Predictive Microbiology in the Remediation Efforts | OMICS International
ISSN: 2155-6199
Journal of Bioremediation & Biodegradation

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Predictive Microbiology in the Remediation Efforts

B. Ramakrishnan*
Division of Microbiology, Indian Agricultural Research Institute, New Delhi 110012, India
Corresponding Author : B. Ramakrishnan
Division of Microbiology
Indian Agricultural Research Institute
New Delhi 110012, India
Tel: +911125847649
Fax: +911125847649
E-mail: [email protected]; [email protected]
Received June 25, 2012; Accepted June 25, 2012; Published June 27, 2012
Citation: Ramakrishnan B (2012) Predictive Microbiology in the Remediation Efforts. J Bioremed Biodeg 3:e117. doi: 10.4172/2155-6199.1000e117
Copyright: © 2012 Ramakrishnan B. This is an open-a ccess article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Numerical dominance and ubiquitous nature mark microbial supremacy over other living organisms in the Earth. Their diversity and more importantly, their functional capabilities even in the absence of oxygen and other extreme conditions show their tenacity for survival over Eons, their abilities to obtain carbon and other nutrients from a widerange of sources, and their multifarious modes of energy generation. Probably, they are more diverse than the chemical substances present in the terrestrial environment. Many chemical substances attain the status of pollutants due to their deleterious effects, especially to humans and they too are utilized by microorganisms for their energy and growth. The constant creation of man-made pollutants is primarily due to population explosion, human struggle against other dangerous and/or competitive species, and the quest for improving the quality of life. Even otherwise, the terrestrial environments receive pollutant analogues from geothermal and volcanic activities, comets, and space almost daily. There is always a constant struggle among different life-forms to modify their polluted environments and to adapt to the conditions on which they can survive.
Hot-spots of man-made chemical pollutants with structural elements or substituents which seldom occur in nature can deprive the diversity of life-forms including those of microorganisms. Many of these chemical substances which are considered to accrue benefits to humans are slowly posing challenges to the natural competence of microorganisms to acquire degradative abilities through evolutionary processes such as mutation, recombination, and gene transfer. Even then, the microbial degradation of chemical pollutants will continue to be one of the chief mechanisms in protecting the environment. Without transferring to another site or to the future, pollution has to be dealt with microbial remediation, with least reliance on the costintensive physical and chemical methods. What is important now is to understand how the pollutant-degrading microorganisms and other organisms interact with each other and under which physical and chemical conditions their performances peak, in order to make use of them for attenuating the polluted environments.
Numerous studies have been attempted to isolate a single organism capable of degrading a particular pollutant or a mixture of pollutants. Better understanding on the metabolic and regulatory interactions within a single organism during the biodegradation process is continually gained with the use of new molecular ‘omics’ tools. The central metabolism of the global biodegradation networks involves transferases, isomerases, hydrolases and ligases [1]. The formalization and categorization of many biodegradation reactions and pathways have led to the development of databases and tools such as the University of Minnesota Biocatalysis/Biodegradation Database (UMBBD) [2] and ‘Metarouter’ [3]. They provide the predictability of a likely metabolic pathway for any given compound. Depending on the environmental fate defined, the biodegradability or recalcitrant nature of chemical pollutant can be predicted.
Because microorganisms are present as communities in the nature, rather than a population of a single isolate, metabolic cooperation exists among the members with in the microbial community for transferring the chemical substances and products during degradation. Future efforts have to emphasize on predictability on the environmental fate of pollutant(s), rather than on isolating a capable microorganism. Stephens et al. [4] provided evidence that the responses to stress show cell to cell variability. Whether polluted or not, functional stability is achieved due to large number of microorganisms in the natural ecosystems. Moving beyond the ‘complete system’ of a single cell, the complexities of the ‘system’ involving multiple biotic and abiotic components require assessment methods, especially at the microbial community level for pollutant degradation. The systems biology approach to microbial communities requires the application of new theories such as the network theory [5], which will be useful in understanding the mechanisms involved in their organization and predicting their responses to different stimuli. The responses to stimuli and the activation of adaptive pathways depend on the amount of available energy. Induction of energy consuming mechanism and the subsequent depletion of energy determine the establishment of microbial communities. The theoretical framework for understanding the peak performance of the pollutant-degrading microorganisms within the community requires the knowledge on ‘ecological stoichiometry’ which is concerned with supply of nutrients and elemental stoichiometry relative to the nutritional demands of microbial members within a community.
Mapping of complex networks and identification of microbial responses to different environmental stimuli require both knowledge databases and computational tools including modelling [6]. Although the deterministic models are useful in predicting microbial growth or decline as an outcome at particular time point, the probability (stochastic) approaches are required when the microorganisms are under survival mode rather than growth mode. The basic premise of predictive microbiology is that the responses of microbial communities to environmental factors and stress events are reproducible. Due to the failure from not considering the interaction effect of other biota, critical levels of nutrients and/or other pollutants in a mixture on the growth and activities of the pollutant-degrading microorganisms, some models may suffer from the ‘completeness error.’ When the estimates of environmental influences on microbial responses in the kinetic (deterministic and/or stochastic) models on pollutant degradation from different sources are comparable, predictability can increase. Only then, they can form the scientific basis for predictive microbiology in formulating remediation plans, for identification of the nature, and specifying limits for pollutant degradation.

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