Abstract
Microbial significance in human lives has been gaining importance due to their biotechnological applications and ability to cause diseases. The use of antibiotics to kill them has proved counterproductive. Bacterial resistance to antibiotics has caused huge economic losses. Many bacteria have turned highly drug resistant due to modifications in their genetic reservoirs. It has been recognized that bacteria had another mechanism to circumvent the impact of antibiotics. Bacteria causing infectious diseases form biofilm at high cell density. Biofilm protects bacteria from even extremely high dosages of antibiotics. Under all these conditions, the most important aspect to initiate treatment is to diagnose the organism responsible for the disease. Bacterial identification through the rrs gene sequence has been the most prevalent and effective approach. The trouble arises in two main situations: (1) high similarity among gene sequences and (2) the presence of multiple copies of rrs gene within a genome. An obvious solution is to employ other highly conserved genes (housekeeping genes), which is uneconomical in terms of time and money. However, a few studies have revealed the presence of latent features within rrs. A set of genomic tools allowed identification of organisms up to the species level from their previous status of genus level identity. The most interesting aspect is that the strategy can be extended to all genes from all kinds of organisms.
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Acknowledgments
We are thankful to the Director of CSIR-Institute of Genomics and Integrative Biology (IGIB) and CSIR project GENESIS (BSC0121) for providing the necessary funds, facilities, and moral support. Authors are also thankful to the Academy of Scientific and Innovative Research (AcSIR), New Delhi.
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Kalia, V.C., Kumar, R., Koul, S. (2017). In Silico Analytical Tools for Phylogenetic and Functional Bacterial Genomics. In: Arora, G., Sajid, A., Kalia, V. (eds) Drug Resistance in Bacteria, Fungi, Malaria, and Cancer. Springer, Cham. https://doi.org/10.1007/978-3-319-48683-3_15
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