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Strength in Numbers – Droplet Microfluidics for Multicellular Ensemble Applications
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Nano Biotechnology.ORCID iD: 0000-0002-2081-3629
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Abstract [sv]

Det arbete som presenteras i den här doktorsavhandlingen utforskar multicellulära, biologiska och biotekniska tillämpningar för mikrofluidiska droppar och utnyttjar ett antal unika egenskaper hos dessa miniatyriserade reaktionskärl.

Droppmikrofluidik använder pico- till nanoliterstora vattendroppar i en oljefas som inte löser vatten, och lånar tekniker från området mikrofluidik, nämligen vätskestyrning, detektionssystem och elektronisk kringutrustning. Många av dessa tekniker har möjliggjorts genom upptäckter och uppfinningar som ursprungligen utvecklades för mikroelektronikproduktion och omfattar tillverkning av strukturer i mikrometerskala. Kanaler med bredd och djup i storleksordningen bråkdelsmillimeter möjliggör den tillförlitliga och exakta hantering av vätskor som krävs för att uppnå hög genomströmning med bibehållen noggrannhet.Många underdiscipliner inom biologisk forskning är beroende av storskaliga analyser, som ger strength in numbers, i den meningen att endast ett tillräckligt stort antal prover ger insikt i en organisms genom, transkriptom eller proteom, i populationers heterogenitet eller i ett framtida läkemedels effektivitet. Precis som vissa andra tekniker för analys av enstaka celler, t.ex. flödescytometri, så möjliggör droppmikrofluidik stora antal analyser. Dessutom kan droppmikrofluidik som teknisk plattform bearbeta och analysera flercelliga ensembler eller undersöka extracellulära egenskaper. Detta är särskilt fördelaktigt för biotekniska eller farmaceutiska forskningstillämpningar.

I artikel 1 undersöker vi hur insulinproducerande celler kan kapslas in i mucingel-droppar. Den gel som används kan skydda cellerna, till exempel efter en transplantation, från ett kraftigt immunsvar, samtidigt som den tillåter passage av näringsämnen och gaser samt spridning av utsöndrat insulinet.

I artikel II presenterar vi ett arbetsflöde för droppassisterad sfäroidbildning för produktion och analys med hög genomströmning. Vi använder deep learning för att träna en modell som stöd för optimering av inkubationsförhållanden i dropparna. De resulterande minisfäroiderna möjliggör storskalig screening med 3D-cellkulturmodeller.

Artikel 3 handlar om utveckling och utvärdering av ett litet och bärbart lågkostnads-instrument med enbart kommersiellt tillgängliga komponenter och visar dess mångsidighet genom att dynamiskt anpassa dropparnas storlek och sammansättning. Slutligen visade vi att instrumentet kan användas för inkapsling av primära mänskliga celler för att bilda sfäroider i ett biosäkerhetsskåp.

I artikel 4 använder vi mikrofluidiska droppar för att förbättra biotekniska screening-kampanjer. Vi undersöker mikrokolonier av jäst i stället för enskilda celler i droppar för att mäta ett genomsnittligt värde för flera celler med samma arvsmassa. Detta medelvärde är mer informativt än en mätning av enskilda celler, eftersom det minskar mätvariationen på grund av minimala variationer celler emellan som annars skulle förhindra utsortering av de bästa cellvarianterna.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2022. , p. 67
Series
TRITA-CBH-FOU ; 2022:66
Keywords [en]
Droplet Microfluidics, High-Throughput Screening, Microtissues, Microreactors, Cell Factories, Cell Culture, Biomaterials, Spheroids
National Category
Engineering and Technology
Research subject
Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-321636ISBN: 978-91-8040-438-9 (print)OAI: oai:DiVA.org:kth-321636DiVA, id: diva2:1711922
Public defence
2022-12-20, Air & Fire, Science for Life Laboratory, Tomtebodavägen 23A, via Zoom: https://kth-se.zoom.us/j/62767518179, Solna, 10:00 (English)
Opponent
Supervisors
Note

QC 2022-11-21

Available from: 2022-11-21 Created: 2022-11-18 Last updated: 2023-04-04Bibliographically approved
List of papers
1. Immune-Modulating Mucin Hydrogel Microdroplets for the Encapsulation of Cell and Microtissue
Open this publication in new window or tab >>Immune-Modulating Mucin Hydrogel Microdroplets for the Encapsulation of Cell and Microtissue
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2021 (English)In: Advanced Functional Materials, ISSN 1616-301X, E-ISSN 1616-3028, Vol. 31, no 42, p. 2105967-2105967Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Wiley, 2021
Keywords
Electrochemistry, Condensed Matter Physics, Biomaterials, Electronic, Optical and Magnetic Materials
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:kth:diva-306074 (URN)10.1002/adfm.202105967 (DOI)000678111400001 ()2-s2.0-85110951038 (Scopus ID)
Funder
Swedish Foundation for Strategic ResearchSwedish Research CouncilGerman Research Foundation (DFG)
Note

QC 20211221

Available from: 2021-12-14 Created: 2021-12-14 Last updated: 2026-03-25Bibliographically approved
2. High-throughput cell spheroid production and assembly analysis by microfluidics and deep learning
Open this publication in new window or tab >>High-throughput cell spheroid production and assembly analysis by microfluidics and deep learning
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

3D cell culture models are an important tool in translational research but have been out of reach for high-throughput screening due to complexity, requirement of large cell numbers and inadequate standardization. Here, we present a high-throughput workflow to produce and characterize the formation of miniaturized spheroids using deep learning. We train a convolutional neural network (CNN) for cell ensemble morphology classification, benchmark it against more conventional image analysis, and characterize spheroid assembly determining optimal surfactant concentrations and incubation times for spheroid production for three cell lines with different spheroid formation properties. Notably, this format is compatible with large-scale spheroid production and screening. The presented workflow and CNN offer a template for large scale minispheroid production and analysis and can be extended and re-trained to characterize morphological responses in spheroids to additives, culture conditions and large drug libraries.

Keywords
High Throughput Screenings • Microreactors • Machine Learning • Cell Spheroids
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-321614 (URN)
Funder
Knut and Alice Wallenberg FoundationVinnova
Note

QC 20221129

Available from: 2022-11-18 Created: 2022-11-18 Last updated: 2022-11-29Bibliographically approved
3. A Portable, Negative-Pressure Actuated, Dynamically Tunable Microfluidic Droplet Generator
Open this publication in new window or tab >>A Portable, Negative-Pressure Actuated, Dynamically Tunable Microfluidic Droplet Generator
2022 (English)In: Micromachines, E-ISSN 2072-666X, Vol. 13, no 11, p. 1823-1823Article in journal (Refereed) Published
Abstract [en]

Droplet microfluidics utilize a monodisperse water-in-oil emulsion, with an expanding toolbox offering a wide variety of operations on a range of droplet sizes at high throughput. However, translation of these capabilities into applications for non-expert laboratories to fully harness the inherent potential of microscale manipulations is woefully trailing behind. One major obstacle is that droplet microfluidic setups often rely on custom fabricated devices, costly liquid actuators, and are not easily set up and operated by non-specialists. This impedes wider adoption of droplet technologies in, e.g., the life sciences. Here, we demonstrate an easy-to-use minimal droplet production setup with a small footprint, built exclusively from inexpensive commercially sourced parts, powered and controlled by a laptop. We characterize the components of the system and demonstrate production of droplets ranging in volume from 3 to 21 nL in a single microfluidic device. Furthermore, we describe the dynamic tuning of droplet composition. Finally, we demonstrate the production of droplet-templated cell spheroids from primary cells, where the mobility and simplicity of the setup enables its use within a biosafety cabinet. Taken together, we believe this minimal droplet setup is ideal to drive broad adoption of droplet microfluidics technology.

Place, publisher, year, edition, pages
MDPI AG, 2022
National Category
Biomedical Laboratory Science/Technology Other Medical Biotechnology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-321611 (URN)10.3390/mi13111823 (DOI)000883971900001 ()36363843 (PubMedID)2-s2.0-85141745865 (Scopus ID)
Funder
Vinnova, 2018-03338Swedish Foundation for Strategic Research, FFF20-0027Knut and Alice Wallenberg Foundation, 2016.0077
Note

QC 20221129

Available from: 2022-11-18 Created: 2022-11-18 Last updated: 2024-01-17Bibliographically approved
4. High-throughput fluorescence area sorting of droplet microfluidic S. cerevisiae microcolonies
Open this publication in new window or tab >>High-throughput fluorescence area sorting of droplet microfluidic S. cerevisiae microcolonies
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Cellular heterogeneity in isogenic cell populations is a major obstacle for single-cell screening campaigns, as the phenotype of individual cells might differ drastically from the mean, leading to large overlaps between productivity assessments of populations. At the other end of the spectrum, isogenic bulk assays provide a more accurate picture of a strain’s capacity at production scale, but suffers from low throughput and high reagent consumption.

Here, we present a screening format for cell factory variant libraries, aiming at combining the advantages of single-cell screening and bulk assay formats. Using microfluidic droplets, we compartmentalize yeast cell producer candidates, culture them to form isogenic microcolonies and sort colonies at higher throughput than bulk experiments to assess the genetic potential more accurately than in a single-cell screening format. To this end, we developed a fluorescence area-based sorting method that integrates the fluorescence signal from the entire fluorescence profile of a droplet and bases the sorting decision on that integrated fluorescence area. We validate the concept by sorting droplet microcolonies of fluorescent protein expressing Escherichia coli. Finally, we successfully sorted encapsulated iso-genic microcolonies of a low-producing and a high-producing strain of Saccharomyces cerevisiae by Triacylglycerol (TAG) production at 220 Hz, enriching the high-producing strain 4.45-fold.

National Category
Bioenergy
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-321635 (URN)
Note

QC 20221129

Available from: 2022-11-18 Created: 2022-11-18 Last updated: 2022-11-29Bibliographically approved

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