Cultural dependent methods for deciphering microbial communities
Authors: Ajay Kumar*, Aman Jaiswal, Deepak Kumar Koli, Swati Sagar
Division of Microbiology, ICAR-Indian Agricultural Research Institute, New Delhi (India) 110 012


The concerted activity of interacting microbes was critical to the development of environmental conditions on Earth that led to the evolution of multicellular organisms, and their catalysis of biogeochemical reactions has a central function in sustaining conditions that are compatible with a robust and diverse biosphere. At a time in which human beings are concerned with historically rapid global change, understanding the control mechanisms whereby microbial communities determine ecosystem function is particularly relevant. Current ecosystem simulation models do not include microbial composition, and often neither explicitly consider the effects of environmental conditions on microbial activities nor the interactions between diverse microbial processes. As microbial communities are of primary importance in biogeochemical transformations, a deeper understanding of their dynamics will be critical to refined predictions regarding how the biosphere modulates and responds to future environmental conditions. At a more fundamental level, understanding natural microbial communities will deepen our understanding of how ecosystems function. In turn, this understanding may elucidate novel interaction mechanisms among multiple species at the single cell level. There are many cultural dependent method which are very robust and popular to concurrently study both the identity and the function of complex microbial communities. However, effective application requires a clear delineation of what is meant by a ‘microbial community’ and identification of important characteristics specific to community ecology.

What is a microbial community?

The concept of community ecology arose in plant and animal ecology. Communities are defined as multi-species assemblages, in which organisms live together in a contiguous environment and interact with each other. This discipline seeks to analyze how biological assemblages are structured, what are their functional interactions and how community structure changes in space and time. Clements (1916) viewed the community as a ‘supra-organism’, which had a well-defined level of organization with tight interactions among organisms that comprise a causal system and gives rise to emergent properties. Many species co-occur in a habitat because they tolerate similar physical and chemical conditions and do not necessarily interact with each other. The practical delineation of ‘community’ may then reflect the interests of the ecologist rather than any inherent characteristics. The problems in rigorously defining community are heightened in the case of microbial ecology. In particular, delineating a ‘contiguous environment’ and the meaning of ‘interact’ may be problematic. Microorganisms react to and in turn influence conditions in their microenvironments, which usually have length scales of microns rather than millimetres, except in cases of multicellular structures such as fungal hyphae. To increase rigor in the meaning of ‘microbial community,’ it would be valuable for microbial ecologists to explicitly articulate their meaning for each specific research effort. Microbes strongly interacting with each other in a microenvironment comprise a local community. However, the distribution of organisms and physicochemical properties within most habitats is patchy; even in apparently well-mixed oligotrophic planktonic habitats, nutrient-rich foci of marine snow may occur. The patchwork of local communities has been termed as a phenomenological community for the purposes of microbial ecology, this would represent a range of macroscale habitats delineated by the investigator, in which the assemblage of microbes persists in spatial association. The phenomenological community could be constrained to a smaller number of populations by defining an indexical community—the set of populations that directly interact with a key population or defined biogeochemical process, together with other local populations that affect the directly interacting populations. Recent developments in community ecology have begun to recognize that the biological assemblage cannot be defined without reference to its abiotic environment. An appreciation for the tight interrelationship between microbes and their microscale physical and chemical environments is particularly important for delineation of microbial communities. In this spirit, it may be instructive to define microbial communities not from a macroscale perspective (for example aquatic vs terrestrial habitats), but rather based on a bottom up analysis of the physicochemical characteristics of the microenvironment, with upscaling to a spatial domain (the ‘contiguous environment’) defined by the region over which substantial direct interactions or indirect chemical interactions are occurring. Each has particular characteristics that define important selective forces in that habitat, but which also impact the spatial scale over which microbial interactions occur.

Significance of Analysis of Microbial Community

  1. Diversity of micro-organism in soil.
  2. To get better strain.
  3. Change in community with environmental change.
  4. Dynamics of biogeological Cycle.
  5. Diagnosis of different type of microorganism in tissues.
  6. Bioremediation of waste pollutants.
  7. To study about interaction among organisms.

  8. Culture Dependent Method

    Plate counts

    Traditionally, diversity was assessed using selective plating and direct viable counts. These methods are fast, inexpensive and can provide information on the active, heterotrophic component of the population. Limitations include the difficulty in dislodging bacteria or spores from soil particles or biofilms, growth medium selections, growth conditions (temperature, pH, light), the in- ability to culture a large number of bacterial and fungal species with current techniques and the potential for colony – colony inhibition or of colony spreading .In addition, plate growth favours those microorganisms with fast growth rates and those fungi that produce large numbers of spores. All of these limitations can influence the apparent diversity of the microbial community.

    Most Probable Number

    MPN test is a method to estimate the concentration of viable microorganisms in a sample by means of replicate liquid broth growth in ten-fold dilutions and is particularly useful with samples that contain particulate rnaterial that interferes with plate count enumeration methods. The basic concept to the MPN method is similar to the fraction negative method of D-value determination. Nutrient broth will support growth of organisms and turn turbid.

    This provides information particularly when low numbers of organisms are present in the sample. The accuracy can be greatly increased by diluting the inoculum and then comparing the recoveries of all tubes in the dilution series. This is the basis of the MPN method. The method offers real opportunities as an enumeration tool. It can also be employed for semi-quantitative estimation of growth-promotion capability of liquid media and in estimation of precision for alternate microbiological methods with a simple modification.


    A biochemical method that does not rely on culturing of microorganisms is fatty acid methyl ester (FAME) analysis. This method provides information on the microbial community composition based on groupings of fatty acids. Fatty acids make up a relatively constant proportion of the cell biomass and signature fatty acids exist that can differentiate major taxonomic groups within a community. Therefore, a change in the fatty acid profile would represent a change in the microbial population. It has been used to study microbial community composition and population changes due to chemical contaminants and agricultural practices. For FAME analysis, fatty acids are extracted directly from soil, methylated and analyzed by gas chromatography. FAME profiles of different soils can be compared using multivariate analysis. This method will detect changes in the composition of the bacterial and/or fungal community, as well as enable one to follow signature fatty acids of different groups of micro- organisms. Bossio et al. (1998) used phospholipid fatty acid profiles to detect changes in microbial communities consistent with different farming practices. But when these researchers calculated the Shannon diversity index based on PLFA relative abundance, no difference was detected. This could be because although the community was structurally different, diversity was not, or it could represent some problems with using fatty acid profiles to measure diversity.

    But FAME method has community has many limitations. It may obscure detection of minor species in the population. Cellular fatty acid composition can be influenced by factors such as temperature and nutrition, and the possibility exists that other organisms can confound the FAME profiles. In addition, individual fatty acids cannot be used to represent specific species because individuals can have numerous fatty acids and the same fatty acids can occur in more than one species.


    It is a technique in which a commercially available 96-well microtitre plate is used to assess the potential functional diversity of the bacterial population through sole source carbon utilization (SSCU) patterns. Gram-negative (GN) and gram-positive (GP) plates are available and each contains 95 different carbon sources and one control well without a substrate. GN and GP plates were developed originally for characterization of clinical bacterial isolates and not for community analysis. Subsequently, Biolog introduced an Eco-plate containing 3 replicates of 31 different environmentally relevant carbon sources and one control well per replicate. Carbon sources not found in GN plates include D-cellobiose, D- xylose, D-malic acid, L-arginine, 2-hydroxybenzoic acid and 4-hydrobenzoic acid.

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