Neutrophils are a vital component of the innate immune system and play an essential function in the recognition and clearance of bacterial and fungal pathogens. There is great interest in understanding mechanisms of neutrophil dysfunction in the setting of disease and deciphering potential side effects of immunomodulatory drugs on neutrophil function. We developed a high throughput flow cytometry-based assay for detecting changes to four canonical neutrophil functions following biological or chemical triggers. Our assay detects neutrophil phagocytosis, reactive oxygen species (ROS) generation, ectodomain shedding, and secondary granule release in a single reaction mixture. By selecting fluorescent markers with minimal spectral overlap, we merge four detection assays into one microtiter plate-based assay. We demonstrate the response to the fungal pathogen, Candida albicans and validate the assay’s dynamic range using the inflammatory cytokines G-CSF, GM-CSF, TNFα, and IFNγ. All four cytokines increased ectodomain shedding and phagocytosis to a similar degree while GM-CSF and TNFα were more active in degranulation when compared to IFNγ and G-CSF. We further demonstrated the impact of small molecule inhibitors such as kinase inhibition downstream of Dectin-1, a critical lectin receptor responsible for fungal cell wall recognition. Bruton’s tyrosine kinase (Btk), Spleen tyrosine kinase (Syk), and Src kinase inhibition suppressed all four measured neutrophil functions but all functions were restored with lipopolysaccharide co-stimulation. This new assay allows for multiple comparisons of effector functions and permits identification of distinct subpopulations of neutrophils with a spectrum of activity. Our assay also offers the potential for studying the intended and off-target effects of immunomodulatory drugs on neutrophil responses.

Interleukin-6 (IL-6) has been linked to several life-threatening disease processes. Developing a point-of-care testing platform for the immediate and accurate detection of IL-6 concentrations could present a valuable tool for improving clinical management in patients with IL-6-mediated diseases. Drawing on an available biobank of samples from 35 patients hospitalized with COVID-19, a novel quantum-magnetic sensing platform is used to determine plasma IL-6 concentrations. A strong correlation was observed between IL-6 levels measured by QDTI10x and the Luminex assay (r = 0.70, p-value < 0.001) and between QDTI80x and Luminex (r = 0.82, p-value < 0.001). To validate the non-inferiority of QDTI to Luminex in terms of the accuracy of IL-6 measurement, two clinical parameters—the need for intensive care unit admission and the need for mechanical intubation—were chosen. IL-6 concentrations measured by the two assays were compared with respect to these clinical outcomes. Results demonstrated a comparative predictive performance between the two assays with a significant correlation coefficient. Conclusion: In short, the QDTI assay holds promise for implementation as a potential tool for rapid clinical decision in patients with IL-6-mediated diseases. It could also reduce healthcare costs and enable the development of future various biomolecule point-of-care tests for different clinical scenarios.

Fever is a common presentation to urgent-care services and is linked to multiple disease processes. To rapidly determine the etiology of fever, improved diagnostic modalities are necessary. This prospective study of 100 hospitalized febrile patients included both positive (FP) and negative (FN) subjects in terms of infection status and 22 healthy controls (HC). We evaluated the performance of a novel PCR-based assay measuring five host mRNA transcripts directly from whole blood to differentiate infectious versus non-infectious febrile syndromes as compared to traditional pathogen-based microbiology results. The FP and FN groups observed a robust network structure with a significant correlation between the five genes. There were statistically significant associations between positive infection status and four of the five genes: IRF-9 (OR = 1.750, 95% CI = 1.16–2.638), ITGAM (OR = 1.533, 95% CI = 1.047–2.244), PSTPIP2 (OR = 2.191, 95% CI = 1.293–3.711), and RUNX1 (OR = 1.974, 95% CI = 1.069–3.646). We developed a classifier model to classify study participants based on these five genes and other variables of interest to assess the discriminatory power of the genes. The classifier model correctly classified more than 80% of the participants into their respective groups, i.e., FP or FN. The GeneXpert prototype holds promise for guiding rapid clinical decision-making, reducing healthcare costs, and improving outcomes in undifferentiated febrile patients presenting for urgent evaluation.