Biology subjects

Zechner, C.

Publications and source records attributed to Zechner, C..

11 recordsLinked to original sources

bioRxiv2026

Live-cell imaging of enhancer-promoter dynamics reveals transient contact-driven gene activation

Enhancers are key regulators of mammalian gene expression, yet how they interact with promoters in space (contact vs. action-at-a-distance) and in time (transient vs. stable) remains poorly understood. Recent studies suggest that enhancers can activate promoters across distances exceeding 200 nanometers, challenging classical contact models, but limited spatiotemporal resolution has obscured the mechanistic details of enhancer-promoter (E-P) interactions and their link to transcription. Here, we engineered a synthetic biology platform optimized for the simultaneous visualization of E-P 3D distance and nascent transcription using super-resolution live-cell imaging. By applying five complementary approaches integrating imaging, 3D genomics, and gene expression data across cell lines, we estimate that transcriptional activation is mediated by [~]25-42 nanometer contacts on the seconds timescale. Our results support a transient contact mechanism for E-P-mediated gene activation.

biophysics↗

bioRxiv2025

Genome-wide absolute quantification of chromatin looping

3D genomics methods such as Hi-C and Micro-C have uncovered chromatin loops across the genome and linked these loops to gene regulation. However, these methods only measure 3D interaction probabilities on a relative scale. Here, we overcome this limitation by using live imaging data to calibrate Micro-C in mouse embryonic stem cells, thus obtaining absolute looping probabilities for 36,804 chromatin loops across the genome. We find that the looped state is generally rare, with a mean probability of 2.3% and a maximum of 26% across the quantified loops. On average, CTCF-CTCF loops are stronger than loops between cis-regulatory elements (3.2% vs. 1.1%). Our findings can be extended to human stem cells and differentiated cells under certain assumptions. Overall, we establish an approach for genome-wide absolute loop quantification and report that loops generally occur with low probabilities, generalizing recent live imaging results to the whole genome.

biophysics↗

bioRxiv2024

Anisotropic stretch biases the self-organization of actin fibers in multicellular Hydra aggregates

During development, groups of cells generate shape by coordinating their mechanical properties through an interplay of self-organization and pre-patterning. Hydra displays a striking planar pattern of actin fibers at the organism scale, and mechanics influence the morphogenesis of biological structures during its pre-patterned regeneration. However, how mechanics participate in the formation of an ordered pattern from a totally disordered state remains unknown. To study this, we used cellular aggregates formed from dissociated Hydra cells, which initially lose all actin polarity yet regenerate a long-range actin pattern. We showed quantitatively that the actin meshwork evolves from a disordered symmetric state to an ordered state in which rotational symmetry is broken, and translation symmetry is partially broken, with the nematic and smectic order parameters increasing over days. During the first hours, the actin meshwork displayed spatial heterogeneity in the nematic order parameter, and ordered domains separated by lines of defects progressively grew and fused. This suggests that local cell-cell interactions drive the transition from disorder to order. To understand the mechanism of ordering, we perturbed the tissues physical constraints. We showed that while topology and geometry do not have a direct effect, anisotropic stretch biases the emerging orientation of the actin meshwork within hours. Surprisingly, although a Wnt protein gradient is expected to play a role in the actin ordering, the stretch-associated alignment happened without a Wnt enrichment. This demonstrates the role of tissue mechanics in the alignment of the actin fibers during the disorder-to-order transition.

developmental biology↗

bioRxiv2024

On the relationship between concentration buffering and noise reduction in phase separating systems

Biomolecular condensates have been proposed to buffer intracellular concentrations and reduce noise. Recent results demonstrate that concentrations need not be buffered in multicomponent systems, leading to a non-constant saturation concentration ( csat ) when individual components are varied. Simplified equilibrium considerations suggest that noise reduction might be closely related to concentration buffering and that a fixed saturation concentration is required for noise reduction to be effective. Here we present a theoretical analysis to demonstrate that these suggestions do not apply to mesoscopic fluctuating systems. We show that concentration buffering and noise reduction are distinct concepts, which cannot be used interchangeably. We further demonstrate that concentration buffering - and a constant csat - are neither necessary nor sufficient for noise reduction to be effective. Clarity about these concepts is important for studying the role of condensates in controlling cellular noise and for the interpretation of concentration relationships in cells.

biophysics↗

bioRxiv2023

Cell-free quorum sensing to drive feedback and communication within populations of droplet interface bilayers

Building synthetic multicellular systems using non-living molecular components is a grand challenge in the field of bottom-up synthetic biology. Towards this goal, a diverse range of chemistries have been developed to provide mechanisms of intercellular communication and methods to assemble multicellular compartments. However, building bottom-up synthetic multicellular systems is still challenging because it requires the integration of intercellular reaction networks with compatible cellular compartment properties. In this study, we encapsulated cell-free expression systems (CFES) expressing two quorum sensing genetic circuits into droplet interface bilayer (DIB) synthetic cells to demonstrate intercellular communication and feedback. We further develop a method of generating custom DIB multicellular structures by acoustic liquid handling to automatically dispense the CFES droplets and show the potential for multiplexing compartmentalized gene circuits for generating heterogeneous populations of cells. Our work provides a step towards building more complex multicellular systems with feedback mechanisms from the bottom-up to study and experimentally model biological multiscalar processes.

synthetic biology↗

bioRxiv2023

Quantifying single cell lipid signaling kinetics after photo-stimulation

Studying the role of molecularly distinct lipid species in cell signaling remains challenging due to a scarcity of methods for performing quantitative lipid biochemistry in living cells. We have recently used lipid uncaging to quantify lipid-protein affinities and rates of lipid transbilayer movement and turnover in the diacylglycerol signaling pathway using population average time series data. So far, this approach does not allow to account for the cell-to-cell variability of cellular signaling responses. We here report a framework that allows to uniquely identify model parameters such diacylglycerol-protein affinities and transbilayer movement rates at the single cell level for a broad variety of structurally different diacylglycerol species. We find that lipid unsaturation degree and longer side chains generally correlate with faster lipid transbilayer movement and turnover and higher lipid-protein affinities. In summary, our work demonstrates how rate parameters and lipid-protein affinities can be quantified from single cell signaling trajectories with sufficient sensitivity to resolve the subtle kinetic differences caused by the chemical diversity of cellular signaling lipid pools.

cell biology↗

bioRxiv2022

Deterministic and probabilistic fate decisions co-exist in a single retinal lineage

Correct nervous system development depends on the timely differentiation of progenitor cells into neurons. While the output of progenitor differentiation is well investigated at the population and clonal level, the possibilities and constraints for fate decisions of specific progenitors over development are less explored. Particularly little is known about their variability and competence plasticity. To fill this gap, we here use long-term live imaging to follow the outcome of progenitor divisions in the zebrafish retina. We find that neurogenic Atoh7 expressing progenitors produce different neuronal types over development with time-dependent probabilities. Interestingly, deterministic and probabilistic fate decisions co-exist in the same lineage. While interference with the deterministic fate affects lineage progression, interference with fate probabilities of the stochastic lineage branch results in a broader range of fate possibilities than seen in controls. When tissue development is challenged, Atoh7 expressing progenitors can produce any neuronal type, arguing against the concept of fixed competence windows. Stochastic modelling of fate probabilities in challenged conditions revealed a simple gene regulatory network able to recapitulate the observed competence changes during development. Based on our results, we postulate that fate plasticity could be involved in robust retinal development, a concept possibly applicable to other tissues.

developmental biology↗

bioRxiv2021

A combined transcriptional and dynamic roadmap of single human pancreatic endocrine progenitors reveals proliferative capacity and differentiation continuum

Basic helix-loop-helix genes, particularly proneural genes, are well-described triggers of cell differentiation, yet limited information exists on their dynamics, notably in human development. Here, we focus on Neurogenin 3 (NEUROG3), which is crucial for pancreatic endocrine lineage initiation. Using a double reporter to monitor endogenous NEUROG3 transcription and protein expression in single cells in 2D and 3D models of human pancreas development, we show peaks of expression for the RNA and protein at 22 and 11 hours respectively, approximately two-fold slower than in mice, and remarkable heterogeneity in peak expression levels all triggering differentiation. We also reveal that some human endocrine progenitors proliferate once, mainly at the onset of differentiation, rather than forming a subpopulation with sustained proliferation. Using reporter index-sorted single-cell RNA-seq data, we statistically map transcriptome to dynamic behaviors of cells in live imaging and uncover transcriptional states associated with variations in motility as NEUROG3 levels change, a method applicable to other contexts.

developmental biology↗

bioRxiv2021

Dynamics of CTCF and cohesin mediated chromatin looping revealed by live-cell imaging

Animal genomes are folded into loops and topologically associating domains (TADs) by CTCF and cohesin, but whether these loops are stable or dynamic is unknown. Here, we directly visualize chromatin looping at the Fbn2 TAD in mouse embryonic stem cells using super-resolution live-cell imaging and quantify looping dynamics by Bayesian inference. Our results are consistent with cohesin-mediated loop extrusion in cells, and with CTCF both stopping and stabilizing cohesin. Surprisingly, the Fbn2 loop is both rare and dynamic, with a looped fraction of ~3-6.5% and a median loop lifetime of ~10-30 minutes. Instead of a stable loop, our results establish a highly dynamic view of TADs and loops where the Fbn2 TAD exists predominantly in a partially extruded conformation. This dynamic and quantitative view of TADs may facilitate a mechanistic understanding of their functions.

biophysics↗

bioRxiv2019

The gift of gab: probing the limits of dynamic concentration-sensing across a network of communicating cells

Many systems in biology and beyond employ collaborative, collective communication strategies for improved efficiency and adaptive benefit. One such paradigm of particular interest is the community estimation of a dynamic signal, when, for example, an epithelial tissue of cells must decide whether to react to a given dynamic external concentration of stress signaling molecules. At the level of dynamic cellular communication, however, it remains unknown what effect, if any, arises from communication beyond the mean field level. What are the limits and benefits to communication across a network of neighbor interactions? What is the role of Poissonian vs. super Poissonian dynamics in such a setting? How does the particular topology of connections impact the collective estimation and that of the individual participating cells? In this letter we construct a robust and general framework of signal estimation over continuous time Markov chains in order to address and answer these questions. Our results show that in the case of Possonian estimators, the communication solely enhances convergence speed of the Mean Squared Error (MSE) of the estimators to their steady-state values while leaving these values unchanged. However, in the super-Poissonian regime, MSE of estimators significantly decreases by increasing the number of neighbors. Surprisingly, in this case, the clustering coefficient of an estimator does not enhance its MSE while reducing total MSE of the population.

systems biology↗

bioRxiv2019

Phase separation provides a mechanism to reduce noise in cells

A central problem in cellular control is how cells cope with the inherent noise in gene expression. Although transcriptional and posttranscriptional feedback mechanisms can suppress noise, they are often slow, and cannot explain how cells buffer acute fluctuations. Here, by using a physical model that links fluctuations in protein concentration to the theory of phase separation, we show that liquid droplets can act as fast and effective buffers for gene expression noise. We confirm our theory experimentally using an engineered phase separating protein that forms liquid-like compartments in mammalian cells. These data suggest a novel role of phase separation in biological information processing.

biophysics↗