Rxivist logo

SARS-CoV-2 proteome microarray for mapping COVID-19 antibody interactions at amino acid resolution

By Hongye Wang, Xin Hou, Xian Wu, Te Liang, Xiaomei Zhang, Dan Wang, Fei Teng, Jiayu Dai, Hu Duan, Shubin Guo, Yongzhe Li, Xiaobo Yu

Posted 28 Mar 2020
bioRxiv DOI: 10.1101/2020.03.26.994756 (published DOI: 10.1021/acscentsci.0c00742)

COVID-19 has quickly become a worldwide pandemic, which has significantly impacted the economy, education, and social interactions. Understanding the humoral antibody response to SARS-CoV-2 proteins may help identify biomarkers that can be used to detect and treat COVID-19 infection. However, no immuno-proteomics platform exists that can perform such proteome-wide analysis. To address this need, we created a SARS-CoV-2 proteome microarray to analyze antibody interactions at amino acid resolution by spotting peptides 15 amino acids long with 5-amino acid offsets representing full-length SARS-CoV-2 proteins. Moreover, the array processing time is short (1.5 hours), the dynamic range is ~2 orders of magnitude, and the lowest limit of detection is 94 pg/mL. Here, the SARS-CoV-2 proteome array reveals that antibodies commercially available for SARS-CoV-1 proteins can also target SARS-CoV-2 proteins. These readily available reagents could be used immediately in COVID-19 research. Second, IgM and IgG immunogenic epitopes of SARS-CoV-2 proteins were profiled in the serum of ten COVID-19 patients. Such epitope biomarkers provide insight into the immune response to COVID-19 and are potential targets for COVID-19 diagnosis and vaccine development. Finally, serological antibodies that may neutralize viral entry into host cells via the ACE2 receptor were identified. Further investigation into whether these antibodies can inhibit the propagation of SARS-CoV-2 is warranted. Antibody and epitope profiling in response to COVID-19 is possible with our peptide-based SARS-COV-2 proteome microarray. The data gleaned from the array could provide invaluable information to the scientific community to understand, detect, and treat COVID-19. ### Competing Interest Statement The authors have declared no competing interest.

Download data

  • Downloaded 5,327 times
  • Download rankings, all-time:
    • Site-wide: 2,341
    • In biochemistry: 32
  • Year to date:
    • Site-wide: 25,231
  • Since beginning of last month:
    • Site-wide: 46,624

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide