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Lanyon HE, Downard KM. Rapid identification of SARS CoV-2 omicron sub-variant JN.1 (BA.2.86.1.1) with mass spectrometry. J Mass Spectrom Adv Clin Lab 2024; 33:38-42. [PMID: 39263330 PMCID: PMC11387365 DOI: 10.1016/j.jmsacl.2024.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 08/07/2024] [Accepted: 08/10/2024] [Indexed: 09/13/2024] Open
Abstract
Objective The rapid detection and differentiation of strains of the BA.2.86 lineage including the new sub-variant JN.1 (BA.2.86.1.1) is demonstrated employing selected ion monitoring (SIM) and high resolution mass spectrometry. Methods A study of a preliminary set of BA.2.86 lineage positive specimens, identified BA.2.86 and BA.2.86.1.1 peptide markers in 62.5 % and 29.1 % of samples. Results Peptide-specific markers in the surface spike protein associated with the L455S mutation are confidently detected with high sensitivity in protein and virus digests.The virus was thus confidently assigned in over 91 % of positive specimens. Conclusions A rise in the global prevalence of the JN.1 (BA.2.86.1.1) immune evasive sub-variant, that emerged in late 2023, requires that new strategies and protocols to detect such strains in human specimens are accelerated and implemented.
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Affiliation(s)
- Henry E Lanyon
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, NSW, Sydney, Australia
| | - Kevin M Downard
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, NSW, Sydney, Australia
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Yan T, Zheng R, Li Y, Sun S, Zeng X, Yue Z, Liao Y, Hu Q, Xu Y, Li Q. Epidemiological Insights into the Omicron Outbreak via MeltArray-Assisted Real-Time Tracking of SARS-CoV-2 Variants. Viruses 2023; 15:2397. [PMID: 38140638 PMCID: PMC10748191 DOI: 10.3390/v15122397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
The prolonged course of the COVID-19 pandemic necessitates sustained surveillance of emerging variants. This study aimed to develop a multiplex real-time polymerase chain reaction (rt-PCR) suitable for the real-time tracking of Omicron subvariants in clinical and wastewater samples. Plasmids containing variant-specific mutations were used to develop a MeltArray assay. After a comprehensive evaluation of both analytical and clinical performance, the established assay was used to detect Omicron variants in clinical and wastewater samples, and the results were compared with those of next-generation sequencing (NGS) and droplet digital PCR (ddPCR). The MeltArray assay identified 14 variant-specific mutations, enabling the detection of five Omicron sublineages (BA.2*, BA.5.2*, BA.2.75*, BQ.1*, and XBB.1*) and eight subvariants (BF.7, BN.1, BR.2, BQ.1.1, XBB.1.5, XBB.1.16, XBB.1.9, and BA.4.6). The limit of detection (LOD) of the assay was 50 copies/reaction, and no cross-reactivity was observed with 15 other respiratory viruses. Using NGS as the reference method, the clinical evaluation of 232 swab samples exhibited a clinical sensitivity of > 95.12% (95% CI 89.77-97.75%) and a specificity of > 95.21% (95% CI, 91.15-97.46%). When used to evaluate the Omicron outbreak from late 2022 to early 2023, the MeltArray assay performed on 1408 samples revealed that the epidemic was driven by BA.5.2* (883, 62.71%) and BF.7 (525, 37.29%). Additionally, the MeltArray assay demonstrated potential for estimating variant abundance in wastewater samples. The MeltArray assay is a rapid and scalable method for identifying SARS-CoV-2 variants. Integrating this approach with NGS and ddPCR will improve variant surveillance capabilities and ensure preparedness for future variants.
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Affiliation(s)
- Ting Yan
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Rongrong Zheng
- Xiamen Centre for Disease Control and Prevention, Xiamen 361021, China; (R.Z.); (X.Z.)
| | - Yinghui Li
- Shenzhen Centre for Disease Control and Prevention, Shenzhen 518055, China; (Y.L.); (Z.Y.); (Q.H.)
| | - Siyang Sun
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Xiaohong Zeng
- Xiamen Centre for Disease Control and Prevention, Xiamen 361021, China; (R.Z.); (X.Z.)
| | - Zhijiao Yue
- Shenzhen Centre for Disease Control and Prevention, Shenzhen 518055, China; (Y.L.); (Z.Y.); (Q.H.)
| | - Yiqun Liao
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Qinghua Hu
- Shenzhen Centre for Disease Control and Prevention, Shenzhen 518055, China; (Y.L.); (Z.Y.); (Q.H.)
| | - Ye Xu
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
| | - Qingge Li
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China; (T.Y.); (S.S.); (Y.L.)
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Lanyon HE, Todd BP, Downard KM. Distinguishing common SARS-CoV2 omicron and recombinant variants with high resolution mass spectrometry. Analyst 2023; 148:6306-6314. [PMID: 37936487 DOI: 10.1039/d3an01376f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
A selected ion monitoring (SIM) approach combined with high resolution mass spectrometry is employed to identify and distinguish common SARS-CoV2 omicron and recombinant variants in clinical specimens. Mutations within the receptor binding domain (RBD) within the surface spike protein of the virus result in a combination of peptide segments of unique sequence and mass that were monitored to detect BA.2.75 (including CH.1.1) and XBB (including 1.5) variants prevalent in the state's population in early 2023. SIM detection of pairs of peptides unique to each variant were confidently detected and differentiated in 57.3% of the specimens, with a further 10 or 17.5% (for a total of 74.8%) detected based on a single peptide biomarker. The BA.2.75 sub-variant was detected in 18.7%, while recombinant variants XBB and XBB.1.5 were detected in 13.3% and 25.3% of the specimens respectively, consistent with circulating levels in the population characterised by RT-PCR. Virus was detected in 75 SARS-CoV2 positive specimens by mass spectrometry down to the low or mid 104 copy level, with a single false positive and no false negative identified. This article is the first paper to characterise recombinant strains of the SARS-CoV2 virus by this, or any other, MS method.
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Affiliation(s)
- Henry E Lanyon
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, Sydney, Australia.
| | - Benjamin P Todd
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, Sydney, Australia.
| | - Kevin M Downard
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, Sydney, Australia.
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Downard KM. 25 Years Responding to Respiratory and Other Viruses with Mass Spectrometry. Mass Spectrom (Tokyo) 2023; 12:A0136. [PMID: 38053835 PMCID: PMC10694638 DOI: 10.5702/massspectrometry.a0136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 10/24/2023] [Indexed: 12/07/2023] Open
Abstract
This review article presents the development and application of mass spectrometry (MS) approaches, developed in the author's laboratory over the past 25 years, to detect; characterise, type and subtype; and distinguish major variants and subvariants of respiratory viruses such as influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). All features make use of matrix-assisted laser desorption ionisation (MALDI) mass maps, recorded for individual viral proteins or whole virus digests. A MALDI-based immunoassay in which antibody-peptide complexes were preserved on conventional MALDI targets without their immobilisation led to an approach that enabled their indirect detection. The site of binding, and thus the molecular antigenicity of viruses, could be determined. The same approach was employed to study antivirals bound to their target viral protein, the nature of the binding residues, and relative binding affinities. The benefits of high-resolution MS were exploited to detect sequence-conserved signature peptides of unique mass within whole virus and single protein digests. These enabled viruses to be typed, subtyped, their lineage determined, and variants and subvariants to be distinguished. Their detection using selected ion monitoring improved analytical sensitivity limits to aid the identification of viruses in clinical specimens. The same high-resolution mass map data, for a wide range of viral strains, were input into a purpose-built algorithm (MassTree) in order to both chart and interrogate viral evolution. Without the need for gene or protein sequences, or any sequence alignment, this phylonumerics approach also determines and displays single-point mutations associated with viral protein evolution in a single-tree building step.
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Affiliation(s)
- Kevin M. Downard
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, Sydney, NSW, Australia
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Hoyle JS, Downard KM. High resolution mass spectrometry of respiratory viruses: beyond MALDI-ToF instruments for next generation viral typing, subtyping, variant and sub-variant identification. Analyst 2023; 148:4263-4273. [PMID: 37587867 DOI: 10.1039/d3an00953j] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/18/2023]
Abstract
In the wake of the SARS-CoV2 pandemic, a point has been reached to assess the limitations and strengths of the analytical responses to virus identification and characterisation. Mass spectrometry has played a growing role in this area for over two decades, and this review highlights the benefits of mass spectrometry (MS) over PCR-based methods together with advantages of high mass resolution, high mass accuracy strategies over conventional MALDI-ToF and ESI-MS/MS instrumentation. This review presents the development and application of high resolution mass spectrometry approaches to detect, characterise, type and subtype, and distinguish variants of the influenza and SARS-CoV-2 respiratory viruses. The detection limits for the identification of SARS-CoV2 virus variants in clinical specimens and the future uptake of high resolution instruments in clinical laboratories are discussed. The same high resolution mass data can be used to monitor viral evolution and follow evolutionary trajectories.
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Affiliation(s)
- Joshua S Hoyle
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, Sydney, Australia.
| | - Kevin M Downard
- Infectious Disease Responses Laboratory, Prince of Wales Clinical Research Sciences, Sydney, Australia.
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