Biology subjects

Danzl, J. G.

Publications and source records attributed to Danzl, J. G..

11 recordsLinked to original sources

bioRxiv2025

Image-based 3D active sample stabilization on the nanometer scale for optical microscopy

Super-resolution microscopy often entails long acquisition times of minutes to hours. Since drifts during the acquisition adversely affect data quality, active sample stabilization is commonly used for some of these techniques to reach their full potential. While drifts in the lateral plane can often be corrected after acquisition, this is not always possible or may come with drawbacks. Therefore, it is appealing to stabilize sample position in three dimensions during acquisition. Various schemes for active sample stabilization have been demonstrated previously, with some reaching sub-nm stability in three dimensions. However, these high-performance implementations significantly added to the complexity of the hardware and/or sample preparation. Here, we present a scheme for active drift correction that delivers the nm-scale 3D stability demanded by state-of-the-art super-resolution techniques and is straightforward to implement. Using a refined algorithm that does not depend on sparse peaks typically provided by fiducial markers added to the sample, we stabilized our sample position to [~]1 nm in 3D using objective lenses both with high and low numerical aperture. Our implementation requires only the addition of a standard widefield imaging path and we provide an open-source control software with graphical user interface to facilitate easy adoption of the module. Finally, we demonstrate how this has the potential to enhance data collection for diffraction-limited and super-resolution imaging techniques using single-molecule localization microscopy and cryo-confocal imaging as showcases. Why it mattersSuper-resolution light microscopy has enabled the visualization of biological structures down to the nm-scale. However, uncorrected drifts during often extended acquisition times may adversely affect data quality. Active drift correction in three dimensions has achieved sub-nm stabilization, but state-of-the-art techniques come with considerable overhead on sample preparation and/or hardware. Here, we demonstrate an image-based stabilization scheme which allows for flexibility regarding structures used for stabilization and is straightforward to adopt. Using a maximally simple implementation, we stabilized the position of our sample to around 1 nm over extended acquisition times and demonstrated usefulness in two example imaging settings where sample drifts are critical, super-resolution single-molecule localization microscopy and confocal imaging at cryogenic temperatures.

biophysics↗

bioRxiv2024

niiv: Fast Self-supervised Neural ImplicitIsotropic Volume Reconstruction

Three-dimensional (3D) microscopy data often is anisotropic with significantly lower resolution (up to 8x) along the z axis than along the xy axes. Computationally generating plausible isotropic resolution from anisotropic imaging data would benefit the visual analysis of large-scale volumes. This paper proposes niiv, a self-supervised method for isotropic reconstruction of 3D microscopy data that can quickly produce images at arbitrary output resolutions. The representation embeds a learned latent code within a neural field that describes the implicit higher-resolution isotropic image region. We use a novel attention-guided latent interpolation approach, which allows flexible information exchange over a local latent neighborhood. Under isotropic volume assumptions, we self-supervise this representation on low-/high-resolution lateral image pairs to reconstruct an isotropic volume from low-resolution axial images. We evaluate our method on simulated and real anisotropic electron (EM) and light microscopy (LM) data. Compared to a state-of-the- art diffusion-based method, niiv shows improved reconstruction quality (+1 dB PSNR) and is over three orders of magnitude faster (1,000x) to infer. Specifically, niiv reconstructs a 1283 voxel volume in 2/10th of a second, renderable at varying (continuous) high resolutions for display.

bioinformatics↗

bioRxiv2024

Human hippocampal CA3 uses specific functional connectivity rules for efficient associative memory

The human brain has remarkable computational power. It generates sophisticated behavioral sequences, stores engrams over an individuals lifetime, and produces higher cognitive functions up to the level of consciousness. However, so little of our neuroscience knowledge covers the human brain, and it remains unknown whether this organ is truly unique, or is a scaled version of the extensively studied rodent brain. To address this fundamental question, we determined the cellular, synaptic, and connectivity rules of the hippocampal CA3 recurrent circuit using multicellular patch clamp-recording. This circuit is the largest autoassociative network in the brain, and plays a key role in memory and higher-order computations such as pattern separation and pattern completion. We demonstrate that human hippocampal CA3 employs sparse connectivity, in stark contrast to neocortical recurrent networks. Connectivity sparsifies from rodents to humans, providing a circuit architecture that maximizes associational power. Unitary synaptic events at human CA3-CA3 synapses showed both distinct species-specific and circuit-dependent properties, with high reliability, unique amplitude precision, and long integration times. We also identify differential scaling rules between hippocampal pathways from rodents to humans, with a moderate increase in the convergence of CA3 inputs per cell, but a marked increase in human mossy fiber innervation. Anatomically guided full-scale modeling suggests that the human brains sparse connectivity, expanded neuronal number, and reliable synaptic signaling combine to enhance the associative memory storage capacity of CA3. Together, our results reveal unique rules of connectivity and synaptic signaling in the human hippocampus, demonstrating the absolute necessity of human brain research and beginning to unravel the remarkable performance of our autoassociative memory circuits.

neuroscience↗

bioRxiv2024

Light-microscopy based dense connectomic reconstruction of mammalian brain tissue

The information-processing capability of the brains cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution with dense cellular labeling. Light microscopy is uniquely positioned to visualize specific molecules but dense, synapse-level circuit reconstruction by light microscopy has been out of reach due to limitations in resolution, contrast, and volumetric imaging capability. Here we developed light-microscopy based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning based segmentation and analysis of connectivity, thus directly incorporating molecular information in synapse-level brain tissue reconstructions. LICONN will allow synapse-level brain tissue phenotyping in biological experiments in a readily adoptable manner. One-Sentence SummaryHydrogel expansion enables molecularly informed reconstruction of brain tissue at synaptic resolution with light microscopy.

neuroscience↗

bioRxiv2024

Super-resolution expansion microscopy in plant roots

Super-resolution methods enable spatial resolution far better than the optical diffraction limit of about half the wavelength of light ([~]200-300 nm) but have yet to attain widespread use in plants, owing in large part to plants challenging optical properties. Expansion microscopy improves effective resolution by isotropically increasing physical distances between sample structures while preserving relative spatial arrangements, and clears the sample. However, its application to plants has been hindered by the rigid, mechanically cohesive structure of plant tissues. Here, we report on whole-mount expansion microscopy of Arabidopsis thaliana root tissues (PlantEx), achieving 4-fold resolution increase over conventional microscopy, highlighting microtubule cytoskeleton organization and interaction between molecularly defined cellular constituents. By combining PlantEx with STED microscopy, we increase nanoscale resolution further and visualize the complex organization of subcellular organelles from intact tissues by example of the densely packed COPI-coated vesicles associated with the Golgi apparatus and put these into cellular structural context.

plant biology↗

bioRxiv2022

Chiral and nematic phases of flexible active filaments

The emergence of large-scale order in self-organized systems relies on local interactions between individual components. During bacterial cell division, the tubulin-homolog FtsZ polymerizes into treadmilling filaments that further assemble into a cytoskeletal ring. Although minimal in vitro assays have shown the striking self-organization capacity of FtsZ filaments, such as dynamic chiral assemblies, how these large-scale structures emerge and relate to individual filament properties remains poorly understood. To understand this quantitatively, we combined minimal chiral active matter simulations with biochemical reconstitution experiments. Using STED and TIRF microscopy as well as high-speed AFM, we imaged the behavior of FtsZ filaments on different spatial scales. Simulations and experiments revealed that filament density and flexibility define the local and global order of the system: At intermediate densities, flexible filaments organize into chiral rings and polar bands, while an effectively nematic organization dominates for high filament densities and for mutant filaments with increased rigidity. Our predicted phase diagram captured these features quantitatively, demonstrating how filament flexibility, density and chirality cooperate with activity to give rise to a large repertoire of collective behaviors. These properties are likely important for the dynamic organization of soft chiral matter, including that of treadmilling FtsZ filaments during bacterial cell division.

biophysics↗

bioRxiv2022

Uncovering brain tissue architecture across scales with super-resolution light microscopy

Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanoscopic synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS leverages fixation-compatible extracellular labeling and advanced optical readout, in particular stimulated-emission depletion and expansion microscopy, to comprehensively delineate cellular structures. It enables 3D-reconstructing single synapses and mapping synaptic connectivity by identification and tailored analysis of putative synaptic cleft regions. Applying CATS to the hippocampal mossy fiber circuitry, we demonstrate its power to reveal the systems molecularly informed ultrastructure across spatial scales and assess local connectivity by reconstructing and quantifying the synaptic input and output structure of identified neurons.

neuroscience↗

bioRxiv2022

Saturated reconstruction of living brain tissue

Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1-5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6-12 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy6,13 in extracellularly labelled tissue14 for high SNR and near-isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to single synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue.

neuroscience↗

bioRxiv2022

Entorhinal layer 6b subplate neurons govern spatial learning and memory

The mammalian hippocampal formation (HF) plays a key role in several higher brain functions, such as spatial coding, learning and memory. Its simple circuit architecture is often viewed as a "trisynaptic loop", processing input originating from the superficial layers of the entorhinal cortex (EC) in a linear fashion, and sending it back to its deeper layers. Here, we show that contrary to this canonical view, excitatory neurons in the deepest layer of the mouse EC, exhibiting the unique morphology and molecular profile of layer 6b cortical subplate neurons (SPNs), project to all sub-regions comprising the HF, with a preference towards CA3 pyramidal neurons, and receive input from the CA1, thalamus and claustrum. Furthermore, their output is characterized by unique slow-decaying excitatory post-synaptic currents (EPSCs), capable of driving plateau-like potentials in their target cells. Optogenetic inhibition of the EC-6b pathway markedly affects spatial coding in CA1 pyramidal neurons, while cell ablation impairs not only acquisition of new spatial memories, but also degradation of previously acquired ones. Our results provide the first evidence of a functional role for the cortical layer 6b neurons in the adult brain and elucidate a critical novel element determining cortico-hippocampal activity patterns.

neuroscience↗

bioRxiv2020

Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development

De novo loss of function mutations in the ubiquitin ligase-encoding gene Cullin3 (CUL3) lead to autism spectrum disorder (ASD). Here, we used Cul3 mouse models to evaluate the consequences of Cul3 mutations in vivo. Our results show that Cul3 haploinsufficient mice exhibit deficits in motor coordination as well as ASD-relevant social and cognitive impairments. Cul3 mutant brain displays cortical lamination abnormalities due to defective neuronal migration and reduced numbers of excitatory and inhibitory neurons. In line with the observed abnormal columnar organization, Cul3 haploinsufficiency is associated with decreased spontaneous excitatory and inhibitory activity in the cortex. At the molecular level, employing a quantitative proteomic approach, we show that Cul3 regulates cytoskeletal and adhesion protein abundance in mouse embryos. Abnormal regulation of cytoskeletal proteins in Cul3 mutant neuronal cells results in atypical organization of the actin mesh at the cell leading edge, likely causing the observed migration deficits. In contrast to these important functions early in development, Cul3 deficiency appears less relevant at adult stages. In fact, induction of Cul3 haploinsufficiency in adult mice does not result in the behavioral defects observed in constitutive Cul3 haploinsufficient animals. Taken together, our data indicate that Cul3 has a critical role in the regulation of cytoskeletal proteins and neuronal migration and that ASD-associated defects and behavioral abnormalities are primarily due to Cul3 functions at early developmental stages.

neuroscience↗

bioRxiv2019

Advantages of acute brain slices prepared at physiological temperature in characterization of synaptic functions

Acute brain slice preparation is a powerful experimental model for investigating the characteristics of synaptic function in the brain. Although brain tissue is usually cut at ice-cold temperature (CT) to facilitate slicing and avoid neuronal damage, exposure to CT causes molecular and architectural changes of synapses. To address these issues, we investigated ultrastructural and electrophysiological features of synapses in mouse acute cerebellar slices prepared at ice-cold and physiological temperature (PT). In the slices prepared at CT, we found significant spine loss and reconstruction, synaptic vesicle rearrangement and decrease in synaptic proteins, all of which were not detected in slices prepared at PT. Consistent with these structural findings, slices prepared at PT showed higher release probability and higher detectability of long-term depression after motor learning compared with slices prepared at CT. These results indicate substantial advantages of the slice preparation at PT for investigating synaptic functions in different physiological conditions.

neuroscience↗