Evidence map›Paper›PMID 39994575›Full record

ArticleBMC infectious diseases2025

Validation and implementation of TaqMAMA RT-PCR for SARS-CoV-2 variant surveillance: experience from a high-volume setting.

José Nicolas Aguirre-Pineda, Mario Alberto Mújica-Sánchez, Hansel Hugo Chávez-Morales, Gabriel Cojuc-Konigsberg, Alan Braverman-Poyastro, Alberto Moscona-Nissan, Gastón Becherano-Razon, Alberto Guijosa, Damilda Duarte, Maria Del Carmen García-Colín and 2 more

Abstract readValidation Study
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

12 authors.

José Nicolas Aguirre-PinedaLaboratorio de Microbiología, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Calzada de Tlalpan 4502, Belisario Domínguez Secc 16, Alcaldía Tlalpan, Mexico City, 14080, Mexico.
Mario Alberto Mújica-SánchezLaboratorio de Microbiología, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Calzada de Tlalpan 4502, Belisario Domínguez Secc 16, Alcaldía Tlalpan, Mexico City, 14080, Mexico.
Hansel Hugo Chávez-MoralesLaboratorio de Microbiología, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Calzada de Tlalpan 4502, Belisario Domínguez Secc 16, Alcaldía Tlalpan, Mexico City, 14080, Mexico.
Gabriel Cojuc-KonigsbergFaculty of Health Sciences, Universidad Anahuac Mexico, Av. Universidad Anáhuac 46, Lomas Anahuac, Mexico City, 52786, Mexico.
Alan Braverman-PoyastroFaculty of Health Sciences, Universidad Anahuac Mexico, Av. Universidad Anáhuac 46, Lomas Anahuac, Mexico City, 52786, Mexico.
Alberto Moscona-NissanSchool of Medicine, Universidad Panamericana, Donatello 59, Insurgentes Mixcoac, Mexico City, 03920, Mexico.
Gastón Becherano-RazonFaculty of Health Sciences, Universidad Anahuac Mexico, Av. Universidad Anáhuac 46, Lomas Anahuac, Mexico City, 52786, Mexico.
Alberto GuijosaSchool of Medicine, Universidad Panamericana, Donatello 59, Insurgentes Mixcoac, Mexico City, 03920, Mexico.
Damilda DuarteDepartment of Clinical Infectious Diseases. National Institute of Respiratory Diseases, Mexico City, Mexico.
Maria Del Carmen García-ColínLaboratorio de Microbiología, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Calzada de Tlalpan 4502, Belisario Domínguez Secc 16, Alcaldía Tlalpan, Mexico City, 14080, Mexico.
Martha Angella Durán-BarrónLaboratorio de Microbiología, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Calzada de Tlalpan 4502, Belisario Domínguez Secc 16, Alcaldía Tlalpan, Mexico City, 14080, Mexico.
Eduardo Becerril-VargasDepartment of Clinical Infectious Diseases. National Institute of Respiratory Diseases, Mexico City, Mexico. edobec.var@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe genomic surveillance of SARS-CoV-2 is challenging in high-volume, resource-limited settings. Faster and less expensive methods are required for the prompt detection of variants of interest. This study aimed to validate and implement the TaqMAMA RT-PCR method for the detection of SARS-CoV-2 variants.

methodsWe developed the TaqMAMA RT-PCR method for SARS-CoV-2 variants. From the viral genomes obtained from the GISAID database, fluorescent amplification probes and oligonucleotides were designed to detect two specific mutations for each variant. The study consisted of an assay validation phase comparing the newly designed method to WGS in COVID-19-positive samples, followed by a large-scale implementation phase to calculate its performance.

resultsDuring the assay validation phase, we included 232 samples for analysis using TaqMAMA and WGS. TaqMAMA identified 82.3% as positive, and had sensitivities of 82%, 100%, and 50%, specificities of 91%, 99%, and 100%, with PPVs of 99%, 75%, and 100%, and NPVs of 20%, 100%, and 100% for the Delta, Alpha, and Gamma variants, respectively. For the implementation phase, we included 1315 samples, TaqMAMA identified 68% positive samples, 97.5% as delta. The predicted performance using Bayesian statistics was 95%, 55%, and 0% for the positive, and 29%, 0%, and < 1% for the negative delta, alpha, and gamma variants, respectively.

conclusionsThe diagnostic performance of TaqMAMA RT-PCR was acceptable for the detection of the most prevalent SARS-CoV-2 variants of interest. This method offers a cost and time-saving alternative for the genomic surveillance of SARS-CoV-2 in high-volume settings.

Indexed as

COVID-19COVID-19 Nucleic Acid TestingReverse Transcriptase Polymerase Chain ReactionSARS-CoV-2Genome, ViralHumansMutationRNA, ViralSensitivity and SpecificityRNA, ViralClinical microbiologyDiagnostic toolsGenomic surveillanceRT-PCRSARS-CoV-2TaqMAMAVariants of interestWhole genome sequencing

Identifiers

PMID39994575
PMCPMC11849270

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.