Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.

The SARS-CoV-2 genome occupies a unique place in infection biology - it is the most highly sequenced genome on earth (making up over 20% of public sequencing datasets) with fine scale information on sampling date and geography, and has been subject to unprecedented intense analysis. As a result, these phylogenetic data are an incredibly valuable resource for science and public health. However, the vast majority of the data was sequenced by tiling amplicons across the full genome, with amplicon schemes that changed over the pandemic as mutations in the viral genome interacted with primer binding sites. In combination with the disparate set of genome assembly workflows and lack of consistent quality control (QC) processes, the current genomes have many systematic errors that have evolved with the virus and amplicon schemes. These errors have significant impacts on the phylogeny, and therefore over the last few years, many thousands of hours of researchers time has been spent in "eyeballing" trees, looking for artefacts, and then patching the tree. Given the huge value of this dataset, we therefore set out to reprocess the complete set of public raw sequence data in a rigorous amplicon-aware manner, and build a cleaner phylogeny. Here we provide a global tree of 3,960,704 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of March 2023, viewable at https://viridian.taxonium.org. Each genome was constructed using a novel assembly tool called Viridian (https://github.com/iqbal-lab-org/viridian), developed specifically to process amplicon sequence data, eliminating artefactual errors and mask the genome at low quality positions. We provide simulation and empirical validation of the methodology, and quantify the improvement in the phylogeny. Phase 2 of our project will address the fact that the data in the public archives is heavily geographically biased towards the Global North. We therefore have contributed new raw data to ENA/SRA from many countries including Ghana, Thailand, Laos, Sri Lanka, India, Argentina and Singapore. We will incorporate these, along with all public raw data submitted between March 2023 and the current day, into an updated set of assemblies, and phylogeny. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers.

Evaluation of RT-qPCR and Loop-Mediated Isothermal Amplification (LAMP) Assays for the Detection of SARS-CoV-2 in Argentina.

Our aim was to evaluate the analytical and clinical performance of the SARS-CoV-2 molecular detection kits used in Argentina. Nine real-time reverse-transcription polymerase chain reaction (RT-qPCR) and three reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assays were evaluated using the World Health Organization (WHO) recommended test as reference method. A secondary standard calibrated for the E, N and RdRp genes against the Pan American Health Organization-World Health Organization-International Standard was used to calculate the limit of detection (LoD). A panel of artificial clinical samples, 32 positive and 30 negative for SARS-CoV-2, were analyzed to estimate the kappa concordance (κ) and the diagnostic performance. Differences among the LoD values for the target genes amplified by each kit were >1 log copies/reaction. The κ for the RT-qPCR kits was greater than 0.9, whereas that for the RT-LAMP assays ranged from 0.75 to 0.93. The clinical performance of RT-qPCR kits showed 100% specificity and high sensitivity, although with variations according to the gene analyzed. The E and N genes provided greater clinical sensitivity, whereas the RdRp gene increased the clinical specificity. The RT-LAMP assays revealed a variable diagnostic performance. The information provided can be useful to choose the most appropriate diagnostic test and may contribute to the establishment of a consensus in the diagnosis of SARS-CoV-2 in Argentina and the region.

A combined approach of MALDI-TOF mass spectrometry and multivariate analysis as a potential tool for the detection of SARS-CoV-2 virus in nasopharyngeal swabs.

Coronavirus disease 2019, known as COVID-19, is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The early, sensitive and specific detection of SARS-CoV-2 virus is widely recognized as the critical point in responding to the ongoing outbreak. Currently, the diagnosis is based on molecular real time RT-PCR techniques, although their implementation is being threatened due to the extraordinary demand for supplies worldwide. That is why the development of alternative and / or complementary tests becomes so relevant. Here, we exploit the potential of mass spectrometry technology combined with machine learning algorithms, for the detection of COVID-19 positive and negative protein profiles directly from nasopharyngeal swabs samples. According to the preliminary results obtained, accuracy = 67.66 %, sensitivity = 61.76 %, specificity = 71.72 %, and although these parameters still need to be improved to be used as a screening technique, mass spectrometry-based methods coupled with multivariate analysis showed that it is an interesting tool that deserves to be explored as a complementary diagnostic approach due to the low cost and fast performance. However, further steps, such as the analysis of a large number of samples, should be taken in consideration to determine the applicability of the method developed.