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Computation 2015, 3(1), 72-98; doi:10.3390/computation3010072

Use of CMEIAS Image Analysis Software to Accurately Compute Attributes of Cell Size, Morphology, Spatial Aggregation and Color Segmentation that Signify in Situ Ecophysiological Adaptations in Microbial Biofilm Communities

Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA
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Author to whom correspondence should be addressed.
Academic Editor: Rainer Breitling
Received: 24 November 2014 / Revised: 23 February 2015 / Accepted: 25 February 2015 / Published: 9 March 2015
(This article belongs to the Section Computational Biology)
View Full-Text   |   Download PDF [1389 KB, uploaded 9 March 2015]   |  

Abstract

In this review, we describe computational features of computer-assisted microscopy that are unique to the Center for Microbial Ecology Image Analysis System (CMEIAS) software, and examples illustrating how they can be used to gain ecophysiological insights into microbial adaptations occurring at micrometer spatial scales directly relevant to individual cells occupying their ecological niches in situ. These features include algorithms that accurately measure (1) microbial cell length relevant to avoidance of protozoan bacteriovory; (2) microbial biovolume body mass relevant to allometric scaling and local apportionment of growth-supporting nutrient resources; (3) pattern recognition rules for morphotype classification of diverse microbial communities relevant to their enhanced fitness for success in the particular habitat; (4) spatial patterns of coaggregation that reveal the local intensity of cooperative vs. competitive adaptations in colonization behavior relevant to microbial biofilm ecology; and (5) object segmentation of complex color images to differentiate target microbes reporting successful cell-cell communication. These unique computational features contribute to the CMEIAS mission of developing accurate and freely accessible tools of image bioinformatics that strengthen microscopy-based approaches for understanding microbial ecology at single-cell resolution. View Full-Text
Keywords: biofilm; biovolume; cell aggregation; CMEIAS; color segmentation; computer-assisted microscopy; image analysis; morphological diversity; spatial ecology biofilm; biovolume; cell aggregation; CMEIAS; color segmentation; computer-assisted microscopy; image analysis; morphological diversity; spatial ecology
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Dazzo, F.B.; Niccum, B.C. Use of CMEIAS Image Analysis Software to Accurately Compute Attributes of Cell Size, Morphology, Spatial Aggregation and Color Segmentation that Signify in Situ Ecophysiological Adaptations in Microbial Biofilm Communities. Computation 2015, 3, 72-98.

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