Biology subjects

Chen, Z.

Publications and source records attributed to Chen, Z..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Quantifying sprint force-velocity elasticity: implications for individualized training decisions

This study aimed to (1) develop an elasticity framework for the sprint force-velocity (F-V) relationship and (2) examine how maximal force (F_{0}), maximal velocity (v_{0}), and sprint distance modulate the four derived elasticity metrics, and (3) explore these elasticity metrics' interrelation. After modelling the F-V relationship differential equation, four elasticity metrics were defined as force elasticity (F_{e}), the elasticity of sprint time to F_{0}; velocity elasticity (v_{e}), the elasticity of sprint time to v_{0}; the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), capturing the combined sprint time sensitivity to proportional changes in F_{0} and v_{0}; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the sprint time response. Model simulations showed that F_{e} decreased with rising F_{0} and increased with rising v_{0}, while v_{e} showed the opposite pattern. With increasing sprint distance, F_{e} decreased and v_{e} increased. Given its negligible effect on sprint time, ignoring air resistance yields a conservation law (2F_{e}+v_{e}\equiv 1), indicating that a gain in one elasticity metric necessarily diminishes the other in a fixed proportion. This framework also identifies a valley distance (d_{valley}) at {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=2, where {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} is minimized (\sqrt{0.2}) and sprint time is least responsive to changes in F-V relationship variables. Empirical data confirmed that the two theoretical laws still hold approximately when air resistance is considered. By linking changes in F_{0} and v_{0} to sprint time across different distances, the elasticity framework provides a quantitative basis for estimating the theoretical sprint time response to documented changes in F-V relationship variables.

biophysics↗

bioRxiv2026

Single-atom inhibition of oncogenic drivers through cysteine coordination

Small-molecule inhibitors rely on molecular recognition within suitable binding pockets, leaving many disease-associated proteins difficult to target. Here, we introduce the concept of a single-atom inhibitor in which gold (Au) engages critical cysteine residues of oncogenic drivers to suppress their activity. We used an AI-assisted few-shot learning approach to identify EGFR-targeting peptides for in vivo Au delivery and showed that the lead candidate, 10714, promoted Au accumulation in EGFR-expressing cells and tumors. In vivo, Au exploited its intrinsic affinity for cysteine to inhibit two structurally distinct oncogenic proteins, engaging Cys797 in EGFR T790M and the mutation-derived Cys12 in KRAS G12C adjacent to their respective nucleotide-binding pockets. Structural and computational analyses supported stabilization of inactive nucleotide-bound states, while mutation of these cysteine residues abrogated Au-mediated inhibition. 10714-Au consequently suppressed oncogenic signaling, reduced non-small-cell lung cancer cell viability, and inhibited tumor growth in EGFR- and KRAS-mutant xenograft models and patient-derived organoids. These findings establish proof of principle for single-atom inhibition across structurally distinct oncogenic drivers and suggest that localized atomic coordination could provide an alternative mode of target engagement to conventional pocket-dependent inhibition.

molecular biology↗

bioRxiv2026

Structural basis for covalent inhibition of sulfatases by sulfamate warheads

The enzymatic removal of sulfate groups regulates processes ranging from steroid metabolism to carbohydrate degradation. Most sulfatases belong to the S1 family, whose members use a co-translationally installed formylglycine residue to hydrolyse sulfate esters. Arylsulfamates are potent covalent inhibitors of aryl and steroid sulfatases, including the clinical steroid sulfatase inhibitor Irosustat, yet the structure and stability of the inhibited complex remain unresolved. Arylsulfamates and carbohydrate sulfamates do not covalently inhibit many S1 carbohydrate sulfatases despite conservation of their sulfate-binding sites and formylglycine residue. Using enzyme kinetics, X-ray crystallography, molecular dynamics simulations and density functional theory calculations, we define the basis of these contrasting behaviours. High-resolution structures of the Pseudomonas aeruginosa arylsulfatase PaAtsA treated with two arylsulfamates reveal a long-lived tetrahedral, O-linked -hydroxysulfamate adduct attached to formylglycine. Molecular simulations show that replacing sulfate with sulfamate disrupts the favourable Ca2+-oxyanion interaction and alters ligand binding geometry. The permissive hydrophobic binding site of PaAtsA accommodates this rearrangement while retaining a trajectory compatible with nucleophilic attack. By contrast, in the Bacteroides thetaiotaomicron carbohydrate sulfatase BT16363S-Gal, sulfate-to-sulfamate substitution weakens binding and displaces the sulfamate from a reactive pose near the catalytic nucleophile due to a restrictive active site with conserved sugar binding. These findings define the structure and persistence of the arylsulfamate-derived covalent intermediate and explain why sulfamate warheads are tolerated by aryl sulfatases but not carbohydrate sulfatases.

biochemistry↗

bioRxiv2026

Spatial multi-omics analysis reveals vimentin-high macrophages-endothelial cells niche shapes CAFs heterogeneity in colorectal cancer metastasis

The spatial architecture of the tumor microenvironment (TME) is pivotal in the progression of colorectal cancer (CRC) liver metastasis. By applying high-plex spatial multi-omic mapping and neighborhood analysis to a discovery cohort of colorectal cancer primary tumor (PT) and paired liver metastases (LM), we identified a specialized vimentin-high macrophages-endothelial cells niche that orchestrates cancer-associated fibroblast (CAF) phenotypes. Mechanistically, in primary tumors, vimentin-high macrophages secrete INHBA to activate the ACVR2/TGF-{beta} axis in endothelial cells, driving CAFs toward a myCAF phenotype. Conversely, in liver metastases, these macrophages secrete CXCL9 to trigger the PI3K-Akt/NF-[kcy]B/CXCL12 cascade in endothelial cells, directing CAFs toward an iCAF state. Clinically, high niche activity predicts poor survival. Divergent endothelial signaling in primary versus metastatic lesions exposes site-specific stromal vulnerabilities for therapeutic targeting, with architectural features discernible from routine histopathology. These findings reveal a site-specific regulatory mechanism of the macrophage-endothelial niche, offering a novel and clinically significant biomarker for CRC prognosis.

cancer biology↗

bioRxiv2026

DQHTFI: Dynamic-Query Hypergraph Transformer for Fine-Grained Drug-Target Interaction and Affinity Prediction

Drug-target interaction prediction and binding affinity prediction are two key tasks in drug discovery and drug repurposing. Although deep learning methods have made significant progress, existing models typically rely on global representations of drugs and proteins, making it difficult to adequately model fine-grained interactions between their local units. Fixed multimodal fusion strategies also struggle to dynamically adjust the contributions of different modalities for different drug-target combinations. To address these issues, we propose DQHTFI, a fine-grained interaction prediction framework for drug-target interaction classification and binding affinity regression. DQHTFI employs BRICS fragments and Pfam functional domains as the basic interaction units and jointly learns semantic and structural representations. We design a dynamic-query hypergraph Transformer framework in which hyperedges are constructed among the multimodal features of fragment-domain pairs. Dynamic queries are generated from the cross-conditioned features of fragment-domain pairs to adaptively adjust the contribution of each modality, thereby modeling higher-order interactions between local units. Our proposed model achieves competitive results on multiple benchmark datasets.

bioinformatics↗

bioRxiv2026

Functional Differentiation of GH172 Arabinofuranosidases Through Divergent Quaternary Structures

Mycobacteria synthesise the unusual glycan [x1D05]-arabinan as a major component of the cell wall glycoconjugates arabinogalactan (AG) and lipoarabinomannan (LAM). We previously identified Dysgonomonas gadei, a member of the Bacteroidota, as capable of complete [x1D05]-arabinan degradation through the concerted action of endo- and exo-acting enzymes. Among these are three glycoside hydrolase family 172 (GH172) enzymes with exo--[x1D05]-arabinofuranosidase activity against AG and LAM, although their linkage specificities were unknown. Here, using defined synthetic substrates, we show that the three enzymes possess distinct linkage preferences. We also develop -[x1D05]-arabinofuranosyl cyclophellitol aziridines as covalent inhibitors and activity-based probes for GH172 enzymes. X-ray crystallography and cryo-EM to reveal strikingly different quaternary assemblies across the three homologues, while a 1.5 [A] cryo-EM structure of dodecameric Dg67 covalently modified by an aziridine inhibitor identifies the catalytic nucleophile and provides direct structural support for a retaining mechanism. A BODIPY-tagged aziridine probe selectively labelled the three GH172 enzymes in D. gadei cell lysates. Together, these findings define functional and structural diversity within GH172 and establish chemical probes for profiling -[x1D05]-arabinofuranosidase activity in complex biological samples.

biochemistry↗

bioRxiv2026

High prevalence of KPC-3 in carbapenem-resistant Pseudomonas aeruginosa across multiple clonal lineages in China

Background The epidemiology of Klebsiella pneumoniae carbapenemase (KPC)-producing Pseudomonas aeruginosa is rapidly evolving in China. While blaKPC-2 remains the predominant KPC variant in P. aeruginosa, blaKPC-3 has rarely been documented in this pathogen. This study investigated the molecular epidemiology, resistance and virulence characteristics, and plasmid features of blaKPC-3-producing CRPA isolates collected from a tertiary hospital in eastern China. Methods A total of 65 non-duplicate CRPA isolates collected in 2023 were subjected to whole-genome sequencing. Antimicrobial susceptibility testing, phylogenetic analysis, plasmid characterization, conjugation experiments, and virulence assays were performed. Results Among the 65 CRPA isolates, 37 (56.9%) carried blaKPC-3. These blaKPC-3-positive isolates belonged to four sequence types (STs), including ST1076 (62.2%), ST463 (21.6%), ST646 (10.8%), and ST3393 (5.4%). To our knowledge, this is the first report of blaKPC-3 in P. aeruginosa ST463, ST646 and ST3393. All isolates exhibited extensive drug resistance, and 51.8% were resistant to ceftazidime-avibactam. Phylogenetic analysis indicated that blaKPC-3 dissemination was driven by both clonal expansion and horizontal transmission. Comparative genomic analysis identified three kinds of blaKPC-3 -carrying plasmid. A transferable IncP-2 megaplasmid was widely distributed among ST1076, ST646, and ST3393 isolates, whereas non-transferable IncP-10 plasmids were primarily restricted to ST463. The genetic environments and plasmid backbones of blaKPC-3 were highly conserved and closely related to those of blaKPC-2 and its variants, suggesting evolution from pre-existing blaKPC-2-associated plasmids. Virulence analysis demonstrated marked heterogeneity across lineages. ST463 isolates co-harbored exoU and exoS, exhibited enhanced biofilm formation and pyocyanin production, and caused significantly higher mortality in the G. mellonella infection model, indicating a hypervirulent phenotype. Conclusions The blaKPC-3 is becoming an increasingly important determinant of carbapenem resistance in P. aeruginosa in China. The IncP-2 megaplasmid and IncP-10 plasmid derived blaKPC-3 spread across multiple lineages. Continuous genomic surveillance and enhanced infection control measures are urgently needed to prevent its further prevalence in clinical settings.

microbiology↗

bioRxiv2026

PG-MLD: Physics-Guided Molecular Representation Learning via Dynamic 3D Trajectory Distillation

Molecular representation learning underpins molecular property prediction and drug design by capturing molecular structure-property relationships. SMILES-based molecular language models learn chemical semantics from large-scale unlabeled data and support efficient inference. However, the one-dimensional nature of SMILES constrains their ability to capture 3D geometry and conformational evolution, whereas 3D molecular models require conformer generation and substantial computational resources. To bridge this gap, we propose PG-MLD, a dynamic 3D-to-1D physical knowledge distillation paradigm for molecular representation learning. PG-MLD constructs a dynamic 3D physical teacher by combining equivariant geometric encoding with Liquid Time-Constant modeling to capture 3D geometry, atom-level electronic descriptors, and conformational evolution. PG-MLD subsequently distills the learned trajectory knowledge into SMILES-based students through atom- and molecule-level representation alignment and cross-modal contrastive learning, with masked language modeling retained where supported. The distilled students perform downstream tasks using only SMILES, without conformer generation or molecular dynamics simulations. Experiments on MoleculeNet show that PG-MLD improves overall property prediction performance across three molecular language student architectures while maintaining SMILES-only inference. The learned representations also encode 3D geometry and conformational dynamics more effectively, demonstrating that dynamic 3D physical knowledge can be transferred to SMILES-based molecular language models with different architectures.

bioinformatics↗

bioRxiv2026

Real-time electrochemical protein monitoring using molecular pendulum sensors

Continuous monitoring of proteins in complex biological fluids is essential for advancing personalized medicine, yet existing biosensors are often limited by instability, single-use designs, and insufficient sensitivity. Here, we describe a detailed protocol for the fabrication and operation of molecular pendulum (MP) electrochemical sensors integrated with an active-reset mechanism to enable real-time, reversible, and ultrasensitive protein detection. The protocol is described in two parts. First, we describe the microfabrication of gold microelectrodes and their nanostructured modification, followed by assembly of DNA-based pendulum probes with redox reporters and affinity receptors that translate binding into kinetic electron-transfer shifts. Second, we detail the sensing and active-reset approach, which detects the target analyte and applies tunable oscillatory potentials to accelerate its dissociation, regenerate sensor surfaces, and extend operational lifetime. The protocol includes detailed guidance on device fabrication, surface functionalization, sensing and reset cycles, and data analysis. When implemented, MP sensors with active-reset achieve pg/ml sensitivity, rapid equilibration, and robust performance across biofluids and in situ models, enabling continuous protein monitoring over extended periods. This combined technology represents a biosensing platform with significant potential, opening new avenues for wearable and implantable molecular monitoring, early disease detection, and personalized therapeutic guidance.

bioengineering↗

bioRxiv2026

IL-1β/IL-6 signaling circuit in the tumor microenvironment drives prostate cancer development

Despite considerable progress in elucidating mechanisms leading to castration-resistant prostate cancer (CRPC), insight into the early stages of prostate cancer initiation and progression remains limited. Genomic drivers of prostate cancer initiation have been defined through patient tumor sequencing, but the subsequent events responsible for local tissue invasion are poorly understood. Here we leverage a well-studied genetically engineered mouse prostate cancer model (Hi-Myc) that, based on robust and reproducible kinetics for transitioning from pre-invasive prostatic intraepithelial neoplasia (PIN) to invasive prostate adenocarcinoma (PCa), provides an ideal system to systematically address this question using single-cell analysis. Surprisingly, the transcriptomic profiles of early PIN lesions are indistinguishable from those of late-stage, highly invasive tumor cells, suggesting that MYC activation at the PIN stage establishes a transcriptional program that is fully capable of driving invasion but is restrained by the local tumor microenvironment (TME). Indeed, we find that progression to PCa is associated with progressive infiltration of IL-1{beta}+ tumor-infiltrating macrophages at the PIN stage that, based on immunodepletion and cytokine neutralization experiments, are required for the PIN-to-PCa transition. Mechanistically, IL-1{beta} from macrophages acts directly on prostate fibroblasts, leading to the release of IL-6, which drives invasion by activating IL-6R in tumor cells. Collectively, these findings identify a pro-tumorigenic IL-1{beta}/IL-6 signaling circuit mediated through local macrophages and fibroblasts that unleashes the full oncogenic potential of a cancer driver (MYC) activated at the PIN stage. We also find evidence of this circuit in other (non-MYC-driven) prostate cancer models as well as human prostate and lung adenocarcinoma, with implications for TME-specific targeted therapeutics in early-stage disease.

cancer biology↗

bioRxiv2026

The Capillary endothelial cell-governed niche sustains angiogenesis in proliferating infantile hemangioma via multilayer stromal support

Infantile hemangioma (IH), the most common benign vascular tumor in infants, is characterized by the aberrant proliferation of hemangioma endothelial cells (HemECs) and excessive angiogenesis. However, it is unclear how the tumor microenvironment sustains these active angiogenic signals. We performed single-cell RNA sequencing and spatial transcriptomic to profile 30 samples from proliferating IH, involuting IH, and normal skin. The results indicated that HemECs comprised distinct subpopulations. Among them, capillary endothelial cells (Cap.ECs) had an immature phenotype and functioned as the core drivers of IH. The endothelial-to-mesenchymal transition endothelial cells (endoMT-ECs) secreted collagen and engaged in CD44-mediated crosstalk with Cap.ECs to construct the angiogenesis-active niche in the tumor microenvironment (TME) of proliferating IH. Blockade of CD44-mediated intercellular communication effectively suppresses the angiogenesis of HemECs and promotes tumor regression. Beyond the endothelial layer, pericytes tightly enveloped Cap.ECs, with SERPINE2+ subtypes sustaining their angiogenic activity via ANGPT signaling. Pseudotime trajectory analysis revealed that the mesenchymal stem cells (MSCs)-enriched niche serves as a progenitor pool for Cap.ECs in proliferating IH. Our findings thus revealed that IH progression relies on CD44-mediated endoMT-EC-Cap.EC crosstalk and on both pericyte and MSC niches to sustain angiogenesis. HIGHLIGHTSO_LICapillary endothelial cells drive infantile hemangioma progression, with pericytes tightly ensheathing them. C_LIO_LICD44-mediated capillary and endoMT-derived endothelial cells crosstalk construct the angiogenic-active niche in the tumor microenvironment of proliferating infantile hemangioma. C_LIO_LIThe MSC-enriched niche provides a progenitor pool for the capillary endothelial cells in proliferating infantile hemangioma. C_LI

cancer biology↗

bioRxiv2026

Reconstructing whole-organism cell phylogenies with resolved ancestral transcriptional states

Combining cell lineage tracing with single-cell RNA sequencing can reconstruct a phylogenetic tree to integrate single-cell transcriptomic atlas. However, the internal nodes of this tree - representing ancestral cells - remain transcriptionally silent, preventing along-lineage longitudinal tracing of cell state dynamics. Here, we overcome this by reconstructing high-resolution zygote-to-larva developmental cell phylogenies for 15 zebrafish larvae, with directly measured transcriptomes of the terminal nodes (i.e., sampled cells). Leveraging a set of lineage-committed upregulated genes (LUGs), we developed LUG-encoded ancestral projection (LEAP), a novel phylogeny-based computational framework, and successfully imputed the transcriptional states of internal nodes of the phylogenies. This enabled, for the first time in a non-nematode organism, lineage-informed longitudinal analysis of cell state dynamics throughout development. Our analysis revealed a major, previously unappreciated wave of fate specializations associated with hatching, distinct from the well-characterized events of gastrulation. Furthermore, we uncovered abundant incipient cell states that are already fate-determined but exhibit minimal transcriptional differentiation, revealing a hidden layer of developmental fate specializations. In sum, by resolving ancestral transcriptional states of a reconstructed cell phylogeny, this work paves the way for constructing lineage-resolved cell atlases in complex organisms to characterize comprehensive cell state dynamics.

developmental biology↗

bioRxiv2026

Bio-CM{superscript 2}: Distributed computational optics for cortex-widecellular imaging

Understanding distributed biological systems, particularly neural circuits, requires simultaneous cellular-resolution imaging across millimeter-scale fields of view (FOV). Existing miniature microscopes remain fundamentally constrained by trade-offs among FOV, spatial resolution, and optical complexity, limiting their ability to bridge cellular microscopy with cortex-scale imaging. Here we introduce distributed computational optics, a framework that distributes image formation across coordinated optical modules and computationally integrates their measurements into a unified image. We realize this framework in Bio-CM2, a computational miniature mesoscope that partitions the imaging field across four optical modules while converging their measurements onto a common image sensor. This architecture overcomes the aberration-scaling limitations of conventional miniature optics while avoiding the hardware complexity of multi-camera systems and the contrast degradation associated with optical multiplexing. Bio-CM2 achieves a 7.5 x 10 mm2 FOV while enabling cellular-resolution in vivo imaging at video rates. We demonstrate its utility through two complementary imaging modalities in head-fixed mice: cortex-wide functional vascular imaging, enabling simultaneous quantification of pial arteriole vasomotion and mesoscale hemodynamic functional connectivity, and cellular-resolution calcium imaging, resolving the activity of over 3,000 neurons together with mesoscale neuronal functional connectivity. We further demonstrate the versatility of the platform through cellular-resolution imaging of entire coronal mouse brain sections, population-scale imaging of freely behaving Caenorhabditis elegans, and odor-evoked calcium imaging of the main olfactory bulb in head-fixed mice, highlighting its broad applicability across diverse biological systems and imaging modalities. By overcoming the conventional trade-off between FOV and spatial resolution in a compact miniature platform, Bio-CM2 establishes distributed computational optics as a scalable framework for multiscale biological imaging.

bioengineering↗

bioRxiv2026

A self-organized geometry sensing oscillator spatially regulates cell division in archaea

Cell division must be tightly regulate in time and space. Many bacteria and eukaryotes employ geometry sensing systems to regulate cell division spatiotemporally. However, how archaea ensure they divide in the right place at the right time is little understood. Here, we report the discovery of a geometry sensing oscillator that determines the division plane in the model haloarcheon Haloferax volcanii, which relies on two tubulin-like proteins, FtsZ1 and FtsZ2, for division. This archaeal oscillator (named as Arco system) is composed of three components, ArcoA, ArcoB and ArcoC, which are a membrane associated Ras superfamily GTPase, a SepF-like protein and an antagonist of FtsZ1, respectively. ArcoA interacts with both ArcoB and ArcoC. ArcoAB sense the geometry of the cell to oscillate between the two cell poles, generating a time-averaged ArcoC gradient which is high at the cell poles but low at the midcell, where FtsZs can assemble into the Z ring to initiate cytokinesis. As a result, deletion of the Arco system caused aberrant FtsZ assembly throughout the cell, leading to irregular division and formation of minicells. Interestingly, the Arco system is globally distributed among archaea and co-occurs with FtsZ1, suggesting that it emerged in the last archaeal common ancestor (LACA). The oscillatory behavior and phenotypes of the archaeal Arco system is remarkably analogous to the bacterial Min system and yet share no protein homology, representing a remarkable example of convergent evolution. Overall, these results suggest that archaea, similar to bacteria and eukaryotes, independently evolved self-organized Turing reaction diffusion systems to sense geometry and spatially regulate cell division.

microbiology↗

bioRxiv2026

The Aspergillus fumigatus C2-Domain Protein SppA is required for septal integrity and alters susceptibility to echinocandins and neutrophil killing during infection

Aspergillus fumigatus is a major opportunistic fungal pathogen whose ability to maintain hyphal integrity and withstand host defenses is critical for virulence. Septal pores, which connect hyphal compartments, are dynamically regulated to preserve cellular integrity under stress, yet the molecular components governing this process remain incompletely defined. Here, we identify and characterize a septal pore-associated protein, SppA, and demonstrate its essential role in maintaining septal integrity in A. fumigatus. We show that expression of SppA is positively regulated by the transcription factor ZfpA and is induced in response to the cell wall-targeting antifungal caspofungin. Deletion of sppA resulted in defective septal organization and increased susceptibility to hyphal damage. The mutant exhibited heightened sensitivity to cell wall-targeting antifungal agents, indicating a role in cell wall stress tolerance. In a zebrafish model of invasive aspergillosis, loss of SppA significantly attenuated virulence which was abrogated in neutrophil-deficient zebrafish. Further, the mutant strain displayed increased susceptibility to killing by primary human neutrophils, suggesting that proper septal pore formation contributes to fungal survival during host immune attack. Together, our findings establish SppA as a critical determinant of septal integrity, antifungal tolerance, and pathogenicity in A. fumigatus, and position it as part of a ZfpA-regulated, caspofungin-responsive pathway that supports fungal survival during stress and infection. Author SummaryAspergillus fumigatus is a common environmental mold that can cause life-threatening infections in people with weakened immune systems. For successful invasion of host tissue, the fungus requires the ability to protection sections of its hyphae from cell wall targeting antifungals and host immune cell attack by closing septal (cross wall) pores distributed throughout hyphal strands. We have identified an A. fumigatus protein, SppA, required for proper septal pore closure. Loss of SppA reduces the ability of hyphae to withstand treatment with antifungals and the ability of A. fumigatus to cause disease in a zebrafish infection model. The SppA mutant was particularly susceptible to killing by neutrophils, key immune cells that help control fungal infections. Our findings reveal an important mechanism that helps A. fumigatus survive environmental and host-imposed stresses and highlight septal pore regulation as a potential target for future antifungal strategies.

microbiology↗

bioRxiv2026

FLD Is Required for N-Hydroxypipecolic Acid Accumulation and Associated Growth Defects in Arabidopsis pmr4 Mutant

The Arabidopsis mutants lacking the pathogen-inducible callose synthase POWDERY MILDEW RESISTANCE 4 (PMR4)/GLUCAN SYNTHASE-LIKE 5 (GSL5) exhibit enhanced disease resistance accompanied by reduced growth, spontaneous necrosis, and premature senescence. This autoimmune phenotype of pmr4 is associated with a high accumulation of N-hydroxypipecolic acid (NHP) and a moderate increase in salicylic acid. We previously reported three suppressors of pmr4 (spm), PAD4 and the NHP biosynthetic genes ALD1 and FMO1, whose loss-of-function mutations abolish NHP accumulation and completely suppress the growth defects of pmr4, demonstrating that NHP is critical to the autoimmune growth phenotype. Here, we characterize a fourth suppressor, spm4, which similarly fully suppresses the growth defects of pmr4. Map-based cloning and molecular genetic analyses revealed that spm4 carries a mutation in FLOWERING LOCUS D (FLD). Reintroduction of a wild-type FLD allele into the pmr4 spm4 background restored both NHP accumulation and the characteristic growth defects of pmr4. Conversely, independent FLD loss-of-function alleles generated by CRISPR/Cas-mediated genome editing suppressed NHP accumulation and rescued the autoimmune growth defects of pmr4, confirming that FLD is required for manifestation of the pmr4 phenotype. Beyond its established role in flowering-time regulation, FLD has been implicated in plant immunity, particularly in systemic acquired resistance (SAR), although the mechanistic basis of its immune function remains poorly understood. Our findings identify FLD as an essential positive regulator of NHP accumulation, thereby providing a mechanistic link between FLD-dependent epigenetic regulation, NHP-mediated signaling, and SAR.

plant biology↗

bioRxiv2026

DNA-Programmed Condensate-Membrane Wetting and Cellular Internalization

Deformable condensates offer dynamic interfaces for biomolecule delivery, yet membrane adhesion does not necessarily lead to cellular internalization. The physical transition that determines whether a membrane-bound soft material remains surface-anchored or proceeds through wetting towards productive uptake remains poorly understood, particularly at active living-cell membranes. Here, we engineer sequence-defined DNA condensates through liquid-liquid phase separation (LLPS) and program their interfacial behavior by tuning sticky-end valency and cholesterol organization. These molecular designs precisely regulate condensate fluidity, fusion dynamics and internal organization, generating distinct states of weak contact, persistent anchoring and rapid wetting. Increasing cholesterol-mediated affinity does not enhance uptake. Instead, productive internalization emerges from a balance between membrane adhesion and condensate fluidity and deformability. Native membrane composition further modulates condensate interfacial fate across mammalian cells and plant protoplasts. DNA condensates enrich and deliver CpG ODNs, mRNA ([~]2000 nt) and proteins, while cargo loading experiments reveal that preserving condensate architecture is essential for functional delivery. Our findings identify wetting competence as a design parameter for controlling soft material engagement and cellular entry.

biophysics↗

bioRxiv2026

Massively parallel characterization and predictive modelling of neuronal regulatory variation

Disease-associated variants reside frequently in noncoding cis-regulatory elements (CREs), yet their functional consequences remain poorly understood. We performed a large-scale lentiMPRA in human excitatory neurons, quantifying the impact of >46,000 naturally occurring variants across >27,000 candidate CREs near 524 disease-associated genes. These data improved regulatory variant effect predictions beyond state-of-the-art models. Significant allelic effects occurred at comparable rates across common, rare, and singleton variants, demonstrating that, within MPRA-measurable effects, population frequency carries limited information about per-variant regulatory impact. Variant effect detectability and magnitude were governed primarily by baseline activity of the enclosing regulatory element and local sequence context. Regulatory effects were distributed across numerous transcription factors rather than concentrated in master regulators, consistent with a combinatorial enhancer architecture. We establish a large-scale functional variant catalog and provide a complementary benchmark and resource for developing and evaluating models of noncoding regulatory variation.

genetics↗