{"doi":"10.3389/fimmu.2021.696370","title":"Antibody Mediated Immunity to SARS-CoV-2 and Human Coronaviruses: Multiplex Beads Assay and Volumetric Absorptive Microsampling to Generate Immune Repertoire Cartography","abstract":"The COVID-19 pandemic is caused by SARS-CoV-2, a novel zoonotic coronavirus. Emerging evidence indicates that preexisting humoral immunity against other seasonal human coronaviruses (HCoVs) plays a critical role in the specific antibody response to SARS-CoV-2. However, current work to assess the effects of preexisting and cross-reactive anti-HCoVs antibodies has been limited. To address this issue, we have adapted our previously reported multiplex assay to simultaneously and quantitatively measure anti-HCoV antibodies. The full mPlex-CoV panel covers the spike (S) and nucleocapsid (N) proteins of three highly pathogenic HCoVs (SARS-CoV-1, SARS-CoV-2, MERS) and four human seasonal strains (OC43, HKU1, NL63, 229E). Combining this assay with volumetric absorptive microsampling (VAMS), we measured the anti-HCoV IgG, IgA, and IgM antibodies in fingerstick blood samples. The results demonstrate that the mPlex-CoV assay has high specificity and sensitivity. It can detect strain-specific anti-HCoV antibodies down to 0.1 ng/ml with 4 log assay range and with low intra- and inter-assay coefficients of variation (%CV). We also estimate multiple strain HCoVs IgG, IgA and IgM concentration in VAMS samples in three categories of subjects: pre-COVID-19 (n=21), post-COVID-19 convalescents (n=19), and COVID-19 vaccine recipients (n=14). Using metric multidimensional scaling (MDS) analysis, HCoVs IgG concentrations in fingerstick blood samples were well separated between the pre-COVID-19, post-COVID-19 convalescents, and COVID-19 vaccine recipients. In addition, we demonstrate how multi-dimensional scaling analysis can be used to visualize IgG mediated antibody immunity against multiple human coronaviruses. We conclude that the combination of VAMS and the mPlex-Cov assay is well suited to performing remote study sample collection under pandemic conditions to monitor HCoVs antibody responses in population studies.","journal":"Frontiers in Immunology","year":2021,"id":177560,"datarank":0.8063762909412395,"base_score":3.044522437723423,"endowment":3.044522437723423,"self_citation_contribution":0.4566783656585135,"citation_network_contribution":0.34969792528272603,"self_endowment_contribution":0.4566783656585135,"citer_contribution":0.34969792528272603,"corpus_percentile":null,"corpus_rank":null,"citation_count":20,"citer_count":13,"citers_with_citation_signal":12,"citers_with_endowment":12,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9611,"is_data_producer":true,"deposit_databanks":{"figshare":["10.6084/ m9.figshare.13490166"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":278344,"name":"Dongmei Li","orcid":"0000-0001-9140-2483","position":1,"is_corresponding":false},{"id":721911,"name":"Qian Zhou","orcid":"0000-0003-3954-5449","position":2,"is_corresponding":false},{"id":576790,"name":"Alexander Wiltse","orcid":null,"position":3,"is_corresponding":false},{"id":378547,"name":"Martin S. Zand","orcid":"0000-0002-7095-8682","position":4,"is_corresponding":false},{"id":408834,"name":"Jiong Wang","orcid":"0000-0002-4938-5074","position":0,"is_corresponding":true}],"reference_count":38,"raw_metadata":null,"created_at":"2026-07-18T23:47:32.096934Z","pmid":"34386006","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}