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Bretschneider, T.

Publications and source records attributed to Bretschneider, T..

10 recordsLinked to original sources

The Effects of Physical Exercise on Osteocyte Lacunar Morphology and Orientation around Bioresorbable Implants

In this study, we used synchrotron radiation micro-computed tomography (SR-CT) to investigate the effect of early post-operative physical exercise at 2, 4, and 6 weeks on osteocyte lacunar distribution and morphology in a Sprague Dawley rat femoral defect model after implantation of a bioresorbable pin. Physical exercise has been shown to improve bone remodeling after fracture, but its effects on the lacuno-canalicular network in the presence of bioresorbable implants remain unclear. The structure of lacunae is linked to that of osteocytes, which play an important role in bone remodeling and adaptation to stress. We studied a large number of lacunae (around 670 000 per sample) in terms of their location, morphology, and orientation. We show that in newly formed bone, lacunae are larger and rounder with exercise, while in previously existing bone, lacunae are less oriented along the long bone axis when exercise is performed. In addition, close to the implant, lacunar density is higher with exercise in both newly formed bone and previously existing bone. These findings point to a higher degree of remodeling and a pronounced lacunar response to mechanical stimulation and may thus help clarify bone behavior with exercise around implants to better design post-surgical recovery treatments.

bioengineering↗

SAMPLE-BASED TRAINING DATA FOR EFFECTIVE 3D CELL SEGMENTATION

Deep learning remains the leading choice for cell segmentation, a critical step in bioimaging analysis. Whilst deep learning models provide excellent segmentation accuracy, a large number of hand-annotated samples are required which are scarce in 3D. We propose a method for generating synthetic data for training deep learning models to augment or replace such datasets. By preserving key features in real data, we show that a standard UNet trained on synthetic data can segment single motile cells with branching filopodia with high accuracy. We also demonstrate how low-effort slice annotations can sufficiently replace volume annotations in our data generation pipeline. Overall, we provide a simple alternative to annotating large 3D datasets for training neural networks to segment cell imaging data.

bioinformatics↗

High-Quality Synthetic Annotated Tissue Data Using Conditional Generative Adversarial Networks

We present a deep-learning based pipeline for generating high-quality synthetic instance-segmentation datasets of tissues undergoing early gastrulation in chick embryo. We create point-clouds using the Lennard-Jones potential and learn an image-to-image translation from these point-clouds to create synthetic tissue images and auxiliary flow tensors using a Generative Adversarial Network, from which the segmentation masks are derived. We evaluate the downstream utility of our synthetic data by training Cellpose and Stardist models from scratch under data replacement and data augmentation scenarios, show that the synthetic datasets effectively capture the statistical properties of the real dataset, and show that our synthetic data improves segmentation performance on a held-out test set. This approach substantially reduces expert annotation time, as late-stage gastrulation data are challenging to acquire and manually label, while similar synthetic examples can be flexibly generated from easily obtainable and annotated early-stage data. Code: https://gitlab.com/siddharthsrivastava/synthetic-tissue-data

bioinformatics↗

Functional genomics analysis of developing zebrafish and human endoderm reveals highly conserved cis-regulatory modules controlling vertebrate organogenesis

While vertebrate species are superficially diverse, they share key commonalities in terms of overall morphology, and organ configuration and function. Maintenance of these traits during evolution is partially explained by conservation of critical genes governing embryonic development. However, for conserved genes to deliver consistent developmental outcomes between species, similar gene regulatory programmes and gene expression patterns must also be maintained. The endoderm germ layer makes major contributions to the respiratory and gastrointestinal tracts, and associated organs including liver and pancreas. We used functional genomics approaches to identify highly conserved endodermal cis-regulatory modules (CRMs) functioning across the 400 million years of evolution separating zebrafish and humans. Our analyses suggest that there are few endoderm-specific CRMs, with many CRMs governing pancreas developmental also likely acting within the nervous system. Furthermore, these highly conserved CRMs are strongly enriched for binding sites of "neuro-pancreatic" transcription factors governing both pancreas and nervous system development, potentially suggesting function across these distinct organ systems. Additionally, we identify highly conserved CRMs likely participating endodermal patterning of adjacent craniofacial structures and sensory tissues. The highly conserved CRMs we identify are characterised by conserved patterns of transcription factor binding site co-occurrence. However, they are not characterised by rigid arrangement of binding sites, suggesting more complex or individual grammatical rules. Overall, our analyses provide key insights into critical gene regulatory control during vertebrate endoderm organogenesis, and define a compendium of highly conserved CRMs that should be prioritised for analysis of neuro-pancreatic gene transcriptional control, and anterior embryonic patterning.

developmental biology↗

CelFDrive: Artificial Intelligence assisted microscopy for automated detection of rare events

11.1 SummaryCelFDrive automates high-resolution 3D imaging cells of interest across a variety of fluorescence microscopes, integrating deep learning cell classification from auxiliary low resolution widefield images. CelFDrive enables efficient detection of rare events in large cell populations, such as the onset of cell division, and subsequent rapid switching to 3D imaging modes, increasing the speed for finding cells of interest by an order of magnitude. 1.2 Availability and ImplementationCelFDrive is available freely for academic purposes at the CelFDrive GitHub repository. and can be installed on Windows, macOS or Linux-based machines with relevant conda environments [1]. To interact with microscopy hardware requires additional software; we use SlideBook software from Intelligent Imaging Innovations (3i), but CelFDrive can be deployed with any microscope control software that can interact with a Python environment. Graphical Processing Units (GPUs) are recommended to increase the speed of application but are not required. On 3i systems the software can be deployed with a range of microscopes including their Lattice LightSheet microscope (LLSM) and spinning disk confocal (SDC). 1.3 Contacts.brooks.2@warwick.ac.uk

bioengineering↗

A multi-tiered mechanical mechanism shapes the early neural plate

The formation of complex tissues during embryonic development requires an intricate spatiotemporal coordination of local mechanical processes regulating global tissue morphogenesis. Here, we uncover a novel mechanism that mechanically regulates the shape of the anterior neural plate (ANP), a vital forebrain precursor, during zebrafish gastrulation. Combining in vivo and in silico approaches we reveal that the ANP is shaped by global tissue flows regulated by distinct force generating processes. We show that mesendoderm migration and E-cadherin-dependent differential tissue interactions control distinct flow regimes in the neuroectoderm. Initial opposing flows lead to progressive tissue folding and neuroectoderm internalisation which in turn provide forces driving ANP tissue reshaping. We find that convergent extension is dispensable for internalisation but required for ANP tissue extension. Our results highlight how spatiotemporal regulation and coupling of different mechanical processes between tissues in the embryo controls the first folding event in the developing brain.

developmental biology↗

The formation and closure of macropinocytic cups in a model system

Macropinocytosis is a conserved endocytic process where cells take up medium into micron-sized vesicles. In Dictyostelium, macropinocytic cups form around domains of PIP3 in the plasma membrane and extend by actin polymerization. Using lattice light-sheet microscopy, we describe how cups originate, are supported by an F-actin scaffold and shaped by a ring of actin polymerization, created around PIP3 domains. How cups close is unknown. We find two ways: lip closure, where actin polymerization at the lip is re-directed inwards; and basal closure, where it stretches the cup, eventually causing membrane delamination and vesicle sealing. Cups grow as expanding waves of actin polymerization that travel across the cell surface, capturing new membrane. We propose that cups close when these waves stall. This stalled wave hypothesis is tested through a conceptual model, where the interplay of forces from actin polymerization and membrane tension recreates many of our observations.

cell biology↗

A Curvature-Enhanced Random Walker Segmentation Method For Detailed Capture of 3D Cell Surface Membranes

High-resolution 3D microscopy is a fast advancing field and requires new techniques in image analysis to handle these new datasets. In this work, we focus on detailed 3D segmentation of Dictyostelium cells undergoing macropinocytosis captured on an iSPIM microscope. We propose a novel random walker-based method with a curvature-based enhancement term, with the aim of capturing fine protrusions, such as filopodia and deep invaginations, such as macropinocytotic cups, on the cell surface. We tested our method on both real and synthetic 3D image volumes, demonstrating that the inclusion of the curvature enhancement term can improve the segmentation of the aforementioned features. We show that our method performs better than other state of the art segmentation methods in 3D images of Dictyostelium cells, and performs competitively against CNN-based methods in challenge datasets, demonstrating the ability to obtain accurate segmentations without the requirement of large training datasets. We also present an automated seeding method for microscopy data, which, combined with the curvature-enhanced random walker method, enables the segmentation of large time series with minimal input from the experimenter.

bioinformatics↗

TOG domain MT polymerases accelerate MT plus end growth via electrostatically-steered diffusion-to-capture and electrostatic templating of GTP-tubulin

TOG domain microtubule polymerases track microtubule plus ends, bind GTP-tubulin and catalyse microtubule growth, by mechanisms that are not yet understood. In this work, we use computational analysis and simulation to probe the detailed mechanism of tubulin capture and exchange by TOG domains. TOG domains display a ridge of 5 surface loops that form the core of the TOG-tubulin interface. Using computational mutagenesis, we confirm that this row of loops, which is positively charged, plays a dominant role in setting the overall electrostatic field on the TOG domain. Brownian dynamics simulations establish that diffusion-to-capture of TOGs by tubulin is very strongly electrostatically steered. Under a range of conditions and in all trajectories examined, TOGs are initially captured and oriented by tubulin at high radius so that their basic loops faced inwards towards the tubulin. Thereafter, the loops continue to face inwards towards the tubulin and to scan its surface until stereospecific docking the crystallographic binding site occurs. We find that the acidic C-terminal tails of tubulin are not required for electrostatic steering, but instead serve to widen the acceptance angles for electrostatically steered diffusion-to-capture. All-atom normal mode analysis indicates that TOGs are remarkably stiff, enabling them to drive free GTP-tubulin into a partially-curved state by conformational selection. Electrostatic free energy calculations show that the complex that each TOG makes with its cognate tubulin is stable. Our work argues that TOGs accelerate microtubule plus end growth by two complementary electrostatic mechanisms, first by electrostatically steered diffusion-to-capture, and second by electrostatic stabilisation of a partially bent conformation of GTP-tubulin that exchanges rapidly into the tip-lattice. To explain this rapid exchange, we propose a model in which simultaneous binding of the GTP-tubulin to the TOG and the microtubule tip-lattice can occur and is required to de-stabilise the crystallographic complex and release and recycle the TOG.\n\nAuthor SummaryTOG domain microtubule polymerases are protein machines that accelerate the growth of microtubule plus ends by capturing tubulin building blocks from solution and feeding them into the growing microtubule tip. Exactly how TOGs manage to do this remains unclear. Several lines of evidence suggest that electrostatic interactions play a key role, but the detailed role of electrostatics in the polymerase mechanism of TOGs is so far little explored. Here using linked computational approaches we analyse the electrostatic fields of TOGs from the TOG polymerase superfamily and simulate their tubulin binding trajectories. We find that each TOG domain has a shaped electrostatic field that is precisely matched to its tubulin binding partner, such that each TOG is electrostatically orientated at high radius and thereafter electrostatically guided to its capture site. Our work shows that electrostatic steering dramatically accelerates the diffusion-to-capture of tubulin by TOGs. The resulting TOG-tubulin complexes are electrostatically stabilized and we suggest that release of the TOG from this complex requires that tubulin first be incorporated into the growing microtubule, thereby being driven into a TOG-incompatible conformation.

biophysics↗

QuimP - Analyzing transmembrane signalling in highly deformable cells

SummaryTransmembrane signalling plays important physiological roles, with G protein-coupled cell surface receptors being particularly important therapeutic targets. Fluorescent proteins are widely used to study signalling, but the analysis of image time series can be challenging, in particular when changes in cell shape are involved. To this end we have developed QuimP software. QuimP semi-automatically tracks cell outlines, quantifies spatio-temporal patterns of fluorescence at the cell membrane, and tracks local shape deformations. QuimP is particularly useful for studying cell motility, for example in immune or cancer cells.\n\nAvailability and ImplementationQuimP (http://warwick.ac.uk/quimp) consists of a set of Java plugins for Fiji/ImageJ (http://fiji.sc/) and can be easily installed through the Fiji Updater (http://warwick.ac.uk/quimp/wiki-pages/installation). It is compatible with Mac, Windows and Unix-based operating systems, requiring version >1.45 of Fiji/ImageJ and Java 8. QuimP is released as open source (https://github.com/CellDynamics/QuimP/) under an academic licence.\n\nContactT.Bretschneider@warwick.ac.uk\n\nSupplementary InformationSupplementary materials (SI-A to SI-D) are available at Bioinformatics online. Test data is available from http://warwick.ac.uk/quimp/test_data.

bioinformatics↗