Biology subjects

Tischer, C.

Publications and source records attributed to Tischer, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Life-cycle trajectory inference links temperature-gated progenitors to reproductive fate

Temperature shapes reproductive strategies across animals, yet how individuals switch between sexual and asexual reproduction remains unknown. We establish the planarian Phagocata morgani as a model for temperature-dependent reproductive plasticity and adapt multiplexed single-cell transcriptomics to profile >1 million nuclei from >300 animals across body sizes and temperatures. Leveraging individual variation in cell composition, we reconstruct an organism-wide trajectory that bifurcates toward alternative reproductive fates. Temperature extremes constrain worms to one fate, whereas intermediate conditions permit probabilistic commitment to either. At the bifurcation, temperature gates a stem cell pool: warmth suppresses differentiation and promotes progenitor accumulation, whereas cold transcriptionally activates this pool for de novo sexual organogenesis. These findings reveal how environmental inputs act on stem cells to couple body size, temperature, and reproductive fate.

Developmental Biology↗

bioRxiv2026

Microtubules sustain the fidelity of cellularization in a coenocytic relative of animals

Cellularization is the coordinated division of a multinucleate cytoplasm into many cells.1-3 Multinucleation is a common life cycle strategy observed across eukaryotic lineages, including in microbial eukaryotes, fungi, plants and animals, and is associated with the ability to transition to a unicellular state through cellularization.4 In the best-studied model for this process, Drosophila melanogaster, cellularization requires the coordinated action of actin and microtubule (MT) networks to bring about the synchronous invagination of plasma membrane furrows, but the extent of conservation of these mechanisms across eukaryotes remains unknown.1,5,6 Here we investigate cellularization in the ichthyosporean Sphaeroforma arctica, a close relative of animals with a multinucleate life cycle stage.7-9 Using live cell imaging, ultrastructure expansion microscopy (U-ExM) and volume electron microscopy, we define the membrane, MT and actin dynamics that accompany cellularization in S. arctica. Using pharmacological inhibitors and centrifugation, we show that MTs, in addition to positioning nuclei, play a role in guiding nascent furrows to sustain equi-partitioning of nuclei and cytoplasm between daughter cells. Our findings indicate that cellularization is regulated through crosstalk between actin and MT networks, exhibiting mechanistic parallels with canonical cytokinesis, and establish S. arctica as a valuable model for investigating general principles of cellularization.

cell biology↗

bioRxiv2025

Clathrin adaptors drive phase separation in endocytosis and trafficking

Liquid-liquid phase separation (LLPS) underlies the formation of biomolecular condensates that organize cellular processes, including endocytosis and membrane trafficking. Although LLPS has been implicated in clathrin-mediated pathways, the specific contribution of adaptor proteins to condensate formation and function remains unclear. Here we show that two yeast adaptors, Ent5 and Sla2, undergo LLPS in vitro and that this property correlates with their distinct roles in membrane trafficking and condensate recruitment in vivo. Ent5 condensation is driven by a dynamic helix within its disordered region that acts as a molecular "sticker." Deletion of this helix disrupts membrane-associated condensation and leads to altered cargo trafficking dynamics in vivo, with Ent5-dependent transport events becoming delayed. In contrast, Sla2 behaves both as a driver and as a client of LLPS, with its coiled-coil (CC) region mediating condensation. Together, these findings reveal that endocytic adaptors can promote condensate formation through distinct structural features, thereby coupling clathrin binding and membrane association through phase separation.

biophysics↗

bioRxiv2025

iss-nf: A Nextflow-based end-to-end in situ sequencing decoding workflow

In situ sequencing (ISS) offers a powerful approach for spatially resolved gene expression profiling within tissue samples, but the complexity of analyzing the resulting data has limited its broader use. Here, we present iss-nf, a Nextflow-based, end-to-end workflow designed to streamline the decoding of large ISS datasets. The workflow automates critical steps, including image registration, fluorescent spot detection, transcript decoding, and quality control (QC), offering a scalable, reproducible, and user-friendly solution for ISS data analysis. We successfully applied iss-nf on multiple large datasets, including publicly available mouse brain and breast cancer tissue datasets, as well as an in-house non-small cell lung cancer (NSCLC) ISS dataset. The workflow is designed to be accessible for both experienced researchers, as well as newcomers to spatial transcriptomics, providing a robust tool for analyzing large-scale ISS data. Our results suggest that iss-nf is a valuable contribution to the growing field of spatial transcriptomics, enabling precise, modular, reproducible, and, by means of automated tiling and parallelization, scalable analysis of tissue-specific gene expression.

bioinformatics↗

bioRxiv2025

Quantitative high-resolution imaging of mouse nephron formation to study Wnt signaling dynamics

IntroductionNephron formation is initiated when Wnt9b from the ureteric bud acts on nephron progenitor cells in the metanephric mesenchyme. For mouse embryonic kidneys, this process can be studied in real time using ex vivo organ cultures. Previous imaging methods relied on Transwell filters with a long distance between objective and sample as well as low signal-to-noise ratio due to the filter membrane. Moreover, Wnt signaling was previously visualized with the expression reporters TCF/Lef:H2B-GFP. MethodsWe developed an ex vivo culture system based on low-volume media and fibronectin coating for real time imaging. We further made use of endogenously tagged Cherry-Lef1 and Ctnnb1-Venus reporter mouse lines as reporters for Wnt signaling during kidney development. Furthermore, we established an adaptive feedback microscopy pipeline to track the signal with high resolution. ResultsUsing these approaches, we found that Cherry-Lef1 proteins are only expressed in the nascent nephron and derivatives. Expression is graded along distal-proximal nephron axis suggesting that the ureteric bud-derived Wnt9b is controlling its expression. Interestingly, we observed that Cherry-Lef1 gradient shifts from distal to proximal axis during nephron patterning. {beta}-catenin-Venus, on the other hand, first became visible in the ureteric bud, then in the nascent nephron after Lef1. ConclusionsUsing a novel imaging approach we demonstrate a dynamic regulation of Wnt signaling that correlates with nephrogenesis in mouse kidney development. Combined with our two new Wnt signaling reporters, nephron formation can be studied in real-time with high resolution.

developmental biology↗

bioRxiv2024

Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression

Kidney fibrosis, characterized by excessive extracellular matrix deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. This study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFR{beta}+ mesenchymal cells aimed at unraveling disease mechanisms. Using transcriptomics, proteomics, phosphoproteomics, and secretomics we quantified over 14,000 biomolecules across seven time points following TGF-{beta} stimulation. This revealed distinct temporal patterns in the expression and activity of known and potential kidney fibrosis markers and modulators. Data integration resulted in time-resolved multi-omic network models which allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and regulatory mechanisms underlying kidney fibrosis. In particular, we show that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a resource to be further leveraged by the community. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/618507v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@d2bfaborg.highwire.dtl.DTLVardef@257d34org.highwire.dtl.DTLVardef@13f06f3org.highwire.dtl.DTLVardef@e16e6c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

systems biology↗

bioRxiv2024

Benchmarking Large Language Models for Bio-Image Analysis Code Generation

In the computational age, life-scientists often have to write Python code to solve bio-image analysis (BIA) problems. Many of them have not been formally trained in programming though. Code-generation, or coding assistance in general, with Large Language Models (LLMs) can have a clear impact on BIA. To the best of our knowledge, the quality of the generated code in this domain has not been studied. We present a quantitative benchmark to estimate the capability of LLMs to generate code for solving common BIA tasks. Our benchmark currently consists of 57 human-written prompts with corresponding reference solutions in Python, and unit-tests to evaluate functional correctness of potential solutions. We demonstrate our benchmark here and compare 18 state-of-the-art LLMs. To ensure that we will cover most of our community needs we also outline mid- and long-term strategies to maintain and extend the benchmark by the BIA open-source community. This work should support users in deciding for an LLM and also guide LLM developers in improving the capabilities of LLMs in the BIA domain.

bioinformatics↗

bioRxiv2024

Pervasive sublethal effects of agrochemicals as contributing factors to insect decline

Insect biomass is declining across the globe at an alarming rate. Climate change and the widespread use of pesticides have been hypothesized as two underlying drivers. However, the lack of systematic experimental studies across chemicals and species limits our causal understanding of this problem. Here, we employed a chemical library encompassing 1024 different molecules--including insecticides, herbicides, fungicides, and plant growth inhibitors --to investigate how insect populations are affected by varying concentrations of pesticides, focusing on sublethal doses. Using a controlled laboratory pipeline for Drosophila melanogaster, we found that 57% of these chemicals affect the behavior of larvae at sublethal concentrations, and an even higher proportion compromises long-term survivability after acute exposure. Consistent with these results, we observed that exposure to chemicals at doses orders of magnitude below lethality induced widespread phosphorylation changes across the larval proteome. The effects of agrochemicals were amplified when the ambient temperature was increased by four degrees. We also tested the synergistic effects of multiple chemicals at doses found widely in nature and observed fitness-reducing changes in larval developmental time, behavior, and reproduction. Finally, we expanded our investigation to additional fly species, mosquitos, and butterflies and detected similar behavioral alterations triggered by pesticides at sublethal concentrations. Our results provide experimental evidence that strongly suggests sublethal doses of agrochemicals coupled with changes in environmental temperatures are contributing to the global decline in insect populations. We anticipate that our assays can contribute to improving chemical safety assessment, better protect the environment, secure food supplies, and safeguard animal and human health, as well as understand our rapidly changing world.

ecology↗

bioRxiv2023

Dextromethorphan inhibits collagen transport in the endoplasmic reticulum eliciting an anti-fibrotic response in ex-vivo and in vitro models of pulmonary fibrosis

Excessive deposition of fibrillar collagen in the interstitial extracellular matrix (ECM) of human lung tissue causes fibrosis, which can ultimately lead to organ failure. Despite our understanding of the molecular mechanisms underlying the disease, a cure for pulmonary fibrosis has not yet been found. In this study, we screened an FDA-approved drug library containing 712 drugs and found that Dextromethorphan (DXM), a cough expectorant, significantly reduces the amount of excess fibrillar collagen deposited in the ECM in in-vitro cultured primary human lung fibroblasts (NHLF) and ex-vivo cultured human precision-cut lung slice (hPCLS) models of lung fibrosis. Reduced extracellular fibrillar collagen levels in the ECM upon DXM treatment are due to a reversible trafficking inhibition of collagen type I (COL1) in the endoplasmic reticulum (ER) in TANGO1 and HSP47 positive structures. Mass spectrometric analysis shows that DXM causes hyper-hydroxylation of proline and lysine residues on Collagen (COL1, COL3, COL4, COL5, COL7, COL12) and Latent-transforming growth factor beta-binding protein (LTBP1 and LTBP2) peptides coinciding with their secretion block. In addition, thermal proteome profiling of cells treated with DXM shows increased thermal stability of prolyl-hydroxylases such as P3H2, P3H3, P3H4, P4HA1 and P4HA2, suggesting a change in activity. Transcriptome analysis of pro-fibrotic stimulated NHLFs and hPCLS upon DXM treatment showed activation of an anti-fibrotic program via regulation of pathways such as those involved in the MMP-ADAMTS axis, WNT, and fibroblast-to-myofibroblast differentiation. Taken together, the data obtained from both in-vitro and ex-vivo models of fibrogenesis show that Dextromethorphan has potent anti-fibrotic activity by efficient inhibition of COL1 membrane trafficking in the ER.

cell biology↗

bioRxiv2023

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself - OME-Zarr - along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

bioinformatics↗

bioRxiv2022

MoBIE: A Fiji plugin for sharing and exploration of multi-modal cloud-hosted big image data

Facing the challenge of exploring and sharing multi-terabyte, multi-modal and multi-scale image data of heterogeneous dimensionality, we developed MoBIE, a Fiji plugin that provides rich visualization features to enable browsing data from numerous biomedical applications on a standard laptop computer. MoBIE also supports segmentations, associated measurements and annotations. Users can configure complex views of datasets, share them with collaborators, and use them for interactive figure panels. The MoBIE plugin also offers a convenient interface for converting data into compatible data formats; an additional Python library facilitates managing diverse MoBIE projects.

bioinformatics↗

bioRxiv2022

The Image Data Explorer: interactive exploration of image-derived data

Many bioimage analysis projects produce quantitative descriptors of regions of interest in images. Associating these descriptors with visual characteristics of the objects they describe is a key step in understanding the data at hand. However, as many bioimage data and their analysis workflows are moving to the cloud, addressing interactive data exploration in remote environments has become a pressing issue. To address it, we developed the Image Data Explorer (IDE) as a web application that integrates interactive linked visualization of images and derived data points with exploratory data analysis methods, annotation, classification and feature selection functionalities. The IDE is written in R using the shiny framework. It can be easily deployed on a remote server or on a local computer. The IDE is available at https://git.embl.de/heriche/image-data-explorer and a cloud deployment is accessible at https://shiny-portal.embl.de/shinyapps/app/01_image-data-explorer.

cell biology↗

bioRxiv2021

Volumetric morphometry reveals mitotic spindle width as the best predictor of spindle scaling

The function of cellular structures at the mesoscale is dependent on their geometry and proportionality to cell size. The mitotic spindle is a good example why length and shape of intracellular organelles matter. Spindle length determines the distance over which chromosomes will segregate and spindle shape ensures bipolarity. While we still lack a systematic and quantitative understanding of subcellular morphometrics, new imaging techniques and volumetric data analysis promise novel insights into scaling relations across different species. Here, we introduce Spindle3D, an open-source plug-in that allows for the quantitative, unbiased, and automated analysis of 3D fluorescent data of spindles and chromatin. We systematically analyse different cell types, including somatic cells, stem cells and one-cell embryos across different phyla to derive volumetric relations of spindle, chromatin, and cell volume. Taken together, our data indicate that mitotic spindle width is a robust indicator of spindle volume, which correlates linearly with chromatin and cell volume both within single cell types and across metazoan phyla.

systems biology↗

bioRxiv2021

OME-NGFF: scalable format strategies for interoperable bioimaging data

Biological imaging is one of the most innovative fields in the modern biological sciences. New imaging modalities, probes, and analysis tools appear every few months and often prove decisive for enabling new directions in scientific discovery. One feature of this dynamic field is the need to capture new types of data and data structures. While there is a strong drive to make scientific data Findable, Accessible, Interoperable and Reproducible (FAIR 1), the rapid rate of innovation in imaging impedes the unification and adoption of standardized data formats. Despite this, the opportunities for sharing and integrating bioimaging data and, in particular, linking these data to other "omics" datasets have never been greater. Therefore, to every extent possible, increasing "FAIRness" of bioimaging data is critical for maximizing scientific value, as well as for promoting openness and integrity. In the absence of a common, FAIR format, two approaches have emerged to provide access to bioimaging data: translation and conversion. On-the-fly translation produces a transient representation of bioimage metadata and binary data but must be repeated on each use. In contrast, conversion produces a permanent copy of the data, ideally in an open format that makes the data more accessible and improves performance and parallelization in reads and writes. Both approaches have been implemented successfully in the bioimaging community but both have limitations. At cloud-scale, those shortcomings limit scientific analysis and the sharing of results. We introduce here next-generation file formats (NGFF) as a solution to these challenges.

bioinformatics↗

bioRxiv2021

CLEMSite, a software for automated phenotypic screens using light microscopy and FIB-SEM

Correlative light and electron microscopy (CLEM) combines two imaging modalities, balancing out the limits of one technique with the other. In recent years, Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) has emerged as a flexible method that enables semi-automated volume acquisition at the ultrastructural level. We present a toolset for adherent cultured cells that enables tracking and finding cell regions previously identified in light microscopy, in the FIB-SEM along with automatic acquisition of high-resolution volume datasets. We detect a grid pattern in both modalities (LM and EM), which identifies common reference points. The novel combination of these techniques enables complete automation of the workflow. This includes setting the coincidence point of both ion and electron beams, automated evaluation of the image quality and constantly tracking the sample position with the microscopes field of view reducing or even eliminating operator supervision. We show the ability to target the regions of interest in EM within 5 {micro}m accuracy, while iterating between different targets and implementing unattended data acquisition. Our results demonstrate that executing high throughput volume acquisition in electron microscopy is possible.

cell biology↗

bioRxiv2020

BigDataProcessor2: A free and open-source Fiji plugin for inspection and processing of TB sized image data

Modern bioimaging and related areas such as sensor technology has seen tremendous development the last years allowing several contemporary imaging techniques, electron microscopy (EM) and light sheet microscopy in particular, to generate datasets frequently reaching the size of several terabytes (TB). As a consequence, even seemingly simple data operations such as cropping, chromatic- and drift-corrections and even visualisation, poses challenges when applied to thousands of time points or tiles. To address this we developed BigDataProcessor2 - a Fiji plugin facilitating processing workflows for TB sized image datasets. Availability and implementationBigDataProcessor2 is available as a Fiji plugin via the BigDataProcessor update site. The application is implemented in Java and the code is publicly available on GitHub (https://github.com/bigdataprocessor/bigdataprocessor2). Contactchristian.tischer@embl.de, nils.norlin@med.lu.se

bioinformatics↗

bioRxiv2020

Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera

Emergence of the novel pathogenic coronavirus SARS-CoV-2 and its rapid pandemic spread presents numerous questions and challenges that demand immediate attention. Among these is the urgent need for a better understanding of humoral immune response against the virus as a basis for developing public health strategies to control viral spread. For this, sensitive, specific and quantitative serological assays are required. Here we describe the development of a semi-quantitative high-content microscopy-based assay for detection of three major classes (IgG, IgA and IgM) of SARS-CoV-2 specific antibodies in human samples. The possibility to detect antibodies against the entire viral proteome together with a robust semi-automated image analysis workflow resulted in specific, sensitive and unbiased assay which complements the portfolio of SARS-CoV-2 serological assays. The procedure described here has been used for clinical studies and provides a general framework for the application of quantitative high-throughput microscopy to rapidly develop serological assays for emerging virus infections.

microbiology↗

bioRxiv2020

Dense encoding of developmental regulatory information may constrain evolvability

Gene regulatory changes underlie much of phenotypic evolution. However, the evolutionary potential of regulatory evolution is unknown, because most evidence comes from either natural variation or limited experimental perturbations. Surveying an unbiased mutation library for a developmental enhancer in Drosophila melanogaster using an automated robotics pipeline, we found that most mutations alter gene expression. Our results suggest that regulatory information is distributed throughout most of a developmental enhancer and that parameters of gene expression--levels, location, and state--are convolved. The widespread pleiotropic effects of most mutations and the codependency of outputs may constrain the evolvability of developmental enhancers. Consistent with these observations, comparisons of diverse drosophilids reveal mainly stasis and apparent biases in the phenotypes influenced by this enhancer. Developmental enhancers may encode a much higher density of regulatory information than has been appreciated previously, which may impose constraints on regulatory evolution. Quote"Rock, robot rock Rock, robot rock Rock, robot rock" Daft Punk (2005)

evolutionary biology↗