Serological assays that can reveal immune status against COVID-19 play a critical role in informing individual and public healthcare decisions. Currently, antibody tests are performed in central clinical laboratories, limiting broad access to diverse populations. Here we report a multiplexed and label-free nanoplasmonic biosensor that can be deployed for point-of-care antibody profiling. Our optical imaging-based approach can simultaneously quantify antigen-specific antibody response against SARS-CoV-2 spike and nucleocapsid proteins from 50 µL of human sera. To enhance the dynamic range, we employed multivariate data processing and multi-color imaging and achieved a quantification range of 0.1-100 µg/mL. We measured sera from a COVID-19 acute and convalescent (N = 24) patient cohort and negative controls (N = 5) and showed highly sensitive and specific past-infection diagnosis. Our results were benchmarked against an electrochemiluminescence assay and showed good concordance (R∼0.87). Our integrated nanoplasmonic biosensor has the potential to be used in epidemiological sero-profiling and vaccine studies.

Serological population surveillance plays a crucial role in monitoring the spread, evolution, and outbreak risks of infectious diseases, including COVID-19. However, current commercial rapid serological tests fall short of capturing...

Serological population surveillance can elucidate immunity landscapes against SARS-CoV-2 variants and are critical in monitoring infectious disease spread, evolution, and outbreak risks. However, current serological tests fall short of capturing complex humoral immune responses from different communities. Here, we report a machine-learning (ML)-aided nanobiosensor that can simultaneously quantify antibodies against the ancestral strain and Omicron variants of SARS-CoV-2 with epitope resolution. Our approach is based on a multiplexed, rapid, and label-free nanoplasmonic biosensor, which can detect past infection and vaccination status and is sensitive to SARS-CoV-2 variants. After training an ML model with antigen-specific antibody datasets from four COVID-19 immunity groups (naive, convalescent, vaccinated, and convalescent-vaccinated), we tested our approach on 100 blind blood samples collected in Dane County, WI. Our results are consistent with public epidemiological data, demonstrating that our user-friendly and field-deployable nanobiosensor can capture community-representative public health trends and help manage COVID-19 and future outbreaks.

Serological assays can reveal immune status against COVID-19 informing individual and public healthcare decisions. We report a multiplexed and label-free nanoplasmonic biosensor that can discriminate healthy from convalescent samples with high sensitivity (95%) and specificity (100%) based on anti-SARS-CoV-2 antibody quantification. Our results show high concordance (R~ 0.87) with commercial assays in detecting anti-SARS-CoV-2 antibodies.