Phylogenetics analysis of TP53 gene in humans and its use in biosensors for breast cancer diagnosis

Abstract

Biosensors are small devices that use biological reactions to detect target analytes. Such devices combine a biological component with a physical transducer, which converts bio-recognition processes into measurable signals. Its use brings a number of advantages, as they are highly sensitive and selective, relatively easy in terms of development, as well as accessible and ready to use. Biosensors can be of direct detection, using a non-catalytic ligand, such as cell receptors and antibodies, or indirect detection, in which there is the use of fluorescently marked antibodies or catalytic elements, such as enzymes. They also appear as bio-affinity devices, depending only on the selective binding of the target analyte to the ligative attached to the surface (e.g., oligonucleotide probe). The objectives were to evaluate the levels of genetic diversity existing in fragments of the TP53 gene deposited in molecular databases and to study its viability as a biosensor in the detection of breast cancer. The methodology used was to recover and analyze 301 sequences of a fragment of the TP53 gene of humans from GENBANK, which, after being aligned with the MEGA software version 6.06, were tested for the phylogenetic signal using TREE-PUZZLE 5.2. Trees of maximum likelihood were generated through PAUP version 4.0b10 and the consistency of the branches was verified with the bootstrap test with 1000 pseudo-replications. After aligning, 783 of the 791 sites remained conserved. The maximum likelihood had a slight manifestation since the gamma distribution used 05 categories + G for the evolutionary rates between sites with (0.90 0.96, 1.00, 1.04 and 1.10 substitutions per site). To estimate ML values, a tree topology was automatically computed with a maximum Log of −1058,195 for this calculation. All positions containing missing gaps or data were deleted, leaving a total of 755 sites in the final dataset. The evolutionary history was represented by consensus trees generated by 500 replications, which according to neighbor-join and BioNJ algorithms set up a matrix with minimal distances between haplotypes, corroborating the high degree of conservation for the TP53 gene. GENE TP53 seems to be a strong candidate in the construction of Biosensors for breast cancer diagnosis in human populations.