COMMUNITY LEVEL PHYSIOLOGICAL PROFILING OF MICROORGANISMS IN THE RHIZOSPHERE OF TRANSGENIC PLANTS – A REVIEW

Since 1996, when the first genetically modified seeds were planted in field conditions, the commercial growing of genetically modified crops increased to over 134 millions of hectares in 2009 worldwide. Along with the great potential of transgenic plants for future agriculture, considerable concerns on their biosafety have been raised, including their potential impact on soil microbial communities. This review briefly summarizes the important features of soil microorganisms for plant health and ecosystem stability, the numerous methods available for microbial ecologists to study soil microbial diversity, with emphasis on the method of community level physiological profiling (CLPP) based on carbon substrate utilization patterning, and finally the use of CLPP for assessing the effects of transgenic crops on soil microbial communities.


Introduction
The first transgenic plant, tobacco containing a selectable marker gene nptII from a bacterium conferring resistance to kanamycin, was produced at the University of Ghent, Belgium, in 1983(ZAMBRYSKI et al., 1983), only 30 years after the discovery of the structure of DNA.Now, some 27 years later, genetically modified (or transgenic) crops became a common feature of the agricultural landscape in 25 countries of the both Americas, Europe, Asia, Africa and Australia (JAMES, 2009).The unprecedented high growth rate of adoption of transgenic crops started in the U.S.A. in 1996 with 1.7 million hectares.In 2009, the global area of genetically modified (GM) crops reached 134 million hectares (JAMES 2009), which is more than the total land area of six neighboring countries: Slovakia, Czech Republic, Poland, Hungary, Ukraine and Austria together (122 mil.ha).The first commercially grown transgenic crops contained one gene of interest or one introduced novel trait (single trait GM crops).At present, however, combination or stacking different traits or genes in one plant is rapidly gaining popularity and recent growth of GM crops hectarage over the last few years comes largely from deployment of these so called "stacked traits" GM crops (TAVERNIERS et al., 2008;JAMES, 2009).Several transgenic plants containing two, three or more genes of interest are currently under evaluation by national authorities of different countries for deliberate release of transgenic plants into environment (TAVERNIERS et al., 2008).
Along with the increasing potential for widespread commercial use and the benefits of transgenic crops, considerable concerns on their safety have been raised, including safety aspects relating to their potential impact on the environment (WIDMER, 2007).The rapid development of agricultural biotechnology and release of transgenic plants into environment have provided many agronomic and economic benefits, however they also raised a multitude of concerns over the potential ecological effects of transgenic plants.These concerns include unintended consequences of transgene flow to indigenous organisms through pollen transfer, plant invasiveness, the development of resistance in target pests, and direct or non-direct effects on nontarget flora, fauna and microorganisms and ecosystems (SEIDLER and LEVIN, 1994;NIELSEN et al., 2001;DALE et al., 2002;BRUINSMA et al., 2003;FILION, 2008).In addition to the relatively abundantly studied aboveground effects, underground impacts of GM crops have also been recognized as a result of recent methodological advances in soil microbial ecology (BRUINSMA et al., 2003;ZHANG et al., 2005).Nevertheless, the impact of GM crops on soil-associated microfauna, including soil microbial communities, still represents one of the least studied and understood areas, probably due in part to the inherent technical difficulties involved in the study of soilborne living organisms (FILION, 2008).
Recently several excellent reviews on the effects of transgenic plants on soil microbial communities have been published (e.g.BRUINSMA et al., 2003;DUNFIELD and GERMIDA, 2004;WIDMER, 2007;FILION, 2008).In this review, we focused on the methodological aspects, as well as the use of Community level physiological profiling (CLPP) based on sole carbon source utilization analysis to study the functional diversity of microbial communities in the rhizosphere of transgenic plants.We provide also a brief overview of the microbial characteristics of soils and methods used for analyses of soil microbial communities.

Microbial characteristics of soils
Soil is a complex and dynamic physical, chemical and biological system and a major component in agro-ecosystems (NANNIPIERI et al., 2003).It is considered to be the greatest reservoir of biodiversity on the planet (CRAWFORD et al., 2005).Prokaryotic organisms comprise more than half of the biodiversity on Earth and their diversity in soil has been estimated to be about three orders-of-magnitude greater than in all other environments combined (CURTIS et al., 2002).
Microorganisms are fundamentally important components of the soil habitat where they play key roles in ecosystem functioning through controlling nutrient cycling reactions essential for maintaining soil fertility, and they also contribute to the genesis and maintenance of soil structure (KIRK et al., 2004).The microbial community of arable soils is a key agent in biologically mediated processes such as degradation of organic residues, transformation of organic matter, mineralization of nutrients, formation of soil aggregates, and soil nutrient balance.Soil microorganisms are also a component with multiple functions of importance to soil fertility, such as catalysis of nutrient transformations, storage of nutrients, formation and stabilization of soil structure, and control of plant pathogens (KENNEDY and PAPENDICK, 1995;PETERSEN et al., 2002;GÖMÖRYOVÁ et al., 2009a).
Soil microbial communities have great potential for temporal and spatial change, and thus represent a powerful tool for understanding community dynamics in both basic and applied ecological research (GARLAND, 1997).The soil microbial community structure is considered as an early and sensitive indicator of anthropogenic effects on soil ecology (NIELSEN and WINDING, 2002).Soil microorganisms are able to respond more quickly to environmental stress because, compared to higher organisms, they have a high surface-to-volume ratio, which means they are capable of a much more intense exchange of matter and energy with their environment.Therefore, changes in size, composition and activity of microbial communities can frequently be observed before detectable changes in soil physical and chemical properties occur (NIELSEN and WINDING, 2002;WIDMER and OBERHOLZER, 2003;GÖMÖRYOVÁ et al., 2009a).Moreover, bacteria interact with plants during their entire life cycles and therefore can act as precise and fast indicators of environmental changes.
Plants depend on the ability of roots to communicate with microbes.The converse is also true; many bacteria and fungi are dependent on associations with plants that are often regulated by root exudates (BAIS et al., 2004).Crop plants interact with soil microbial communities through a micro-zone at the root-soil interface that is under the influence of the plant root.This complex habitat composed of the fraction of soil adhering to plant roots and altered by root activity is referred to as rhizosphere.The rhizosphere environment hosts a complex microorganism network which interacts very closely with plant roots, the outcome of such interaction being seen in the strong influence plant type has on the microbial ecosystem of the soil (BRUSETTI et al., 2004).It is well known, that rhizosphere exerts a selective influence on the associated microbial communities and these microorganisms in turn have a great impact on root biology, they influence plant growth, nutrition and development, and are important for long-term sustainability of agricultural soils (MANTELIN and TOURAINE, 2004).A number of studies have shown that the rhizosphere has much higher population densities of bacteria and fungi compared with bulk soil (MALONEY et al., 1997;SEMENOV et al., 1999).
Plants modify their rhizosphere environment through release of assimilates in the form of root exudates (UREN, 2001).The four types of main ingredients in plant root exudates are carbohydrates, amino acids, fatty acids and nucleotides, other compounds, such as organic acids, steroids, growth hormones, flavones and enzymes are also involved (ZHANG et al., 2005).This complex mixture of organic compounds provides a source of reduced carbon, nitrogen, and other nutrients for soil inhabiting microorganisms (BUYER et al., 2002).The composition of compounds which are released from the roots and interact with bacteria in the rhizosphere vary depending on the plant species, cultivar, and physiological status of the plants (SORENSEN, 1997;SAXENA et al., 1999).Root exudates are known to mediate both positive and negative interactions in the rhizosphere.The positive interactions include enhancement of growth rates of bacteria (HARTWIG et al., 1991), acting as chemoattractants to attract bacteria towards the root (DHARMATILAKE and BAUER, 1992), and acting as transcriptional signals in the communication between soil bacteria and host plants during nodule formation and biological nitrogen fixation by plants (REDMOND et al., 1986).On the other side, plant-microbe interactions often involve also plant activities to suppress growth of bacteria in the rhizosphere, e.g., by secretion of bactericidal substances (GARCIA-OLMEDO et al., 1998).Bactericidal substances naturally released from the plant roots may include toxic components like benzofurans, terpenoids, butyrolactones, and other phytoalexins (BOWEN and ROVIRA, 1991).
Previous studies revealed that qualitative and quantitative differences in root exudation could strongly affect the structure of microbial communities in the rhizosphere (OGER et al., 1997;SAVKA and FARRAND, 1997;MALONEY et al., 1997).The composition of microbial communities in the rhizosphere is governed mainly by the quality and quantity of carbon substrates that are released as root exudates (MALONEY et al., 1997).Root exudation may create a niche that influences which microorganisms colonize the rhizosphere, thereby altering the composition and diversity of rhizomicrobial communities in a plant-specific manner (GRAYSTON et al., 1998).Even small modifications, as may exist between different cultivars of the same plant species may cause altered composition of root exudates, which can eventually result in the occurrence of different microbial communities in the rhizosphere (RENGEL et al., 1998).
It was shown previously that microbial population density and diversity can be influenced by introducing genes into plants for the production of novel compounds (OGER et al., 1997;SAVKA and FARRAND, 1997).Genetically engineered plants might change the bacterial consortia in the rhizosphere due to the release of transgene products or an altered composition of root exudates (OGER et al., 1997).The insertion of transgenes may unintentionally alter plant characteristics of the transgenic crop others then the desired trait.In turn, these changes may influence the growth and species composition of soil microorganisms associated with the roots of these plants, and therefore they may have ecological effects (DONEGAN et al., 1995).An altered composition of root exudates may induce a different community of rhizosphere microorganisms and even small modifications, as may exist between different cultivars of the same plant species, can result in the occurrence of different microbial communities in the rhizospheres (RENGEL et al., 1998).
Comparative studies assessing whether there are differences between microbial communities living in the rhizospheres of transgenic and non-transgenic plants represent an important first step in determining if the presence of transgenic material can catalyze changes in the environment.This knowledge of the impact of transgenic crops on soil microbial ecology is essential for understanding the long-term agronomic and environmental effects of genetically modified crops and for developing appropriate management practices for minimizing potential negative impacts (FANG et al., 2007).

Methods of studying soil microbial communities
Over the past ten years, approaches to studying soil microbial communities changed dramatically.A number of new techniques have been developed and are now available to soil microbiologists to gain deeper insight into community-level responses to changes in soil properties or management.
The methods for the analysis of microbiological soil characteristics and assessment of the impact of environmental or anthropogenic factors, including the cultivation of genetically modified crops, on soils are generally categorized into two broad groups: (1) culture-dependent methods and (2) culture-independent methods (HILL et al., 2000;WIDMER, 2007).
There are several cultivation-dependent methods which are used to retrieve microorganisms from soils.The plating method (syn.plate count method) offers a simple but useful tool to identify and characterize changes of specific microbial strains, or groups of species (BRUSETTI et al., 2004;LIU et al., 2005;FARAGOVÁ et al., 2005;MULDER et al., 2006).It can be used to detect effects of transgenic plants on specific soil microorganisms such as symbiotic nitrogen-fixing bacteria, degraders of recalcitrant organic matter, nitrifying bacteria, denitrifying bacteria, cellulolytic bacteria, actinomycetes, and others (BRUINSMA et al., 2003;FARAGOVÁ et al., 2005, FARAGOVÁ andFARAGÓ, 2010).One limitation of the method is, however, that it is affected by the cultivation bias precluding analysis of the entire microbial diversity in soils (WIDMER, 2007).Development of the metabolic fingerprinting method referred to as community-level physiological profiling (CLPP), syn.community-level substrate utilization (CLSU), based on parallel cultivation of soil microorgamisms on a set of different carbon sources have significantly improved the capacity and robustness of cultivation-dependent methods.This method is also a cultural technique, and as such, its use is restricted to culturable microorganisms only (PRESTON-MAFHAM et al., 2002;LIU et al., 2005;WIDMER, 2007).Nevertheless, CLPP is often used as an efficient method capable of revealing the effects of transgenic plants on soil microbial communities (DONEGAN et al., 1995;DI GIOVANNI et al., 1999;DUNFIELD and GERMIDA, 2003;GRIFFITHS et al., 2000;HEUER et al., 2002;TESFAYE et al., 2003;BRUSETTI et al., 2004;FANG et al., 2005;LUPWAYI et al., 2007).
Inherent limitations of culture-based methods have lead soil microbiologists to explore culture independent methods of microbial community analysis.These methods allow to characterize the composition and diversity of soil microbial communities based on the extraction, identification and quantification of molecules from soil that are specific to certain microorganisms or microbial groups (HILL et al., 2000).Such molecules include fatty acids and nucleic acids.Phospholipid fatty acid (PLFA) analysis is based on the analysis of the presence and abundance of specific fatty acids in soil which are indicative of specific groups of microorganisms.A biochemical method fatty acid methyl ester (FAME) analysis provides information on the microbial community composition based on separation and identification of methylated fatty acids extracted directly from soil.These methods are capable of providing a quantitative measure of the viable or potentially viable microbial biomass (LIU et al., 2005).Both, PLFA and FAME are extensively used to assess the effects of transgenic plants on soil microbial communities (DUNFIELD and GERMIDA, 2003;GRIFFITHS et al., 2007).
Advances in molecular biology in last years considerably improved our knowledge of morphological, physiological, biochemical and ecological features of soil microorganisms.Using the DNA based methods specific marker sequences can be analyzed in soil DNA extracts by means of polymerase chain reaction (PCR) amplification (HILL et al., 2000;WIDMER, 2007).Of the various marker genes used to estimate microbial community composition and diversity, the most used are those encoding 16S ribosomal RNA (rRNA) in prokaryotic, and 18S rRNA in eukaryotic microorganisms.A number of molecular-based techniques have been developed to assess the microbial community diversity (HILL et al., 2000;KIRK et al., 2004;WIDMER, 2007).These include DNA guanine plus cytosine content analysis (NUSSLEIN and TIEDJE, 1999), DNA reassociation (TORSVIK et al., 1990), DNA-DNA hybridization (GUO et al., 1997), and different PCR-based methods such as terminal restriction fragment length polymorphism (T-RFLP) (LIU et al, 1997;RASCHE et al., 2006), amplified ribosomal DNA restriction analysis (ARDRA) (LIU et al., 1997;WIDMER et al., 2001;LOTTMANN et al., 2010), denaturing gradient gel electrophoresis (DGGE) (MUYZER et al., 1993;CASTALDINI et al., 2005;COSTA et al., 2006), temperature gradient gel electrophoresis (TGGE) (MUYZER and SMALLA, 1998), single-strand conformation polymorphism (SSCP) (SCHWEIGER and TEBBE, 1998;MIETHLING-GRAFF et al., 2010), and ribosomal intergenic spacer analysis (RISA) (FISHER and TRIPLETT, 1999;BRUSETTI et al., 2004).The RFLP and ARDRA techniques distinguish sequences based on different locations of restriction enzyme recognition sites.DGGE and TGGE rely on differences in the stability of DNA duplex, while SSCP analysis detects differences in secondary structures of single stranded DNA.RISA, on the other hand, resolves length differences of the amplified marker gene sequence (WIDMER, 2007).These methods, used for DNA fingerprint analyses, enables cultivation-independent analysis of microbial community structure and diversity through the detection and characterization of microbial nucleic acid sequences within samples (LIU et al., 2005), however, they do not provide quantitative analyses of microbial groups in soil.Recently, a new DNA-DNA hybridization technique, taxonomic microarray analysis, has been adopted to assess soil microbial diversity (GREENE and VOORDOUW, 2003).This technique has been shown to be able to discriminate and characterize bacterial community composition in related biological samples, offering extensive possibilities for systematic exploration of bacterial diversity in different ecosystems (SANGUIN et al., 2006).

Community level physiological profiling
To understand the role of microbial communities in different environments, it is essential to have knowledge of microbial community function and functional diversity (PRESTON-MAFHAM et al., 2002).Although molecular techniques are now widely used to characterize soil bacterial communities, these techniques provide little information regarding functional properties of microbial communities, for example, on the ability of microbial communities to metabolize specific chemical compounds.To address these functional features of microbial communities, the method of community level physiological profiling (CLPP) using Biolog ® microplates (Biolog, Inc., Hayward, USA) have been developed.GARLAND and MILLS (1991) were the first who introduced the use of commercially available Biolog ® microtitre plate bacterial identification system based on the utilization pattern of 95 different single carbon sources, to assess functional diversity of microorganisms in environmental samples.The Biolog ® system was originally developed for rapid identification of pure bacterial cultures by sole carbon source utilization, using plastic 96 well microtiter plates containing 95 different carbon substrates in separate wells, and no substrate in one well, which is used as control.Among the 95 substrates on Biolog GN and GP plates, there are several groups of chemical compounds, such as carbohydrates, amino acids, carboxylic acids, amines, amides and polymers (Fig. 1).In addition, each well contains a colourless tetrazolium dye.Upon inoculation of plate with a pre-grown isolate, metabolism of the substrate and the production of NADH via cell respiration lead to reduction of colourless tetrazolium to violet formazan (Fig. 2).The colour development is measured colorimetrically at specific absorbance and a data set of optical density (O.D.) values is obtained (GARLAND and MILLS, 1991;PRESTON-MAFHAM et al., 2002).Individual species may be identified by a specific pattern of colour change on the plate, providing an identifiable metabolic fingerprint (PRESTON-MAFHAM et al., 2002).Differences in sole carbon source utilization have been used successfully to distinguish among different bacterial isolates for more than 60 years.At present, the Microbial Identification Database for Biolog Systems (Biolog, Inc.) contains more than 1950 entries for rapid identification of broad spectrum of aerobic and anaerobic bacteria, yeasts and filamentous fungi, mainly of medicinal importance.
The commercially available 96 well Biolog ® microtitre plates were first used to compare metabolic activities of heterotrophic microbial communities from environmental habitats (water, soil and wheat rhizosphere) by GARLAND and MILLS (1991).
Currently several different types of Biolog plates are available to microbial ecologists, all of them containing different substrates appropriate for specific groups of microorganisms.The Biolog GN TM plates were developed for identification of Gramnegative bacteria and contain substrates appropriate for this group of microorganisms (Fig. 1A), whereas Biolog GP TM plates contain carbon sources appropriate for Grampositive bacteria (Fig. 1B).Even though GN and GP plates were successfully used for ecological microbiology research, Biolog ECO TM plates have been developed specifically for ecological applications.Contrary to GN and GP plates, the ECO plates contain only 31 substrates (plus a control well without a substrate) in three replicates on the microtitre plate.These substrates have previously been found to have high relevance to soil bacterial communities, or are known to be included in plant root exudates (PRESTON-MAFHAM et al., 2002).The tetrazolium dye used in GN, GP and ECO plates is not metabolizable by fungi, therefore specific Biolog FF plates have been designed for identification of fungal microorganisms.The FF plates contain different carbon sources from GN, GP, and ECO plates and a modified tetrazolium dye specifically metabolizable solely by fungi.To prevent interference of growth and colour development by bacteria, an appropriate combination of antibiotics is frequently included into FF plates (BUYER et al., 2001).Biolog MT plates, containing a redox dye and no substrate, are also available, which allow researchers to produce customized plates (PRESTON-MAFHAM et al., 2002;STEFANOWITZ, 2006).The use of Biolog microtitre plates enables analyzing microbial communities on both, the individual-as well as community levels (GARLAND, 1997).At the individual-level, the analysis of microbial communities requires the isolation of microorganisms, isolation and characterization of individual isolates, and description of the community based on the relative abundances and diversities of different isolates.The community-level approach, established by GARLAND and MILLS (1991), bypasses the isolation step and the environmental samples are directly inoculated into microplates and the resulting response (colour change pattern) is used to describe differences in microbial communities (GARLAND, 1997).
Community-level Biolog analysis is generally accomplished in five consecutive steps: (1) sample processing to obtain suspension of microorganisms, (2) inoculation of aliquots of microbial suspension into wells of Biolog ® microplates, (3) incubation of plates for 2-8 days in defined culture conditions, (4) regular monitoring the colour development in each well and (5) data processing and statistical analysis of results.
For analyses of pure culture isolates, the samples are prepared from freshly grown cells on a standard enriched medium (GARLAND, 1997;KONOPKA et al., 1998).In contrast, analyses of environmental samples have used a number of different sample processing techniques, including direct inoculation of aquatic samples into microtitre plates (GARLAND and MILLS, 1991), shaking plant roots in a solution to release rhizosphere microorganisms (GARLAND, 1996), and extraction of microbial cells from complex soil matrices using sieving, shaking, blending and sedimentation or centrifugation of samples (HAACK et al., 1999;KONOPKA et al., 1998;DOBLER et al., 2001).For comparisons it is important that samples are of equivalent size, in term of volume and/or weight (PRESTON-MAFHAM et al., 2002).
In most cases the processed sample is diluted prior to use as inoculum.As bacterial cell density in the inoculum affects colour development in Biolog plates (GARLAND and MILLS, 1991;HAACK et al., 1995;GARLAND, 1996), it is very important to determine dilution levels that reduce additional colour development caused by excess utilizable organic matter in the sample (KONOPKA et al., 1998;PRESTON-MAFHAM et al., 2002).It is known, that a minimum number of about 10 8 metabolically active cells per ml in a well is required for observable colour development (HAACK et al., 1995).Therefore, in dilute inocula, the kinetics of colour development will be a function of time and will follow a sigmoidal curve with an initial lag phase, followed by linear growth phase and a final plateau phase.The lag phase represents the time period during which the inoculum grows to a population density of 10 8 cells ml -1 , while during the linear phase the specific metabolic activity of a microorganism on a specific substrate causes accumulation of formazan and colour development.At the plateau phase the production of formazan upon the oxidation of a specific substrate by the activity of a microorganism reaches its maximum yield due to organic substrate depletion.Especially when the goal is identification of pure cultures, it is recommended to adjust all microbial suspensions to a standardized cell density prior to inoculation into Biolog ® plates.Alternatively, with community-level Biolog analysis, adoption of appropriate data analysis can account for different inoculum densities (GARLAND and MILLS, 1991).
Most studies of soil microbial community composition and diversity employing Biolog ® plates use fixed incubation temperatures between 15 and 28°C ( PRESTON-MAFHAM, 2002).Another important variable in Biolog analysis is incubation time, as both the colour intensity in individual wells, and the number of positive wells will increase with incubation time.Too short incubation times (48 h and less) may cause absence of colour development in some wells (especially with those of slow growing microorganisms), while longer incubations (>48 h) will result in more positive responses and reaching the colour saturation levels in some wells (KONOPKA et al., 1998;PRESTON-MAFHAM et al., 2002).To reduce the effects of differential rates of colour development due to inoculum density and inoculation time, appropriate transformations of original raw data are recommended (GARLAND and MILLS, 1991;PRESTON-MAFHAM et al., 2002).
In principle, the Biolog assay is done by colorimetrically measuring tetrazolium dye reduction that is coupled to substrate oxidation.Any microtitre plate reader equipped with an appropriate filter (590 nm) can be used to quantify the colour development in individual wells of plates.The degree to which each of the 95 substrates is oxidized is determined after a fixed incubation period.A positive response is identified as an absorbance or optical density value greater than that occurring in the blank well (HAACK et al. 1995).The number and types of utilized substrates, as well as developed colour intensities, constitute a data set from which the functional diversity of microbial communities involved may be assessed.Colour development in each well reflects species activity and density, as well as the ability of the bacterial community to respond to particular substrates (ZAK et al., 1994).The data obtained by quantifying the colour development in individual wells are usually expressed as individual well optical densities or average well colour development (AWCD) (GARLAND and MILLS, 1991;PRESTON-MAFHAM et al., 2002).The AWCD value for each microplate is obtained by calculating the raw difference between the optical density in each well and that in the control well and then summing all these values and dividing by 95.On the other hand, SIGLER (2004) uses two parameters to describe the microbial community structure: the average metabolic response (AMR), and community metabolic diversity (CMD).AMR describes the average respiration of the C-sources by the microbial community and provides a single metric by which communities can be compared.The AMR is calculated as the average of the mean difference between the O.D. of the C-source-containing wells and the control well.The second parameter, CMD, represents the number of substrates utilized by the microbial community and is analogous to community functional richness.CMD is calculated by summing the number of positive responses (violet-coloured wells) observed following incubation (SIGLER, 2004).
The CLPP generates a rich data set of 95 values for each sample (if GN or GP plates are used) or 31 values in triplicate (if ECO plates are evaluated).Data are corrected against the control well (without a carbon substrate) or the initial reading at time zero, before subjecting to multivariate statistical analysis.Regardless of the chose of absorbance measurement, i.e.net O.D. of individual substrates, AWCD, or parameters received from kinetic analyses, the use of multidimensional statistical analyses is necessary (KONOPKA et al., 1998;STEFANOWICZ, 2006).The most commonly used method is principal component analysis (PCA) of the quantitative colour data, which reduces the number of variables to a few significant principal components.The use of cluster analysis based on the presence or absence of colour in wells (ZAK et al., 1994) is also possible.In kinetic studies, one may process the data by calculating the area under curve for each well O.D. for the entire period of incubation, or by estimation of kinetic parameters by fitting the curve of O.D. versus time to a density dependent logistic growth equation (GUCKERT et al., 1996;LINDSTROM et al, 1998;INSAM and GOBERNA, 2004).
Analysis of microbial community functional diversity using sole carbon source utilization profiles is, despite some limitations (GARLAND, 1997;KONOPKA et al., 1998;PRESTON-MAFHAM et al., 2002), a rapid, reproducible and useful tool to discriminate among bacterial communities from diverse environmental samples.Its strength lies in the low manpower it requires, which enables intensive sampling across temporal and spatial scales, and the reliance of the method on metabolic traits that could lead to functionally relevant characterization of changes in microbial communities (GARLAND, 1997).Although CLPP is a culture based assay, it has been found that non culturable cells also respond to this assay, and therefore this assay seems not to be as biased as the classical culture-based techniques (PRESTON-MAFHAM et al., 2002).

Assessing the effect of transgenic crops on soil microbial communities using CLPP
The CLPP using Biolog ® plates has been used to date for characterizing bacterial communities from a range of environments, including comparisons of rhizosphere bacterial communities of transgenic vs. non-transgenic plants.As the method can provide important insights into ecosystem function and stability, it was used to study the metabolic responses of microbial communities from rhizosphere and bulk soils (SÖDERBERG et al., 2004), from the rhizosphere of different plant species (GRAYSTON et al., 1998;MIETHLING et al., 2003) or from different parts of the rhizosphere along the root (BAUDOIN et al., 2001).The Biolog method is also frequently applied for estimating the influences of different cropping systems (LARKIN and HONEYCUTT, 2006), agronomic procedures such as tillage (GRIFFITHS et al., 2007), soil management (GOMEZ andCORREA, 2008), or factors involved in ecosystem changes (GÖMÖRYOVÁ et al., 2009b) on microbial community physiological profiles.Currently one of the most frequent applications of Biolog ® system is for assessing the impacts of different stressing factors, such as heavy metals (DOBLER et al., 2001;LIAO and XIE, 2007), herbicides (MIJANGOS et al., 2009), explosive elements (ANDERSON et al., 2010) and high salinity and low pH (PANKHURST et al., 2001).DONEGAN et al. (1995) first used the Biolog GN plates to assess changes in soil microorganisms associated with transgenic cotton plants expressing the Bacillus thuringiensis endotoxin (Bt).From that time, the CLPP method using Biolog ® GN, GP or ECO plates proved to be a quick, reproducible and useful method to discriminate among microbial communities associated with the roots of transgenic vs. nontransgenic plants (DI GIOVANNI et al., 1999;SCHMALENBERGER and TEBBE, 2002;TESFAYE et al., 2003;BRUSSETTI et al., 2005;FANG et al., 2005;MULDER et al., 2006;WATRUD et al., 2006;LUPWAYI et al., 2007;TRAVIS et al., 2007 and many others).
Some authors (BRUSSETTI et al., 2005;FANG et al., 2005;GRIFFITHS et al., 2007) could not find any statistically significant differences in functional diversities of rhizosphere microorganisms between transgenic and non-transgenic plants using Biolog ® microplates.In these studies, whether in greenhouse or field conditions, soil texture, crop type and pest management regime, rather than cultivation of transgenic plants affected the rhizosphere microbial communities.Other authors reported very few changes in functional diversity of rhizosphere soil bacteria associated with growing GM crops (LUPWAYI et al., 2007), or significant shifts in the carbon utilization patterns of culturable microbial communities in the rhizospheres of transgenic plants, or soils amended with residues from transgenic plants (DI GIOVANNI et al., 1999;TESFAYE et al., 2003;FANG et al., 2007;TRAVIS et al., 2007).At least some of these differences in carbon source utilization patterns may be explained by the possible effects of site of insertion or simply somaclonal variation on the availability of endogenous nutrients in the soil mix on microbial populations (WATRUD et al., 2006). FANG et al. (2007) hypothesized, that amendment of soils with Bt corn residues may affect selected activities of soil bacteria carried by specific enzymes.Altered composition of root exudates of transgenic plants may also induce a different community of rhizosphere microorganisms.
In general, however, if shifts in bacterial communities due to cultivation of transgenic plants were observed, these were similar to those observed when nontransgenic cultivars are compared.In comparison with other factors, the impact of the genetic modification of the plant on soil microbial communities was usually minor and transient, or comparable to variations due to plant genotype, plant physiological and developmental stage, soil type, agricultural practice used and pathogen exposure.
Nevertheless, despite the research performed up to now, it is not yet clear whether GM plants or their products exert any ecological effect on the microbiota and microbial processes in soil.To elucidate this question, more studies on the impact of transgenic plants on soil microbial communities is needed, preferably employing the polyphasic approach using different methods of soil microbial communities analysis, including plate count, biochemical and molecular methods.

Conclusions
Community level physiological profiling is a quick and easy method of investigating the functional diversity of microbial communities from a range of environmental habitats.The method, which employs Biolog ® microplates containing 95 different carbon sources, are gaining increasing importance not only in general soil ecology, but also is increasingly used as a method which is able to provide functional information on the microbial community structure and diversity in the rhizosphere of transgenic plants.The simplicity, speed, and low cost of the method compared with other approaches are very attractive to microbial ecologists and other microbiologists.However, the researcher should keep in mind, that to fully exploit its potential the technique requires very careful data acquisition, appropriate statistical analysis and cautious interpretation of results.