Evaluation of serological lateral flow assays for severe acute respiratory syndrome coronavirus-2.

BACKGROUND: COVID-19 has resulted in significant morbidity and mortality worldwide. Lateral flow assays can detect anti-Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibodies to monitor transmission. However, standardized evaluation of their accuracy and tools to aid in interpreting results are needed. METHODS: We evaluated 20 IgG and IgM assays selected from available tests in April 2020. We evaluated the assays' performance using 56 pre-pandemic negative and 56 SARS-CoV-2-positive plasma samples, collected 10-40 days after symptom onset, confirmed by a molecular test and analyzed by an ultra-sensitive immunoassay. Finally, we developed a user-friendly web app to extrapolate the positive predictive values based on their accuracy and local prevalence. RESULTS: Combined IgG + IgM sensitivities ranged from 33.9 to 94.6%, while combined specificities ranged from 92.6 to 100%. The highest sensitivities were detected in Lumiquick for IgG (98.2%), BioHit for both IgM (96.4%), and combined IgG + IgM sensitivity (94.6%). Furthermore, 11 LFAs and 8 LFAs showed perfect specificity for IgG and IgM, respectively, with 15 LFAs showing perfect combined IgG + IgM specificity. Lumiquick had the lowest estimated limit-of-detection (LOD) (0.1 µg/mL), followed by a similar LOD of 1.5 µg/mL for CareHealth, Cellex, KHB, and Vivachek. CONCLUSION: We provide a public resource of the accuracy of select lateral flow assays with potential for home testing. The cost-effectiveness, scalable manufacturing process, and suitability for self-testing makes LFAs an attractive option for monitoring disease prevalence and assessing vaccine responsiveness. Our web tool provides an easy-to-use interface to demonstrate the impact of prevalence and test accuracy on the positive predictive values.

Comparison of proteomic and transcriptomic profiles in the bronchial airway epithelium of current and never smokers.

BACKGROUND: Although prior studies have demonstrated a smoking-induced field of molecular injury throughout the lung and airway, the impact of smoking on the airway epithelial proteome and its relationship to smoking-related changes in the airway transcriptome are unclear. METHODOLOGY/PRINCIPAL FINDINGS: Airway epithelial cells were obtained from never (n = 5) and current (n = 5) smokers by brushing the mainstem bronchus. Proteins were separated by one dimensional polyacrylamide gel electrophoresis (1D-PAGE). After in-gel digestion, tryptic peptides were processed via liquid chromatography/ tandem mass spectrometry (LC-MS/MS) and proteins identified. RNA from the same samples was hybridized to HG-U133A microarrays. Protein detection was compared to RNA expression in the current study and a previously published airway dataset. The functional properties of many of the 197 proteins detected in a majority of never smokers were similar to those observed in the never smoker airway transcriptome. LC-MS/MS identified 23 proteins that differed between never and current smokers. Western blotting confirmed the smoking-related changes of PLUNC, P4HB1, and uteroglobin protein levels. Many of the proteins differentially detected between never and current smokers were also altered at the level of gene expression in this cohort and the prior airway transcriptome study. There was a strong association between protein detection and expression of its corresponding transcript within the same sample, with 86% of the proteins detected by LC-MS/MS having a detectable corresponding probeset by microarray in the same sample. Forty-one proteins identified by LC-MS/MS lacked detectable expression of a corresponding transcript and were detected in

Molecular weight assessment of proteins in total proteome profiles using 1D-PAGE and LC/MS/MS.

BACKGROUND: The observed molecular weight of a protein on a 1D polyacrylamide gel can provide meaningful insight into its biological function. Differences between a protein's observed molecular weight and that predicted by its full length amino acid sequence can be the result of different types of post-translational events, such as alternative splicing (AS), endoproteolytic processing (EPP), and post-translational modifications (PTMs). The characterization of these events is one of the important goals of total proteome profiling (TPP). LC/MS/MS has emerged as one of the primary tools for TPP, but since this method identifies tryptic fragments of proteins, it has not generally been used for large-scale determination of the molecular weight of intact proteins in complex mixtures. RESULTS: We have developed a set of computational tools for extracting molecular weight information of intact proteins from total proteome profiles in a high throughput manner using 1D-PAGE and LC/MS/MS. We have applied this technology to the proteome profile of a human lymphoblastoid cell line under standard culture conditions. From a total of 1 x 10(7) cells, we identified 821 proteins by at least two tryptic peptides. Additionally, these 821 proteins are well-localized on the 1D-SDS gel. 656 proteins (80%) occur in gel slices in which the observed molecular weight of the protein is consistent with its predicted full-length sequence. A total of 165 proteins (20%) are observed to have molecular weights that differ from their predicted full-length sequence. We explore these molecular-weight differences based on existing protein annotation. CONCLUSION: We demonstrate that the determination of intact protein molecular weight can be achieved in a high-throughput manner using 1D-PAGE and LC/MS/MS. The ability to determine the molecular weight of intact proteins represents a further step in our ability to characterize gene expression at the protein level. The identification of 165 proteins whose observed molecular weight differs from the molecular weight of the predicted full-length sequence provides another entry point into the high-throughput characterization of protein modification.