Skip to main content

Strength in Numbers – Droplet Microfluidics for Multicellular Ensemble Applications

Time: Tue 2022-12-20 10.00

Location: Air & Fire, Science for Life Laboratory, Tomtebodavägen 23A, Solna

Video link: https://kth-se.zoom.us/j/62767518179

Language: English

Subject area: Biotechnology

Doctoral student: Martin Trossbach , Nanobioteknologi

Opponent: Professor Nicole Pamme, Stockholms Universitet

Supervisor: Professor Aman Russom, Nanobioteknologi, Science for Life Laboratory, SciLifeLab; Universitetslektor Håkan Jönsson, Nanobioteknologi, Science for Life Laboratory, SciLifeLab, Proteinvetenskap

Export to calendar

QC 2022-11-21

Abstract

The work presented in this doctoral thesis explores multicellular, biological, and biotechnological applications for microfluidic droplets, making use of a number of unique features of these miniaturized, highly scalable reaction vessels.

Droplet microfluidics specializes in pico- to nanoliter sized aqueous droplets in an immiscible oil phase, borrowing techniques from the field of microfluidics, namely fluid actuation, detection systems and electronic peripherals. A lot of these techniques have been made possible by discoveries and inventions originally developed for microelectronics and relate to the fabrication of micrometer scale features. Channels with a width and depth of fractions of a millimeter allow for the reliable and precise manipulation of fluids necessary to achieve high throughput while maintaining accuracy.

Many subdisciplines of biological research rely on scale, on strength in numbers, in a sense that only a sufficient number of samples enables insights into the genome, transcriptome, or proteome of an organism, into the heterogeneity of populations, into the efficacy of a prospective drug. Just like some other single-cell analysis techniques, such as flow cytometry, droplet microfluidics facilitates that scale of analysis. However, in addition to this, droplet microfluidics as a technology platform is capable of processing and analyzing multicellular ensembles, or interrogating extracellular traits. This is especially beneficial for biotechnological or pharmaceutical research applications.

In Paper I, we investigated the encapsulation of insulin secreting cells in mucin gel beads. The gel protects the cells against a host’s immune system response while allowing for nutrient and gas passage as well as diffusion of the secreted insulin.

In Paper II, we present a high-throughput production and analysis workflow for droplet-assisted spheroid formation. We use deep learning to train a model to support the optimization of droplet incubation conditions. The resulting minispheroids enable large-scale 3D cell culture model screening.

In Paper III, we developed and characterized a portable, compact droplet generation setup, using exclusively commercially available parts and demonstrated its versatility by dynamically tuning droplet size and composition. Finally, we demonstrated its use for the encapsulation of human primary cells to form spheroids in the sterile environment of a biosafety cabinet.

For Paper IV, we developed an integrated fluorescence area sorting approach to sort cell colonies in microfluidic droplets. After validating the sorter, we screened yeast microcolonies in droplets and used averaging over the entire droplet width to ameliorate the impact of cell heterogeneity within isoclonal populations.

urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-321636