Biology subjects

Schmied, C.

Publications and source records attributed to Schmied, C..

9 recordsLinked to original sources

bioRxiv2024

Semi-supervised Contrastive Learning for Bioactivity Prediction using Cell Painting Image Data

Morphological profiling has recently demonstrated remarkable potential for identifying the biological activities of small molecules. Alongside the fully supervised and self-supervised machine learning methods recently proposed for bioactivity prediction from Cell Painting image data, we introduce here a semi-supervised contrastive (SemiSupCon) learning approach. This approach combines the strengths of using biological annotations in supervised contrastive learning and leveraging large unannotated image datasets with self-supervised contrastive learning. SemiSupCon enhances downstream prediction performance of classifying MeSH pharmacological classifications from PubChem, as well as mode of action and biological target annotations from the Drug Repurposing Hub across two publicly available Cell Painting datasets. Notably, our approach has effectively predicted the biological activities of several unannotated compounds, and these findings were validated through literature searches. This demonstrates that our approach can potentially expedite the exploration of biological activity based on Cell Painting image data with minimal human intervention.

bioinformatics↗

bioRxiv2024

Morphological Profiling Dataset of EU-OPENSCREEN Bioactive Compounds Over Multiple Imaging Sites and Cell Lines

Morphological profiling with the Cell Painting assay has emerged as a promising method in drug discovery research. The assay captures morphological changes across various cellular compartments enabling the rapid identification of the effect of compounds. We present a comprehensive morphological profiling dataset using the carefully curated and well-annotated EU-OPENSCREEN Bioactive Compound Set. Our profiling dataset was generated across multiple imaging sites with high-throughput confocal microscopes using the Hep G2 as well as the U2 OS cell line. We employed an extensive assay optimization process to achieve high data quality across the different imaging sites. An analysis of the four replicates validates the robustness of the generated data. We compare morphological features of the different cell lines and map the profiles to activity, toxicity, and basic compound targets to further describe the dataset as well as to demonstrate the potential of this dataset to be used for mechanism of action exploration.

cell biology↗

bioRxiv2024

Cardiovascular responses to natural and auditory evoked slow waves predict post-sleep cardiac function

The interplay between slow-wave sleep and cardiovascular health is increasingly recognized. Our prior research showed that auditory-enhanced slow waves can boost cardiac function, yet the mechanisms behind this remain unclear. Advancing these findings, our current analysis dissected the effects of two slow wave types on cardiovascular function, using data from 18 middle-aged men across three nights. We found that the strength of heart rate and blood pressure responses concurrent with slow waves predicts cardiac function post-sleep. Notably, we identified that highly synchronized type I slow waves, as opposed to lower-amplitude type II slow waves, primarily co-occur with these cardiovascular pulsations. While auditory stimulation enhances both types of slow waves, they exhibit distinct temporal dynamics, pointing to different underlying biological mechanisms. This study crucially addresses how distinct slow wave types can affect cardiovascular function, implying that targeted slow wave stimulation could be a strategic approach to improve heart health.

neuroscience↗

bioRxiv2024

Septin-associated PIPKIγ splice variants drive centralspindlin association with the midbody via PI(4,5)P2

Mammalian cytokinesis critically depends on the phospholipid phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] which serves as docking site for crucial components of the cytokinetic machinery at the plasma membrane. PI(4,5)P2 supports several stages of cytokinesis, including actomyosin ring assembly and constriction, membrane tethering of spindle microtubules, and midbody organization. How these various activities of PI(4,5)P2 and the underlying mechanisms of local PI(4,5)P2 synthesis are orchestrated in space and time has remained elusive. Here, we identify a pivotal role of septin-binding splice variants of PIPKI{gamma} that couple nanoscale PI(4,5)P2 synthesis at the ingressing cleavage furrow to late midbody formation. Depletion of PIPKI{gamma} isoforms causes multinucleation and perturbs anillin and septin deposition at the intercellular bridge and at the midbody. These defects are rescued by wild-type kinase, but not by septin binding-deficient or catalytically inactive PIPKI{gamma} variants. We further show that both, septins and PIPKI{gamma} form a complex with centralspindlin, and thereby facilitate the recruitment of centralspindlin to the midbody. Taken together, our findings establish septin-associated PIPKI{gamma} isoforms as key regulators of midbody organization that act through generating a local pool of PI4,5P2 required for centralspindlin recruitment and maintenance at the midbody, and for septin association with microtubules.

cell biology↗

bioRxiv2023

OrgaMapper: A robust and easy-to-use workflow for analyzing organelle positioning

Eukaryotic cells are highly compartmentalized by a variety of organelles that carry out specific cellular processes. The position of these organelles within the cell is elaborately regulated and vital for their function. For instance, the position of lysosomes relative to the nucleus controls their degradative capacity and is altered in pathophysiological conditions. The molecular components orchestrating the precise localization of organelles remain incompletely understood. A confounding factor in these studies is the fact that organelle positioning is surprisingly non-trivial to address. E.g., perturbations that affect the localization of organelles often lead to secondary phenotypes such as changes in cell or organelle size. These phenotypes could potentially mask effects or lead to the identification of false positive hits. To uncover and test potential molecular components at scale, accurate and easy to use analysis tools are required that allow robust measurements of organelle positioning. Here, we present an analysis workflow for the faithful, robust, and quantitative analysis of organelle positioning phenotypes. Our workflow consists of an easy to use Fiji plugin and an R Shiny App. These tools enable users without background in image or data analysis to (1) segment single cells and nuclei and to detect organelles, (2) to measure cell size and the distance between detected organelles and the nucleus, (3) to measure intensities in the organelle channel plus one additional channel, and (4) to plot the results in informative graphs. Using simulated data and immunofluorescent images of cells in which the function of known factors for lysosome positioning has been perturbed, we show that the workflow is robust against common problems for the accurate assessment of organelle positioning such as changes of cell shape and size, organelle size and background.

cell biology↗

bioRxiv2022

Effects of auditory sleep modulation approaches on brain oscillatory and cardiovascular dynamics

Sleep modulation techniques to elucidate the functional role of sleep brain oscillations in brain and body functions have gained large interest. Slow waves, the hallmark feature of deep non-rapid eye movement sleep, do potentially drive restorative effects on brain and cardiovascular functions. Auditory stimulation to modulate slow waves is a promising tool, however, directly comparing different auditory stimulation approaches within a night and analyzing induced dynamic brain and cardiovascular effects are yet missing. Here, we tested various auditory stimulation approaches in a windowed, 10 s ON (stimulations) followed by 10 s OFF (no stimulations), within-night stimulation design and compared them to a SHAM control condition. We report the results of three studies and a total of 51 included stimulation nights. We found a large and global increase in slow wave activity (SWA) in the stimulation window compared to SHAM. Furthermore, slow wave dynamics were most pronouncedly increased at the start of the stimulation and declined across the stimulation window. Beyond the changes in brain oscillations, we observed, for some conditions, a significant increase in the mean interval between two heartbeats within a stimulation window, indicating a slowing of the heart rate, and increased heart rate variability derived parasympathetic activity. Those cardiovascular changes were positively correlated with the change in SWA and thus, our findings provide mechanistic insight into the potential of auditory slow wave enhancement to modulate cardiovascular restorative conditions during sleep. However, future studies need to investigate whether the potentially increased restorative capacity through slow wave enhancements translates into a more rested cardiovascular system on the subsequent day.

neuroscience↗

bioRxiv2021

Labkit: Labeling and Segmentation Toolkit for Big Image Data

We present LO_SCPLOWABKITC_SCPLOW, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to single- and multi-channel images as well as to timelapse movies in 2D or 3D. LO_SCPLOWABKITC_SCPLOW is specifically designed to work efficiently on big image data and enables users of consumer laptops to conveniently work with multiple-terabyte images. This efficiency is achieved by using ImgLib2 and BigDataViewer as the foundation of our software. Furthermore, memory efficient and fast random forest based pixel classification inspired by the Waikato Environment for Knowledge Analysis (Weka) is implemented. Optionally we harness the power of graphics processing units (GPU) to gain additional runtime performance. LO_SCPLOWABKITC_SCPLOW is easy to install on virtually all laptops and workstations. Additionally, LO_SCPLOWABKITC_SCPLOW is compatible with high performance computing (HPC) clusters for distributed processing of big image data. The ability to use pixel classifiers trained in LO_SCPLOWABKITC_SCPLOW via the ImageJ macro language enables our users to integrate this functionality as a processing step in automated image processing workflows. Last but not least, LO_SCPLOWABKITC_SCPLOW comes with rich online resources such as tutorials and examples that will help users to familiarize themselves with available features and how to best use LO_SCPLOWABKITC_SCPLOW in a number of practical real-world use-cases.

bioinformatics↗

bioRxiv2018

Selective increases in inter-individual variability in response to environmental enrichment

One manifestation of individualization is a progressively differential response of individuals to the non-shared components of the same environment. Individualization has practical implications in clinical setting, where subtle differences between patients are often decisive for the success of an intervention, yet there has been no suitable animal model to study its underlying biological mechanisms. Here we show that enriched environment (ENR) can serve as a model of brain individualization. We kept 40 isogenic mice for 3 months in ENR and compared the effects on a wide range of phenotypes on both mean and variance to an equally sized group of standard-housed control animals. While ENR influenced multiple parameters and restructured correlation patterns between them, it only increased differences among individuals in traits related to brain and behavior (adult hippocampal neurogenesis, motor cortex thickness, open field and object exploration, rotarod performance), in agreement with the hypothesis of a specific activity-dependent development of brain individuality.

neuroscience↗

bioRxiv2017

Continuous high-resolution in vivo imaging reveals tumor-specific dissemination in an embryonic zebrafish xenograft model

Mechanisms mediating tumor metastasis are crucial for diagnostic and therapeutic targeting. Here, we take advantage of a transparent embryonic zebrafish xenograft model (eZXM) to visualize and track injected human leukemic and breast cancer cells in real time using selective plane illumination microscopy (SPIM) for up to 30 hours. Injected cells exhibited disease-specific patterns of intravascular distribution with leukemic cells moving faster than breast cancer cells. While breast cancer cells predominantly adhered to nearby regions, about 30% invaded the avascularized tissue, reminiscent of their metastatic phenotype. Survival of the injected tumor cells was partly inhibited by the cellular innate immune system of the recipient embryos and leukemic cell dissemination was effectively inhibited by pharmacological ROCK1 blockade. These observations, and the ability to image several embryos simultaneously, support the use of eZXM and SPIM imaging as a functional screening platform to identify compounds that restricts cancer cell spread and invasion.

cancer biology↗