Biology subjects

Jiang, F.

Publications and source records attributed to Jiang, F..

At least 19 recordsLinked to original sources

bioRxiv2026

VenusGenome: Genome-Aware Masked Autoencoding for Microbial Genome Representation Learning

Genomic-context models have shown that contextualizing protein embeddings can improve predictions of microbial function. We observe that a gene's protein embedding is partially predictable from the embeddings of neighboring genes in the genome, motivating high-ratio masking that requires reconstruction from sparser genomic context. Genomic modeling must also distinguish biological relationships from assembly conventions, since the ordering of separate contigs does not imply adjacency and strand labels depend on the reference orientation. We therefore introduce VenusGenome, a gene-resolution masked autoencoder that combines visible-only encoding with genome-aware attention incorporating contig boundaries, relative strand orientations, and gene positions. We pretrain this model on a curated corpus of over 1.7 million microbial genome assemblies from isolate and metagenomic sources, using frozen protein embeddings as gene-level inputs. Across genome-level phenotype prediction and gene-level tasks, the resulting frozen representations achieve the highest mean performance among the evaluated models on nine of eleven primary metrics. An exploratory gene-input perturbation analysis further links representation sensitivity to experimentally measured fitness defects. Ablations support the contribution of genome-aware attention and show the benefits of masked autoencoding over BERT-style masked modeling, with further gains from higher masking ratios.

bioinformatics↗

bioRxiv2026

FLASH X-rays preserve neutrophil chromatin to boost antitumor immunity

Ultrahigh dose-rate FLASH radiotherapy spares normal tissue while preserving antitumor activity, positioning it as a promising technology in radiation oncology, but its immunomodulatory mechanisms remain elusive. Here, using a bilateral subcutaneous tumor model in mice, we show that 8-Gy FLASH X-rays, versus an equal dose of conventional dose-rate (CONV) X-rays, elicit a robust abscopal antitumor effect with anti-PD-1 therapy. Single-cell transcriptome and T cell receptor (TCR) profiling reveal that FLASH X-rays plus anti-PD-1 enhance antitumor immune infiltration and TCR clonal expansion in both irradiated and abscopal tumor lesions. Mechanistically, the ultrashort temporal continuity of FLASH dose delivery conserves chromatin compaction in neutrophils during exposure and inhibits neutrophil extracellular trap (NET) formation, thereby dismantling NET-mediated CD8+ T-cell exclusion within primary tumors. Conversely, CONV or split-dose FLASH X-rays induce marked chromatin modifications prior to dose completion, leading to chromatin hyper-relaxation which promotes NETosis and consequently abrogates systemic antitumor immunity. Notably, this detrimental effect can be reversed by pharmacologically suppressing PARylation-mediated chromatin modification and decondensation in neutrophils. These findings identify radiation-induced aberrant chromatin relaxation in neutrophils as a critical determinant of radioimmunotherapy outcomes, providing a rationale for redefining the FLASH effect and advancing its clinical translation.

cancer biology↗

bioRxiv2026

TomatoPGFM: A graph-conditioned foundation model for tomato pangenomes

Most genomic foundation models are pretrained on independent linear assemblies and therefore do not explicitly represent population-level segment sharing or local graph connectivity. We developed TomatoPGFM, a graph-conditioned model pretrained on 54.65 Gb of sequence from 66 tomato (Solanum spp.) accessions. Sequence tokens were conditioned on pangenome node attributes and local adjacency, and the model was optimised using masked language modelling and graph-feature reconstruction. To evaluate model responses to graph-conditioned input, we compared aligned, shuffled and disabled graph inputs in 25,000 windows from the training panel. Sequence-aligned graph input produced lower masked language modelling loss than graph-off at all five curriculum stages in both training-panel strata, while the shuffled perturbation generally yielded intermediate losses. We then assessed sequence-only transfer in Solanum sitiens LA1974 and S. lycopersicum MicroTom, neither of which was used for graph construction or pretraining. Frozen-probe AUROC values for gene-versus-intergenic and coding-sequence-versus-intergenic classification ranged from 0.8489 to 0.9593. TomatoPGFM produced higher AUROC point estimates than DNABERT-2 in all four comparisons. Enabling the zero-feature GraphAdapter pathway with adjacency messaging disabled changed throughput by less than 1% at 512-2,048 positions under the tested configuration. Together, these results show that TomatoPGFM responds consistently to sequence-aligned pangenome context in training-panel sequences and provides informative sequence representations for genic-region classification in accessions excluded from graph construction and pretraining.

bioinformatics↗

bioRxiv2026

Long-Term Grazing Drives Compositional Shifts in Root-Associated Microbial Communities of Desert Steppe Plants

Grassland microbial communities are central to mediating ecosystem function and stability, yet how long-term grazing reshapes root-associated microbiomes across contiguous soil-root habitats remains poorly understood. This limits our ability to identify robust microbial bioindicators for grassland health monitoring. In this study, we investigated the community assembly and functional variation of root-associated microbiomes of Stipa breviflora, a dominant perennial clonal grass in desert steppes, across a 17-year continuous grazing experiment with four grazing intensity treatments (no grazing, light, moderate, and heavy grazing). We show that grazing intensity induces niche-specific restructuring of microbial communities, with the most profound compositional and functional shifts occurring in the rhizosphere, followed by root endophytic compartments and bulk soil. Light and moderate grazing significantly enriches the phylum Bacillota in rhizosphere and endophytic compartments, whereas the genus Pseudomonas dominates ungrazed grassland soils and is markedly depleted under grazing conditions. Microbial community responses to grazing follow a unimodal intermediate disturbance pattern, with moderate grazing triggering the strongest microbial community differentiation, enhanced microbial network connectivity and modularity, and the highest abundance of grazing-responsive microbial biomarkers. Notably, grazing-induced microbial community variation is decoupled from intraspecific phenotypic changes in S. breviflora. Our findings demonstrate that long-term grazing acts as a strong selective filter partitioning core beneficial microbial taxon, establishing Bacillota and Pseudomonas as complementary bioindicators for evaluating desert steppe ecosystem health. This study advances the understanding of plant-microbe interactions under anthropogenic disturbance and provides microbiome-based insights for sustainable grassland management.

microbiology↗

bioRxiv2026

MAXWELL: Calibrating the probabilistic outputs of protein language models to the mutation-induced stability change landscape

Designing mutations that enhance protein stability is a central goal in protein engineering. However, experimentally screening large numbers of candidate mutations is costly and time-consuming, creating a strong need for computational methods that can identify potentially stabilizing mutations. Among these approaches, protein language models are particularly promising because they learn context-dependent amino acid preferences from large-scale sequence and structure datasets. Nevertheless, most existing stability prediction methods use these models primarily as feature extractors and do not fully exploit the amino acid probability distributions they encode. Here, we introduce MAXWELL (Matrix-wise Landscape Learning), a novel post-training method that calibrates the probabilistic outputs learned by protein language models during pretraining to generate mutational landscapes that quantify the effects of individual amino acid substitutions on protein stability. When applied to ProteinMPNN, MAXWELL yields a state-of-the-art predictor of the effects of protein mutations on stability, outperforming ThermoMPNN and other representative methods on a curated benchmark of experimentally measured stability changes. We next applied MAXWELL to the design of ten single-point mutations in the DhaA dehalogenase, seven of which (70%) increased thermal stability. Among them, G171W showed the largest improvement, with a measured {Delta}Tm of 4.91 {degrees}C. These experimental results establish MAXWELL as a novel post-training strategy for protein language models and a practical framework for designing stabilizing mutations. Repositoryhttps://github.com/ai4protein/Venus-MAXWELL

bioinformatics↗

bioRxiv2026

CENO: A Genome-Scale World Model for Evolutionary Sequence Interpretation and Programmable Regulatory Design

DNA encodes biological function across a continuum of sequence scales, from single-nucleotide and motif-level grammar to regulatory neighborhoods, chromatin-scale organization and evolutionary constraint. A useful model of genomes should therefore do more than classify short sequence windows: it should maintain nucleotide-resolution state over long contexts, score counterfactual mutations, condition on homologous sequence evidence and generate candidates that can be evaluated against structural or functional objectives. We define such a system operationally as a genomic world model: a general-purpose generative model of genome sequence space that unifies sequence understanding and sequence design through a shared state and likelihood interface. Here we introduce CENO, a family of long-context generative genomic world models designed to preserve local DNA grammar while extending usable context to regulatory and chromatin scales. CENO combines Mamba sequence-mixing layers, sparse attention layers and mixture-of-experts capacity in a single autoregressive backbone, and is trained at 300M, 600M and 1B parameter scales with a staged curriculum that progresses from 8k-token cross-domain genomic pretraining to 131k- and 1M-token whole-genome long-context continuation. We evaluate CENO under a unified world-model benchmark paradigm spanning retrieval, representation, counterfactual perturbation, reconstruction, evolutionary conditioning and design. CENO retains practical long-context inference and retrieves distal sequence in synthetic assays. In zero-shot long-context analyses, without task-specific fine-tuning, long-context continuation yields annotation- and chromatin-boundary-associated attention patterns and frozen-state representations that generalize across human cell types and mouse cell or tissue settings. To incorporate evolutionary information, we further post-train CENO on packed real multiple-sequence-alignment contexts and score variants by reference-mutant likelihood deltas, improving matched variant-effect prediction and producing evolutionary enrichment signals across species. Complementing these perturbation-based variant tests, we evaluate zero-shot long-sequence generation by partial-gene continuation, asking whether the model can recover withheld gene-scale sequence structure across eukaryotic, bacterial and archaeal species; recovery improves with model scale and later whole-genome long-context training. Finally, we use CENO as the backbone for a cell-type-specific enhancer design workflow in mouse cortex, coupling a CENO-based accessibility oracle with conditional supervised fine-tuning and oracle-guided reinforcement learning. Together, CENO provides a genome-scale sequence world-model framework for sequence interpretation, evolutionary reasoning, gene-scale reconstruction and programmable regulatory sequence generation.

genomics↗

bioRxiv2026

Engineering Oncolytic Measles Virus with MG53 Couples Pyroptotic Tumor Killing with Immune Microenvironment Remodeling to Enhance Checkpoint Immunotherapy in Non-small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related mortality worldwide, with only approximately 30% of patients benefiting from current immune checkpoint immunotherapy. Oncolytic virotherapy offers a promising strategy to overcome this resistance; however, achieving both potent tumor cytotoxicity and robust antitumor immune activation remains a major challenge. Here, we engineered oncolytic measles virus expressing the tumor suppressor MG53 (TRIM72), designated rMeV-MG53, and evaluated its therapeutic potential against non-small cell lung cancer (NSCLC). rMeV-MG53 retained replication kinetics comparable to parental MeV while driving significantly greater cytotoxicity than an unarmed control in NSCLC cells. Mechanistically, MG53 arming amplified caspase-3-dependent apoptosis and potentiated Gasdermin E (GSDME) cleavage, engaging GSDME-mediated pyroptosis as a key tumor-killing mechanism; pharmacological inhibition confirmed caspase-dependent apoptosis as the initiating event leading to pyroptosis, while excluding necroptosis and ferroptosis as significant contributors to rMeV-MG53-induced cytotoxicity. MG53 overexpression induced an intrinsic pro-inflammatory transcriptional signature enriched for TNF, NF-{kappa}B, and IL-17 signaling, and rMeV-MG53 elicited significantly stronger type I interferon and pro-inflammatory cytokine induction than the unarmed control. In an immunocompetent, MeV-permissive syngeneic NSCLC model, intratumoral rMeV-MG53 achieved superior tumor growth inhibition, amplified caspase-3/GSDME pyroptosis, selectively upregulated Cxcl10, Ifng, and Il1b, and drove robust CD8 T-cell and Granzyme B effector infiltration. This immune remodeling was accompanied by compensatory PD-L1 upregulation, and combining rMeV-MG53 with anti-PD-L1 blockade achieved the strongest tumor suppression of all treatment groups. These findings establish MG53-armed oncolytic MeV as a strategy coupling GSDME-mediated pyroptosis with antitumor immune remodeling to sensitize immune-resistant NSCLC to checkpoint immunotherapy.

immunology↗

bioRxiv2026

Cumulative Transfer Function for Assessment of MRI-Induced RF Heating Risk in Pediatric Patients Implanted with Bifurcated Leads

PurposeRF-induced heating remains a major barrier to MRI access for patients with epicardial cardiac implantable electronic devices (CIEDs). Although ISO/TS 10974 Tier-3 transfer function (TF) methods are established for unbranched leads, no analogous framework exists for bifurcated leads, in which branch asymmetry and inter-branch coupling may substantially alter heating. We developed and validated a cumulative transfer function (cTF) framework to address this gap. MethodsFollowing ISO/TS 10974 Tier-3 formalism, we measured, calibrated, and validated cTFs for a commercial 35 cm bipolar epicardial lead at 1.5 T. The framework explicitly accounts for branch-specific response and cross-branch coupling. Validation was performed with 24 canonical lead configurations in a homogeneous phantom and, without recalibration, in a heterogeneous anthropomorphic pediatric phantom with clinically derived trajectories. A single-branch TF approximation served as a comparator. The validated cTF was applied to predict RF heating across adult and pediatric human models at multiple imaging landmarks. ResultsCompared with the single-branch TF approximation, the cTF reduced prediction error by nearly 70% in the primary validation dataset. In secondary validation, the cTF maintained low error across clinically relevant trajectories and imaging landmarks. In human models, the framework revealed marked anatomy- and landmark-dependent variation in predicted heating for the tested 35 cm lead, with low predicted heating in pediatric models and substantially higher heating in selected adult chest and upper abdominal imaging scenarios. ConclusionThe cTF provides a validated framework for RF-heating assessment of bifurcated leads and substantially improves prediction accuracy over single-branch TF approximations that neglect branch coupling.

bioengineering↗

bioRxiv2026

RF Heating of Bipolar Epicardial Implants during MRI at 0.55 T and 1.5T: Effect of Device Length and Termination Conditions

Pediatric patients with epicardial cardiac implantable electronic devices (CIEDs) are frequently excluded from the Magnetic Resonance Imaging (MRI) primarily due to RF heating safety concerns. In this study we evaluate RF heating of two bipolar epicardial leads during MRI at 0.55 T and 1.5 T under different termination conditions. Our findings showed that the mean RF heating was significantly reduced at 0.55 T MRI compared to that at 1.5 T. Similarly, the RF heating at 0.55 T MRI was highest for full system whereas, during MRI at 1.5 T, the RF heating was highest for the capped abandoned lead, showing dependence of RF heating pattern on MRI field strength. While RF heating at both fields surpassed the safety limit, the capped abandoned leads at 1.5 T MRI showed significantly higher RF heating with temperature rise surpassing 50{degrees}C in some of the cases. These results highlight the difference in RF heating of bipolar epicardial leads compared to the previously reported findings for monopolar epicardial lead which showed smallest heating for capped abandoned lead at both field strengths. These findings emphasize the necessity of device-specific evaluations at each field-strength to inform clinical decision-making and expand MRI access for this vulnerable population.

biophysics↗

bioRxiv2026

A Cross-tissue Temporal Multi-omics Atlas Reveals the Molecular Architecture of Pressure Injury

Pressure injury induces progressive necrosis of skin and deep muscle, yet how mechanical loading reshapes molecular programs across tissues and time remains poorly defined. To address this gap, we established a rat pressure-injury model and performed longitudinal integrated profiling of skin and deep muscle across four stages, combining transcriptomics, proteomics and untargeted metabolomics with histological assessment. This multi-layered atlas revealed a staged injury program dominated by early transcriptional activation of innate immunity and complement-coagulation crosstalk, accompanied by neutrophil-associated responses and engagement of upstream regulatory networks. As injury advanced, a second axis of remodeling emerged, characterized by sustained suppression of mitochondrial energy metabolism and oxidative phosphorylation, particularly in muscle, together with extracellular matrix and adhesion rewiring. In parallel, skin preferentially activated barrier-repair and protein-homeostasis programs, including keratinization and autophagy-linked processes, indicating tissue-specific adaptation to the same mechanical insult. Temporal clustering and pathway-network analysis further showed that immune activation and metabolic collapse are not independent events but are dynamically coupled across stages, with muscle exhibiting broader molecular reprogramming and a stronger shift toward irreversible structural failure. Together, these data define a cross-tissue, stage-resolved molecular framework for pressure injury progression and identify pathway-level windows that may inform tissue-targeted and stage-specific intervention strategies.

systems biology↗

bioRxiv2026

Integrated optimization of experimental and computational workflows improves genome recovery in long-read gut metagenomics

Short-read metagenomic sequencing has been widely applied in microbial research due to its high quality and decreasing cost. However, short reads are inherently fragmented, which limits assembly contiguity and the recovery of complete microbial genomes. In contrast, long-read sequencing, with significantly longer read lengths, helps overcome these limitations. Achieving complete and accurate genome recovery is the core goal of metagenomics. To address this challenge, we systematically evaluated and optimized the long-read metagenomic workflow, from sample processing to computational assembly, using the CycloneSEQ platform.

bioinformatics↗

bioRxiv2026

Genomic Decoding of Specialized Aromatic Hydrocarbon Degradation in Mangrove-Derived Gordonia sp. B7 2

Petroleum pollution has increased worldwide, driving the search for microorganisms with efficient hydrocarbon-degrading capabilities. Here, we report a novel bacterium, Gordonia sp. B7-2, isolated from mangrove sediments in Hainan, China. Phylogenetic analysis based on the 16S rRNA gene and whole-genome sequences, together with digital DNA-DNA hybridization and average nucleotide identity values, supported its classification as a new species within the genus Gordonia. The complete genome of strain B7-2 consists of a single circular chromosome of 5.39 Mb with a G+C content of 65.99%, and encodes 4,887 protein-coding genes. Genomic annotation revealed a complete pathway for aromatic hydrocarbon degradation, including genes encoding protocatechuate 3,4-dioxygenase and biphenyl-2,3-diol 1,2-dioxygenase, whereas genes involved in the initial oxidation of alkanes were absent. Consistent with these genomic predictions, strain B7-2 degraded 64.33% of crude oil (300 mg/L) within 28 days, with rapid degradation during the initial 14 days, followed by a slower phase thereafter, reflecting the dynamics of complex hydrocarbon mixtures. Together, these results demonstrate that strain B7-2 is specialized for the degradation of aromatic hydrocarbons and highlight its potential for targeted petroleum bioremediation. IMPORTANCEMangrove ecosystems are highly vulnerable to petroleum contamination, yet the microorganisms responsible for hydrocarbon turnover in these environments remain poorly characterized. This study describes a new bacterial species, Gordonia sp. B7-2, that exhibits a strong metabolic specialization for aromatic hydrocarbon degradation. Unlike many known oil-degrading bacteria that preferentially utilize alkanes, strain B7-2 targets aromatic components of crude oil, which are among the most persistent and toxic fractions.Its ability to efficiently degrade crude oil highlights its potential in the bioremediation of contaminated coastal environments and expands our understanding of microbial contributions to hydrocarbon cycling in mangrove sediments

microbiology↗

bioRxiv2026

Therapeutic targeting of fibrin-microglia interactions ameliorates Alzheimer disease-related hyperexcitability and brain network dysfunction

Brain network dysfunction--including hyperexcitability, altered oscillations, and sleep disruption--is prominent in Alzheimers disease (AD), but the contribution of vascular-neuroimmune processes to these alterations remains unclear. Here, we blocked the pro-inflammatory interaction of the blood protein fibrin with microglia using genetic (Fgg{gamma}390-396A mice) and antibody-based (5B8 and THN392) strategies to test its role in AD-related network dysfunction. The 5xFAD model of AD exhibited network hyperexcitability associated with oscillatory slowing, sleep states, and disrupted sleep-circadian rhythms. These deficits were largely attenuated by blocking fibrin-microglia interactions in 5xFAD;Fgg{gamma}390-396A mice. Notably, pharmacological interventions after disease onset with both anti-fibrin antibodies similarly attenuated these AD-related network deficits and behavioral abnormalities. We conclude that vascular-neuroimmune processes driven by fibrin-microglia interactions promote AD-related network dysfunction and that targeting the fibrin-microglia axis--currently under clinical evaluation with the humanized antibody THN391-- represents a promising therapeutic strategy for AD. There is a companion manuscript submitted to bioRxiv (Yan et al., 2026).110 HIGHLIGHTSO_LIFibrin promotes AD-related network hyperexcitability and oscillatory slowing in 5xFAD mice C_LIO_LIFibrin promotes AD-related disruption of sleep and circadian rhythms in 5xFAD mice C_LIO_LIGenetic blocking of fibrin-microglia interactions rescues AD-related brain network dysfunction C_LIO_LIAnti-fibrin antibodies (5B8 and THN392) show acute and chronic therapeutic benefit C_LI

neuroscience↗

bioRxiv2026

An Isoform-Centric, Structure-Aware Framework for Protein Function Prediction and Evaluation, Instantiated in 3DisoDeepPF

Understanding and accurately predicting function across protein isoforms has been a long-standing challenge with profound implications for both biological and translational research. However, most functional annotations and benchmarks remain tied to genes or reference protein sequences, leaving limited support for distinguishing protein isoforms from the same gene whose sequence, structure and domain composition may lead to different functions. To address this gap, we developed an isoform-centric framework for protein function and domain annotation that integrates a dense graph of sequence and structure similarity with protein features. We implemented this framework as 3DisoDeepPF, a graph-based multimodal model, and applied it to a breast cancer isoform atlas. Across canonical benchmarks and evaluations at isoform resolution, 3DisoDeepPF showed strong performance in predicting GO terms and Pfam domains and remained robust in tests with homology control. It further captured changes in Pfam domain composition among isoforms from the same gene, including reference-relative domain gain and loss. An evidence tracing module links predicted labels to supporting proteins in the graph, as illustrated by the calcium and integrin binding protein 1 (CIB1). Together, this study provides a framework informed by protein structure for function and domain annotation at isoform resolution, converting human protein isoform diversity into traceable functional evidence for cancer atlas interpretation.

cancer biology↗

bioRxiv2026

Experimental Validation of Finite Element Models for Directional DBS: The Critical Role of Boundary Conditions on VTA Accuracy

ObjectiveComputational models and visualization toolboxes for Deep Brain Stimulation (DBS) increasingly rely on pre-computed electric field libraries to estimate the Volume of Tissue Activated (VTA). However, the boundary conditions (BCs) and source models used to generate these fields vary widely across studies, and there is currently no experimental consensus regarding which parameters most accurately reflect the physical device output. The objective of this study was to experimentally validate the electric potential distribution of directional DBS leads in order to determine the optimal Finite Element Method (FEM) configuration. ApproachThe voltage distribution surrounding a Boston Scientific Vercise Gevia directional lead was mapped in a saline phantom using a custom high-precision robotic scanning system. Experimental measurements were compared against six FEM configurations that varied in source formulation (Dirichlet vs. Neumann boundary conditions) and ground definitions. For each configuration, the resulting VTA volume was computed to assess the clinical impact of modeling assumptions. ResultsThe FEM configuration implementing a Dirichlet (voltage) boundary condition on the active contact with a grounded implantable pulse generator (IPG) surface demonstrated the highest accuracy, achieving a Symmetric Mean Absolute Percent Error (SMAPE) of less than 9% across all contact levels. In contrast, conventional current-controlled simulations employing Neumann boundary conditions with disparate ground definitions substantially overestimated electric field spread. Suboptimal boundary condition selection resulted in an approximate 67% overestimation of VTA volume (137 mm3 vs. 82 mm3) relative to the experimentally validated model. SignificanceAlthough clinical DBS systems operate as current sources, standard Neumann (current density) boundary conditions do not adequately represent the equipotential behavior of the electrode-tissue interface, resulting in nearly a two-fold error in predicted VTA volume. To improve the validity of predictive clinical models, we recommend the use of Dirichlet boundary conditions derived from the device operating impedance (V = Itarget x Zmeasured) rather than conventional current density specifications.

bioengineering↗

bioRxiv2026

MG53 Protects Against Intestinal Inflammation by Inhibiting NLRP3 Inflammasome Activation

Background and ObjectivesInflammatory bowel disease (IBD) involves dysregulated immune responses and chronic intestinal inflammation. The nod-like receptor pyrin domain-containing 3 (NLRP3) inflammasome plays a critical role in IBD pathogenesis, but regulatory mechanisms remain not fully understood. Mitsugumin 53 (MG53, also known as TRIM72), originally identified as a critical membrane repair protein, has emerged as a novel regulator of inflammatory processes. To investigate the protective role of MG53 in colitis and elucidate its mechanisms in regulating NLRP3 inflammasome activation in IBD. MethodsWe used dextran sodium sulfate (DSS)-induced colitis models comparing MG53 knockout (MG53-/-) and wild-type (WT) mice, assessing disease severity, MG53 tissue uptake, and therapeutic effects of recombinant human MG53 (rhMG53). In vitro studies examined rhMG53s effects on NLRP3 inflammasome activation, caspase-1 cleavage, interleukin-1{beta} (IL-1{beta}) secretion, and MG53-NLRP3 interactions. ResultsMG53-/- mice showed more severe colitis with increased weight loss, higher disease activity scores, shortened colons, and greater inflammation. DSS treatment induced the accumulation of circulating MG53 in inflamed colonic tissue. rhMG53 administration ameliorated colitis severity in MG53-/- mice and dose-dependently suppressed NLRP3 inflammasome activation in vitro. MG53 interacted with NLRP3 and reduced apoptosis-associated speck-like protein containing a CARD (ASC) speck formation and NLRP3 oligomerization without affecting upstream signaling or NLRP3 stability. ConclusionMG53 is a physiological regulator of NLRP3 inflammasome activation that protects against colitis, suggesting therapeutic potential for IBD.

immunology↗

bioRxiv2026

Proteostasis sustains T cell differentiation potential and tumor-infiltrating lymphocyte function

Tumor-infiltrating lymphocytes (TIL) often fail to restrain tumor growth due to progressive differentiation to an exhausted state. In healthy tissues, tissue-resident memory T cells (TRM) maintain protection for years, and patient tumors that contain TIL with TRM features are associated with better prognosis. Proteomic and transcriptomic profiling of T cell populations identified proteostasis as a significant factor distinguishing TRM and progenitor-exhausted TIL from terminally-exhausted TIL, including loss of E3 ubiquitin ligases NEURL3, RNF149, and WSB1, with accumulation of unfolded proteins in spite of functional proteasome activity. Enforced expression of these ligases by TIL preserved stem-like TCF1+ populations and improved anti-tumor function, whereas their knockout impaired TIL and altered T cell differentiation in acute infection. Sustained ligase expression rescued accumulation of unfolded proteins in TIL and improved immunotherapy outcome in preclinical models, highlighting the critical role of proteostasis in TIL function and identifying new avenues for advancing cancer immunotherapy.

immunology↗

bioRxiv2025

Tryptophan-substitution antimicrobial peptide temporin-1CEb: in vitro and in vivo antibacterial activity against clinically isolated multidrug-resistant Klebsiella pneumoniae

Tryptophan (Trp)-substitution antimicrobial peptides (AMPs) exhibit enhanced interactions with bacterial cell membranes, potentially improving their antimicrobial efficacy. K. pneumoniae (20.59% of 2054 ICU isolates) is resistant to multiple clinically used antibiotics and presents significant treatment challenges. In the present study, three Trp-modified peptides (I4W, L12W, and I1WL5W) were generated by substituting Ile or Leu residues in temporin-1CEb, a peptide derived from frog skin, with Trp at various sites to assess their antibacterial effects and mechanisms against K. pneumoniae. Compared with L12W, both I4W and I1WL5W displayed superior antimicrobial activity and lower cytotoxicity. Mechanistic studies revealed that the AMPs exerted antibacterial and bactericidal effects through bacterial surface charge neutralization, insertion into bacterial cell membranes, increased permeability of both the inner and outer membranes, and disruption of membrane integrity. Notably, I1WL5W exhibited the most potent membrane-disrupting activity. Assessment of the impact of Trp-containing peptides on bacterial biofilms revealed that these peptides not only inhibited exopolysaccharide production and biofilm formation but also degraded preformed biofilms. A murine lung infection model was established to investigate the therapeutic efficacy of I1WL5W against MDRKP 1203-induced lung infection in mice. Compared with the control treatment, treatment with I1WL5W resulted in reduced bacterial counts and levels of IL-6 and TNF- in both the blood and lung tissues of MDRKP 1203-infected mice, and treatment with I1WL5W improved lung tissue structure. The present study provides valuable insights for designing Trp-containing peptides with potent antimicrobial properties by facilitating their penetration across bacterial membranes.

pharmacology and toxicology↗