Label-free single particle analysis and separation

Abstract

Analysing and separating single particles are crucial processes in many biomedical applications. Particles (cells) are usually present as heterogeneous populations, and retrieval and analysis of single particles frequently relies on specific biochemical “labels” (which commonly involve expensive and complex protocols). As a result, there is an increasing interest in performing analysis and separation with “label-free” methods, i.e., solely relying on the particle’s inherent biophysical properties or phenotype, such as size or dielectric properties.

This thesis describes methods for the analysis of human pathogenic organisms using microfluidic impedance cytometry (MIC), a label-free, single-cell analysis technique. The first of these is the water-borne protozoan Cryptosporidium parvum. Current detection methods cannot speciate or assess the viability these pathogens. Experiments with MIC revealed both a high degree of discrimination between viable and non-viable parasites, and a high level of discrimination between pathogenic (C. parvum and Giardia lamblia) and non-pathogenic (C. muris) species.

Cells infected with intracellular pathogens, specifically malaria parasite-infected erythrocytes and leishmania-infected macrophages, were also analysed using MIC. By fitting the impedance data with multi-shell models the dielectric properties of erythrocytes and malaria parasites were estimated at various stages of infection. Finally, dielectric analysis of leishmania-infected macrophages at different activation states were also analysed, but these showed little variation in their biophysical characteristics.

Label-free methods for the separation of single particles were also described. This was done using deterministic lateral displacement (DLD), a label-free, size-based sorting technique. This technique was integrated with MIC, permitting single-cell level identification of enriched target cells. The integrated system was used to enrich for the blood dwelling parasites Trypanosoma cyclops from a blood sample with high specificity and sensitivity.

In summary, the integration of label-free methods for analysis and separation of rare single particles moves a step forward towards the goal of simpler point-of-care analytical technologies to diagnose and analyse human pathogens.

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Identifiers

ORCID for Carlos Honrado: orcid.org/0000-0002-4151-2147

ORCID for Hywel Morgan: orcid.org/0000-0003-4850-5676

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