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Infiltration is important to modeling the overland transport of microorganisms in environmental waters.
Detection of signature lipid biomarkers is an effective means of detecting general groupings of microorganisms in environmental matrices [43].
The application of molecular methods for rapid detection of specific microorganisms in environmental samples would be valuable as a supporting tool for the evaluation of oil quality in production reservoirs.
Metagenomic sequencing facilitates the study of a large number of microorganisms in environmental samples [ 1].
Although great progress has been made in the development of bioinformatics software and tools, the complete reconstruction of the entire genome of microorganisms in environmental samples, in particular those from complex environments, remains difficult.
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In addition, more than 1000 ribosomal RNA sequences from both prokaryotic and eukaryotic microorganisms present in environmental water and soil samples were included into the design process to avoid cross-reactivity with rRNA.
One such strategy is by a culture-independent method that analyzes DNA extracted from all the microorganisms present in environmental samples (Riesenfeld et al. 2004).
In 1998, Handelsman et al. first put forward the concept of the "metagenome" (Handelsman et al. 1998), and defined it as the genes and genomes of all of the microorganisms in an environmental sample.
In the last decade molecular cultivation-independent techniques have allowed the access to yet uncultivated microorganisms in several environmental niches (Handelsman 2004; Sleator et al. 2008), providing significant insights into bacterial communities in wastewater treatment processes (Sercu et al. 2006; Miura et al. 2007; Zang et al. 2008; Silva et al. 2010a; Silva et al. 2010b).
We conclude by recommending DNA extraction methods towards an optimised real-time PCR assay for quantifying M. bovis and similar hard to lyse microorganisms in complex environmental substrates.
Metabolic flux patterns of microorganisms in different environmental conditions may be best described by different optimality principles [ 32].
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