Machine Learning-Based Fragment Selection Improves the Performance of Qualitative PRM Assays.

Targeted mass spectrometry-based platforms have become a valuable tool for the sensitive and specific detection of protein biomarkers in clinical and research settings. Traditionally, developing a targeted assay for peptide quantification has involved manually preselecting several fragment ions and establishing a limit of detection (LOD) and a lower limit of quantitation (LLOQ) for confident detection of the target. Established thresholds such as LOD and LLOQ, however, inherently sacrifice sensitivity to afford specificity. Here, we demonstrate that machine learning can be applied to qualitative PRM assays to discriminate positive from negative samples more effectively than a traditional approach utilizing conventional methods. To demonstrate the utility of this method, we trained an ensemble machine learning model using 282 SARS-CoV-2 positive and 994 SARS-CoV-2 negative nasopharyngeal swabs (NP swab) analyzed using a targeted PRM method. This model was then validated using an independent set of 200 positive and 150 negative samples and achieved a sensitivity of 92% relative to results obtained by RT-PCR, which was superior to a traditional approach that resulted in 86.5% sensitivity when analyzing the same data. These results demonstrate that machine learning can be applied to qualitative PRM assays and results in superior performance relative to traditional methods.

Analytical Sensitivity and Specificity of Four Point of Care Rapid Antigen Diagnostic Tests for SARS-CoV-2 Using Real-Time Quantitative PCR, Quantitative Droplet Digital PCR, and a Mass Spectrometric Antigen Assay as Comparator Methods.

BACKGROUND: We evaluated the analytical sensitivity and specificity of 4 rapid antigen diagnostic tests (Ag RDTs) for severe acute respiratory syndrome coronavirus 2, using reverse transcription quantitative PCR (RT-qPCR) as the reference method and further characterizing samples using droplet digital quantitative PCR (ddPCR) and a mass spectrometric antigen test. METHODS: Three hundred fifty (150 negative and 200 RT-qPCR positive) residual PBS samples were tested for antigen using the BD Veritor lateral flow (LF), ACON LF, ACON fluorescence immunoassay (FIA), and LumiraDx FIA. ddPCR was performed on RT-qPCR-positive samples to quantitate the viral load in copies/mL applied to each Ag RDT. Mass spectrometric antigen testing was performed on PBS samples to obtain a set of RT-qPCR-positive, antigen-positive samples for further analysis. RESULTS: All Ag RDTs had nearly 100% specificity compared to RT-qPCR. Overall analytical sensitivity varied from 66.5% to 88.3%. All methods detected antigen in samples with viral load >1 500 000 copies/mL RNA, and detected ≥75% of samples with viral load of 500 000 to 1 500 000 copies/mL. The BD Veritor LF detected only 25% of samples with viral load between 50 000 to 500 000 copies/mL, compared to 75% for the ACON LF device and >80% for LumiraDx and ACON FIA. The ACON FIA detected significantly more samples with viral load <50 000 copies/mL compared to the BD Veritor. Among samples with detectable antigen and viral load <50 000 copies/mL, sensitivity of the Ag RDT varied between 13.0% (BD Veritor) and 78.3% (ACON FIA). CONCLUSIONS: Ag RDTs differ significantly in analytical sensitivity, particularly at viral load <500 000 copies/mL.

Targeted Detection of SARS-CoV-2 Nucleocapsid Sequence Variants by Mass Spectrometric Analysis of Tryptic Peptides.

COVID-19 vaccines are becoming more widely available, but accurate and rapid testing remains a crucial tool for slowing the spread of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus. Although the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) remains the most prevalent testing methodology, numerous tests have been developed that are predicated on detection of the SARS-CoV-2 nucleocapsid protein, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and immunoassay-based approaches. The continuing emergence of SARS-CoV-2 variants has complicated these approaches, as both qRT-PCR and antigen detection methods can be prone to missing viral variants. In this study, we describe several COVID-19 cases where we were unable to detect the expected peptide targets from clinical nasopharyngeal swabs. Whole genome sequencing revealed that single nucleotide polymorphisms in the gene encoding the viral nucleocapsid protein led to sequence variants that were not monitored in the targeted assay. Minor modifications to the LC-MS/MS method ensured detection of the variants of the target peptide. Additional nucleocapsid variants could be detected by performing the bottom-up proteomic analysis of whole viral genome-sequenced samples. This study demonstrates the importance of considering variants of SARS-CoV-2 in the assay design and highlights the flexibility of mass spectrometry-based approaches to detect variants as they evolve.

A SISCAPA-based approach for detection of SARS-CoV-2 viral antigens from clinical samples.

SARS-CoV-2, a novel human coronavirus, has created a global disease burden infecting > 100 million humans in just over a year. RT-PCR is currently the predominant method of diagnosing this viral infection although a variety of tests to detect viral antigens have also been developed. In this study, we adopted a SISCAPA-based enrichment approach using anti-peptide antibodies generated against peptides from the nucleocapsid protein of SARS-CoV-2. We developed a targeted workflow in which nasopharyngeal swab samples were digested followed by enrichment of viral peptides using the anti-peptide antibodies and targeted parallel reaction monitoring (PRM) analysis using a high-resolution mass spectrometer. This workflow was applied to 41 RT-PCR-confirmed clinical SARS-CoV-2 positive nasopharyngeal swab samples and 30 negative samples. The workflow employed was highly specific as none of the target peptides were detected in negative samples. Further, the detected peptides showed a positive correlation with the viral loads as measured by RT-PCR Ct values. The SISCAPA-based platform described in the current study can serve as an alternative method for SARS-CoV-2 viral detection and can also be applied for detecting other microbial pathogens directly from clinical samples.

A mass spectrometry-based targeted assay for detection of SARS-CoV-2 antigen from clinical specimens.

BACKGROUND: The COVID-19 pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has overwhelmed health systems worldwide and highlighted limitations of diagnostic testing. Several types of diagnostic tests including RT-PCR-based assays and antigen detection by lateral flow assays, each with their own strengths and weaknesses, have been developed and deployed in a short time. METHODS: Here, we describe an immunoaffinity purification approach followed a by high resolution mass spectrometry-based targeted qualitative assay capable of detecting SARS-CoV-2 viral antigen from nasopharyngeal swab samples. Based on our discovery experiments using purified virus, recombinant viral protein and nasopharyngeal swab samples from COVID-19 positive patients, nucleocapsid protein was selected as a target antigen. We then developed an automated antibody capture-based workflow coupled to targeted high-field asymmetric waveform ion mobility spectrometry (FAIMS) - parallel reaction monitoring (PRM) assay on an Orbitrap Exploris 480 mass spectrometer. An ensemble machine learning-based model for determining COVID-19 positive samples was developed using fragment ion intensities from the PRM data. FINDINGS: The optimized targeted assay, which was used to analyze 88 positive and 88 negative nasopharyngeal swab samples for validation, resulted in 98% (95% CI = 0.922-0.997) (86/88) sensitivity and 100% (95% CI = 0.958-1.000) (88/88) specificity using RT-PCR-based molecular testing as the reference method. INTERPRETATION: Our results demonstrate that direct detection of infectious agents from clinical samples by tandem mass spectrometry-based assays have potential to be deployed as diagnostic assays in clinical laboratories, which has hitherto been limited to analysis of pure microbial cultures. FUNDING: This study was supported by DBT/Wellcome Trust India Alliance Margdarshi Fellowship grant IA/M/15/1/502023 awarded to AP and the generosity of Eric and Wendy Schmidt.

Mass Spectrometric Analysis of Urine from COVID-19 Patients for Detection of SARS-CoV-2 Viral Antigen and to Study Host Response.

SARS-CoV-2 infection has become a major public health burden and affects many organs including lungs, kidneys, the liver, and the brain. Although the virus is readily detected and diagnosed using nasopharyngeal swabs by reverse transcriptase polymerase chain reaction (RT-PCR), detection of its presence in body fluids is fraught with difficulties. A number of published studies have failed to detect viral RNA by RT-PCR methods in urine. Although microbial identification in clinical microbiology using mass spectrometry is undertaken after culture, here we undertook a mass spectrometry-based approach that employed an enrichment step to capture and detect SARS-CoV-2 nucleocapsid protein directly from urine of COVID-19 patients without any culture. We detected SARS-CoV-2 nucleocapsid protein-derived peptides from 13 out of 39 urine samples. Further, a subset of COVID-19 positive and COVID-19 negative urine samples validated by mass spectrometry were used for the quantitative proteomics analysis. Proteins with increased abundance in urine of SARS-CoV-2 positive individuals were enriched in the acute phase response, regulation of complement system, and immune response. Notably, a number of renal proteins such as podocin (NPHS2), an amino acid transporter (SLC36A2), and sodium/glucose cotransporter 5 (SLC5A10), which are intimately involved in normal kidney function, were decreased in the urine of COVID-19 patients. Overall, the detection of viral antigens in urine using mass spectrometry and alterations of the urinary proteome could provide insights into understanding the pathogenesis of COVID-19.