plant surface microbiology.pdf

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Frank B. Dazzo
including its resistance, resilience, and ecological succession in a polyphasic
taxonomy study of microbial community responses to nutrient perturbation,
using complex anaerobic bioreactors as the model system (Fernandez et al.
2000; Hashsham et al. 2000). CMEIAS v. 1.27 will soon be released for free
Internet download at a website linked to the Michigan State University Center
for Microbial Ecology (http://cme.msu.edu/cmeias).
6.2 CMEIAS v. 3.0: Comprehensive Image Analysis of Microbial
Communities
A significantly upgraded version of CMEIAS is being developed with several
new analytical modules designed to extract four ecologically relevant, in situ
features of microbial communities in digital images: (1) morphotype classification
and diversity,(2) microbial abundance for both filamentous and nonfilamentous
morphotypes, (3) in situ studies of microbial phylogeny/autecology/metabolism,
and (4) in situ spatial distribution analysis of microbial
colonization on various surfaces. Significant new features will include an
advanced morphotype classifier that incorporates default size and shape
dimensional borders that are taxonomically relevant and has user-defined
flexibility to discriminate any customized level of morphological diversity;
various computations of cell density, biovolume, biomass carbon, biosurface
area, and filamentous length; color recognition of foreground objects stained
with fluorescent molecular probes; various measurement features of plot-less,
plot-based,and georeferenced patterns of spatial distribution analysis; spreadsheet
macros for automatic data preparation, sampling statistics and spatial
statistics analyses; and automated image editing routines (Reddy et al.2002a,b;
see http://lter.kbs.msu.edu/Meetings/2003_All_inv_Meeting/Abstracts.dazzo.
htm). Data extracted from images by CMEIAS can be used in other advanced
ecological statistics programs, e.g., EcoStat (Towner 1999), and GS+Geostatistics
(Robertson 2002), to compute numerous other statistical indices that further
characterize microbial community structure. Our vision is for CMEIAS to
become an accurate, robust and user-friendly software tool that can analyze
microbial communities without cultivation, thereby creating many new
approaches to study microbial ecology in situ at spatial scales physiologically
relevant to the individual microbes.
To illustrate some of the awesome computational power of CMEIAS that
can be applied to in situ studies of plant surface microbiology, examples of
analyses have been performed on (1) the abundance and spatial distribution
of Rhizobium leguminosarum bv. trifolii cells colonized on a white clover
seedling root in gnotobiotic culture; (2) a comparison of the morphological
diversity and distribution of abundance in natural microbial communities
that colonize the phylloplane leaf surface of two different varieties of fieldgrown
corn, and (3) the in situ spatial patterns of root colonization by the pio-