A polymer gel index-matched to water enables diverse applications in fluorescence microscopy [preprint]

We demonstrate diffraction-limited and super-resolution imaging through thick layers (tens-hundreds of microns) of BIO-133, a biocompatible, UV-curable, commercially available polymer with a refractive index (RI) matched to water. We show that cells can be directly grown on BIO-133 substrates without the need for surface passivation and use this capability to perform extended time-lapse volumetric imaging of cellular dynamics 1) at isotropic resolution using dual-view light-sheet microscopy, and 2) at super-resolution using instant structured illumination microscopy. BIO-133 also enables immobilization of 1) Drosophila tissue, allowing us to track membrane puncta in pioneer neurons, and 2) Caenorhabditis elegans, which allows us to image and inspect fine neural structure and to track pan-neuronal calcium activity over hundreds of volumes. Finally, BIO-133 is compatible with other microfluidic materials, enabling optical and chemical perturbation of immobilized samples, as we demonstrate by performing drug and optogenetic stimulation on cells and C. elegans

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

Designing Scalable Biological Interfaces

This thesis presents the analysis and design of biological interfacing technologies in light of a need for radical improvements in scalability. It focuses primarily on structural and functional neural data acquisition, but also extends to other problems including genomic editing and nanoscale spatial control. Its main contributions include analysis of the physical limits of large-scale neural recording, experimental development of a screening platform for ion-dependent molecular recording devices, characterization of the design space for molecularly-annotated neural connectomics, and new designs for high-speed genome engineering and bio-nano-fabrication. Articulating governing principles and roadmaps for these domains has contributed to the initiation of multi-institutional projects that are strategically targeted towards scalability

Microscopy Conference 2021 (MC 2021) - Proceedings

Das Dokument enthält die Kurzfassungen der Beiträge aller Teilnehmer an der Mikroskopiekonferenz "MC 2021"

Mathematical modelling of fibroblasts in cancer

Cancer-associated fibroblasts (CAFs) and the associated extracellular matrix (ECM) constitute a significant part of the tumour microenvironment (TME), playing an important role in the invasive potential of the tumour. The alignment of CAFs and the corresponding ECM which they produce and organise is linked with increased cancer invasion. Additionally, massive variation in the physical architecture of the ECM is observed in both normal and pathological tissues for example swirling, diffuse or porous patterns. How these mesoscale patterns arise remains largely unexplored. An agent-based flocking model was developed to investigate CAF properties and their involvement in emergent alignment. The model established that aligning cells had a requirement of highly persistent migration coupled with an active cell-cell collision guidance mechanism. The model predicted that alignment was a fragile state which could be easily destroyed in a heterogeneous population. These findings were confirmed experimentally. The model was then extended to include a second underlying layer of ECM fibres that the CAFs could produce, degrade and rearrange but were also instructed to follow, constituting a CAF-ECM feedback loop. This mechanism was capable of generating diverse matrix patterns, reminiscent of those seen in vivo. The model was challenged to unpick the process of interconversion between matrix patterns as seen in cancer, wound healing and ageing, which it elucidated with considerable success. Finally, clinical samples of ECM were quantified to establish if certain metrics of ECM architecture could be useful clinical prognostic factors. Early results suggest this to be true. Matrix patterns were quantified by a carefully constructed software pipeline suitable for use by other researchers on versatile data samples.Open Acces

29th Annual Computational Neuroscience Meeting: CNS*2020

Meeting abstracts This publication was funded by OCNS. The Supplement Editors declare that they have no competing interests. Virtual | 18-22 July 202

Computational Methods for Analysis of Data for Conformational and Phase Equilibria of Disordered Proteins

Intrinsically disordered proteins and regions (IDPs / IDRs) are a class of proteins with diverse conformational heterogeneity that do not fold into a tertiary structure due to the lack of a native structural state. Consequently, disordered proteins are remarkably flexible and exhibit multivalent properties that enable them to adopt myriad functional roles within the cell such as: signaling transduction, transcription, enzymatic catalysis, translation, and many more. Due to their multivalency, some IDPs undergo monomeric and heterotypic interactions which can drive phase separation. Such IDPs can form membraneless organelles with specific regulatory roles within the cell which include, but are not limited to: RNA storage, neurotransmission, and cell-cycle regulation. However, the driving forces behind these mechanisms are not well understood. Dysregulation of these roles through the introduction of sequence mutations or cellular stress can lead to the formation of protein aggregates that can detrimentally impact cellular function and ability. Thus, IDPs are also implicated in multiple diseases like Type II diabetes, numerous cancers, and several neurodegenerative disorders such as Alzheimer’s and Parkinson’s disease. Therefore, there is keen interest to understand the sequence-determinants of IDPs and characterize properties of their conformational ensembles that inform their function. This thesis is focused on the development and application of computational tools that can characterize the spatiotemporal properties of IDP simulations, as well as classify and identify possible sequence-determinants of phase separation