Two-dimensional multiplexed assay for rapid and deep SARS-CoV-2 serology profiling and for machine learning prediction of neutralization capacity.
Akiko KoideTatyana PanchenkoChan WangSara A ThannickalLarizbeth A RomeroKai Wen TengFrancesca-Zhoufan LiPadma AkkappediAlexis D CorradoJessica CaroCatherine S DiefenbachMarie I SamanovicMark J MulliganTakamitsu HattoriKenneth A StaplefordHuilin LiShohei KoidePublished in: bioRxiv : the preprint server for biology (2021)
Antibody responses serve as the primary protection against SARS-CoV-2 infection through neutralization of viral entry into cells. We have developed a two-dimensional multiplex bead binding assay (2D-MBBA) that quantifies multiple antibody isotypes against multiple antigens from a single measurement. Here, we applied our assay to profile IgG, IgM and IgA levels against the spike antigen, its receptor-binding domain and natural and designed mutants. Machine learning algorithms trained on the 2D-MBBA data substantially improve the prediction of neutralization capacity against the authentic SARS-CoV-2 virus of serum samples of convalescent patients. The algorithms also helped identify a set of antibody isotypeâ€"antigen datasets that contributed to the prediction, which included those targeting regions outside the receptor-binding interface of the spike protein. We applied the assay to profile samples from vaccinated, immune-compromised patients, which revealed differences in the antibody profiles between convalescent and vaccinated samples. Our approach can rapidly provide deep antibody profiles and neutralization prediction from essentially a drop of blood without the need of BSL-3 access and provides insights into the nature of neutralizing antibodies. It may be further developed for evaluating neutralizing capacity for new variants and future pathogens.
Keyphrases
- machine learning
- sars cov
- high throughput
- end stage renal disease
- newly diagnosed
- ejection fraction
- respiratory syndrome coronavirus
- binding protein
- big data
- single cell
- gene expression
- peritoneal dialysis
- deep learning
- artificial intelligence
- small molecule
- prognostic factors
- dendritic cells
- patient reported
- patient reported outcomes
- drug delivery
- dna methylation
- rna seq
- immune response
- zika virus
- transcription factor
- cell death
- gram negative
- cancer therapy
- pi k akt
- genome wide
- copy number
- quantum dots
- body composition
- dna binding
- antimicrobial resistance