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bioRxiv2026

Ablation of a maternal Cryptosporidium mRNA-binding protein results in sterile sporozoites

Infection with Cryptosporidium is a leading cause of diarrheal disease and early childhood mortality. This apicomplexan parasite undergoes asexual and sexual replication within the same host and recent studies have shown an intrinsic developmental program of obligate transition to male and female gametes and sex. While factors were identified that control male fate and development, how female gene expression is orchestrated remains largely unknown. Here we use the Cryptosporidium Single Cell Atlas to discover an RNA binding protein (F-RBP) as one of the earliest markers of female identity. Reporter parasites engineered based on this gene allowed us to calibrate transcriptional pseudotime against the real time of female development revealing a significant window of transcriptional fate ambiguity. While F-RBP is an early transcript, the protein persists throughout female development and into the zygote. Conditional ablation of the F-RBP gene showed it to be dispensable for sex determination and early female development in vitro. However, the gene is essential in vivo and its loss results in rapid cure. Cell biological experiments link this loss to the production of sterile oocysts which release sporozoites incapable of host cell invasion. F-RBP binds transcripts highly expressed in the female gamete enriched for a YBOX primary sequence motif and forms mRNA protein complexes in late females akin to processing or P bodies. We propose F-RBPs essential role to be in the regulation of long-term homeostasis of maternally inherited RNA required for sporozoite infectivity.

microbiology↗

bioRxiv2024

Biological aging of different blood cell types

A biological age (BA) indicator is intended to capture detrimental age-related changes occurring with passing time. To date, the best-known and used BA indicators include DNA-methylation-based epigenetic ages (epigenetic clocks) and telomere length. The most common biological sample material for epidemiological aging studies is composed of different cell types, whole blood. We aimed to compare differences in BAs between blood cell types and assessed BA indicators cell type-specific associations with donors calendar age. Analysis on DNA methylation-based BA indicators including telomere length, methylation level at cg16867657 (a CpG-site in ELOVL2) and the Hannum, Horvath, DNAmPhenoAge and DunedinPACE epigenetic clocks was performed in 428 biological samples from 12 blood cell types. BA values were different (p<0.05) in the majority of pairwise comparisons between the cell types. Most cell types also displayed differences as compared to whole blood (p<0.05). Some of the observed differences persisted across blood donors calendar ages from 20 to 80 years (50-years-difference in DNAmPhenoAge between naive CD4+ T cells and monocytes), while others did not (up to four-fold difference in DunedinPACE values between monocytes and B cells). All BA indicators, except DunedinPACE, had mostly a very strong correlation with donors calendar age within a cell type. Our findings demonstrate that DNA methylation-based indicators of biological age exhibit cell type-specific characteristics, underscoring the importance of accounting for cell composition in related studies. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and and provide guidance for utilizing them as indicators for success of aging interventions.

molecular biology↗

bioRxiv2023

GreenMemTraX: A User-Friendly Software for Super-Resolution Analysis of Membrane Protein Dynamics and Nanoscale Organization in Plants

Super-resolution microscopy (SRM) approaches revolutionize cell biology by providing insights into the nanoscale organization and dynamics of macromolecular assemblies and single molecules in living cells. A major hurdle limiting SRM democratization is post-acquisition data analysis which is often complex and time-consuming. Here, we present OneFlowTraX, a user-friendly and open-source software dedicated to the analysis of single-molecule localization microscopy (SMLM) approaches such as single-particle tracking photoactivated localization microscopy (sptPALM). Through an intuitive graphical user interface, OneFlowTraX provides an automated all-in-one solution for single-molecule localization, tracking, as well as mobility and clustering analyses. OneFlowTraX allows the extraction of diffusion and clustering parameters of millions of molecules in a few minutes. Finally, OneFlowTraX greatly simplifies data management following the FAIR (Findable, Accessible, Interoperable, Reusable) principles. We provide a detailed step-by-step manual and guidelines to assess the quality of single-molecule analyses. Applying different fluorophores including mEos3.2, PA-GFP, and PATagRFP, we exemplarily used OneFlowTraX to analyze the dynamics of plant plasma membrane-localized proteins including an aquaporin, the brassinosteroid receptor Brassinosteroid Insensitive 1 (BRI1) and the Receptor-Like Protein 44 (RLP44).

plant biology↗

bioRxiv2023

GENEPT: A SIMPLE BUT HARD-TO-BEAT FOUNDATION MODEL FOR GENES AND CELLS BUILT FROM CHATGPT

There has been significant recent progress in leveraging large-scale gene expression data to develop foundation models for single-cell biology. Models such as Geneformer and scGPT implicitly learn gene and cellular functions from the gene expression profiles of millions of cells, which requires extensive data curation and resource-intensive training. Here we explore a much simpler alternative by leveraging ChatGPT embeddings of genes based on literature. Our proposal, GenePT, uses NCBI text descriptions of individual genes with GPT-3.5 to generate gene embeddings. From there, GenePT generates single-cell embeddings in two ways: (i) by averaging the gene embeddings, weighted by each genes expression level; or (ii) by creating a sentence embedding for each cell, using gene names ordered by the expression level. Without the need for dataset curation and additional pretraining, GenePT is efficient and easy to use. On many downstream tasks used to evaluate recent single-cell foundation models -- e.g., classifying gene properties and cell types -- GenePT achieves comparable, and often better, performance than Geneformer and other models. GenePT demonstrates that large language model embedding of literature is a simple and effective path for biological foundation models.

bioinformatics↗

bioRxiv2020

Highly Multiplexed Single-Cell Full-Length cDNA Sequencing of human immune cells with 10X Genomics and R2C2

Single cell transcriptome analysis elucidates facets of cell biology that have been previously out of reach. However, the high-throughput analysis of thousands of single cell transcriptomes has been limited by sample preparation and sequencing technology. High-throughput single cell analysis today is facilitated by protocols like the 10X Genomics platform or Drop-Seq which generate cDNA pools in which the origin of a transcript is encoded at its 5 or 3 end. These cDNA pools are most often analyzed by short read Illumina sequencing which can identify the cellular origin of a transcript and what gene it was transcribed from. However, these methods fail to retrieve isoform information. In principle, cDNA pools prepared using these approaches can be analyzed with Pacific Biosciences and Oxford Nanopore long-read sequencers to retrieve isoform information but current implementations rely heavily on Illumina short-reads for analysis in addition to long reads. Here, we used R2C2 to sequence and demultiplex 12 million full-length cDNA molecules generated by the 10X Chromium platform from [~]3000 peripheral blood mononuclear cells (PBMCs). We used these reads to - independent from Illumina data - cluster cells into B cells, T cells, and Monocytes and generate isoform-level transcriptomes for these cell types. We also generated isoform-level transcriptomes for all single cells and used this information to identify a wide range of isoform diversity between genes. Finally, we also designed a computational workflow to extract paired adaptive immune receptors - T cell receptor and B cell receptor (TCR and BCR) - sequences unique to each T and B cell. This work represents a new, simple, and powerful approach that - using a single sequencing method - can extract an unprecedented amount of information from thousands of single cells.

genomics↗

bioRxiv2020

A Portable Impedance Microflow Cytometer for Measuring Cellular Response to Hypoxia

This paper presents the development and testing of a low-cost, portable microflow cytometer based on electrical impedance sensing, for single cell analysis under controlled oxygen microenvironment. The cytometer system is based on an AD5933 impedance analyzer chip, a microfluidic chip, and an Arduino microcontroller operated by a custom Android application. A representative case study on human red blood cells (RBCs) affected by sickle cell disease is conducted to demonstrate the capability of the cytometry system. Equivalent circuit model of a suspending biological cell is used to interpret the electrical impedance of single flowing RBCs. In normal blood, cytoplasmic resistance and membrane capacitance do not change significantly with the change in oxygen tension. In contrast, RBCs affected by sickle cell disease show that upon hypoxia treatment, the cytoplasmic resistance decrease from 11.6 M{Omega} to 23.4 M{Omega}, and membrane capacitance decrease from 1.1 pF to 0.8 pF. Strong correlations are identified between the changes in these subcellular electrical components of single cells and the cell sickling process induced by hypoxia treatment. The representative results reported in this paper suggest that single cell electrical impedance can be used as a sensitive biophysical marker for quantifying cellular response to change in oxygen concentration. The developed flow cytometry system and the methodology can also be extended to analysis of cellular response to hypoxia in other cell types. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/224006v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@147f903org.highwire.dtl.DTLVardef@2d4c35org.highwire.dtl.DTLVardef@1e63b0dorg.highwire.dtl.DTLVardef@2eeb0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2021

Thermosynechococcus switches the direction of phototaxis by a c-di-GMP dependent process with high spatial resolution

Many cyanobacteria, which use light as an energy source via photosynthesis, show directional movement towards or away from a light source. However, the molecular and cell biological mechanisms for switching the direction of movement remain unclear. Here, we visualized type IV pilus-dependent cell movement in the rod-shaped thermophilic cyanobacterium Thermosynechococcus vulcanus using optical microscopy at physiological temperature and light conditions. Positive and negative phototaxis were controlled on a short time scale of 1 min. The cells smoothly moved over solid surfaces towards green light, but the direction was switched to backward movement when we applied additional blue light illumination. The switching was mediated by three photoreceptors, SesA, SesB and SesC, which have cyanobacteriochrome photosensory domains and synthesis/degradation activity of the bacterial second messenger cyclic dimeric GMP (c-di-GMP). Our results suggest that the decision-making process for directional switching in phototaxis involves light-dependent changes in the cellular concentration of c-di-GMP. Furthermore, we reveal that rod-shaped cells can move perpendicular to the light vector, indicating that the polarity can be controlled not only by pole-to-pole regulation but also within-a-pole regulation. This study provides insights into previously undescribed rapid bacterial polarity regulation via second messenger signalling with high spatial resolution.

microbiology↗

bioRxiv2021

Scellseg: a style-aware cell instance segmentation tool with pre-training and contrastive fine-tuning

Deep learning-based cell segmentation is increasingly utilized in cell biology and molecular pathology, due to massive accumulation of diverse large-scale datasets and excellent progress in cell representation. However, the development of specialized algorithms has long been hampered by a paucity of annotated training data, whereas the performance of generalist algorithm was limited without experiment-specific calibration. Here, we present a deep learning-based tool called Scellseg consisted of novel pre-trained network architecture and contrastive fine-tuning strategy. In comparison to four commonly used algorithms, Scellseg outperformed others in average precision and Aggregated Jaccard Index on three disparate datasets. Interestingly, we found that eight images are sufficient for model tuning to achieve satisfied performance based on a shot data scale experiment. We also developed a graphical user interface integrated with functions of annotation, fine-tuning and inference, that allows biologists to easily specialize their self-adaptive segmentation model for analyzing images at the single-cell level.

bioinformatics↗

bioRxiv2023

Tunable photoinitiated hydrogel microspheres for direct quantification of cell-generated forces in complex three-dimensional environments

We present a high-throughput method using standard laboratory equipment and microfluidics to produce cellular force microscopy probes with controlled size and elastic modulus. Mechanical forces play crucial roles in cell biology but quantifying these forces in physiologically relevant systems remains challenging due to the complexity of the native cell environment. Polymerized hydrogel microspheres offer great promise for interrogating the mechanics of processes inaccessible to classic force microscopy methods. However, despite significant recent advances, their small size and large surface-to-volume ratio impede the high-yield production of probes with tunable, monodisperse distributions of size and mechanical properties. To overcome these limitations, we use a flow-focusing microfluidic device to generate large quantities of droplets with highly reproducible, adjustable radii. These droplets contain acrylamide gel precursor and the photoinitiator Lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) as a source of free radicals. LAP provides fine control over microsphere polymerization due to its high molar absorptivity at UV wavelengths and moderate water solubility. The polymerized microspheres can be functionalized with different conjugated extracellular matrix proteins and embedded with fluorescent nanobeads to promote cell attachment and track microsphere deformation. As proof of concept, we measure the mechanical forces generated by a monolayer of vascular endothelial cells engulfing functionalized microspheres. Individual nanobead motions are tracked in 3D and analyzed to determine the 3D traction forces within seconds and without the need for solving an ill-posed inverse problem. These results reveal that the cell monolayer collectively exerts strong radial compression and subtle lateral distortions on the encapsulated probe.

biophysics↗

bioRxiv2024

Spatial control of sensory adaptation modulates mechanosensing in Pseudomonas aeruginosa

Sensory signaling pathways use adaptation to dynamically respond to changes in their environment. Here, we report the mechanism of sensory adaptation in the Pil-Chp mechanosensory system, which the important human pathogen Pseudomonas aeruginosa uses to sense mechanical stimuli during surface exploration. Using biochemistry, genetics, and cell biology, we discovered that the enzymes responsible for adaptation, a methyltransferase and a methylesterase, are segregated to opposing cell poles as P. aeruginosa explore surfaces. By coordinating the localization of both enzymes, we found that the Pil-Chp response regulators influence local receptor methylation, the molecular basis of bacterial sensory adaptation. We propose a model in which adaptation during mechanosensing spatially resets local receptor methylation, and thus Pil-Chp signaling, to modulate the pathway outputs, which are involved in P. aeruginosa virulence. Despite decades of bacterial sensory adaptation studies, our work has uncovered an unrecognized mechanism that bacteria use to achieve adaptation to sensory stimuli.

microbiology↗

bioRxiv2025

Loss of Ag85A disrupts plasma membrane domains and promotes free mycolic acid accumulation in mycobacteria.

The mycomembrane of mycobacteria, composed primarily of long-chain mycolic acids, is critical for cell survival, structural integrity, and resistance to environmental stress, yet its underlying synthesis mechanisms remain incompletely understood. This study investigates the role of Ag85A, a key enzyme in mycomembrane synthesis, in regulating plasma membrane domains and cell envelope organization in Mycobacterium smegmatis. Using {Delta}Ag85A deletion mutants, we combined microscopy, biochemical assays, thin-layer chromatography, and lipid analysis to evaluate changes in membrane structure, chemical accumulation, and lipid composition. Ag85A deletion leads to altered plasma membrane domain organization, increased chemical accumulation, changes in cell envelope lipid composition. Unexpectedly, lipid analysis revealed accumulation--not depletion--of mycolic acids in the mutant, suggesting that increased permeability is not directly due to mycolic acid loss. These findings highlight a novel link between mycomembrane composition and plasma membrane domain stability. Our study not only advances understanding of mycobacterial cell envelope architecture but also identifies potential targets for enhancing drug penetration in resistant mycobacterial infections. SignificanceThe unique cell envelope of mycobacteria is central to survival, enabling it to resist immune defenses and antibiotic treatment. In this study, we reveal a novel function of Ag85A, a synthase of outmost layer of mycobacteria beyond its known role in mycolyltransferase activity: it is essential for the formation of plasma membrane domains that orchestrate cell envelope synthesis. By structuring plasma membrane domains, Ag85A contributes directly to the resilience of the cell envelope, reinforcing mycobacterial survival mechanisms under hostile conditions. Our findings provide a pivotal insight into mycobacterial cell biology, with broad implications for therapeutic development. Disrupting Ag85A-dependent membrane domain formation could weaken the protective cell envelope, offering a promising approach to enhance current treatments.

microbiology↗

bioRxiv2019

Accurate and efficient discretisations for stochastic models of cell migration and cell proliferation with crowding

Understanding how cells proliferate, migrate, and die in various environments is essential in determining how organisms develop and repair themselves. Continuum mathematical models, such as the logistic equation and the Fisher-Kolmogorov equation, can describe the global characteristics observed in commonly-used cell biology assays, such as proliferation and scratch assays. However, these continuum models do not account for single-cell-level mechanics observed in high-throughput experiments. Mathematical modelling frameworks that represent individual cells, often called agent-based models, can successfully describe key single-cell-level features of these assays, but are computationally infeasible when dealing with large populations. In this work, we propose an agent-based model with crowding effects that is computationally efficient and matches the logistic and Fisher-Kolmogorov equations in parameter regimes relevant to proliferation and scratch assays, respectively. This stochastic agent-based model allows multiple agents to be contained within compartments on an underlying lattice, thereby reducing the computational storage compared to existing agent-based models that allow one agent per site only. We propose a systematic method to determine a suitable compartment size. Implementing this compartment-based model with this compartment size provides a balance between computational storage, local resolution of agent behaviour, and agreement with classical continuum descriptions.

biophysics↗

bioRxiv2026

Move BeTween modAlities (MBTA) employs flow matching to predict single cell data modalities

Integrating diverse molecular modalities to obtain a comprehensive view of cellular identity remains a major challenge in single-cell biology. A fundamental but underappreciated obstacle is structural mismatch -- the phenomenon in which the neighborhood structure of a cell differs depending on which molecular modality is used to define it. Existing approaches typically embed modalities into a shared latent space, which actively erases the structural differences between modalities that make multimodal measurements scientifically valuable. Here we introduce Move BeTween modAlities (MBTA), the first framework explicitly designed to address structural mismatch. Rather than forcing modalities into a shared representation, MBTA maintains modality-specific latent spaces and connects them via flow matching, preserving the structural integrity of each modality while enabling accurate cross-modal translation. Across extensive benchmarks on multi-modal single-cell datasets, MBTA consistently outperformed existing methods, with the largest gains observed in datasets with pronounced structural mismatch. Applied to joint genomic and transcriptomic profiles of breast cancer patients, MBTA identified transcriptomic lineage relationships corroborated by genomic variation and outperformed state-of-the-art transcriptomics-based copy number inference methods. Extending this framework to mouse embryonic development, we reconstructed temporal trajectories jointly defined by gene expression and seven complementary epigenetic modalities. MBTA can connect any number of molecular readouts without erasing their individual character, serving as the computational foundation for assembling multi-layered portraits of cells.

bioinformatics↗

bioRxiv2026

Bidirectional disruption of Lrrk2 function drives T cell dysregulation and an exhaustion-like immune response

Background: Neurodegenerative diseases including Parkinson's disease (PD) are increasingly associated with dysfunction in both central and peripheral immune systems. Pathogenic mutations in leucine-rich repeat kinase 2 (LRRK2) represent a major cause of familial PD, while common polymorphisms are associated with inflammatory diseases. Methods: Here, using immunophenotyping flow cytometry and quantitative PCR (qPCR), we compared immune cell populations and function across both the central and peripheral immune systems in C57BL/6J wild type (WT), Lrrk2 p.G2019S knock-in (GKI) and Lrrk2 knock-out (LKO) models in basal and ex vivo immune-stimulated conditions. Results: With a focus on T cell biology, compared to their WT counterparts at baseline, GKI mice exhibit higher populations of Cd8+ and TH17 T cell subsets in the brain, whereas LKO mice exhibited unique central memory (TCM), follicular helper (TFH), and TH2 lineages. In the periphery, GKI mice demonstrated higher TH1, TH2, and TH17 subset expansions, whereas peripheral alterations in LKO are largely restricted to TH17 subsets. Within mutant genotypes, a striking discrepancy was observed between baseline gene expression and the translated proteins encoded, that reveals a fundamental loss of basal immune homeostasis. This phenomenon was further exposed following an acute (6-hour) ex vivo lipopolysaccharide (LPS) immune challenge. Following stimulation, GKI immune cells had reduced transcription, alongside stalled translation, for almost all effector molecules examined, while LKO immune cells had fewer transcriptional changes compared to wild type. Overall, both mutant lines had stalled or flatline effector molecule production after immune stimulation, suggesting a profound loss of functional responsiveness. This hypothesis was supported by a significant increase in surface protein of the inhibitory receptor Pd-1 on regulatory T cells (TREG) and TH1/TH2 Cd4+ T cell subsets in GKI mice. LKO immune landscapes trended toward similar exhaustion patterns, albeit less evident. Conclusions: These data suggest that bidirectional disruptions to normal Lrrk2 function break immune homeostasis. Immune cell function should be carefully considered when targeting LRRK2 kinase activity in patients with PD.

immunology↗

bioRxiv2026

Interaction of light-dark and dietary cues prime Drosophila ovarian stem cell properties by precisely tuning Drp1 recruitment and organization on mitochondria

The quiescent adult stem cells are activated to maintain tissue integrity. Mitochondria have emerged as critical regulators of stem/progenitor cells. Scattered literature suggests existence of a high-potency stemness state with characteristic mitochondrial structure-function properties that may prime stem cell activation. Precise tuning of mitochondrial structure by the mitochondrial fission protein, Drp1, can prime a stem cell state for neoplasticity in vitro. However, the in vivo significance and regulation of such a proposed primed stemness state remains elusive. We use quantitative genetic and cell biological approaches to demonstrate that light-dark cycling driven precise tuning of Drp1 primes the Drosophila ovarian germline stem cell (GSC) response to protein-rich dietary supplement towards stimulating egg production. This can be reversed by repressing mitochondrial fusion protein, Opa1, and is disrupted in the absence of functional Cry protein that maintains light-dark rhythm. Mechanistically, this is achieved by light or dark allowing protein-rich supplements to stimulate distinct characteristic recruitment and organization of Drp1 on mitochondria in GSC subpopulations. Screening of essential amino acids reveals the importance of interaction between Threonine supplementation, Cry, Drp1 and Opa1 in such priming of the GSCs and egg production. The priming of the ovarian follicle stem cells happens at a different tuned level of Drp1. Such Drp1-tuning driven priming of Drosophila ovarian stem cells reverses the inhibitory impact of diabetes-like condition on egg development in the presence of protein-rich supplement. Thus, our study revealing the paradigm of adult stem cell regulation by integration of light-dark and dietary cues via precise mitochondrial modulation, is significant in regenerative health and degenerative diseases.

developmental biology↗

bioRxiv2022

A quantitative and site-specific atlas of the in vivo citrullinome reveals widespread existence of citrullination

Citrullination is the conversion of peptidyl-arginine into the non-coded amino acid citrulline. Despite its importance in physiology and disease, global identification of citrullinated proteins and precise modification sites has remained challenging. Here, we employed quantitative mass spectrometry-based proteomics to generate a comprehensive atlas of citrullination sites in a physiologically relevant cell type. Collectively, we identified 14.056 citrullination sites within 4.008 proteins and quantified their regulation upon inhibition of the citrullinating enzyme PADI4. Using this rich dataset, we uncover general mechanistic and cell biological principles of citrullination function, while providing site-specific and quantitative information on thousands of PAD4 substrates within cells. Our findings include signature histone marks and numerous modifications on transcriptional regulators and chromatin-related signaling effectors. Additionally, we identify precise citrullination sites on an extensive list of known autoantigens. Collectively, we describe systems attributes of the human citrullinome and provide a resource framework for understanding citrullinaiton at the mechanistic level.

molecular biology↗

bioRxiv2019

Transitions in filament geometry drive ESCRT-III-mediated membrane remodelling and fission

ESCRT-III is an evolutionarily conserved membrane remodeling machinery that, with the Vps4 ATPase, forms filaments able to cut biological membranes from the cytosolic side. This activity of ESCRT-III is essential for the final stage of cell division in archaea and in many eukaryotes, the formation of vesicles, the creation of exosomes, the release of viruses such as HIV-1 and Ebola, and for the repair and sealing of cellular membranes. While there has been recent rapid progress in describing the biochemical and cell biology details of different ESCRT-III functions, we lack an understanding of the physical mechanism involved in ESCRT-III-mediated membrane remodelling. Here, through the development of coarse-grained molecular dynamic simulations, we present a minimal model that captures the ability of ESCRT-III to induce experimentally reported cases of ESCRT-III driven membrane sculpting, including the formation of cones and tubules, and membrane scission. This model suggests a universal physical mechanism of action, that differs from that of other cytoskeletal elements, whereby a change in the twist of membrane bound ESCRT-III filaments drives transitions between a flat spiral and a 3D helix to induce membrane deformation and scission. We expect the mechanistic principles revealed here to be useful in manipulating ESCRT-III-driven processes in cells and in guiding the engineering of synthetic membrane-sculpting systems.

biophysics↗

bioRxiv2025

Actin Counters Geometry to Guide Plant Cell Division

In multicellular organisms, cell division shapes tissue architecture, cell identity, and function. In walled organisms like plants, division plane orientation irreversibly defines tissue topology and is tightly regulated. While divisions often follow the shortest path enclosing cell volume, certain cells deviate, dividing perpendicular to the growth axis. Tissue-scale mechanical stress has been proposed to guide such orientation, but how these cues are integrated remains unclear. Here, we re-examine the role of the actin cytoskeleton in orienting cell division in Arabidopsis root epidermis. Combining cell biology, genetics, pharmacological treatments, 3D segmentation, and modelling, we show that actin is a central molecular actor required to establish cell division orientation against the geometrical rules, highlighting its role in integrating spatial information.

plant biology↗