Background: Mycobacterium tuberculosis’ rapid detection is still a formidable challenge to have control over the lethal disease. New diagnostic methods such as LED fluorescence microscopy, Genexpert, Interferon Gamma Release Assay (IGRA) are limited on efficacy spectrum owing to their high cost, time-intensive and laborious nature, in addition their low sensitivity hinders their robustness and portability. Electroanalytical methods are now being considered as an excellent alternative, being currently employed for efficient detection of the analytes with the potential of being portable. This report suggests label-free electrochemical detection of Mycobacterium tuberculosis (Mtb) via its marker, insertion sequence (IS6110). Methods: In this pursuit, graphene oxide-chitosan nanocomposite (GO-CHI), a biocompatible matrix, having a large electroactive area with an overall positively charged surface, is fabricated and characterized. The obtained GO-CHI nanocomposite is then immobilized on the ITO surface to form a positively functionalized electrochemical sensor for the detection of Mtb. DNA probe, specific for the IS6110, was electrostatically anchored on a positively charged electrode surface and the resistance of charge transfer was investigated for the sensitive and specific (complementary vs non-complementary) detection of Mtb by cyclic voltammetry and differential pulse voltammetry techniques. Results: The cyclic voltammetry was found to be diffusion controlled facilitating the absorption of analyte on the electrode surface. The label-free “genosensor” was found to detect a hybridization efficiency with a limit of detection of 3.4 pM, and correlation coefficient R²=0.99 when analysed over a range of concentrations of DNA from 7.86 pM to 94.3pM. The genosensor was also able to detect target DNA from raw sputum samples of clinical isolates without DNA purification. Conclusion: This electrochemical genosensor provides high sensitivity and specificity; thus offering a promising platform for clinical diagnosis of TB and other infectious diseases in general.

Cyclin-dependent kinase inhibitor 2 A (CDKN2A) gene belongs to the cyclin-dependent kinase family that code for two transcripts (p16INK4A and p14ARF), both work as tumor suppressors proteins. The mutation that occurs in the p14ARF protein can lead to different types of cancers. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that can lead to different types of diseases. In this study, we applied the computational strategy on human p14ARF protein to identify the potential deleterious nsSNPs and check their impact on the structure, function, and protein stability. We applied more than ten prediction tools to screen the retrieved 288 nsSNPs, consequently extracting four deleterious nsSNPs i.e., rs139725688 (R10G), rs139725688 (R21W), rs374360796 (F23L) and rs747717236 (L124R). Homology modeling, conservation and conformational analysis of mutant models were performed to examine the divergence of these variants from the native p14ARF structure. All-atom molecular dynamics simulation revealed a significant impact of these mutations on protein stability, compactness, globularity, solvent accessibility and secondary structure elements. Protein-protein interactions indicated that p14ARF operates as a hub linking clusters of different proteins and that changes in p14ARF may result in the disassociation of numerous signal cascades. Our current study is the first survey of computational analysis on p14ARF protein that determines the association of these nsSNPs with the altered function of p14ARF protein and leads to the development of various types of cancers. This research proposes the described functional SNPs as possible targets for proteomic investigations, diagnostic procedures, and treatments. Communicated by Ramaswamy H. Sarma.