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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/2854| Efficient and Practical Sample Pooling for High-Throughput PCR Diagnosis of COVID-19 | |
| Shani-Narkiss Haran. Gilday Omri David. Yayon Nadav. Landau Itamar Daniel. | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| 10.1101/2020.04.06.20052159 | |
| Diagnostic assays using quantitative Polymerase Chain Reaction (qPCR) most commonly process patient samples one by one. While this is usually an effective and reliable method, the current efforts against the COVID-19 pandemic demand more efficient measures. Diagnostic assays can be scaled up by the method of High-Throughput qPCR via sample pooling. Pooling, the action of combining multiple samples into one tube, is most effective when the chance of positive detection of the target, SARS-CoV-2 RNA, is low. In such cases, large groups of samples can be conclusively classified as negative with a single test, with no need to individually test every sample. However, different frequencies of the target-product presence in the samples, require different pool/batch sizes for optimal results. Here, we present two possible optimized pooling strategies for diagnostic SARSCoV-2 testing on large scales, each one better suited for a different range of target frequency. In the first, we employ a simple information-theoretic heuristic to derive a highly efficient re-pooling protocol: an estimate of the target frequency determines the initial pool size, and any subsequent pools found positive are re-pooled at half-size and tested again. In the range of very rare target (<0.05), this approach can reduce the number of necessary tests dramatically. For example, this method achieves a reduction of a factor of 50 for a target frequency of 0.001. The second method is a simpler approach of optimized one-time pooling followed by individual tests on positive pools. We show that this approach is just as efficient for moderate target-product frequencies (0.05<0.2). For example, it reduces the number of tests needed by half if the frequency of positives samples is 0.07. We show that both methods are comparable to the absolute upper-bound efficiency given by Shannon's source coding theorem. Our strategies require no investment at all, and they offer a significant reduction in the amount of equipment and time needed to test large numbers of samples. Both approaches are dynamic; they can be easily implemented in different conditions with various infection rates and sample numbers. We compare our strategies to the naive way of testing and also to alternative matrix methods. Most importantly, we offer practical pooling instructions for laboratories that perform large scale qPCR assays to diagnose SARS-CoV-2 viral particles. | |
| www.medrxiv.org | |
| 2020 | |
| Artículo | |
| https://www.medrxiv.org/content/medrxiv/early/2020/04/07/2020.04.06.20052159.full.pdf | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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