Quantifying Protein-Specific N-Glycome Profiles by Focused Protein and Immunoprecipitation Glycomics

Serum N-glycans have been reported to be potential diagnostic and therapeutic biomarkers for many diseases and conditions, such as inflammation, fibrosis, and cancer progression. We previously described the focused protein glycomic analysis (FPG) from gel-separated serum proteins. With this methodology, we sought novel glycan biomarkers for nonalcoholic steatohepatitis (NASH) and successfully identified some N-glycans that were significantly elevated in NASH patients compared to nonalcoholic fatty liver patients. Among them, trisialylated monofucosylated triantennary glycan (A3F) of alpha-1 antitrypsin showed the most dynamic change. For rapid identification of N-glycans on the focused proteins, we constructed a simplified method called immunoprecipitation glycomics (IPG), where the target proteins were immunoprecipitated with affinity beads and subsequently subjected to glycomic analysis by MALDI-TOF MS. Focusing on alpha-1 antitrypsin and ceruloplasmin as the target proteins, we compared the values of N-glycans determined by FPG and IPG. The quantified values of each N-glycan by these two methods showed a statistically significant correlation, indicating that high throughput and quantitative N-glycomics of targeted proteins can be achieved by the simplified IPG method. Thus, an analytical strategy combining FPG and IPG can be adapted to general biomarker discovery and validation in appropriate disease areas

Development of a Fully Automated Desktop Analyzer and Ultrahigh Sensitivity Digital Immunoassay for SARS-CoV-2 Nucleocapsid Antigen Detection

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak has had a significant impact on public health and the global economy. Several diagnostic tools are available for the detection of infectious diseases, with reverse transcription-polymerase chain reaction (RT-PCR) testing specifically recommended for viral RNA detection. However, this diagnostic method is costly, complex, and time-consuming. Although it does not have sufficient sensitivity, antigen detection by an immunoassay is an inexpensive and simpler alternative to RT-PCR. Here, we developed an ultrahigh sensitivity digital immunoassay (d-IA) for detecting SARS-CoV-2 nucleocapsid (N) protein as antigens using a fully automated desktop analyzer based on a digital enzyme-linked immunosorbent assay. Methods: We developed a fully automated d-IA desktop analyzer and measured the viral N protein as an antigen in nasopharyngeal (NP) swabs from patients with coronavirus disease. We studied nasopharyngeal swabs of 159 and 88 patients who were RT-PCR-negative and RT-PCR-positive, respectively. Results: The limit of detection of SARS-CoV-2 d-IA was 0.0043 pg/mL of N protein. The cutoff value was 0.029 pg/mL, with a negative RT-PCR distribution. The sensitivity of RT-PCR-positive specimens was estimated to be 94.3% (83/88). The assay time was 28 min. Conclusions: Our d-IA system, which includes a novel fully automated desktop analyzer, enabled detection of the SARS-CoV-2 N-protein with a comparable sensitivity to RT-PCR within 30 min. Thus, d-IA shows potential for SARS-CoV-2 detection across multiple diagnostic centers including small clinics, hospitals, airport quarantines, and clinical laboratories