ABSTRACT
Molecular diagnosis of SARS-CoV-2 in developing countries is still a big challenge. The reference standard, RT-qPCR, recommended by WHO, is not widely available, difficulting early identification of cases. Furthermore, the transport logistic between the sample collection point and the laboratory facilities can alter the samples, producing false negative results. RT-LAMP is a cheaper, simpler molecular technique that can be an interesting alternative to be offered in hospital laboratories. We present the evaluation of a RT-LAMP for diagnosis of SARS-CoV-2 in two steps: the laboratory standardization and the clinical validation, comparing it with the standard RT-qPCR. In the standardization phase, limit of detection and robustness values were obtained using RNA from a Peruvian SARS-CoV-2 strain. It presented 100% agreement between triplicates (RT-LAMP agreement with all RT-qPCR reactions that presented Ct [≤] 30) and robustness (RT-LAMP successful reactions with 80% reaction volume and 50% primer concentration). 384 nasal and pharyngeal swabs collected from symptomatic patients and stored in the INS biobank were tested and we obtained 98.75%, 87.41%, 97.65% and 92.96% for specificity, sensitivity, positive predictive value and negative predictive values respectively. Then, 383 samples from symptomatic patients with less than 15 days of disease, were tested both with the RT-LAMP and with the RT-qPCR, obtaining e 98.8%, 88.1%, 97.7% y 93.3% of specificity, sensitivity, positive predictive value and negative predictive values respectively. The laboratory standardization and the clinical validation presented the same value by Kappa-Cohen index (0.88) indicating an almost perfect agreement between RT-LAMP and RT-qPCR for molecular detection of SARS-CoV-2. We conclude that this RT-LAMP protocol presented high diagnostic performance values and can be an effective alternative for COVID-19 molecular diagnosis in hospitals, contributing to early diagnosis and reducing the spread of virus transmission in the Peruvian population.
ABSTRACT
The dissemination of cases of the new SAR-COV-2 coronavirus represents a serious public health problem for Latin America and Peru. For this reason, it is important to characterize the genome of the isolates that circulate in Latin America. To characterize the complete genome of first samples of the virus circulating in Peru, we amplified seven overlapping segments of the viral genome by RT-PCR and sequenced using Miseq platform. The results indicate that the genomes of the Peruvian SARS-COV-2 samples belong to the genetic groups G and S. Likewise, a phylogenetic and MST analysis of the isolates confirm the introduction of multiple isolates from Europe and Asia that, after border closing, were transmitted locally in the capital and same regions of the country. These Peruvian samples (56%) grouped into two clusters inside G clade and share B.1.1.1 lineage. The characterization of these isolates must be considered for the use and design of diagnostic tools, and effective treatment and vaccine formulations.
ABSTRACT
Influenza caused by A(H1N1)pdm09 is a public health issue with severe conditions in vulnerable populations leading to death. Therefore, it is of interest to characterize and monitor influenza A(H1N1)pdm09 genotypes using High Resolution Melting (HRM), a post PCR molecular biology method. We used HRM analysis (using RotorGene Q thermocycler) to characterize A(H1N1)pdm09 genotypes from several places of Peru. RNA was purified from nasal and pharyngeal swab samples referred to LRNVR-INS, synthesized cDNA, and then the hemagglutinin gene and matrix fragment were amplified. Thus, 287 samples positive for influenza A(H1N1)pdm09 were identified across Peru where places like Lima, Piura, and Arequipa documented highest number of cases. The HRM data was analyzed and results showed different profiles which were further grouped into four genotypes for the HA (A, B, C, D) and 3 for the M (a, b, c) genes. We also report ten genotypes (I-X) of virus using combined HA (hemagglutinin) and M gene profiles representing a national geography. The prevalent genotypes are I and II with a frequency of 35.89% (103) and 29.27% (84), respectively linking with severe acute respiratory infection.
