Biology subjects

Dunkel, J.

Publications and source records attributed to Dunkel, J..

7 recordsLinked to original sources

bioRxiv2025

Embodied behavioural complexity in a ciliated microorganism

Most animals coordinate behaviour using neural computations. Yet, single-celled organisms also exhibit stimulus-responsive, even cognitive, actions. To understand how a single cell can coordinate and drive complex behaviours without any neural encoding, we study an algal protist - a motile cell with four extremely long cilia. The organism displays a surprisingly rich locomotor repertoire, emerging from the intricate dynamics of the cilia, which form a tight bundle when swimming. We leverage high-speed quantitative live imaging to extract the spectrum of possible ciliary beating patterns, and derive a dispersion relation coupling the temporal frequency and spatial wavelength of cilia oscillations. We further reconstruct the attractor manifold embedded in the behavioural space, showing that despite the range and complexity of ciliary beating modes, the underlying behavioural manifold is intrinsically low-dimensional with elaborate topological structure. Dynamic and excitable transitions in motility behaviour are encoded as trajectories in this space.

biophysics↗

bioRxiv2024

HHV-6B, HHV-7, and B19V Are Frequently Found DNA Viruses in the Human Thymus but Show No Definitive Link with Myasthenia Gravis

Myasthenia gravis (MG) is an autoimmune disorder characterised by autoantibodies that target components of the neuromuscular junction, primarily the acetylcholine receptor (AChR), resulting in muscle weakness. The thymus plays a significant role in MG pathogenesis, particularly in patients under the age of 50, who display pathological alterations and possess elements conducive to autoimmune reactions. Although viral infections are suspected drivers of thymic pathogenesis, the exact aetiology of MG remains elusive. This study investigates the potential link between MG and DNA viruses within the thymus. Using targeted next-generation sequencing and quantitative PCR, we analysed the presence of human parvovirus B19 (B19V) and nine human herpesviruses (HSV-1, HSV-2, VZV, EBV, CMV, HHV-6A, HHV-6B, HHV-7, and HHV-8) in fresh tissue samples from 19 non-thymomatous MG patients, 16 thymomas (3 with and 14 without MG), 41 normal thymus tissues, and 20 tonsils from healthy individuals. HHV-6B was the most common virus, found in over 50% of all tissue groups. B19V DNA was detected in 40% of adult control thymic tissue, 72% of MG thymus, 7.7% of non-MG thymoma, and 50% of tonsil samples. HHV-7 was present in 15-30% of thymus tissues and 95% of tonsils, while EBV was detected in less than 25% of all thymus samples but 85% of tonsils. In B19V seropositive individuals, B19V DNA was detected in 100% of thymic tissue from both MG patients and healthy individuals, except in thymomatous tissues, where it was found in only one of thirteen seropositive individuals. Immunohistochemistry for B19V protein expression did not show evident B19V VP1/VP2 protein expression, indicating dormant viral persistence. Laser capture microdissection (LCM) and RNAscope in situ hybridisation pinpointed B19V DNA localisation to the thymus medulla. This study is the first to demonstrate the persistence of various DNA viruses in the human thymus. However, neither B19V nor the nine human herpesviruses showed specific enrichment in MG thymic tissue compared to controls, suggesting that these viral infections are unlikely to be sole environmental triggers for MG.

immunology↗

bioRxiv2021

Multispecies phase diagram reveals biophysical principles of bacterial biofilm architectures

Bacterial biofilms are among the most abundant multicellular structures on Earth and play essential roles in a wide range of ecological, medical, and industrial processes. However, general principles that govern the emergence of biofilm architecture across different species remain unknown. Here, we combine experiments, simulations and statistical analysis to identify shared biophysical mechanisms that determine biofilm architecture development at the single-cell level, for the species Vibrio cholerae, Escherichia coli, Salmonella enterica, and Pseudomonas aeruginosa. Our data-driven analysis reveals that despite the many molecular differences between these species, the biofilm architecture differences can be described by only two control parameters: cellular aspect ratio and cell density. Further experiments using single-species mutants for which the cell aspect ratio and the cell density are systematically varied, and mechanistic simulations, show that tuning these two control parameters reproduces biofilm architectures of different species. Altogether, our results show that early-stage biofilm architecture is determined by mechanical cell-cell interactions which are conserved across different species and, therefore, provide a unifying understanding of biofilm architecture development.

microbiology↗

bioRxiv2020

Dynamics of altruistic fluid transport in egg development

From insects to mice, oocytes develop within cysts alongside nurse-like sister germ cells. Prior to fertilization, the nurse cells cytoplasmic contents are transported into the oocyte, which grows as its sister cells regress and die. Although critical for fertility, the biological and physical mechanisms underlying this transport process are poorly understood. Here, we combined live imaging of germline cysts, genetic perturbations, and mathematical modeling to investigate the dynamics and mechanisms that enable directional and complete cytoplasmic transport in Drosophila melanogaster egg chambers. We discovered that during nurse cell (NC) dumping, most cytoplasm is transported into the oocyte independently of changes in myosin-II contractility, with dynamics instead explained by an effective Young-Laplaces law, suggesting hydraulic transport induced by baseline cell surface tension. A minimal flow network model inspired by the famous two-balloon experiment and genetic analysis of a myosin mutant correctly predicts the directionality of transport time scale, as well as its intercellular pattern. Long thought to trigger transport through squeezing, changes in actomyosin contractility are required only once cell volume is reduced by [~]75%, in the form of surface contractile waves that drive NC dumping to completion. Our work thus demonstrates how biological and physical mechanisms cooperate to enable a critical developmental process that, until now, was thought to be a mainly biochemically regulated phenomenon.

developmental biology↗

bioRxiv2019

Flow-induced symmetry breaking in growing bacterial biofilms

Bacterial biofilms represent a major form of microbial life on Earth and serve as a model active nematic system, in which activity results from growth of the rod-shaped bacterial cells. In their natural environments, ranging from human organs to industrial pipelines, biofilms have evolved to grow robustly under significant fluid shear. Despite intense practical and theoretical interest, it is unclear how strong fluid flow alters the local and global architectures of biofilms. Here, we combine highly time-resolved single-cell live imaging with 3D multi-scale modeling to investigate the mechanisms by which flow affects the dynamics of all individual cells in growing biofilms. Our experiments and cell-based simulations reveal three quantitatively different growth phases in strong external flow, and the transitions between them. In the initial stages of biofilm development, flow induces a downstream gradient in cell orientation, causing asymmetrical droplet-like biofilm shapes. In the later developmental stages, when the majority of cells are sheltered from the flow by the surrounding extracellular matrix, buckling-induced cell verticalization in the biofilm core restores radially symmetric biofilm growth, in agreement with predictions of a 3D continuum model.

biophysics↗

bioRxiv2019

Structural redundancy in supracellular actomyosin networks enables robust tissue folding

Tissue morphogenesis is strikingly reproducible. Yet, how tissues are robustly sculpted, even under challenging conditions, is unknown. Here, we combined network analysis, experimental perturbations, and computational modeling to determine how network connectivity between hundreds of contractile cells on the ventral side of the Drosophila embryo ensures robust tissue folding. We identified two network properties that mechanically promote robustness. First, redundant supracellular cytoskeletal network paths ensure global connectivity, even with network degradation. By forming many more connections than are required, morphogenesis is not disrupted by local network damage, analogous to the way redundancy guarantees the large-scale function of vasculature and transportation networks. Second, directional stiffening of edges oriented orthogonal to the folding axis promotes furrow formation at lower contractility levels. Structural redundancy and directional network stiffening ensure robust tissue folding with proper orientation.

developmental biology↗

bioRxiv2018

Learning dynamical information from static protein and sequencing data

Many complex processes, from protein folding and virus evolution to brain activity and neuronal network dynamics, can be described as stochastic exploration of a high-dimensional energy landscape. While efficient algorithms for cluster detection and data completion in high-dimensional spaces have been developed and applied over the last two decades, considerably less is known about the reliable inference of state transition dynamics in such settings. Here, we introduce a flexible and robust numerical framework to infer Markovian transition networks directly from time-independent data sampled from stationary equilibrium distributions. Our approach combines Gaussian mixture approximations and self-consistent dimensionality reduction with minimal-energy path estimation and multi-dimensional transition-state theory. We demonstrate the practical potential of the inference scheme by reconstructing the network dynamics for several protein folding transitions, gene regulatory network motifs and HIV evolution pathways. The predicted network topologies and relative transition time scales agree well with direct estimates from time-dependent molecular dynamics data, stochastic simulations and phylogenetic trees, respectively. The underlying numerical protocol thus allows the recovery of relevant dynamical information from instantaneous ensemble measurements, effectively alleviating the need for time-dependent data in many situations. Owing to its generic structure, the framework introduced here will be applicable to high-throughput RNA and protein sequencing datasets and future cryo-electron-microscopy data, and can guide the design of new experimental approaches towards studying complex multiphase phenomena.

bioinformatics↗