Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00253-013-4943-5
Title: Bioinformatics and molecular biology for the quantification of closely related bacteria
Authors: Nagarajan, K.
Loh, K.-C. 
Swarup, S. 
Keywords: Bioinformatics
Marker sequence
Mixed culture analysis
Quantitative real-time PCR
Issue Date: Jul-2013
Source: Nagarajan, K., Loh, K.-C., Swarup, S. (2013-07). Bioinformatics and molecular biology for the quantification of closely related bacteria. Applied Microbiology and Biotechnology 97 (14) : 6489-6502. ScholarBank@NUS Repository. https://doi.org/10.1007/s00253-013-4943-5
Abstract: Molecular biological methods for mixed culture analysis outshine conventional culture-based techniques in terms of better sensitivity and reliability. The majority of these methods exploit the 16S rRNA sequences of the community DNA, which often fall short for the analysis of closely related microorganisms. This research details the development and validation of a comprehensive methodology to differentiate and quantitatively characterize two Pseudomonas species in a mixed culture. A bioinformatics tool based on whole-genome polymorphism comparison was used to identify marker sequences to differentiate the two bacteria using quantitative real-time PCR. The quantification of the two species was achieved through a correlation of the genomic DNA versus cell number (genomic DNA purification) and threshold cycle number versus genomic DNA (real-time PCR). Several factors including the limitation of genomic DNA purification, effects of substrate concentrations and growth phase on cellular DNA, and choice of simplex or duplex reaction for real-time PCR were considered and evaluated. The developed method was experimentally validated against synthetically constructed consortia. © 2013 Springer-Verlag Berlin Heidelberg.
Source Title: Applied Microbiology and Biotechnology
URI: http://scholarbank.nus.edu.sg/handle/10635/63540
ISSN: 01757598
DOI: 10.1007/s00253-013-4943-5
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