Paper
10 February 2007 Genomic signal analysis of Mycobacterium tuberculosis
Author Affiliations +
Abstract
As previously shown the conversion of nucleotide sequences into digital signals offers the possibility to apply signal processing methods for the analysis of genomic data. Genomic Signal Analysis (GSA) has been used to analyze large scale features of DNA sequences, at the scale of whole chromosomes, including both coding and non-coding regions. The striking regularities of genomic signals reveal restrictions in the way nucleotides and pairs of nucleotides are distributed along nucleotide sequences. Structurally, a chromosome appears to be less of a "plain text", corresponding to certain semantic and grammar rules, but more of a "poem", satisfying additional symmetry restrictions that evoke the "rhythm" and "rhyme". Recurrent patterns in nucleotide sequences are reflected in simple mathematical regularities observed in genomic signals. GSA has also been used to track pathogen variability, especially concerning their resistance to drugs. Previous work has been dedicated to the study of HIV-1, Clade F and Avian Flu. The present paper applies GSA methodology to study Mycobacterium tuberculosis (MT) rpoB gene variability, relevant to its resistance to antibiotics. Isolates from 50 Romanian patients have been studied both by rapid LightCycler PCR and by sequencing of a segment of 190-250 nucleotides covering the region of interest. The variability is caused by SNPs occurring at specific sites along the gene strand, as well as by inclusions. Because of the mentioned symmetry restrictions, the GS variations tend to compensate. An important result is that MT can act as a vector for HIV virus, which is able to retrotranscribe its specific genes both into human and MT genomes.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul Dan Cristea, Dorina Banica, and Rodica Tuduce "Genomic signal analysis of Mycobacterium tuberculosis ", Proc. SPIE 6447, Nanoscale Imaging, Spectroscopy, Sensing, and Actuation for Biomedical Applications IV, 64470C (10 February 2007); https://doi.org/10.1117/12.724917
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Cited by 20 scholarly publications.
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KEYWORDS
Resistance

Pathogens

Signal analysis

Data conversion

Current controlled current source

Digital signal processing

Image segmentation

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