saccharomyces. All the species studied showed the inhibition of growth in facing colony edges, but only three species showed edge irregularities associated with substrate exhaustion.

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Computer image analysis of microbial colonies

Cited by 8 publications

References 17 publications

Distinct Growth Strategies of Soil Bacteria as Revealed by Large-Scale Colony Tracking

Distinct Growth Strategies of Soil Bacteria as Revealed by Large-Scale Colony Tracking

Image Analysis in Microbiology: A Review

Quantitative analysis of morphological changes in yeast colonies growing on solid medium: the eccentricity and Fourier indices

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