CMEIAS: An Improved Computing Technology for Quantitative Image Analysis of Root Colonization by Rhizobacteria
            <i>In Situ</i>
            At Single‐Cell Resolution

Dazzo, Frank B.; Yanni, Y. G.

doi:10.1002/9781118297674.ch69

Cited by 7 publications

(10 citation statements)

References 7 publications

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“…Spatial segregation of morphotypes colonizing the same habitat can provide insights into their feeding behavior, trophic level, food web dynamics and reproductive capacity. This trend has consistently been found in our spatial ecology studies of microbial biofilms that develop in a variety of natural and managed habitats, including plant rhizoplanes and phylloplanes [46][47][48][49], freshwater streambed pebbles [50], and microscope slides suspended in various river/lake ecosystems [2,51,52].…”

Section: Biofilm Ecophysiology Of Nutrient Acquisition and Utilizatiosupporting

confidence: 72%

“…These awesome foci of strongly clustered cells colocalize with epicenters of -hot spots‖ revealed by the point pattern method of linear alignments (Figure 8a,b), and with the georeferenced posting plots of cells represented by bubbles whose widths are weighted by each individual cell's cluster index (Figure 9a,b). Kriging analysis also predicts the in situ strength of diffusion gradients of extracellular signal molecules that promote/positively regulate these cooperative cell-to-cell interactions within the biofilm [12,49,52].…”

Section: Geostatistical Spatial Distribution Analysismentioning

confidence: 99%

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In Situ Ecophysiology of Microbial Biofilm Communities Analyzed by CMEIAS Computer-Assisted Microscopy at Single-Cell Resolution

et al. 2013

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This paper describes the utility of CMEIAS (Center for Microbial Ecology Image Analysis System) computer-assisted microscopy to extract data from accurately segmented images that provide 63 different insights into the ecophysiology of microbial populations and communities within biofilms and other habitats. Topics include quantitative assessments of: (i) morphological diversity as an indicator of impacts that substratum physicochemistries have on biofilm community structure and dominance-rarity relationships among populations; (ii) morphotype-specific distributions of biovolume body size that relate microbial allometric scaling, metabolic activity and growth physiology; (iii) fractal geometry of optimal cellular positioning for efficient utilization of allocated nutrient resources; (iv) morphotype-specific stress responses to starvation, environmental disturbance and bacteriovory predation; (v) patterns of spatial distribution indicating positive and negative cell-cell interactions affecting their colonization behavior; and (vi) significant methodological improvements to increase the accuracy of color-discriminated ecophysiology, e.g., differentiation of cell viability based on cell membrane integrity, cellular respiratory activity, phylogenetically differentiated substrate utilization, and N-acyl homoserine lactone-mediated cell-cell communication by bacteria while colonizing plant roots. The intensity of these ecophysiological attributes commonly varies at the individual cell level, emphasizing the importance of analyzing them at single-cell resolution and the proper spatial scale at which they occur in situ.

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Section: Biofilm Ecophysiology Of Nutrient Acquisition and Utilizatiosupporting

confidence: 72%

Section: Geostatistical Spatial Distribution Analysismentioning

confidence: 99%

In Situ Ecophysiology of Microbial Biofilm Communities Analyzed by CMEIAS Computer-Assisted Microscopy at Single-Cell Resolution

et al. 2013

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“…The mission of our CMEIAS project is to develop, document and release a comprehensive suite of bioimage informatics analysis software applications designed to strengthen quantitative, microscopy-based approaches for understanding microbial ecology, at spatial scales directly relevant to microbes and their ecological niches without the need for cultivation [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. The wealth of information gained by CMEIAS analysis of digital images can bridge with other modern genotypic and phenotypic technologies to fill knowledge gaps revealing additional insights of in situ phenotypic characteristics of ecological importance to microbial cells, populations, communities and microbiomes.…”

Section: Cmeias Software Developmentmentioning

confidence: 99%

“…The wealth of information gained by CMEIAS analysis of digital images can bridge with other modern genotypic and phenotypic technologies to fill knowledge gaps revealing additional insights of in situ phenotypic characteristics of ecological importance to microbial cells, populations, communities and microbiomes. Examples include their biodiversity, productivity (conversion of available nutrient resources into biomass and metabolic energy), food-web dynamics, landscape ecology, strategies of successful colonization behavior, adaptations and resilience to environmental stresses, and intensities of interaction with each other within biofilms [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. When finalized, the copyrighted CMEIAS software tools and their comprehensive documentations are released as free downloads at our project website [1].…”

Section: Cmeias Software Developmentmentioning

confidence: 99%

Influence of Substratum Hydrophobicity on the Geomicrobiology of River Biofilm Architecture and Ecology Analyzed by CMEIAS Bioimage Informatics

et al. 2017

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Microbial biogeography in terrestrial and freshwater ecosystems is mainly dominated by community biofilm lifestyles. Here, we describe applications of computer-assisted microscopy using CMEIAS (Center for Microbial Ecology Image Analysis System) bioimage informatics software for a comprehensive analysis of river biofilm architectures and ecology. Natural biofilms were developed for four summer days on microscope slides of plain borosilicate glass and transparent polystyrene submerged in the Red Cedar River that flows through the Michigan State University campus. Images of the biofilm communities were acquired using brightfield and phase-contrast microscopy at spatial resolutions revealing details of microcolonies and individual cells, then digitally segmented to the foreground objects of interest. Phenotypic features of their size, abundance, surface texture, contour morphology, fractal geometry, ecophysiology, and landscape/spatial ecology were digitally extracted and evaluated by many discriminating statistical tests. The results indicate that river biofilm architecture exhibits significant geospatial structure in situ, providing many insights on the strong influence that substratum hydrophobicity-wettability exert on biofilm development and ecology, including their productivity and colonization intensity, morphological diversity/dominance/conditional rarity, nutrient apportionment/uptake efficiency/utilization, allometry/metabolic activity, responses to starvation and bacteriovory stresses, spatial patterns of distribution/dispersion/connectivity, and interpolated autocorrelations of cooperative/conflicting cell-cell interactions at real-world spatial scales directly relevant to their ecological niches. The significant impact of substratum physicochemistry was revealed for biofilms during their early immature stage of development in the river ecosystem. Bioimage informatics can fill major gaps in understanding the geomicrobiology and microbial ecology of biofilms in situ when examined at spatial scales suitable for phenotypic analysis at microcolony and single-cell resolutions.

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“…Spatial pattern analyses that reject the null hypothesis of complete spatial randomness are typically followed by other tests that determine whether the pattern is uniform or aggregated, its local vs. regional spatial scale, and its spatial intensity [4,51]. We have found that this trend of nonrandom patterns was dominated by cooperative clustering plus some competitive uniform distributions in microbial biofilms in natural and managed habitats, including on root and leaf surfaces [53][54][55][56][57][58], freshwater streambed pebbles [59], and in river/lake ecosystems [4,22,52,60]. Thus, spatial analyses of microbial biofilms can reveal many insights on the ecological conditions that trigger the colonization behaviors creating them [4].…”

Section: Spatial Pattern Analysis and Its Relationship To Microbial Bmentioning

confidence: 99%

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

Dazzo

Niccum

2015

Computation

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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. OPEN ACCESSComputation 2015, 3 73

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CMEIAS: An Improved Computing Technology for Quantitative Image Analysis of Root Colonization by Rhizobacteria In Situ At Single‐Cell Resolution

Cited by 7 publications

References 7 publications

In Situ Ecophysiology of Microbial Biofilm Communities Analyzed by CMEIAS Computer-Assisted Microscopy at Single-Cell Resolution

In Situ Ecophysiology of Microbial Biofilm Communities Analyzed by CMEIAS Computer-Assisted Microscopy at Single-Cell Resolution

Influence of Substratum Hydrophobicity on the Geomicrobiology of River Biofilm Architecture and Ecology Analyzed by CMEIAS Bioimage Informatics

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

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