Detection of HCV persistent infections in the dental pulp: A novel approach for the detection of past and ancient infections

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Abstract

The dental pulp is a sterile highly vascularized tissue and has been commonly used as a biological material to detect the genome of infectious agents that reach the dental tissue. Indeed, the pulp is also used to reveal past and ancient infections in the field of paleomicrobiology. The present study aimed to detect the presence of Hepatitis C virus (HCV) in a small community (approximately 400 inhabitants) in the Amazon region of Brazil (Nossa Senhora do Perpetuo Socorro, Vizeu, Para, Brazil) and standardize a technique for the detection of the virus in the dental pulp. Serum samples were collected from 48 patients whose teeth were clinically recommended for surgical extraction. The group comprised an equal number of males and females, mostly agriculture workers and housewives, respectively. The majority (64.6%) received less than one minimum wage and were ill educated (less than four years of school years). An enzyme immune assay was used to detect antibodies to HCV and the 9 (18.8%) positive samples were submitted to nucleic acid extraction in the blood (using the EXTRAzol) and the pulp (QIAamp DNA Micro Kit e kit RNeasy Plus Micro). The pulp was removed using a modified protocol without the use of liquid nitrogen. Nucleic acid was found in 8 of the dental pulp, but in 7 of the blood samples. Sequencing of one of the samples showed the presence of genotype 1. Conclusions: A novel simplified methodology for the extraction and amplification of HCV nucleic acid was successful to detect the presence of persistent infections of the virus within the dental pulp tissue. The protocol may be helpful to detect past and ancient infections and to better understand the natural history of HCV.

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Siravenha, L. G., Siravenha, L. Q., Madeira, L. D. P., Oliveira-Filho, A. B., Machado, L. F. A., Feitosa, R. N. M., … Ishak, R. (2016). Detection of HCV persistent infections in the dental pulp: A novel approach for the detection of past and ancient infections. PLoS ONE, 11(10). https://doi.org/10.1371/journal.pone.0165272

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