A high-resolution melt curve toolkit to identify lineage-defining SARS-CoV-2 mutations.

The emergence of severe acute respiratory syndrome 2 (SARS-CoV-2) variants of concern (VOCs), with mutations linked to increased transmissibility, vaccine escape and virulence, has necessitated the widespread genomic surveillance of SARS-CoV-2. This has placed a strain on global sequencing capacity, especially in areas lacking the resources for large scale sequencing activities. Here we have developed three separate multiplex high-resolution melting assays to enable the identification of Alpha, Beta, Delta and Omicron VOCs. The assays were evaluated against whole genome sequencing on upper-respiratory swab samples collected during the Alpha, Delta and Omicron [BA.1] waves of the UK pandemic. The sensitivities of the eight individual primer sets were all 100%, and specificity ranged from 94.6 to 100%. The multiplex HRM assays have potential as a tool for high throughput surveillance of SARS-CoV-2 VOCs, particularly in areas with limited genomics facilities.

Evaluation of eight lateral flow tests for the detection of anti-SARS-CoV-2 antibodies in a vaccinated population.

BACKGROUND: Rapid determination of an individual's antibody status can be beneficial in understanding an individual's immune response to SARS-CoV-2 and for initiation of therapies that are only deemed effective in sero-negative individuals. Antibody lateral flow tests (LFTs) have potential to address this need as a rapid, point of care test. METHODS: Here we present a proof-of-concept evaluation of eight LFT brands using sera from 95 vaccinated individuals to determine sensitivity for detecting vaccination generated antibodies. Samples were analysed on eight different brands of antibody LFT and an automated chemiluminescent microparticle immunoassay (CMIA) that identifies anti-spike antibodies which was used as our reference standard. RESULTS: All 95 (100%) participants tested positive for anti-spike antibodies by the chemiluminescent microparticle immunoassay (CMIA) reference standard post-dose two of their SARS-CoV-2 vaccine: BNT162b2 (Pfizer/BioNTech, n = 60), AZD1222 (AstraZeneca, n = 31), mRNA-1273 (Moderna, n = 2) and Undeclared Vaccine Brand (n = 2). Sensitivity increased from dose one to dose two in six out of eight LFTs with three tests achieving 100% sensitivity at dose two in detecting anti-spike antibodies. CONCLUSIONS: These tests are demonstrated to be highly sensitive to detect raised antibody levels in vaccinated individuals. RDTs are low cost and rapid alternatives to ELISA based systems.

Analytical evaluation of thirty-two severe acute respiratory syndrome 2 lateral flow antigen tests demonstrates sensitivity remains with the SARS-CoV-2 Gamma lineage.

BACKGROUND: The emergence of variants of concern (VOCs) requires an ongoing assessment of the performance of antigen lateral flow tests (Ag-RDTs). The limit of detection (LOD) of 32 Ag-RDTs was evaluated using the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant. METHODS: Ag-RDTs were performed according to the manufacturer's instructions with a clinical isolate of the Gamma variant. RESULTS: Twenty-eight of the 32 Ag-RDTs exceeded the World Health Organization criteria. CONCLUSIONS: This comprehensive analytical evaluation of Ag-RDTs demonstrated that the test performance was maintained with Gamma VOC.

Analytical evaluation of thirty-two severe acute respiratory syndrome 2 lateral flow antigen tests demonstrates sensitivity remains with the SARS-CoV-2 Gamma lineage

ABSTRACT Background: The emergence of variants of concern (VOCs) requires an ongoing assessment of the performance of antigen lateral flow tests (Ag-RDTs). The limit of detection (LOD) of 32 Ag-RDTs was evaluated using the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant. Methods: Ag-RDTs were performed according to the manufacturer's instructions with a clinical isolate of the Gamma variant. Results: Twenty-eight of the 32 Ag-RDTs exceeded the World Health Organization criteria. Conclusions: This comprehensive analytical evaluation of Ag-RDTs demonstrated that the test performance was maintained with Gamma VOC.

Integrated Probabilistic Annotation: A Bayesian-Based Annotation Method for Metabolomic Profiles Integrating Biochemical Connections, Isotope Patterns, and Adduct Relationships.

In a typical untargeted metabolomics experiment, the huge amount of complex data generated by mass spectrometry necessitates automated tools for the extraction of useful biological information. Each metabolite generates numerous mass spectrometry features. The association of these experimental features to the underlying metabolites still represents one of the major bottlenecks in metabolomics data processing. While certain identification (e.g., by comparison to authentic standards) is always desirable, it is usually achievable only for a limited number of compounds, and scientists often deal with a significant amount of putatively annotated metabolites. The confidence in a specific annotation is usually assessed by considering different sources of information (e.g., isotope patterns, adduct formation, chromatographic retention times, and fragmentation patterns). IPA (integrated probabilistic annotation) offers a rigorous and reproducible method to automatically annotate metabolite profiles and evaluate the resulting confidence of the putative annotations. It is able to provide a rigorous measure of our confidence in any putative annotation and is also able to update and refine our beliefs (i.e., background prior knowledge) by incorporating different sources of information in the annotation process, such as isotope patterns, adduct formation and biochemical relations. The IPA package is freely available on GitHub ( https://github.com/francescodc87/IPA ), together with the related extensive documentation.