Engineering a microwell duct-on-chip technology to translate exocrine pancreatic organoids to a cancer model

Das duktale Adenokarzinom der Bauchspeicheldrüse (PDAC) ist eine der tödlichsten Erkrankungen der exokrinen Bauchspeicheldrüse, für die uns relevante Frühdiagnosemarker fehlen. Um PDAC-Marker zu identifizieren, werden in vitro kultivierte exokrine Pankreasmodelle aus dem frühestmöglichen, präkanzerösen Stadium benötigt. Die Übertragung der Pankreasgang-Differenzierung von humanen pluripotenten Stammzellen (hiPSCs) in in vitro-Krankheitsmodelle erfordert ein umfassendes Verständnis der Entwicklungsbahnen von pankreasspezifischen Zelltypen. In dieser Arbeit wurde eine Microwell-Chip-Technologie mit definierten mikrostrukturierten Strukturen entwickelt, um aus hiPSC differenzierte Vorläuferzellen des Pankreas (PP) in einer 3-dimensionalen Zellkultur zu assemblieren. Die Vorteile der Chip-Plattform sind i) die parallele Bildung von Hunderten gleichgroßer 3D-Zellaggregate, ii) eine Matrigel-freie Mikroumgebung, iii) die Kompatibilität mit hochauflösender Bildgebung, iv) die einfache Anwendbarkeit für verschiedene nachfolgende Analysen mit minimaler Störung und v) die Möglichkeit, Ko-Kulturen zu etablieren. Der Chip wurde verwendet, um in weniger als 6 Stunden tausende von 3D-Zellaggregaten aus etwa 600 PPs zu bilden. In den folgenden 14 Tagen wurden die 3D-PP-Kulturen mit einem definierten Wachstumsfaktorprotokoll in pankreatische dukt-ähnliche Organoide differenziert. Zeitaufgelöste Einzelzell-Transkriptionsprofile und Immunfluoreszenz von gereinigten dukt-ähnlichen Organoiden der Bauchspeicheldrüse zeigten die Entstehung von zwei Arten von duktalen Vorläufern, Zwischenstufen, und reifen duktalen Zellen und wenigen nicht-duktalen Zelltypen. Entsprechende dynamische Transkriptionsstadien wiesen auf definierte Differenzierungsrouten der duktalen Zellen hin, die in zwei entweder CFTR+ oder Mucin+ Subpopulationen resultieren. Diese Subpopulationen wurden bereits in primären Einzelzelltranskriptomen des Pankreas gefunden[4]. Die Integration unseres Einzelzelldatensatzes mit drei primären Pankreasdatensätzen[4-6] zeigte, dass unsere dukt-ähnlichen Zellen zusammen mit primären duktalen Zellen zu den beiden Subpopulationen clustern. Außerdem konnten die Marker der Subpopulationen in einem reanalysierten Primärdatensatz[5] erneut identifiziert und in menschlichem Primärgewebe angefärbt werden. Darüber hinaus wurde die Duct-on-Chip-Plattform genutzt, um Organoid-Ko-Kulturen mit humanen Stellat-Zellen zu etablieren. Als zusätzliche Anwendung ermöglichte die Matrigel-freie Chip-Technologie die Entnahme des Sekretoms und Proteoms der Organoide. In Verbindung mit dem Einzelzell-Transkriptom und der klinischen Validierung ermöglichten uns diese Sekretomstudien die Entdeckung eines beispielhaften frühen PDAC-Marker namens FLNB, welcher sowohl in Biopsien als auch im peripheren Blut von Patienten im Frühstadium nachweisbar ist. Zusammenfassend zeigt diese Arbeit die erfolgreiche Herstellung von Pankreas dukt-ähnlichen Organoiden aus hiPSCs, die ein Reifestadium aufweisen, welches mit dem des fötalen Pankreas vergleichbar ist. Durch die Kombination von zeitaufgelöster Einzelzelltranskriptomik mit verschiedenen Analysemethoden, Sekretomstudien, Proteomstudien und klinischer Validierung auf unserem Microwell-Chip wurde ein patientenspezifisches Duktmodell und ein potenzielles Krebsdiagnoseinstrument entwickelt.Pancreatic ductal adenocarcinoma (PDAC) is one of the most severe diseases of the exocrine pancreas, for which relevant early diagnostic markers are still missing. To identify PDAC biomarkers, experimental models employing in vitro cultivation of exocrine pancreas models require as early as possible precancerous stages. The translation of pancreatic ductal differentiation of human pluripotent stem cells (hiPSCs) into in vitro disease models requires a comprehensive understanding of the developmental trajectories of pancreas-specific cell types. In this study, a microwell chip technology exhibiting defined microstructured patterns to assemble hiPSC-derived pancreatic progenitor cells (PP) into a 3-dimensional cell culture was developed. The advantages of the chip platform are i) the parallel formation of hundreds of equally sized 3D cell aggregates, ii) a Matrigel-free microenvironment, iii) the compatibility with high-resolution imaging, iv) simple applicability for several downstream analyses with minimal perturbation, and v) the possibility to establish co-cultures. The chip was used to generate thousands of 3D cell aggregates from approximately 600 PPs, in less than six hours. For the following 14 days, the 3D PP cultures were differentiated towards pancreatic ductal-like organoids by employing defined growth factor protocols. Time-resolved single-cell transcriptional profiling and immunofluorescence of cleared pancreatic duct-like organoids revealed the emergence of two types of ductal progenitors, intermediates, mature duct-like cells, and a few non-ductal cell types. Corresponding dynamic transcriptional stages indicated defined differentiation routes of duct-like cells, cumulating in two either CFTR+ or mucin+ subpopulations, which have been found before in primary single-cell transcriptomes of the pancreas[4]. The integration of the PDLO single-cell dataset into three primary pancreas datasets[4-6] showed that the duct-like cells clustered together with primary ductal cells into the two subpopulations. Furthermore, the markers of the subpopulations could be reidentified in a reanalyzed primary dataset[5] and subjected to confirmation by immunofluorescence in primary human tissue. Additionally, the duct-on-chip platform was exploited to establish organoid co-cultures with stellate cells. As an additional application, the Matrigel-free chip technology allowed the characterization of secretome and proteome. Together with the single-cell transcriptome and clinical validation, these secretome studies revealed an exemplary early PDAC marker, called FLNB, which is detectable in biopsies and early-stage patients' peripheral blood. In conclusion, this study reports the successful engineering of pancreatic duct-like organoids from hiPSCs, which show a maturation stage comparable to the fetal pancreas. By combining time-resolved single-cell transcriptomics with different analysis methods, secretome, proteome and clinical validation on our microwell chip, a patient-specific duct model and a potential cancer diagnostic tool was developed

A tensed pathway to vesicle clustering

Synaptic vesicles play a central role in the functionality and adaptability of the nervous system. They carry inside them molecules called neurotransmitters which allow information to be transmitted from one neuron to another cell. This transmission process can only happen if the vesicles are tightly clustered at the cell junctions, known as synapses, such that a supply of neurotransmitters can be maintained. The mechanism of vesicle clustering had always been considered as mainly biochemistry driven. About a decade ago, newer evidence surprisingly demonstrated that mechanical tension can influence vesicle clustering as well. However, what allowed tension to influence clustering was not understood, and will be explored in this dissertation. The first part of this work explores whether neurons maintain internal tension, and identifies the origin of the tension generators. The existence of internal tension generators allows neurons to regulate their tension state independent of their surrounding tissues, providing a potential pathway for neuronal tension to regulate clustering. Towards this goal, we inhibited multiple proteins in in vivo drosophila motor neurons and subsequently studied their contractility in both the axial and circumferential directions. Contractility was hampered in both directions when either F-actin or myosin motors were inhibited, revealing that there exist internal tension generators that consist of acto-myosin machinery. Our results also showed that this acto-myosin driven contractility is coupled in the axial and circumferential direction, pointing to a misaligned network architecture of the tension generators. The second part describes 2 new enabling methods. The first method is a microfluidic setup that allows partial perfusion of an insuspendable tissue sample. Preexisting partial treatment methodologies can only be applied to suspendable samples. By extending this capability to insuspendable samples, I would be able to perform partial treatment on in vivo drosophila neurons to study neuronal tension. The second method was developed to support the assembly process of the microfluidic setup, which relies on natural adhesion between a soft polymeric material and a stiff substrate. This method uses the delamination induced by a trapped bead at the soft-stiff interface to quantify the adhesion energy at the interface. Both methodologies were verified by experimental results. The final part of this work attempts to explain the relationship between tension and vesicle clustering. By disrupting the tension generators (myosin motors) identified in the first part, I observed the declustering of vesicles after the disassembly of F-actin. I further used the microfluidic device described in the second part to demonstrate that a partial inhibition led to the same result. The microfluidic experiments isolated the treatment region from the synapse such that myosin motors disruption would only hamper neuronal tension but nothing else. It also showed that tension was generated in series along the entire length of the neuron; any failure along the length would lead to a total tension loss. I further accounted for the dynamics of vesicle clustering and declustering by photobleaching the fluorescence proteins fused to the vesicles and subsequently observing the recovery due to other vesicles migrating into the bleached area. Based on all of these experimental observations and results, it appears that F-actin and myosin motors form an in-series network along the neuron to generate tension. This tension is responsible for sustaining the F-actin network at the synapse. The synaptic F-actin is then able to serve as a scaffold for vesicles, such that vesicles can stay clustered. This pathway allows tension to influence, and potentially regulate, vesicle clustering

Multimodal dynamics : self-supervised learning in perceptual and motor systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (leaves 178-192).This thesis presents a self-supervised framework for perceptual and motor learning based upon correlations in different sensory modalities. The brain and cognitive sciences have gathered an enormous body of neurological and phenomenological evidence in the past half century demonstrating the extraordinary degree of interaction between sensory modalities during the course of ordinary perception. We develop a framework for creating artificial perceptual systems that draws on these findings, where the primary architectural motif is the cross-modal transmission of perceptual information to enhance each sensory channel individually. We present self-supervised algorithms for learning perceptual grounding, intersensory influence, and sensorymotor coordination, which derive training signals from internal cross-modal correlations rather than from external supervision. Our goal is to create systems that develop by interacting with the world around them, inspired by development in animals. We demonstrate this framework with: (1) a system that learns the number and structure of vowels in American English by simultaneously watching and listening to someone speak. The system then cross-modally clusters the correlated auditory and visual data.(cont.) It has no advance linguistic knowledge and receives no information outside of its sensory channels. This work is the first unsupervised acquisition of phonetic structure of which we are aware, outside of that done by human infants. (2) a system that learns to sing like a zebra finch, following the developmental stages of a juvenile zebra finch. It first learns the song of an adult male and then listens to its own initially nascent attempts at mimicry through an articulatory synthesizer. In acquiring the birdsong to which it was initially exposed, this system demonstrates self-supervised sensorimotor learning. It also demonstrates afferent and efferent equivalence - the system learns motor maps with the same computational framework used for learning sensory maps.by Michael Harlan Coen.Ph.D

Optical imaging methods for the study of disease models from the nano to the mesoscale

The visualisation of disease phenotypes allows scientists to study fundamental mechanisms of disease. Optical imaging methods are useful not only to observe anatomical features of biological samples, but also to infer interactions between molecular species using fluorescence labelling. This thesis presents the development of imaging and analysis tools to study biological questions in three models of disease, with samples ranging from the sub-cellular to the organ scale. First, the role of the alpha-synuclein (a-syn) protein, whose dysfunction is a hallmark of Parkinson’s Disease, was studied with respect to vesicle trafficking at the synapse. Synaptic vesicles are ∼40 nm in diameter; imaging vesicles therefore requires methods with resolution below the diffraction limit. Single-molecule localisation microscopy (SMLM), which circumvents the diffraction limit by separating fluorophore emission in time to localise individual molecules in space with ∼20 nm precision, was thus implemented to study a-syn in purified synaptic boutons. A software package was developed to analyse the colocalisation of a-syn with internalised vesicles, and the clustering of a-syn under differing synaptic calcium levels. The colocalisation of a-syn and internalised vesicles was found to be temperature independent, suggesting that a-syn is involved in non-canonical trafficking mechanisms. Ground truth simulations from a synaptosome model were used to benchmark two cluster analysis methods. Both methods applied on the experimental data showed that a-syn becomes less clustered at low synaptic calcium levels. Second, the spatiotemporal association of ESCRT-II, a protein complex whose role in the budding of the human immunodeficiency virus (HIV) was previously considered dispensable, and the HIV polyprotein Gag was studied during viral egress using novel image analysis tools. A nearest-neighbour analysis showed the ESCRT-II protein EAP45 colocalises with Gag similarly to ALIX, a protein well known to be involved in HIV budding. However, upon deletion of EAP45’s N-terminus, its colocalisation with Gag was significantly impaired, highlighting the importance of this EAP45 domain in linking to Gag. Single particle tracking was used to trace the trajectories of EAP45 and Gag in live cells, and an algorithm was developed to visualise the simultaneous motion of two particles; these analyses revealed three types of potential dynamic interaction between EAP45 and Gag. Finally, an open-source instrument to visualise phenotypes from large organs in 3D was developed for the study of chronic obstructive pulmonary disease (COPD) models. The instrument implements Optical Projection Tomography, a technique which can reconstruct cross-sectional slices of a transparent object from its orthographic projections, using off-the- shelf components and novel ImageJ plugins for artefact correction and volume reconstructions. Excised and cleared mouse lungs were imaged in which high order airways can be discerned with 50 μm resolution. The raw lung data, instructions for building the instrument, the free ImageJ plugins, and a detailed software manual are available in an online repository to encourage the widespread use of OPT for imaging large samples.Gates Cambridg

THEORETICAL AND QUANTITATIVE METHODS CONNECTING CHARACTERIZING MICORIBAL METABOLISM DIVERSITY: IMPLCIATIONS FROM PHYLOGENETICS, COMMUNITY DIVERSITY, AND ORGANIC GEOCHEMISTRY

Biogeochemistry is controlled by microorganisms obtaining nutrients and energy. Thus, microbial metabolisms directly link microbial ecology and geochemistry. The extent that microbial ecology and geochemistry microbial ecology and geochemistry affects the other requires constraint on the spatiotemporal distribution and abundance of microbial metabolisms with respect to geochemistry, or the microbial niches. Elucidating microbial metabolisms was challenging prior to the advent of ‘omics sequencing technologies, as most microbial lineages lack cultured representatives. Although revolutionizing microbial ecology, challenges still exist in fully leveraging information derived from ‘omics technologies. This dissertation attempts to address a small subset of these challenges that include quantifying the generalizability of microbial metabolism with respect to phylogeny, relating metagenomic sequencing effort to in situ genome discovery rates, quantifying and generalizing the relative contribution to a net ecosystem function by community members, and relating geochemistry gradients to microbial metabolism gradients. As a part of this work, theoretical and quantitative measures are proposed for evaluating microbial metabolism diversity with respect to phylogenetics (permutational multivariate ANOVA and variance component modeling), community diversity (generalized coupon collector equation, parametric diversity), and in situ geochemistry at the field site, White Oak River estuary, North Carolina (USA). Numerical simulations (community rarefaction, community extinction events, and reaction-transport modeling) and public data repositories (Reference Sequence Database, GenBank, Integrated Microbial Genome and Microbiomes, and Sequence Read Archive) are used for the testing efficacy of the proposed theoretical and quantitative methods. The results indicate that numerical simulations and public data repositories can be used for developing and testing ecological theory and concepts. The theoretical and quantitative methods proposed here can now be used in exploring microbial niche distributions in nature

Higher-order interactions in single-cell gene expression: towards a cybergenetic semantics of cell state

Finding and understanding patterns in gene expression guides our understanding of living organisms, their development, and diseases, but is a challenging and high-dimensional problem as there are many molecules involved. One way to learn about the structure of a gene regulatory network is by studying the interdependencies among its constituents in transcriptomic data sets. These interdependencies could be arbitrarily complex, but almost all current models of gene regulation contain pairwise interactions only, despite experimental evidence existing for higher-order regulation that cannot be decomposed into pairwise mechanisms. I set out to capture these higher-order dependencies in single-cell RNA-seq data using two different approaches. First, I fitted maximum entropy (or Ising) models to expression data by training restricted Boltzmann machines (RBMs). On simulated data, RBMs faithfully reproduced both pairwise and third-order interactions. I then trained RBMs on 37 genes from a scRNA-seq data set of 70k astrocytes from an embryonic mouse. While pairwise and third-order interactions were revealed, the estimates contained a strong omitted variable bias, and there was no statistically sound and tractable way to quantify the uncertainty in the estimates. As a result I next adopted a model-free approach. Estimating model-free interactions (MFIs) in single-cell gene expression data required a quasi-causal graph of conditional dependencies among the genes, which I inferred with an MCMC graph-optimisation algorithm on an initial estimate found by the Peter-Clark algorithm. As the estimates are model-free, MFIs can be interpreted either as mechanistic relationships between the genes, or as substructures in the cell population. On simulated data, MFIs revealed synergy and higher-order mechanisms in various logical and causal dynamics more accurately than any correlation- or information-based quantities. I then estimated MFIs among 1,000 genes, at up to seventh-order, in 20k neurons and 20k astrocytes from two different mouse brain scRNA-seq data sets: one developmental, and one adolescent. I found strong evidence for up to fifth-order interactions, and the MFIs mostly disambiguated direct from indirect regulation by preferentially coupling causally connected genes, whereas correlations persisted across causal chains. Validating the predicted interactions against the Pathway Commons database, gene ontology annotations, and semantic similarity, I found that pairwise MFIs contained different but a similar amount of mechanistic information relative to networks based on correlation. Furthermore, third-order interactions provided evidence of combinatorial regulation by transcription factors and immediate early genes. I then switched focus from mechanism to population structure. Each significant MFI can be assigned a set of single cells that most influence its value. Hierarchical clustering of the MFIs by cell assignment revealed substructures in the cell population corresponding to diverse cell states. This offered a new, purely data-driven view on cell states because the inferred states are not required to localise in gene expression space. Across the four data sets, I found 69 significant and biologically interpretable cell states, where only 9 could be obtained by standard approaches. I identified immature neurons among developing astrocytes and radial glial cells, D1 and D2 medium spiny neurons, D1 MSN subtypes, and cell-cycle related states present across four data sets. I further found evidence for states defined by genes associated to neuropeptide signalling, neuronal activity, myelin metabolism, and genomic imprinting. MFIs thus provide a new, statistically sound method to detect substructure in single-cell gene expression data, identifying cell types, subtypes, or states that can be delocalised in gene expression space and whose hierarchical structure provides a new view on the semantics of cell state. The estimation of the quasi-causal graph, the MFIs, and inference of the associated states is implemented as a publicly available Nextflow pipeline called Stator

Striatal Dopamine Dynamics Upon Manganese Accumulation

STRIATAL DOPAMINE DYNAMICS UPON MANGANESE ACCUMULATION by MADIHA KHALID August 2013 Advisor: Dr. Tiffany Mathews Major: Chemistry (Analytical) Degree: Doctor of Philosophy Although manganese (Mn) is fundamental for many biological processes, exposure to excess amounts leads to a neurological disorder termed manganism. Due to its symptomatic similarity to Parkinson\u27s disease, as well its preferential accumulation in dopamine rich brain regions, alterations in the dopamine system are implicated in the onset of manganism. In my research, Mn overexposure is mimicked via subcutaneous administration of manganese chloride to C57BL/6 mice over the course of seven days using a protocol that has been shown to result in accumulation of Mn in the basal ganglia. The subsequent short and long term effects of this treatment on striatal dopamine function were evaluated 1, 7, and 21 days after treatment cessation. This work used a variety of complementary analytical methods to take a multifaceted approach in studying the Mn-treated animals. The first study used fast scan cyclic voltammetry, microdialysis, and tissue content analysis to characterize the dopamine system after the sub-acute treatment protocol. Behavioral tests were subsequently used to elucidate any phenotypic differences in the treated mice as compared to controls. Finally, pharmacological studies were conducted to test the hypothesis of intraneuronal dysfunction to explain the changes observed in the first study. Overall, these findings revealed that the dopamine system in the striatum has lower extracellular levels of dopamine after Mn accumulation due to a functional defect in the release mechanism that is apparent within a week of treatment. Interestingly, most behavioral changes appear to manifest within 24 hours of treatment, when no dopamine change is observed, indicating the involvement of other neurotransmitter systems in the onset of motor deficits following Mn exposure. Finally, by methodically evaluating the quantity and functionality of dopamine vesicles at the axon terminal, we were able to provide evidence against the theory that dopamine release following Mn accumulation is due to an inability of the reserve pool of dopamine to mobilize to the terminal for release

Studying the interplay between ageing and Parkinson's disease using the zebrafish model

Parkinson’s disease (PD) is a neurodegenerative disorder characterised by the loss of dopaminergic neurons in the substantia nigra. Ageing is the major risk factor for developing PD but the interplay between ageing and PD remains elusive. To investigate the effect of ageing on PD-relevant pathological mechanisms, zebrafish mutant lines harbouring mutations in ageing-associated genes (klotho-/-, sirt1-/-, satb1a-/-, satb1b-/- and satb1a-/-;satb1b-/-) were generated, using CRISPR/Cas9 gene editing. Likewise, a chemical model for SIRT1 deficiency was utilised. klotho-/- zebrafish displayed an accelerated ageing phenotype at 3mpf and reduced survival to 6mpf. Dopaminergic neuron number, MPP+ susceptibility and microglial number were unaffected in klotho-/- larvae. NAD+ levels were decreased in 6mpf klotho-/- brains. However, ATP levels and DNA damage were unaffected. sirt1-/- zebrafish did not display a phenotype through adulthood. il-1β and il-6 were not upregulated in sirt1-/- larvae, and chemical inhibition of sirt1 did not increase microglial number. cdkn1a, il-1β and il-6 were not upregulated in satb1a-/- and satb1b-/- larvae. Dopaminergic neuron number and MPP+ susceptibility were unaffected in satb1a-/- larvae. However, satb1b-/- larvae demonstrated a moderate decrease in dopaminergic neuron number but equal susceptibility to MPP+ as satb1b+/+ larvae. Adult satb1a-/- but not adult satb1b-/- zebrafish were emaciated. satb1a-/-;satb1b-/- zebrafish did not display a phenotype through adulthood. Transgenic zebrafish expressing human wildtype α-Synuclein (Tg(eno2:hsa.SNCA-ires-EGFP)) were crossed with klotho-/- and sirt1-/- zebrafish, and treated with a sirt1-specific inhibitor. Neither genetic cross affected survival. The klotho mutation did not increase microglial number in Tg(eno2:hsa.SNCA-ires-EGFP) larvae. Likewise, sirt1 inhibition did not induce motor impairment or cell death in Tg(eno2:hsa.SNCA-ires-EGFP) larvae. In conclusion, the suitability of zebrafish for studying ageing remains elusive, as only 1 ageing-associated mutant line displayed accelerated ageing. However, zebrafish remain an effective model for studying PD-relevant pathological mechanisms due to the availability of CRISPR/Cas9 gene editing, neuropathological and neurobehavioral tools