The Francis Crick Institute
Cytometry Pt A - 2021 - del Molino del Barrio - COVID‐19 Using high‐throughput flow cytometry to dissect clinical (1).pdf (1.91 MB)

COVID-19: Using high-throughput flow cytometry to dissect clinical heterogeneity.

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journal contribution
posted on 2023-02-23, 12:27 authored by Irene Del Molino Del Barrio, Thomas S Hayday, Adam G Laing, Adrian C Hayday, Francesca Di Rosa
Here we consider how high-content flow cytometric methodology at appropriate scale and throughput rapidly provided meaningful biological data in our recent studies of COVID-19, which we discuss in the context of other similar investigations. In our work, high-throughput flow cytometry was instrumental to identify a consensus immune signature in COVID-19 patients, and to investigate the impact of SARS-CoV-2 exposure on patients with either solid or hematological cancers. We provide here some examples of our 'holistic' approach, in which flow cytometry data generated by lymphocyte and myelomonocyte panels were integrated with other analytical metrics, including SARS-CoV-2-specific serum antibody titers, plasma cytokine/chemokine levels, and in-depth clinical annotation. We report how selective differences between T cell subsets were revealed by a newly described flow cytometric TDS assay to distinguish actively cycling T cells in the peripheral blood. By such approaches, our and others' high-content flow cytometry studies collectively identified overt abnormalities and subtle but critical changes that discriminate the immuno-signature of COVID-19 patients from those of healthy donors and patients with non-COVID respiratory infections. Thereby, these studies offered several meaningful biomarkers of COVID-19 severity that have the potential to improve the management of patients and of hospital resources. In sum, flow cytometry provides an important means for rapidly obtaining data that can guide clinical decision-making without requiring highly expensive, sophisticated equipment, and/or "-omics" capabilities. We consider how this approach might be further developed.


Crick (Grant ID: 10093, Grant title: Hayday FC001093)