Biology subjects

Schneider, J.

Publications and source records attributed to Schneider, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Human cerebral assembloids as a model to study the interaction of glioblastoma with resident glial cells

Glioblastoma (GB) is a highly invasive brain cancer characterized by extensive peritumoral glial reactivity. Although GB infiltration and recurrence remain major therapeutic challenges, the contribution of GB-induced gliosis to tumor progression is poorly understood. To investigate glia-GB interactions, we developed human iPSC-derived cerebral forebrain assembloids containing innate microglia and macroglia and transplanted them with GB cells. The model recapitulates key tumor features observed in patients, including distinct tumor regions, reactive gliosis, and altered tissue stiffness. Single-cell RNA sequencing revealed an unexpected enrichment of extracellular vesicles (EVs) in peritumoral reactive glia, which we validated in patient samples. EV inhibition impaired formation of the peritumoral niche, whereas EVs from GB-containing assembloids induced glial reactivity in GB-free assembloids. Furthermore, the modularity of our system enables incorporation of additional niche components, such as monocytes, allowing investigation of the monocyte-glia-tumor axis and providing a powerful platform to dissect mechanisms regulating the GB microenvironment.

neuroscience↗

bioRxiv2026

Provisional extracellular matrix signaling network regulates tumor lymphoneogenesis and response to immunotherapy

Tertiary lymphoid structures (TLS) predict response to checkpoint inhibition, and conventional dendritic cells (cDC) are required to build and maintain them. What renders a niche permissive for their assembly is unknown: chemokines recruit the cellular constituents but do not specify how they organize. Here we show that the organizing signal is a matrix fragment. Proteolysis of the proteoglycan versican (VCAN) releases the matrikine versikine, constitutively in germinal center light zones and inducibly in tumor stroma. Versikine activates CD11b+ cDC and expands cDC1 to assemble TLS-archetypal triads, apposed DC: CD4+ T: CD8+ T units. Versikine-conditioned DC engage progenitor-exhausted CD8+ T cells (Tpex) and Th1-polarized follicular helper CD4+ T cells. Excess unproteolyzed VCAN inverts this toward DC-Treg crosstalk and Tpex loss. Versikine supplied as mRNA or recombinant protein sensitizes refractory tumors to PD-L1 blockade. VCAN proteolysis prospectively predicted outcomes after PD-1 blockade in metastatic colorectal cancer. Matrikines organize chemokine-recruited cells into functional immune niches.

immunology↗

bioRxiv2026

Semaphorin 3G (SEMA3G) is a highly selective marker of cerebral amyloid angiopathy

Biomarkers of cerebral amyloid angiopathy (CAA) are critically needed. We recently identified semaphorin 3G (SEMA3G) as a novel protein selectively enriched in CAA. Here, we aimed to determine if SEMA3G was a selective marker of CAA in a large cohort of human brain tissue spanning multiple neurodegenerative diseases and three brain regions, and to determine if SEMA3G directly interacts with amyloid beta (A{beta}). Multiplexed immunofluorescence showed that SEMA3G significantly accumulated only in CAA+ blood vessels in the brain in all cases. We also showed that SEMA3G preferentially associated with A{beta}40, A{beta}pS8 and A{beta}pE3, but not A{beta}42. Thioflavin T assays and transmission electron microscopy showed that SEMA3G directly interacted with A{beta} and slowed A{beta} aggregation in vitro, and that this effect was more pronounced for A{beta}40 than A{beta}42. Together our results demonstrate that SEMA3G is a highly specific marker of CAA in the brain.

neuroscience↗

bioRxiv2026

Layered helical order reveals assembly states in podosome actin networks

How stochastic molecular events are converted into ordered cellular machines that perform mechanical work remains a central question in biology. Cryo-electron tomography enables visualization of macromolecular assemblies inside cells at molecular resolution, but static tomograms are generally interpreted as structural snapshots, with limited access to assembly state and temporal progression. Here, we show that cellular tomograms retain interpretable information about the assembly of a force-generating actin network. Using human macrophage podosomes as a physiologically relevant system, we combine spatial mapping of actin filaments (F-actin) and Arp2/3-mediated branch junctions, orientation analysis of deep-learning-based filament segmentations and Markov-chain modeling to infer actin-network assembly in situ. We identify favored membrane-directed actin polymerization and Arp2/3-mediated branching, establishing a local growth axis for podosome network organization. At the network scale, podosomes display layered helical order: filament-orientation classes recur at intervals of approximately 33 nm along the membrane-normal axis, forming a three-class cycle that returns to an approximately equivalent non-polar orientation. Markov modeling identifies preferred mother-to-daughter filament-orientation transitions and yields a stationary composition of branch-orientation states that closely matches that observed in structurally more advanced network regions. Together, these results link local actin nucleation, network-scale architecture and structural assembly state in a native cellular machine. Our study advances cryo-electron tomography from structural description toward temporal inference and 4D in situ structural biology.

cell biology↗

bioRxiv2026

pyfraglib: An integrated cfDNA fragmentomics platform

SummaryCell-free DNA (cfDNA) fragmentomics is the analysis of a diverse set of cfDNA fragment features, e.g. fragment length profiles, windowed protection scores, and end motifs. As such it requires software tooling for fragment extraction, statistical feature modeling, and cohort-level comparative analysis. In silico simulations can facilitate the development and validation of new methods by generating testing datasets with known ground truth. Existing tools address individual aspects of this workflow but none provide all necessary capabilities within a single package. ResultsWe present pyfraglib, a platform integrating fragment extraction from short- and long-read sequencing, statistical feature modeling (Gaussian mixture and NMF decomposition of fragment length profiles, end motif diversity, windowed protection scores), cohort-level differential testing of said features, and a simulation module. The library is exposed through a command-line interface, a Python API, and a Nextflow pipeline. We demonstrate pyfraglib in two ways. First, on two simulated 20-sample cohorts we show that pyfraglibs per-sample and cohort-level analyses recover the differences introduced by construction. Second, we apply pyfraglib to 88 cfDNA samples from a central nervous system lymphoma (CNSL) study and construct a fragmentomics score combining an NMF signature with end motif and WPS summaries via a classifier trained on cerebrospinal fluid and healthy donor plasma samples. As a proof of concept and applied to 66 baseline patient plasma samples, the score identifies a high-risk subgroup with worse failure-free survival (log-rank p=0.0247). Conclusionspyfraglib integrates sample- and cohort-level fragmentomics analyses as well as in silico simulation within a consistently engineered Python framework. pyfraglib source code and documentation are available at https://github.com/schwarzlab-ccb/pyfraglib.

bioinformatics↗

bioRxiv2026

Improved 3D Radial Phyllotaxis Trajectories for Uniform Density Distribution of Readout Directions and Sequential Binning

PurposeTo develop 3D radial spiral phyllotaxis trajectories that provide a uniform density distribution of readout directions and support retrospective sequential binning, thereby reducing ringing artifacts and improving image quality. MethodsUPhy trajectory redefines the polar angle to achieve uniform density distribution of readout directions. FlexiPhy further decouples the azimuthal and polar ordering of interleaves through a randomized permutation, improving robustness to sequential binning. The proposed trajectories were evaluated in vivo on 10 healthy volunteers using two gradient-echo sequences on a 3T MRI scanner. Sequential temporal reconstructions were compared with reference reconstructions using structural similarity and relative L2 error metrics. ResultsUPhy presents analytically demonstrated uniform density distribution of readout directions. Quantitative analysis shows significantly higher SSIM values and lower relative L2 errors for FlexiPhy compared with both the original phyllotaxis and UPhy trajectories after Bonferroni correction (pcorrected < 0.05). ConclusionFlexiPhy enables more reliable sequential binning reconstructions by reducing trajectory-induced ringing artifacts and temporal inconsistencies. Moreover, its randomized construction is not tied to a specific binning strategy, making it broadly compatible with retrospective binning approaches used in dynamic and motion-resolved MRI.

bioinformatics↗

bioRxiv2026

Determinants of Blood Group Antigen Expression and Prediction of Phenotypes by Machine Learning

Key PointsO_LIStructural and evolutionary features distinguish null and antigenic blood group variants across multiple systems. C_LIO_LIMachine learning can predict variant effects, enabling improved interpretation of novel mutations in transfusion medicine. C_LI Blood group antigens, defined by epitopes on the erythrocyte surface, are central to transfusion safety and maternal-fetal compatibility. While the genetic basis of many clinically relevant blood group antigens is well established, which structural and biophysical parameters determine whether a single-nucleotide variant gives rise to an antigenic phenotype remains unclear. Here, we integrate structural, biophysical, and evolutionary analyses to systematically evaluate features associated with single amino acid substitutions across 24 human protein-based blood group systems. We analyse 319 variants with curated phenotypic annotations alongside 481 control variants, identifying key determinants of null and antigenic phenotypes. Null variants are characterized by high evolutionary conservation, burial within the protein core, loss of hydrophobicity, increased polarity, and a propensity for arginine substitutions. Antigenic variants are also enriched in arginine; however, in contrast to null variants, they tend to occur at less conserved, more solvent-accessible, and structurally flexible sites. Supervised machine learning models trained on structural and biophysical descriptors were applied to distinguish (i) null and (ii) antigenic variants from controls, achieving balanced accuracies of 0.82 and 0.63, respectively. Feature importance analysis identified predicted pathogenicity, solvent accessibility, and evolutionary conservation as the most predictive determinants of null variants, whereas hydrophobicity, conservation, and flexibility dominated antigen prediction. This work establishes a framework linking molecular variation to blood group phenotypes and provides a foundation for predicting the impact of novel missense mutations in transfusion medicine and beyond.

bioinformatics↗

bioRxiv2026

Kaposi Sarcoma herpesvirus reactivation and replication are dispensable for cell-lineage specific tumorigenesis in whole genome transgenic mice

Herpesvirus reactivation and replication depend on an ordered cascade of gene expression. The viral immediate-early replication and transcription activator protein (Rta) is necessary and sufficient to initiate this process. For Kaposi sarcoma herpesvirus (KSHV), Rta-interacting and Rta-regulated proteins are thought to contribute to cellular transformation. Using a novel, whole-genome transgenic mouse model, we show that KSHV tumorigenesis is independent of Rta in vivo. Rta-deleted, KSHV bacmid transgenic (tgKSHV{Delta}Rta) mice developed latency-associated nuclear antigen (LANA)-positive vascular sarcomas with the same endothelial cell-lineage composition and transcriptional profile as human Kaposi sarcoma (KS). The viral miRNAs were expressed in the tumors, as were all canonical latency and the K1 and K15 oncogenes. Importantly, this system is the first to model both KS and lymphoma, reflecting the development of both malignancies observed in KSHV-infected individuals. These results separate virus replication from KS tumorigenesis, which can proceed independently so long as the virus genome is maintained in a susceptible cell. SignificanceKaposi sarcoma (KS) is the most common cancer in people living with HIV worldwide. Like all herpesviruses, KS-associated herpesvirus (KSHV) has a latent and lytic phase. Hitherto, viral lytic genes are thought to play a role in KS. The KSHV replication and transcription activator (Rta) is both necessary and sufficient for reactivation and lytic viral replication, but Rta was not required for vascular tumor development in a whole virus genome mouse model. This new tgKSHV{Delta}RTA mouse model separates virus replication from viral tumorigenesis and defines a minimal set of viral oncogenes. This model enables mechanistic studies in vivo, and treatment modalities to be evaluated within a complete immune and stromal microenvironment.

Cancer Biology↗

bioRxiv2026

DLDN-Bench: A Benchmark Framework for Deep Learning de Novo Peptide Sequencing in Proteomics

De novo peptide sequencing is an essential approach for analyzing mass spectrometry data because it enables the identification of novel peptides without relying on protein sequence databases. Recent advances in deep learning have substantially improved the performance of de novo sequencing methods, but the rapid emergence of new models has led to heterogeneous evaluation practices and limited comparability. To address this, we introduce DLDN-Bench, a benchmark framework including a set of benchmark datasets derived from human muscle biopsy mass spectrometry data retrieved from PRIDE and annotated through consensus across multiple widely used database search engines. Using these datasets, we systematically benchmark recent deep learning-based de novo sequencing tools alongside traditional approaches. Performance is assessed using established metrics, including precision and coverage relative to a pseudo-ground truth defined by cross-engine agreement. To demonstrate the utility of DLDN-Bench, we benchmark four recent deep learning models and make all results publicly available. This benchmark framework provides a standardized basis for comparing state-of-the-art methods and offers an extensible resource for evaluating future tools in de novo peptide sequencing. Code availabilityhttps://github.com/ddz-icb/DLDN-Bench Data availabilityhttps://doi.org/10.5281/zenodo.19627459

bioinformatics↗

bioRxiv2026

The insect- and plant-associated lifestyles of Pseudomonas protegens CHA0 are preserved following serial passage through insect larvae

The plant-beneficial bacterium Pseudomonas protegens CHA0 (CHA0) is widely studied for the biological control of soil-borne plant diseases. Beyond its root-colonising capabilities, CHA0 can also infect and kill insect larvae and thus exhibits a multi-host lifestyle shared with other plant- and insect-colonising bacteria. To better understand the robustness of this multi-host lifestyle, we subjected CHA0 to ten consecutive passages through larvae of the pest insect Plutella xylostella via repeated cycles of insect colonisation and killing forcing it into an insect-only lifestyle. Overall, serial passaging did not result in consistent changes in insect killing speed, larval or root colonisation, plant protection efficiency, microbial antagonism or in vitro growth. This suggests that its multi-host lifestyle was conserved following serial passage. Nonetheless, a few independently passaged lines showed an increase in larval killing speed, which in one case might be linked to choline uptake. To disentangle changes specific to the insect host from those arising due to the experimental system itself, we conducted parallel serial passages through the same system while omitting the insect host. In some of these lines, exposure to the background of the system led to changes in microbial antagonism and in in vitro growth, which likely are associated with mutations in regions encoding for regulatory systems. Our findings indicate that P. protegens CHA0 remains phenotypically stable in complex environments such as an insect host, suggesting that the multi-host lifestyle might also be conserved when applied in the field and supporting CHA0s potential for reliable biocontrol performance against both plant diseases and insect pests. Author summaryControlling insect pests with living organisms, known as biological control, offers an environmentally friendly alternative to chemical pesticides. The plant-beneficial bacterium Pseudomonas protegens CHA0 is a promising biocontrol candidate that not only colonizes plant roots but also infects and kills certain insect larvae. This ability to colonize different hosts appears to be a conserved trait also observed in other bacteria. To better understand the robustness of this multi-host lifestyle, we repeatedly exposed CHA0 to larvae of the insect pest Plutella xylostella and assessed the resulting physiological and genetic changes. Surprisingly, after ten cycles, CHA0 largely retained its insect-killing and plant-protective traits. Although a few populations showed minor changes, including slightly faster insect killing and traits associated with aspects of the experimental system, these changes were limited in scope. Overall, our findings suggest that P. protegens CHA0 does not change rapidly in complex environments such as an insect host, supporting its potential for reliable biocontrol performance in the field.

microbiology↗

bioRxiv2026

Medulloblastoma-Associated KBTBD4 Mutations Disrupt PP2A-A Orphan Quality Control

Medulloblastoma, the most common malignant pediatric brain tumor, arises from developmental aberrations of cerebellar precursor cells. The CUL3-RING ubiquitin ligase adaptor KBTBD4 is recurrently mutated in medulloblastoma subgroups 3 and 4. While KBTBD4 mutations confer a gain-of-function phenotype leading to aberrant degradation of transcriptional repressors, endogenous targets of this E3 ligase remain unknown. Here, we identify the PP2A-A scaffolding subunit of the PP2A phosphatase as a CRL3KBTBD4 substrate. Using a combination of proteomics, cell biology, biochemical reconstitution, and cryo-EM structural analyses, we show that CRL3KBTBD4 mediates orphan quality control by targeting free PP2A-A for degradation to safeguard phosphatase activity. Loss of KBTBD4 or its mutation in medulloblastoma cause PP2A-A accumulation, hence affecting phospho-dependent signaling pathways in cancer development. Disease mutations in KBTBD4 thus elicit a dual phenotype: gain-of-function degradation of transcriptional repressors combined with loss of PP2A quality control, which dysregulates multiple signaling events implicated in cancer, including telomere length regulation.

cell biology↗

bioRxiv2026

A dynamic displacement mechanism drives protein import into mitochondria

Most mitochondrial proteins are produced in the cytosol and imported through the translocase of the outer mitochondrial membrane (TOM) to reach their final destination. Although this protein entry gate has been structurally characterized, it remains unclear how precursor proteins are handed off from the cytosolic receptor domains to the translocation pore. Here we show that the cytosolic domain of Tom22--traditionally viewed as the central TOM receptor--acts not as a structured scaffold but as a largely disordered, flexible segment that plays an active role in precursor transfer. Atomic-level structural techniques and in vivo experiments identified a conserved short linear motif that forms a transient !-helical element within this disordered domain. By binding to the canonical precursor protein binding sites of the receptors Tom20 and Tom70, this critical -helical segment acts as a precursor protein displacement element (PPDE). This competitive interaction facilitates the release of preproteins directly above the import pore, and thereby drives translocation across the outer mitochondrial membrane. These findings reveal that flexibility, rather than rigid structure, underlies the central transfer step of mitochondrial outermembrane protein translocation. Our results point to a versatile mechanism for ligand displacement in chaperone, receptor, and transport systems that must balance selective binding with efficient release.

cell biology↗

bioRxiv2025

Exploiting TGF-β-mediated Stromal Programming in Homologous Recombination-Deficient Pancreatic Cancer

The tumor microenvironment (TME) actively contributes to pancreatic ductal adenocarcinoma (PDAC) pathogenesis through dynamic bidirectional tumor-stroma interactions. Here, we demonstrate that homologous recombination-defective (HRD) tumor epithelium reprograms the TME in a genotype-specific manner to enhance cancer aggressiveness. Using genetically engineered mouse models, pancreatic stellate cell (PSC) and cancer-associated fibroblast (CAF) co-culture systems, single-nucleus multiomics, and human PDAC models, we show that tumoral loss of ATM serine/threonine kinase drives CAFs toward SMA+ myofibroblastic differentiation, independently of P53 status. These myCAFs, in turn, promote cancer aggressiveness and chemoresistance. Mechanistically, ATM deficiency increases reactive oxygen species and contractility signaling, enhancing TGF-{beta}1 secretion. Pharmacological TGF-{beta} inhibition reverses myCAF differentiation, sensitizes tumors to chemotherapy, and impairs tumor progression in both murine and human ATM-null models. Our findings reveal that ATM-deficient tumors shape a cancer-promoting niche via TGF-{beta} signaling and identify dual targeting of intrinsic and extrinsic vulnerabilities as a promising precision oncology strategy. SIGNIFICANCEHRD pancreatic cancers reprogram the tumor microenvironment in a genotype-specific manner through TGF-{beta}-driven myCAF-enrichment. Targeting this stromal axis alongside platinum-based chemotherapy improves therapeutic efficacy in ATM-deficient models. These findings highlight the need to integrate epithelial genotype and stromal context for truly personalized treatment strategies in PDAC.

cancer biology↗

bioRxiv2025

Modeling cellular influence delineates functionally relevant cellular neighborhoods in primary and metastatic pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, with liver metastases significantly worsening outcomes. However, distinct features of the tumor microenvironment (TME) between primary and metastatic sites remain poorly defined. Cellular neighborhoods within the TME are recognized as functional units that influence tumor behavior. Conventional spatial methods, which assign equal weights to all cells in a region, fail to capture the nuances of cellular interactions. To address this, we developed Functional Cellular Neighborhood (FunCN) quantification, which integrates both the proportion and proximity of surrounding cells. Applying FunCN to PDAC imaging mass cytometry data, we identified neutrophil-enriched interactions in liver metastases compared to primary tumors, correlating with elevated VISTA expression by tumor cells. Additionally, FunCN clusters around CD8+ T cells in pancreas and liver were associated with higher TIGIT and LAG3, respectively. These findings demonstrate the importance of spatial immune landscapes in PDAC and identify potential therapeutic opportunities.

systems biology↗

bioRxiv2023

Discovery of a functionally selective serotonin 5-HT1A receptor agonist for the treatment of pain

The G protein-coupled serotonin receptor 5-HT1AR mediates antinociception and may serve as a valuable target for the treatment of pain. Starting from a chemical library, ST171, a bitopic chemotype activating 5-HT1AR was evolved. In vitro pharmacological investigations of ST171 revealed potent and selective Gi activation (EC50 = 0.3 nM), with marginal Gs and {beta}-arrestin recruitment. Preclinical studies in mice showed that ST171 was effective in acute and chronic (inflammatory and neuropathic) pain models, without causing sedation. Comparison of cryo-EM structures of a 5-HT1AR-Gi complex bound to the functionally biased agonist ST171, with a structure bound to the functionally balanced agonist befiradol, showed that both ligands bind to the same orthosteric site, but address different exo-sites. The individual poses are associated with ligand-specific helical dispositions and rearrangements of microdomains. Complementation of these studies with molecular dynamics simulations allowed us to derive structural features associated with ST171s functional selectivity, a phenomenon that may be crucial to the discovery of more effective and safe GPCR drugs.

pharmacology and toxicology↗

bioRxiv2023

Open access-enabled evaluation of epigenetic age acceleration in colorectal cancer and development of a classifier with diagnostic potential.

Aberrant DNA methylation (DNAm) is known to be associated with the aetiology of cancer, including colorectal cancer (CRC). In the past, the availability of open access data has been the main driver of innovative method development and research training. However, this is increasingly being eroded by the move to controlled access, particularly of medical data, including cancer DNAm data. To rejuvenate this valuable tradition, we leveraged DNAm data from 1,845 samples (535 CRC tumours, 522 normal colon tissues adjacent to tumours, 72 colorectal adenomas, and 716 normal colon tissues from healthy individuals) from 14 open access studies deposited in NCBI GEO and ArrayExpress. We calculated each samples epigenetic age (EA) using eleven epigenetic clock models and derived the corresponding epigenetic age acceleration (EAA). For EA, we observed that most first- and second-generation epigenetic clocks reflect the chronological age in normal tissues adjacent to tumours and healthy individuals (e.g. Horvath (r = 0.77 and 0.79), Zhang EN (r = 0.70 and 0.73)) unlike the epigenetic mitotic clocks (EpiTOC, HypoClock, MiAge) (r < 0.3). For EAA, we used PhenoAge, Wu, and the above mitotic clocks and found them to have distinct distributions in different tissue types, particularly between normal colon tissues adjacent to tumours and cancerous tumours, as well as between normal colon tissues adjacent to tumours and normal colon tissue from healthy individuals. Finally, we harnessed these associations to develop a classifier using elastic net regression (with lasso and ridge regularisations) that predicts CRC diagnosis based on a patients sex and EAAs calculated from histologically normal controls (i.e. normal colon tissues adjacent to tumours and normal colon tissue from healthy individuals). The classifier demonstrated good diagnostic potential with ROC-AUC=0.886, which suggests that an EAA-based classifier trained on relevant data could become a tool to support diagnostic/prognostic decisions in CRC for clinical professionals. Our study also reemphasises the importance of open access clinical data for method development and training of young scientists. Obtaining the required approvals for controlled access data would not have been possible in the timeframe of this study.

genomics↗

bioRxiv2023

Serial Lift-Out - Sampling the Molecular Anatomy of Whole Organisms

Cryo-focused ion beam milling of frozen-hydrated cells and subsequent cryo-electron tomography (cryo-ET) has enabled the structural elucidation of macromolecular complexes directly inside cells. Application of the technique to multicellular organisms and tissues, however, is still limited by sample preparation. While high-pressure freezing enables the vitrification of thicker samples, it prolongs subsequent preparation due to increased thinning times and the need for extraction procedures. Additionally, thinning removes large portions of the specimen, restricting the imageable volume to the thickness of the final lamella, typically < 300 nm. Here, we introduce Serial Lift-Out, an enhanced lift-out technique that increases throughput and obtainable contextual information by preparing multiple sections from single transfers. We apply Serial Lift-Out to C. elegans L1 larvae yielding a cryo-ET dataset sampling the worms anterior-posterior axis and resolve its ribosome structure to 7 [A], illustrating how Serial Lift-Out enables the study of multicellular molecular anatomy.

biophysics↗

bioRxiv2023

Crosslinking by ZapD drives the assembly of short, discontinuous FtsZ filaments into ring-like structures in solution

Bacterial cell division relies on the Z ring, a cytoskeletal structure that acts as a scaffold for the assembly of the divisome. To date, the detailed mechanisms underlying the assembly and stabilization of the Z ring remain elusive. This study highlights the role of the FtsZ-associated protein (Zap) ZapD in the assembly and stabilization of Z-ring-like structures via filament crosslinking. Using cryo-electron tomography and biochemical analysis, we show that, at equimolar concentrations of ZapD and FtsZ, ZapD induces the formation of toroidal structures composed of short, curved FtsZ filaments that are crosslinked vertically, but also laterally and diagonally. At higher concentrations of ZapD, regularly spaced ZapD dimers crosslink FtsZ filaments from above, resulting in the formation of straight bundles. Despite the simplicity of this reconstituted system, these findings provide valuable insights into the structural organization and stabilization of the Z ring by Zap proteins in bacterial cells, revealing the key role of optimal crosslinking density and geometry in enabling filament curvature and ring formation.

biochemistry↗