Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 217 records · Page 12Linked to original sources

bioRxiv2026

Ferrosome Organelles Spatially Insulate a Redox-Active Ferrous Phosphate Biomineral from Cytosolic ROS Chemistry

Ferrosomes are recently discovered lipid-bound bacterial organelles that store iron as iron-phosphate biominerals, yet the chemical nature and physiological consequences of ferrosome-stored iron remain poorly understood. Here, we combined X-ray absorption spectroscopy (XAS), electron microscopy, inductively coupled plasma mass spectrometry (ICP-MS), and physiological analyses to characterize ferrosome iron in Clostridioides difficile. XAS analysis of isolated ferrosomes revealed an amorphous iron-phosphate biomineral containing mixed Fe(II)/Fe(III), consistent with partial oxidation during aerobic isolation. In contrast, whole-cell XAS of intact anaerobically maintained cells demonstrated that ferrosomes predominantly contain a structurally disordered ferrous phosphate biomineral with local Fe-O-P coordination features similar to those of vivianite. Upon air exposure, this ferrous biomineral rapidly oxidized to a ferric phosphate-like state, revealing a highly oxygen-sensitive iron-storage phase. Despite containing abundant redox-active Fe(II), ferrosome-stored iron contributed minimally to the cytosolic labile iron pool. Consistent with this observation, isolated ferrosomes exhibited little ROS-generating activity, and ferrosome-overproducing cells displayed no substantial increase in sensitivity to oxygen, peroxide, or paraquat stress relative to ferrosome-deficient controls. Together, these results establish ferrosomes as iron-storage organelles that sequester redox-active Fe(II) in a mineralized ferrous phosphate phase, limiting its participation in cytosolic ROS chemistry and providing a mechanism for the safe storage of reactive iron. Significance StatementIron is essential for life but can also damage cells because ferrous iron drives oxidative stress. How cells store large amounts of ferrous iron while limiting toxicity therefore remains a fundamental biological question. Ferrosomes are recently discovered bacterial organelles that store iron as iron-phosphate biominerals, but the chemical nature and physiological consequences of ferrosome-associated iron remained unknown. Using Fe K-edge X-ray absorption spectroscopy, we show that ferrosomes in Clostridioides difficile contain a redox-sensitive ferrous phosphate biomineral. Physiological analyses demonstrate that this iron is largely inaccessible to cytosolic reactive oxygen species (ROS) chemistry. These findings reveal that bacteria can combine biomineralization and subcellular compartmentalization to maintain large intracellular iron reservoirs while limiting iron-dependent oxidative damage.

microbiology↗

bioRxiv2026

Foxf1 is required for the specification and maintenance of pulmonary capillary identity

The pulmonary microvasculature consists of two transcriptionally distinct capillary (CAP) endothelial populations, CAP1 and CAP2 cells, that form the alveolar capillary network. While CAP1 and CAP2 are functionally distinct, the transcriptional mechanisms that specify and maintain these endothelial fates remain poorly understood. The Forkhead transcription factor Foxf1 regulates vascular development and is implicated in the neonatal disease alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV). However, its role in the specification of pulmonary endothelial subtypes has not been defined. Using single cell ATAC-sequencing and RNA-sequencing of developing mouse lung endothelial cells (ECs), we found that Foxf1 is broadly expressed across pulmonary ECs but exhibits preferential chromatin accessibility in CAP2 ECs. Endothelial deletion of Foxf1 impaired CAP2 specification and disrupted CAP1 identity, unexpectedly leading to the emergence of a mutant CAP1-like population with a macrovascular transcriptional signature. Adult endothelial deletion of Foxf1 similarly resulted in loss of capillary identity, demonstrating that Foxf1 is required for capillary fate maintenance. Mutant CAP1 ECs upregulated matrix remodeling genes and exhibited altered communication with neighboring mesenchymal populations, suggesting a potential role in disease development. Consistent with these findings, this mutant CAP1 transcriptional signature was present in human lungs with ACDMPV. This work identifies Foxf1 as a key transcriptional regulator for the specification and active maintenance of pulmonary capillary EC fate across the lifespan, and positions capillary identity loss as a driver of vascular remodeling.

Developmental Biology↗

bioRxiv2026

DNA-binding specificity recognition from predicted homologous protein-DNA structures

Predicting protein DNA-binding specificity is essential for understanding gene regulation and disease mechanisms. Existing deep learning methods typically infer specificity from a single protein-DNA complex structure, which limits their ability to capture the diverse geometric patterns underlying protein-DNA recognition. Homologous protein-DNA interfaces provide complementary structural evidence and richer geometric features related to interatomic interactions. To address the limited diversity and coverage of experimentally determined complexes, we constructed a large-scale library of predicted homologous protein-DNA complex structures. Building on this resource, we propose HomoDSP, a template-retrieval-based framework for accurate DNA-binding specificity prediction. Benchmark evaluations and validation on newly released JASPAR 2026 samples indicate that HomoDSP outperforms existing methods in both accuracy and generalization, with particularly substantial gains on high-error samples. Moreover, this performance is largely retained when AlphaFold3-predicted complex structures are used as input. Template- and residue-level interpretability analyses suggest that HomoDSP improves prediction by focusing on DNA-affinity residues across multiple homologous templates. Finally, universal Protein Binding Microarrays evaluations on AI-designed DNA-binding proteins show that HomoDSP rescues a baseline failure mode in which the baseline method produces incorrect predictions because of training-set bias. Together, these results support the use of homologous template interfaces as informative structural priors for decoding protein DNA-binding specificity.

bioinformatics↗

bioRxiv2026

Super-Resolved Single Small Extracellular Vesicle Assay enabled by a Plasmonic Nanohole Array

The accurate quantification of biological nanoparticles, such as small extracellular vesicles (sEVs), is fundamentally hindered by a resolution-coincidence trade-off in digital assays. While physical confinement can isolate single particles, conventional optical readouts remain diffraction-limited, causing multi-particle occupancy to be miscounted as single events and thereby restricting the analytical dynamic range. Here, we report a nanoplasmonic platform that overcomes this limit by introducing a geometry-defined interface that uniquely unifies nanoscale compartmentalisation and near-field-assisted super-resolution imaging. Utilising a gold plasmonic nanohole array, the strict geometric periodicity of the lattice simultaneously serves as a template for single-vesicle confinement and a deterministic grid that generates an array of localised surface plasmon resonance near-field hotspots. This position-deterministic illumination pattern imposes known geometric priors on the excitation field, shifting high-spatial-frequency information into the detectable bandwidth to achieve sub-100 nm lateral resolution. This dual-purpose geometric determinism enables high-fidelity digital readout of individual vesicles with significantly fewer sub-images than stochastic, speckle-based metasurface structured illumination microscopy approaches. The assay achieves an analytical limit of detection of 143 sEVs/{micro}L, matching the performance of state-of-the-art single-EV counting technologies. It successfully differentiates distinct sEV subpopulations based on surface biomarker expression, establishing a clear pathway for future clinical liquid biopsy applications. By replacing stochastic loading and illumination with geometric design, this work establishes a robust framework for precise vesicle interrogation with broad implications for emerging translational applications and fundamental biology.

bioengineering↗

bioRxiv2026

ConformFlow: scalable normalizing flow for protein conformational ensemble generation

AO_SCPLOWBSTRACTC_SCPLOWMolecular dynamics (MD) simulations remain the standard tool for characterizing protein conformational landscapes, but their high computational cost limits large-scale and long-timescale applications. Recent generative models, especially diffusion-based approaches, provide promising alternatives by learning equilibrium conformational distributions across diverse protein systems. We present ConformFlow, the first scalable normalizing-flow framework for sequence-conditioned protein conformational ensemble generation. ConformFlow combines a continuous backbone latent representation with a RealNVP-style flow parameterized by sequence-aware Transformer coupling networks, enabling exact likelihood training, single-step sampling, and plug-and-play conditioning on flexible geometric constraints. Across diverse protein systems, ConformFlow generates ensembles that agree well with reference MD simulations, generalizes to proteins beyond its training data, and achieves substantially faster sampling than diffusion-based baselines. These results establish ConformFlow as an efficient and controllable alternative for protein conformational ensemble generation. Codehttps://github.com/Harrydirk41/ConformFlow.git

biochemistry↗

bioRxiv2026

ARID4 Modulates Stomatal ABA Signaling and Stress-Responsive Gene Expression to Confer Drought Tolerance in Arabidopsis

To identify novel regulators of plant drought tolerance, we performed a forward genetic screen using thermal infrared imaging to detect alterations in leaf temperature, a proxy for transpiration. This screen identified AT-rich Interacting Domain Protein 4 (ARID4), a protein involved in chromatin remodeling, as a modulator of transpiration. arid4 loss-of-function mutants exhibited cooler leaves, increased water loss from detached leaves, and heightened susceptibility to drought relative to wild-type plants. Stomata of arid4 mutants were hyposensitive to abscisic acid (ABA), displaying reduced ABA-induced reactive oxygen species (ROS) production and impaired stomatal closure. Transcriptome profiling under drought revealed extensive misregulation of genes involved in stress-responses, redox homeostasis, iron acquisition, and photosynthesis. These findings indicate that ARID4 modulates the expression of key regulatory genes to maintain redox homeostasis and photosynthetic efficiency, thereby conferring drought stress tolerance.

Plant Biology↗

bioRxiv2026

Aging restricts colorectal tumor growth by epigenetically silencing developmental gene programs

The incidence of early-onset colorectal cancer (CRC) has risen sharply in recent decades1, yet the biological basis underlying the distinct behavior of tumors arising in young versus aged tissues remains poorly understood. Here we show that aging reprograms the epigenetic landscape of the colon, restricting colon tumor growth through stable silencing of developmental and fetal gene programs. We find that colon tumors arising in aged mice are intrinsically less proliferative than those arising in young animals. Multi-omic profiling of normal colon and colon tumors reveals that aging drives DNA hypermethylation, loss of Polycomb-associated chromatin states, and reduced chromatin accessibility at a defined set of developmental genes that are bivalent (marked by both H3K27me3 and H3K4 methylation), transcriptionally active in colon tumors from young animals and repressed in both tumors and normal tissue from old animals. Among the genes most strongly repressed in old animals is Tacstd2 (Trop2), a regulator of fetal intestinal programs and epithelial stemness. Pharmacologic inhibition of DNA methylation reactivates the aging-silenced gene network in organoids from old animals, whereas genetic disruption of Tacstd2 suppresses growth and developmental transcriptional programs in young tumor organoids. TACSTD2, fetal gene signatures, and the aging-associated bivalent gene program are likewise repressed in late-onset vs. early-onset human colorectal cancers. Collectively, these findings identify age-associated epigenetic silencing of developmental gene programs as a causal mechanism that constrains colorectal tumor growth and provide a mechanistic framework for understanding the distinct biology of early-onset colorectal cancer.

cancer biology↗

bioRxiv2026

Robust integration of weakly anchored spatial multi-omics

Spatial multi-omics holds great promise for dissecting complex biological processes, though inherent technical constraints continue to limit its widespread adoption. Currently, most studies therefore measure distinct omics features on separate tissue sections, necessitating spatial diagonal integration. An emerging practical solution is to leverage hematoxylin and eosin (H&E) images as an integration anchor, given their ubiquity, low cost, and compatibility across tissue preparations. However, this anchor is frequently compromised in real-world settings by variations in H&E staining style, absence of reliable histological landmarks, and mismatches in spatial resolutions across omics modalities. To address this, we introduce SpaWeaver, a computational framework that couples a pathology foundation model with a graph Transformer and a latent feature aligner module, providing a highly robust solution for weakly anchored spatial omics data diagonal integration. Extensive experiments demonstrate that SpaWeaver exhibits superior robustness against isolated or synergistic weak-anchoring factors. The spatial multi-omics profiles generated by SpaWeaver link molecular features originally separated on two sections, unlocking diverse downstream analyses once exclusive to co-assayed spatial multi-omics data, including niche-aware cell-cell communication inference and multi-omics resolved cell state. In this study, it unveils tumor-distance-dependent fibroblast-CD4{square}T-cell signaling in human colon adenocarcinoma and identifies a hypoxic glycolytic tumor state with pyknotic nuclei in human ovarian cancer. Overall, our approach bridges readily accessible single-omics measurements across weakly anchored tissue sections, enabling unified spatial multi-omics characterization and system-level tissue analysis.

bioinformatics↗

bioRxiv2026

GYS2 Promotes the Progression of Aortic Dissection and Aortic Aneurysm via C5a/NF-κB-Mediated Pro-Inflammatory Macrophage Polarization

BackgroundAortic aneurysm and aortic dissection (AAD) are lethal cardiovascular emergencies characterized by sudden onset and extremely high early mortality. The pro-inflammatory polarization of macrophages is one of the core factors driving the pathogenesis of AAD, but its underlying mechanism remains unclear. This study focuses on the aberrant expression of glycogen synthase 2 (GYS2) in the AAD microenvironment and its role in driving macrophage polarization toward the pro-inflammatory M1 phenotype. MethodsProteomic analysis was conducted to identify protein heterogeneity associated with AAD. Clinical and animal samples were used to evaluate the correlation between GYS2 expression and AAD progression. Whole-body GYS2 knockout mice and adeno-associated virus (AAV)-mediated macrophage-specific gain- and loss-of-function models were utilized to investigate the regulatory role of GYS2 in macrophage polarization and complement activation. Downstream molecular pathways were identified and validated through in vitro stimulation and in vivo exogenous C5a rescue experiments. ResultsGYS2 expression was significantly upregulated in AAD tissues and primarily localized in macrophages. Activation of GYS2 by LiCl or macrophage-specific overexpression of GYS2 exacerbated aortic dilation and extracellular matrix degradation, and increased mortality in AAD mice. Conversely, whole-body GYS2 knockout or macrophage-specific GYS2 knockdown suppressed inflammatory factors, significantly reduced the incidence of AAD, and attenuated vascular injury. Mechanistically, excessive GYS2 in macrophages specifically triggered the complement-coagulation cascade, promoting the generation of the potent anaphylatoxin C5a. C5a further bound to its receptor C5AR1, activating the downstream PLC{beta}3/NF-{kappa}B signaling pathway, thereby inducing M1 macrophage polarization and matrix metalloproteinase-mediated extracellular matrix degradation. In vivo exogenous C5a rescue completely reversed the vascular protective effects conferred by GYS2 deficiency. ConclusionsThis study demonstrates that highly expressed GYS2 regulates the pro-inflammatory polarization of macrophages and extracellular matrix degradation via the complement C5a/PLC{beta}3/NF-{kappa}B signaling axis, which is a key mechanism driving AAD progression. Specific inhibition of macrophage GYS2 can effectively alleviate aortic vascular inflammation and prevent AAD progression, providing a promising novel strategy for the clinical conservative treatment of AAD.

Molecular Biology↗

bioRxiv2026

A multi-omics map of diabetic nephropathy links c-Jun activation to tubular injury and metabolic stress

Diabetic nephropathy (DN) is a major cause of end-stage renal disease, yet the molecular mechanisms driving tubular injury and fibrosis remain poorly defined. Here, we integrated single-cell multiplexed protein imaging, spatial transcriptomics, single-nucleus and single-cell RNA sequencing and chromatin accessibility profiling to comprehensively characterize human DN pathology. Our multi-modal analysis precisely maps kidney cell types and their spatial distributions, immune-fibrotic interactions, and key transcriptional regulators. We identified eight distinct cellular neighborhoods defining the immune-fibrotic microenvironment and uncovered molecular networks driving tubular injury and fibrosis. JUN (encoding c-Jun) emerged as a central regulator of transcriptional reprogramming during tubular injury and fibrogenic remodeling. In a diabetic mouse model, c-Jun is activated in injured proximal tubules. Using an inducible c-Jun mouse model, we demonstrated that tubular-specific c-Jun activation alone is sufficient to induce tubular injury, chronic inflammation, progressive fibrosis, and systemic metabolic alterations, including impaired glucose homeostasis. We also observed reduced expression of SLC4A4, a bicarbonate transporter essential for proximal tubular function, in injured tubules. Together, our findings establish a spatially resolved framework for understanding DN pathogenesis and identify c-Jun as a key mediator of tubular injury and fibrosis in diabetic kidney disease.

pathology↗

bioRxiv2026

Functional orthogonality of WRN inhibitor resistance enables alternating therapy and mutation-tolerant inhibitor design in MSI-H cancers

Werner syndrome helicase (WRN) is a synthetic-lethal vulnerability in microsatellite instability-high (MSI-H)/mismatch repair-deficient (dMMR) cancers1-5, and non-covalent and covalent WRN inhibitors are now entering clinical development6-9. A central unresolved question is whether resistance to one WRN inhibitor class inevitably compromises the target, or instead creates actionable vulnerabilities to an alternate modality. Here we generated ten stable acquired-resistance models across three MSI-H cell lines using the non-covalent inhibitor HRO761 and the covalent inhibitor VVD-214. Whole-exome sequencing, biochemical reconstitution and isogenic knock-in models identified recurrent on-target WRN missense mutations as dominant resistance drivers, but with sharply modality-specific spectra: HRO761 resistance clustered at G729/F730/I852, whereas VVD-214 resistance concentrated at E846. These mutations impaired inhibitor engagement and abolished the canonical WRN inhibitor (WRNi)-induced pharmacodynamic cascade, including WRN reduction, DNA damage response (DDR) activation and G2/M arrest. Crucially, most resistance mutations retained biochemical, cellular and in vivo sensitivity to the alternate inhibitor modality, revealing a functional orthogonality that enabled a 7-day cyclic alternating regimen to delay tumour regrowth in xenografts. We further identified F730L as an engineered cross-resistant bottleneck model and used structure-guided, artificial intelligence (AI)-enabled optimization to generate GBA-007, a proof-of-concept mutation-tolerant WRN inhibitor candidate with promising activity against F730L in vitro and in vivo. Thus, clinically relevant WRN inhibitor classes impose distinct on-target resistance trajectories that can be exploited through schedule design, while cross-resistant bottlenecks can be addressed by rapid mutation-aware inhibitor engineering.

Cancer Biology↗

bioRxiv2026

Antimicrobial and Cytotoxic Lysolipins I-M Isolated from Streptomyces sp. P8-2B18

Lysolipin I (1) is a highly bioactive xanthone with strong antibacterial and cytotoxic properties. Given the limited number of lysolipin analogues, discovery of new natural lysolipin derivatives is important for understanding their structure-activity relationships. A soil-derived Streptomyces sp. P8-2B18 harbors a putative lysolipin biosynthetic gene cluster and LC-MS based metabolomic analysis revealed the production of lysolipin I along with unreported analogues. Large-scale fermentation followed by isolation led to the discovery of four new analogues, lysolipins J-M (2- 5), the structures of which were elucidated by mass spectrometric and NMR spectroscopic data analyses. Lysolipin L features a five-membered lactam F ring, which was unprecedented in reported lysolipins. Lysolipin M has a novel skeleton, with an extra methyl (Me-36) and a glycosyl group replacing a 1,3-oxane ring in lysolipin I. While lysolipins I, J and K displayed strong activity against Staphylococcus aureus and Aspergillus flavus with MIC values ranging from 0.25 to 4 g/mL and lysolipin L showed only moderate activities, lysolipin M was inactive (>50 g/mL). Lysolipins I-K showed potent cytotoxic activity against prostate cancer cell lines LNCaP and C4-2B, with IC50 values in the submicromolar range. In contrast, lysolipin L exhibited no cytotoxicity and lysolipin M exhibited substantially reduced potency. Their broad, non-selective bioactivities restricted their applicability as therapeutic agents.

microbiology↗

bioRxiv2026

SPOTTER: Automated Tissue-Barcoding Platform for Spatial Proteomics and Phosphoproteomics

Spatial proteomics aims to characterize proteome in situ with regional resolution, linking molecular states to tissue architecture and microenvironments. While recent advances have expanded our access to spatially resolved proteomics, major barriers in scalability and throughput remain. Building on our prior SPOT (Spatial Proteomics through On-site Tissue-protein-labeling) framework1, we introduce SPOTTER, a customizable robotic platform that enables automated, micron-scale spatial barcoding directly on intact tissue sections. SPOTTER barcodes proteins by labeling tissue proteins in situ to encode spatial origin across the whole tissue section. This strategy enables unbiased whole-tissue proteome mapping and, for the first time, spatial phosphoproteome profiling from intact sections. Coupled with high-resolution LC-MS/MS, SPOTTER achieves deep proteome and phosphoproteome coverage while preserving histological integrity. By replacing labor-intensive laser capture microdissection workflows and low-plex antibody arrays, SPOTTER provides a scalable route to high-plex spatial proteomics, resolving spatially distinct regions within a single experiment.

bioengineering↗

bioRxiv2026

DigiMus: a connectome-informed spiking framework for multi-region mouse neural-behavior modeling

Computational models are increasingly used to relate mouse brain structure, neural activity and behavior, but most models still learn from task data with limited constraints from biological circuit organization. Here we present DigiMus, a connectome-informed spiking framework for multi-region-capable mouse neural-behavior modeling. DigiMus combines leaky integrate-and-fire spiking dynamics with brain-region-specific motif regularization in a trainable sequence-modeling architecture, allowing directed three-node circuit motifs derived from 38,481 reconstructed neuronal morphologies across approximately 50 brain regions to guide recurrent coupling during learning. We evaluate DigiMus on 18 rule-based cognitive tasks spanning sensorimotor mapping and perceptual decision-making, and on three mouse neural decoding datasets involving auditory discrimination, fixed-interval licking and visual decoding. Across synthetic tasks, DigiMus showed stable performance relative to TCN, LSTM and Transformer baselines, with stronger advantages in more complex decision-making settings. In real neural datasets, single-region instantiations of DigiMus produced small, consistent and dataset-dependent improvements over a structure-free sequence baseline, while retaining motif-prior signatures in trained connectivity. Internal state analyses further linked task-dependent state dynamics to behavioral error patterns. These results suggest that connectome-derived structural priors can shape neural sequence models, and establish DigiMus as a modular, connectome-informed workflow for mouse neural-behavior modeling and hypothesis generation, rather than a complete digital reconstruction.

neuroscience↗

bioRxiv2026

HOMED enables hierarchical and multimodal optimization of DNA methylation deconvolution across tissues

Cellular heterogeneity is a major confounder in bulk DNA methylation data for epigenome-wide association studies. Existing reference-based DNAm deconvolution methods often ignore hierarchies among related cell types and may generalize poorly across datasets due to limited variability in reference profiles. We developed HOMED (Hierarchically Optimized Methylation Deconvolution), a framework that integrates cell-lineage hierarchies, single-cell RNA sequencing-guided deconvolution, and paired bulk RNA-seq/DNAm data for CpG signature optimization. Across simulated and real peripheral blood mononuclear cell, lung, and placental datasets, HOMED consistently yielded the highest PCCs and lowest RMSEs, outperforming existing scRNA-seq-guided DNAm deconvolution methods, improving accuracy, resolution, and cross-tissue generalizability.

bioinformatics↗

bioRxiv2026

The Gene Version Iteration Hypothesis reveals the Y chromosome-mediated closed-loop transmission and version selection mechanism of mutated genes

The Gene Version Iteration Hypothesis (GVIH) proposes that mutant genes may originate from the Y chromosome, traverse through the X chromosome to autosomes, undergo interchromosomal transfer, and potentially return to the Y chromosome via the X chromosome. This hypothetical closed transmission loop may facilitate the storage, screening, and elimination of different versions of mutant genes. The hypothesis comprises five core propositions: (1) Mutation reservoir: The Y chromosome may serve as a specialized carrier for generating mutant genes, characterized by elevated mutation rates, reduced gene density, and accelerated evolutionary dynamics; (2) Closed-loop transmission: Mutant genes may follow a unidirectional pathway Y[->]X[->]autosomes[->]X[->]Y, forming a complete transmission circuit; (3) Coexistence of multiple versions: A single functional gene may exist in multiple versions across different chromosomes, constituting a dynamic gene version library; (4) Reproductive screening: Environmentally adaptive gene versions may persist across generations and potentially migrate to upstream chromosomes, while maladaptive versions may be eliminated; (5) Terminal elimination: Gene versions reaching the Y chromosome may undergo elimination processes, potentially preventing version monopolization and maintaining evolutionary dynamics. This hypothesis provides a novel framework for understanding adaptive evolution at the genetic level. If empirically validated, it may offer new insights into the molecular mechanisms underlying certain genetic phenomena and evolutionary processes.

genetics↗

bioRxiv2026

A Facile and Versatile Technique for Creating Antifibrotic Coatings on Biomedical Implants

Foreign body response is a common yet serious challenge for biomedical implants. It can trigger inflammation and eventually lead to the formation of a fibrotic capsule, which compromises device function. Although significant efforts have been made to develop antifibrotic surface coatings for implantable materials, developing broadly applicable solutions remains challenging due to the diversity of materials used in biomedical implants. Here, we propose a simple and versatile strategy to develop antifibrotic coatings for biomedical implants. Photoreactive benzophenone groups are incorporated into designer polymers to enable covalent attachment to various substrates. The effect of benzophenone group density within polymer chains on surface coating efficiency was investigated, and an optimal BP incorporation ratio was identified. Polymers incorporating varying ratios of an anti-fibrotic small molecule and anti-fouling zwitterionic moieties were synthesized and successfully attached to silicone implants. In vivo evaluation of these implants in C57BL/6 mice identified an optimized polymer composition that reduced fibrotic capsule thickness by around 60%. Coating of commercial medical catheters with this optimized polymer reduced collagen deposition by over 3.5-fold following 4 weeks of implantation in the peritoneal space of C57BL/6 mice. Finally, we demonstrated that the optimized polymer coating can be readily applied to a variety of commonly used biomedical materials using this straightforward method, highlighting the versatility of the approach. This work provides a facile and broadly applicable strategy for developing antifibrotic coatings, which has the potential to expand the design of surface modifications aimed at improving the performance of biomedical implants.

bioengineering↗

bioRxiv2026

Accurate de novo design of peptides from programming biophysical landscape

Peptides regulate virtually every cellular process and emerge as transformative modalities in bioengineering and therapeutics. However, the de novo design of functional peptides remains challenging, as peptide-protein interactions are governed by delicate and dynamic biophysics that are difficult to model, and experimental datasets are scarce. Here we present NeoPep, a generative deep-learning framework that encodes biophysical principles to accurately design functional peptides de novo. By integrating over 5 million peptide-protein complexes spanning experimentally determined, sequence mimics, and structure ensembles, NeoPep learns the complex biophysical landscape governing peptide function and enables its programmable control. In prospective application across 10 diverse and challenging targets, NeoPep generated potent peptide binders, agonists, and antagonists with hit rates of 12.5-66.7%, even in the absence of defined binding sites or structure information. Beyond de novo co-design, NeoPep supports standalone structure or sequence redesign, readily discriminating subtle context differences. In the structure redesign mode, it generates highly selective peptides with atomic-level conformational accuracy (C RMSD < 2.0 [A] to our solved cryo-EM structure). This structural precision circumvents the need for experimental structure determination, further accelerating iterative sequence redesign to yield a 43.3-fold improvement in potency. These findings establish a general framework for translating biophysical principles into actionable peptide functions, with broad implications for basic research, bioengineering, and medicine.

molecular biology↗