Cellular therapy is emerging as a clinically viable strategy in the field of solid organ transplantation, where it is expected to reduce the dependency on conventional immunosuppression. This has produced a demand for highly sensitive methods to monitor the persistence and tissue distribution of administered cells in vivo. However, tracking cells presents significant challenges. In many cases transplanted cells are autologous with the immune system of the transplant recipient, and hence are invisible to typical methods of detection. To enable their differentiation, the cells must be labelled with a suitable, non-toxic and long lifetime label, prior to their administration to patients. In addition, administered cells represent only a small fraction of the recipient's endogenous cells, which necessitates the use of an extremely sensitive detection method. Laser ablation – inductively coupled plasma – mass spectrometry (LA-ICP-MS) is an exquisitely sensitive analytical technique, capable of imaging trace elements in complex samples, at high spatial resolution.

DNA methylation is an important epigenetic mark spanning all of life's kingdoms. In humans, DNA methylation has been associated with a wide range of age-related pathologies, including type II diabetes and cancer. More recently, in humans, changes in DNA methylation at specific positions in the genome have been found to be predictive of chronological age. Interestingly, DNA methylation age is also predictive of health status and time-to-death. A better understanding of what these DNA methylation changes represent and whether they might be causative in the ageing process will be important to ascertain. However, at present there is no animal model system with which this process can be studied at a mechanistic level. Furthermore, it is becoming increasingly apparent that many disease states that increase in prevalence with age are not caused by all cells within the individual, but are often the result of changes to a subset of cells. This underscores the importance of studying these processes at the single cell level. The recent advances in single cell sequencing approaches now mean that we can study multiple layers of biology within the same single cell, such as the epigenome and the transcriptome (scM&T-Seq). Unfortunately, we are still only able to probe these important aspects of single cell biology in a static sense. This is a major limitation in the study of ageing because ageing and age-related disease processes are inherently dynamic. As such, it is incumbent upon us to develop approaches to assay single cell biology in a dynamic manner. 
In this thesis, I describe an epigenetic age predictor in the mouse. This predictor is tissue-independent and can accurately predict age (with an error of 3.33 weeks) and can record deviations in biological age upon interventions including ovariectomy and high fat diet both of which are known to reduce lifespan. Next, I describe the analysis of a homogeneous population of muscle satellite cells (MuSCs) that I have interrogated at the single cell level, using single cell combined transcriptome and methylome sequencing (scM&T-seq). I found that with age there was increased global transcriptional variability and increased feature-specific methylome variability. These findings explain the loss of functionality of these cells with age. Lastly, I describe two imaging approaches to study DNA methylation dynamically in single cells. Using these methods, I demonstrate that it is possible to accurately determine methylation status across a wide spectrum of global methylation levels and that by using such approaches novel information about dynamic methylation processes can be obtained. These methods represent the first to study DNA methylation dynamically.

Miniaturization of biological analysis is a trend in the field of biotechnology aiming to increase resolution and sensitivity in biological assays. Decreasing the reaction volumes to analyze fewer analytes in each reaction vessel enables the detection of rare analytes in a vast background of more common variants. Droplet microfluidics is a high throughput technology for the generation, manipulation and analysis of picoliter scale water droplets an in immiscible oil. The capacity for high throughput processing of discrete reaction vessels makes droplet microfluidics a valuable tool for miniaturization of biological analysis. In the first paper, detection methods compatible with droplet microfluidics was expanded to include SiNR FET sensors. An integrated droplet microfluidics SiNR FET sensor device capable of extracting droplet contents, transferring a train of droplets to the SiNR to measure pH was implemented and tested. In paper II, a workflow was developed for scalable and target flexible multiplex droplet PCR using fluorescently color-coded beads for target detection. The workflow was verified for concurrent detection of two microorganisms infecting poultry. The detection panel was increased to multiple targets in one assay by the use of target specific capture probes on color-coded detection beads.   In paper III, droplet microfluidics has been successfully applied to single cell processing, demonstrated in paper III, where reverse transcription was performed on 65000 individually encapsulated mammalian cells. cDNA yield was approximately equivalent for reactions performed in droplets and in microliter scale. This workflow was further developed in paper IV to perform reverse transcription PCR in microfluidic droplets for detection of exosomes based on 18S RNA content. The identification of single exosomes based on RNA content can be further developed to detect specific RNA biomarkers for disease diagnostics. Droplet microfluidics has great potential for increasing resolution in biological analysis and to become a standard tool in disease diagnostics and clinical research. / <p>QC 20171024</p>

This thesis focuses on the investigation and development of an integrated optical biosensor based on enhanced Raman techniques that will provide label-free detection of biomolecules. This is achieved by using hollow core photonic crystal fibers (HC-PCF), nanoparticles, or both. HC-PCF is a unique type of optical fiber, with continuous ‘channels’ of air (typically) running the entire length. The channels serve to confine electromagnetic waves in the core of the fiber, and tailor its transmission properties. Using HC-PCF as a biosensor requires development of a robust technique to fill hollow-core photonic crystal fibers. Though several groups have reported selective filling of HC-PCF’s core, the processes are cumbersome and limit the choice of liquid to avoid multimode behavior. In my Master’s thesis, I presented a simple technique to non-selectively fill all the HC-PCF channels with samples. The non-selective filling preserves the photonic bandgap property of the fiber, and yields an extremely strong interaction of light and the sample that produces considerable enhancement of the Raman signal from the analyte. Up to now, non-selective filling was accomplished through capillary action and it delivered a Raman signal enhancement of approximately 30-fold, which is not sensitive enough to detect biomolecules at the clinical level. Moreover, there were issues of reliability and reproducibility, due to evaporation, filling and coupling light into the fiber. The objective of this PhD research was to overcome these problems by developing a robust optical fiber platform based on Raman spectroscopy that can be used in a clinical setting. I initially focused on heparin, an important blood anti-coagulant that requires precise monitoring and control in patients undergoing cardiac surgery or dialysis. Since the Raman spectra of heparin-serum mixtures exhibits Raman peaks of heparin with poor signal-to-noise ratios, I concentrated on enhancing the heparin Raman signal and filtering out the spectral background of the serum to improve detection sensitivity. Reaching maximum enhancement of the Raman signal required a strong interaction of light and analyte, which can be achieved by using hollow core photonic crystal fiber as I had used in my Master’s research. Using a small piece of HC-PCF I was able to reach an enhancement in the heparin Raman signal of greater than 90-fold. With this degree of enhancement, I was able to successfully detect and monitor heparin in serum at clinical levels, something that had never been accomplished previously. After developing HC-PCF as a Raman signal enhancer, I focused on making the HC-PCF sensor robust, reliable and reusable. This was achieved by integrating the HC-PCF with a differential pressure system that allowed effective filling, draining and refilling of the samples in an HC-PCF, under identical optical conditions. To demonstrate the device’s detection capabilities, various concentrations of aqueous ethanol and isopropanol, followed by different concentrations of heparin and adenosine in serum, were successfully monitored. To further improve the sensitivity of the HC-PCF based Raman sensor, I incorporated surface enhanced Raman scattering (SERS), by introducing nanoparticles into the HC-PCF fibers. The research focused on determining the optimal volume and size of silver nanoparticles to achieve maximum enhancement of the Raman signal in the HC-PCF. The HC-PCF enhanced the Raman signal of Rhodamine 6G (R6G) approximately 90-fold. In addition, the optimal size and volume of AgNP enhanced the Raman signal of R6G approximately 40-fold, leading to a total enhancement of approximately 4,000 in HC-PCF. This was then used to demonstrate the application of a SERS based HC-PCF sensing platform in monitoring adenosine (a clinically important molecule), as well as malignant cells such as leukemia. Finally, I used hollow core crystal fibers to significantly enhance the efficiency of two-photon photochemistry. Although two-photon photochemical reactions are difficult to achieve with a small volume, I accomplished it by using a novel platform of HC-PCF to efficiently execute the two-photon induced photodecarbonylation reaction of cyclopropenone 1, and its conversion to the corresponding acetylene. The simple optical design configuration involved coupling an 800-nm tsunami laser to a short piece of HC-PCF filled with the sample. This allowed me to increase the efficiency of two-photon induced photochemistry by 80-fold, compared to a conventional spectrophotometer cuvette. Thus, this work leads to the use of HC-PCFs to more effectively study two-photon induced photochemistry processes, which was limited due to the difficulty of detecting photochemical events with a small excitation volume.

Microorganisms are ubiquitously distributed on the earth and drive the fundamental element cycling in the biosphere. Their metabolic activities serve human societies in countless areas such as biotechnological engineering, food engineering, energy production, waste disposal et cetera. For human beings, and also for animals, microorganisms are imperative for health especially as colonizers of the gut system. Microbial resource management, especially when complex communities are exploited in biotechnology is a key challenge. Therefore, communities are more and more in the focus of basic research in microbiology complementary to pure cultivation technologies. Owing to their complexity, microbial communities are almost exclusively studied on the basis of bulk parameters and empirical expert knowledge. Bulk parameters are representative for an entire community performance but do not allow a segregated analysis of subpopulations or subcommunities, let alone individuals and their disparate functions within a community. This thesis aims to resolve microbial community properties and mechanisms of assembly in managed ecosystems on the individual level (i.e. single cell). For this the flow cytometric toolbox was employed and further expanded, which phenotypically classifies microbial individuals into sub-communities according to their physiological similarities. Workflows for the fast analysis and evaluation of dynamics in community structure, assembly and interaction were developed. Stability properties of communities, i.e. resistance, resilience, displacement speed and elasticity, can now quantitatively be determined based on cytometric data. For resilience behavior an on-line tool was developed. In addition, the relative proportions of neutral and deterministic forces that structure a microbial community can now be unraveled. As consequence, microbial flow cytometry has been proven to be a powerful tool for analysing complex microbial communities, and will allow huge improvements in understanding and control of microbial communities in managed and natural ecosystems.:Contents Summary ............................................................................................................. I Zusammenfassung ........................................................................................... IV 1 Introduction ..................................................................................................... 1 1.1 Microbial community and ecology ........................................................... 1 1.1.1 What is a microbial community? ...................................................... 1 1.1.2 Flow cytometry as a tool to study microbial communities ................ 2 1.2 Community structure and diversity ........................................................ 10 1.2.1 Community structure...................................................................... 10 1.2.2 Diversity metrics ............................................................................ 10 1.2.3 Evaluating structure and diversity with flow cytometry ................... 12 1.3 Community assembly and dynamics ..................................................... 13 1.3.1 Basic assembly processes ............................................................ 13 1.3.2 Evaluating assembly processes with flow cytometry ..................... 16 1.4 Community interactions ......................................................................... 18 1.4.1 Abiotic interactions of microbes and their surroundings................. 18 1.4.2 Biotic interactions of microbial partners ......................................... 18 1.4.3 Evaluating interactions with flow cytometry ................................... 20 1.5 Community functions ............................................................................. 22 1.5.1 Omics approaches to study functions in microbial communities .... 22 1.5.2 Evaluating functions with flow cytometry ....................................... 23 1.6 Aims of this study .................................................................................. 25 2 Publications .................................................................................................. 27 2.1 Overview of publications ....................................................................... 27 2.2 Published articles .................................................................................. 28 2.2.1 Publication 1 .................................................................................. 29 2.2.2 Publication 2 .................................................................................. 42 2.2.3 Publication 3 (under review) .......................................................... 60 3 Discussion .................................................................................................... 81 3.1 The importance of perceiving ecological situations ............................... 81 3.2 Stability properties of a microbial community ........................................ 84 3.3 Assembly processes in insular environments ....................................... 87 3.3.1 Niche differentiation under balanced cultivation conditions ........... 88 3.3.2 Neutral assembly under balanced cultivation conditions ............... 89 3.3.3 From intermediate disturbance to a non‐equilibrium system ......... 90 3.4 On-line analysis of reactor data ............................................................ 93 3.5 Conclusion and outlook ......................................................................... 95 4 References ................................................................................................... 97 5 Acknowledgement ...................................................................................... 105 6 Appendix .................................................................................................... 106 6.1 Declaration of independent work ......................................................... 106 6.2 Author contributions of published articles............................................ 107 6.3 Curriculum vitae .................................................................................. 111 6.4 List of Publications and conference contributions ............................... 112 6.5 Supplementary materials .................................................................... 113 6.5.1 Supplementary material for publication 1 .................................... 113 6.5.2 Supplementary material for publication 2 .................................... 140 6.5.3 Supplementary material for publication 3 .................................... 174

Optical diffraction tomography (ODT) is a tomographic technique that can be used to measure the threedimensional (3D) refractive index distribution within living cells without the requirement of any marker. In principle, ODT can be regarded as a generalization of optical projection tomography which is equivalent to computerized tomography (CT). Both optical tomographic techniques require projection-phase images of cells measured at multiple angles. However, the reconstruction of the 3D refractive index distribution post-measurement differs for the two techniques. It is known that ODT yields better results than projection tomography, because it takes into account diffraction of the imaging light due to the refractive index structure of the sample. Here, we apply ODT to biological cells in a micro uidic chip which combines optical trapping and microfluidic flow to achieve an optofluidic single-cell rotation. In particular, we address the problem that arises when the trapped cell is not rotating about an axis perpendicular to the imaging plane, but instead about an arbitrarily tilted axis. In this paper we show that the 3D reconstruction can be improved by taking into account such a tilted rotational axis in the reconstruction process.

Titanium alloys are frequently used in the medical field as bone implant materials due to their excellent biocompatibility and corrosion resistance. Yet, their elastic modulus is usually significantly higher than the one of bone, which can lead to a reduction of bone tissue at the implant site. The current research is therefore focused on the development of highly porous implants, which promise a low elastic modulus close to that of bone, an enhanced bone ingrowth and an improved vascularization. However, the appropriate pore size for an optimal osseointegration still remains unclear. To that end, a transparent tubular microsystem is developed to mimic such a porous microenvironment in order to study single bone cell behavior and early bone formation processes. The system is fabricated out of an implant material (β-stabilized Ti-45Nb (wt%)). It is demonstrated that the bulk material composition, which is consisting of a high Nb content, can be closely transferred to transparent thin films by using reactive sputtering. These films then self-assemble into tubular microscaffolds (TS) with a diameter range between 10-42 μm. Biological studies are subsequently performed to investigate the response (e.g. cell adhesion, migration, osteogenic differentiation) of human Mesenchymal Stem Cells (MSC) to the TS. It is shown that cells form fewer, more diffuse focal adhesion points inside the TS compared to a planar surface and the spatial confinement causes a switch in between amoeboid and mesenchymal migration modes. In addition, it is demonstrated that cells can survive inside the TS for at least 12 days during osteogenic differentiation and partly mineralize the TS interior. The observed mineralization process is furthermore linked to the formation of hydroxyapatite crystals inside dead cells bodies, which leads to a crystallization over time. All in all, the TS platform offers an easy way to identify key factors of bone cell-implant interactions that can be used to improve the biocompatibility of the bone-implant interface in the future.

No description available.

Die Grundlage der Entwicklung multizellulärer Lebewesen bildet die Herausbildung stabiler Zelllinien aus einer einzelnen Zygote. Die Expression spezifischer Kombinationen von Transkriptionsfaktoren ist von zentraler Bedeutung für diesen Prozess. Des Weiteren sind epigenetische Veränderungen des Genoms von Bedeutung, über deren Verhältnis zu Änderungen der Zell-Identitäten weniger bekannt ist. In dieser Arbeit nutze ich Daten aus scATAC-seq und scRNA-seq (mit metabolischer Markierung; scSLAM-seq) um die regulierenden Elemente im Seeigel zu charakterisieren – vom 4-Zell-Stadium, über die Aktivierung des zygotischen Genoms, bis hin zu den Strukturen der frühen Pluteus-Larve. Die Schicksale der einzelnen Zellen des Seeigels sind gut erforscht und ab der vierten Zellteilung etabliert (auch wenn einzelne Veränderungen bis zum 128-Zell Stadium induziert werden können), wonach die Keimblätter fest verankert sind. Plastizität innerhalb der Keimblätter ist mindestens bis zum Ende der Gastrulation möglich. Mithilfe dieser Daten, sowie den bekannten Ergebnissen der Erforschung der Zellschicksale vergangener Jahrzehnte, ist eine Diversifizierung von Zelltypen ersichtlich, die beim 128-Zell-Stadium mit der großen Welle der zygotischen Genomaktivierung (ZGA), einer Veränderung des Chromatinzustandes und dem Verlust der Entwicklungsplastizität einhergeht. Ein kleiner Teil von Genen, im Allgemeinen zelltypspezifische Transkriptionsfaktoren, wird schon vor der großen Welle der ZGA exprimiert, während sich gut offene Chromatinstrukturen auf wenige, distinkte regulatorische Sequenzen beschränken. Von diesem Zeitpunkt an, wird die Genexpression zelltypspezifisch, auch wenn viele Chromatinelemente weiterhin zelltypübergreifend offen sind. Insgesamt sind die Chromatinelemente recht kompakt und Elemente innerhalb der Gene häufig. Danach porträtiere ich noch die regulatorischen Veränderungen die mit der neuralen Entwicklung, sowie der Diversität von skelettbildenden Zellen im Seeigel einhergehen. Zuletzt identifiziere ich ~ 100 Gene, die in die Kalzifizierung des Skelettes des Seeigels involviert sind. / The emergence of multiple, stable cell lineages from a single-cell zygote is the essence of multicellular development. Combinatorial transcription factor expression is central to this process, as well as epigenetic changes whose relationship to changes in cell-identity are far less well understood. In this thesis, I use data from scATAC-seq and scRNA-seq (with metabolic labeling; scSLAM-seq) to characterize the regulatory landscapes of sea urchin development spanning from the 4-cell embryo through maternal zygotic transition (MZT), gastrulation, and the early pluteus larvae with its ecologically relevant structures (~72h). The early fate-map in sea urchins is well understood, providing an ideal model for this analysis; the basic fate-map is established by the fourth cleavage (though inducible lineage changes are possible up to the 128-cell stage) after which germ-layer identity is locked, though there remains considerable plasticity within lineages at least through gastrulation. Using these data, along-side classic research into cell fate maps in the early embryo, I find that cell-type diversification and a loss of plasticity at 128-cell stage corresponds to a major wave of zygotic genome activation (ZGA) and a clear resolution of the chromatin landscape in the sea urchin. However, a subset of genes, often cell-type-specific transcription factors, shows evidence of pre-MZT zygotic expression with early chromatin accessibility limited to few sites with distinct regulatory sequences. From this time, gene expression profiles become highly cell-type-specific, though many regulatory elements remain ubiquitously accessible, suggesting differential transcription factor occupancy at broadly accessible sites. Overall, the regulatory landscape is fairly compact with accessible intragenic elements being frequent. Subsequently, I profile the regulatory changes underlying neurodevelopment and the diversity of skeletogenic cells in the sea urchin. Finally, I also identify ~ 100 genes that are associated with calcification of the sea urchin skeleton.

Single-cell analysis means to analyze cells on an individual level. This individual analysis enhances the investigation of the heterogeneity among and the classification of individual cells. Single-cell analysis is a broad term and can include various measurements. This thesis utilizes single-cell RNA sequence data that measures RNA sequences representing genes for individual cells. This data is often high-dimensional, with tens of thousands of RNA sequences measured for each cell. Dimension reduction is therefore necessary when analyzing the data. One proposed dimension reduction method is the unsupervised machine learning method variational autoencoders. The scVI framework has previously implemented a variational autoencoder for analyzing single-cell RNA sequence data. The variational autoencoder of the scVI has one latent space with a Gaussian distribution. Several extensions have been made to the scVI framework since its creation. This thesis proposes an additional extension consisting of a variational autoencoder with two latent spaces, called hybridVI. One of these latent spaces has a Gaussian distribution and the other a von Mises-Fisher distribution. The data is separated between these two latent spaces, meaning that some of the genes go through one latent space and the rest go through the other. In this thesis the cell cycle genes go through the von Mises-Fisher latent space and the rest of the genes go through the Gaussian latent space. The motivation behind the von Mises-Fisher latent space is that cell cycle genes are believed to follow a circular distribution. Putting these genes through a von Mises-Fisher latent space instead of a Gaussian latent space could provide additional insights into the data. The main focus of this thesis was to analyze the impact this separation. The analysis consisted of comparing the performance of the hybridVI model, to the original scVI variational autoencoder. The comparison utilized three annotated datasets, one peripheral blood mononuclear cell dataset, one cortex cell dataset, and one B cell dataset collected by the Henriksson lab at Umeå University. The evaluation metrics used were the adjusted rand index, normalized mutual information and a Wilcoxon signed ranks test was used to determine if the results had statistical significance. The results indicate that the size of the dataset was essential for achieving robust and statistically significant results. For the two datasets that yielded statistically significant results, the scVI model performed better than the hybridVI model. However, more research analyzing biological aspects is necessary to declare the hybridVI model’s effect on the biological interpretation of the results. / Individuell cellanalys är en relativt ny metod som möjliggör undersökning av celler på indivudiell nivå. Det här examensarbetet analyserar RNA sekvens data, där RNA sekvenser är specifierade för individuella celler. Den här sortens data är ofta högdimensionell med flera tusen gener noterade för varje cell. För att möjliggöra en analys av den här datan krävs någon form av dimensionreducering. En föreslagen metod är den ovövervakade maskininlärningsmetoden variational autoencoders. Ett ramverk, scVI, har framtagit en variational autoencoder designad för att hantera den här sortens data. Den här modellen har endast en latentrymd med en normalfördelning. Det här examensarbetet föreslår en utökning av det här ramverket med en variational autoencoder med två latentrymder,där den ena är normalfördelad och den andra följer en von Mises-Fisher fördelning. Motiveringen till en sådan fördelning är att cellcykelgener är antagna att tillhöra en cirkulär fördelning. Cellcykelgenerna i datan kan därmed hanteras av den cirkulära latentrymden. Huvudfokuset i den här studien är att undersöka om den här separationen av gener kan förbättra modellens förmåga att hitta korrekta kluster. Experimentet utfördes på tre annoterade dataset, ett som bestod av perifera mononukleära blodceller, ett som bestod av hjärnbarksceller och ett som bestod av B celler insamlat av Henrikssongruppen vid Umeå universitet. Modellen från scVI ramverket jämfördes med den nya metoden med två latentrymder, hybridVI. Måtten som användes för att bedöma de modellerna var adjusted rand index och normaliserad mutual information och ett Wilcoxon Signed-Ranks test användes för att bedöma resultatens statistiska signifikans. Resultaten påvisar att de båda modellerna preseterar bättre och mer konsekvent för större dataset. Två dataset gav statistiskt signifikanta resultat och visade att scVI modellen presterade bättre än hybridmodellen. Det behövs dock en biologisk analys av resultaten för att undersöka vilken modells resultat som har mest biologisk relevans.