A digital signal processing-based bioinformatics approach to identifying the origins of HIV-1 non B subtypes infecting US Army personnel serving abroad
Type: Research Article
Journal: Current HIV Res
Date: Jun 2013
PMID: 23931160
How to cite: Nwankwo N. A digital signal processing-based bioinformatics approach to identifying the origins of HIV-1 non B subtypes infecting US Army personnel serving abroad. Curr HIV Res. 2013 Jun;11(4):271-80. doi: 10.2174/1570162x113119990046. PMID: 23931160.
HIV viruses have remained one of the most recalcitrant disease-causing proteins. Apart from inherent capacity to remain latent, it is also quick to mutate and resist Anti-Retroviral Treatment (ART). Additionally, HIV diversity and cross-typing were found to hamper the development of interventions such as medications and vaccines. Traveling hence, the spread of HIV/AIDS, has also been made easy by the availability of faster aircrafts. To help mitigate against the spread of HIV/AIDS, it became necessary to quickly identify and accurately classify each isolate.
Already, some isolates including the non-B 98US_MSC5007 and 98US_MSC5016 isolates were misclassified. These two isolates were found amongst American soldiers and because their origin was not known, the were classified as American isolates. However, American isolates are categorized as B. To determine the evolutionary roadmap of these viruses, we employed a phenomenon that has demonstrated common originality in human and chimpanzee.
Both human and chimpanzee are known to share originality and several biological characteristics. Our digital signal (FFT-based) assessment of the binding interaction of the CD4 belonging to both human and chimpanzee revealed a common highest interaction at position 68 (frequency position 0.141). This same digital signal (FFT)-based technique was employed on the two non-B HIV isolates (98US_MSC5007 and 98US_MSC5016) isolated from the US soldiers serving abroad. It was revealed that 98US_MSC5007 shared highest amplitude with the Nigerian isolate, and 98USC_MSC5016 with a Zairean counterpart.
Our Finding can be accessed using the Identification ID, PMID: 23931160