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Titze, B.

Publications and source records attributed to Titze, B..

3 recordsLinked to original sources

VP-CLEM-Kit: An accessible pipeline for visual proteomics using super resolution volume correlative light and electron microscopy (SR-vCLEM)

Visual proteomics (VP) aims to allow researchers to visualise, measure and analyse proteins in the context of cell and tissue structure in health and disease. VP is becoming a reality through technological advances across several domains, including in situ structural biology and correlative light and electron microscopy (CLEM). However, widespread adoption remains limited due to the complexity and cost of the various VP approaches reported to date. Here we present the VP-CLEM-Kit, a disruptive cost-effective pipeline for super resolution volume CLEM (SR-vCLEM) that can be implemented with minimal advanced electron microscopy expertise and equipment, making it accessible to light microscopy facilities and research labs. SR-vCLEM is based on in-resin fluorescence (IRF), where fluorophores are preserved through processing into resin. The easyIRF protocol reported here reduces the requirement for complex costly sample preparation equipment and toxic chemicals compared to standard IRF protocols. easyIRF blocks are cut into ultrathin sections that are imaged using tomoSTORM, a new modular and cost-effective openFrame-based light microscope controlled by the open-source software package Micro-Manager that provides serial single molecule localisation microscopy in array tomography format. Sections are then post-stained and imaged using a tabletop scanning electron microscope controlled by open-source SBEMimage software to run in array tomography format. We demonstrate the potential of the VP-CLEM-Kit by imaging organelle reporters in human cell lines and stem cell derived neurons, fluorescently labelled protein in neurons, and immunolabelled cells in human kidney biopsy tissue from transplant patients. The VP-CLEM-Kit delivers a [~]5-fold improvement in resolution at a [~]7-fold lower cost, and thus provides new technical capability as well as a blueprint for more equitable access to advanced imaging workflows.

cell biology↗

Representational learning by optimization of neural manifolds in an olfactory memory network

Cognitive brain functions rely on experience-dependent internal representations of relevant information. Such representations are organized by attractor dynamics or other mechanisms that constrain population activity onto "neural manifolds". Quantitative analyses of representational manifolds are complicated by their potentially complex geometry, particularly in the absence of attractor states. Here we trained juvenile and adult zebrafish in an odor discrimination task and measured neuronal population activity to analyze representations of behaviorally relevant odors in telencephalic area pDp, the homolog of piriform cortex. No obvious signatures of attractor dynamics were detected. However, olfactory discrimination training selectively enhanced the separation of neural manifolds representing task-relevant odors from other representations, consistent with predictions of autoassociative network models endowed with precise synaptic balance. Analytical approaches using the framework of manifold capacity revealed multiple geometrical modifications of representational manifolds that supported the classification of task-relevant sensory information. Manifold capacity predicted odor discrimination across individuals better than other descriptors of population activity, indicating a close link between manifold geometry and behavior. Hence, pDp and possibly related recurrent networks store information in the geometry of representational manifolds, resulting in joint sensory and semantic maps that may support distributed learning processes.

neuroscience↗

Whole-body integration of gene expression and single-cell morphology

Animal bodies are composed of hundreds of cell types that differ in location, morphology, cytoarchitecture, and physiology. This is reflected by cell type-specific transcription factors and downstream effector genes implementing functional specialisation. Here, we establish and explore the link between cell type-specific gene expression and subcellular morphology for the entire body of the marine annelid Platynereis dumerilii. For this, we registered a whole-body cellular expression atlas to a high-resolution electron microscopy dataset, automatically segmented all cell somata and nuclei, and clustered the cells according to gene expression or morphological parameters. We show that collective gene expression most efficiently identifies spatially coherent groups of cells that match anatomical boundaries, which indicates that combinations of regionally expressed transcription factors specify tissue identity. We provide an integrated browser as a Fiji plugin to readily explore, analyse and visualise multimodal datasets with remote on-demand access to all available datasets.

cell biology↗