Alberto-Antony Venancio-Landeros

Dr. Alberto-Antony Venancio-Landeros

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Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 July 2023 in Research in Microbiology
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Journal Article
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LZLina Angélica Zermeño-Cervantes
Lina Angélica Zermeño-Cervantes
SDSergio Francisco Martínez Díaz
Sergio Francisco Martínez Díaz
AVAlberto-Antony Venancio-Landeros
Alberto-Antony Venancio-Landeros
CCCesar Cardona-Felix
Cesar Cardona-Felix

Verified
Journal Article
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José Francisco Muñoz-ValleJosé Francisco Muñoz-Valle
José Francisco Muñoz-Valle
AVAlberto-Antony Venancio-Landeros
Alberto-Antony Venancio-Landeros
RSRocío Sánchez-Sánchez
Rocío Sánchez-Sánchez
KRKaren Reyes-Díaz
Karen Reyes-Díaz
BOByron Galindo Ornelas
Byron Galindo Ornelas
OGOctavio-Patricio García-González
Octavio-Patricio García-González
SARS-CoV-2 variants surveillance is a worldwide task that has been approached with techniques such as Next Generation Sequencing (NGS); however, this technology is not widely available in developing countries because of the lack of equipment and limited funding in science. An option is to deploy a RT-qPCR screening test which aids in the analysis of a higher number of samples, in a shorter time and at a lower cost. In this study, variants present in samples positive for SARS-CoV-2 were identified with a RT-qPCR mutation screening kit and were later confirmed by NGS. A sample with an abnormal result was found with the screening test, suggesting the simultaneous presence of two viral populations with different mutations. The DRAGEN Lineage analysis identified the Delta variant, but there was no information about the other three mutations previously detected. When the sequenced data was deeply analyzed, there were reads with differential mutation patterns, that could be identified and classified in terms of relative abundance, whereas only the dominant population was reported by DRAGEN software. Since most of the software developed to analyze SARS-CoV-2 sequences was aimed at obtaining the consensus sequence quickly, the information about viral populations within a sample is scarce. Here, we present a faster and deeper SARS-CoV-2 surveillance method, from RT-qPCR screening to NGS analysis.

1 January 2024 in Biology Methods and Protocols
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Journal Article
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JVJoel Armando Vazquez-Pérez
Joel Armando Vazquez-Pérez
EMEber Martínez-Alvarado
Eber Martínez-Alvarado
AVAlberto-Antony Venancio-Landeros
Alberto-Antony Venancio-Landeros
CSCarlos Santiago-Olivares
Carlos Santiago-Olivares
FMFidencio Mejía-Nepomuceno
Fidencio Mejía-Nepomuceno
EREvelyn Rivera-Toledo
Evelyn Rivera-Toledo
It is convenient to study complete genome sequences of human respiratory syncytial virus (hRSV) for ongoing genomic characterization and identification of highly transmissible or pathogenic variants. Whole genome sequencing of hRSV has been challenging from respiratory tract specimens with low viral loads. Herein, we describe an amplicon-based protocol for whole genome sequencing of hRSV subgroup A validated with 24 isolates from nasopharyngeal swabs and infected cell cultures, which showed cycle threshold (Ct) values ranging from 10 to 31, as determined by quantitative reverse-transcription polymerase chain reaction. MinION nanopore generated 3200 to 5400 reads per sample to sequence over 93% of the hRSV-A genome. Coverage of each contig ranged from 130× to 200×. Samples with Ct values of 20.9, 25.2, 27.1, 27.7, 28.2, 28.8, and 29.6 led to the sequencing of over 99.0% of the virus genome, indicating high genome coverage even at high Ct values. This protocol enables the identification of hRSV subgroup A genotypes, as primers were designed to target highly conserved regions. Consequently, it holds potential for application in molecular epidemiology and surveillance of this hRSV subgroup.