Biology subjects

Li, B.

Publications and source records attributed to Li, B..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Single-cell lung eQTL dataset of Asian never-smokers highlights the roles of alveolar cells in lung cancer etiology

Single-cell expression quantitative trait loci (sc-eQTL) analyses are powerful in identifying context-specific susceptibility genes from genome-wide association studies (GWAS) loci. However, few studies have comprehensively investigated cells of lung cancer origin in non-European populations. Here, we built a lung sc-eQTL dataset from 129 Korean women never-smokers with epithelial cell enrichment. eQTL mapping identified 2,229 genes with an eQTL in 33 cell types, including East Asian-specific findings when compared to predominantly European datasets. Integration with single-cell chromatin accessibility data demonstrated an enrichment of cell-type specific eQTLs in cell-type matched candidate enhancers, while shared eQTLs were more frequently found near promoters. Colocalization and transcriptome-wide association study unveiled 36 susceptibility genes from 22 cell types in 22 lung cancer loci, including 10 loci not achieving genome-wide significance in prior GWAS. Around 47% of these genes were from cells of the alveoli, underscoring their importance, especially in lung adenocarcinoma (LUAD) susceptibility. Focusing on the trajectory of alveolar epithelial cell regeneration, we detected 785 cell-state-interacting QTLs, which overlapped with 28% (10) of the identified susceptibility genes. Finally, we experimentally validated East Asian-and alveolar type 2 cell-specific eQTL of TCF7L2 underlying East Asian LUAD locus, 10q25.2. Consistent with its role as a Wnt/{beta}-catenin effector, TCF7L2 displayed significant effect on lung adenocarcinoma cell growth. Our data highlighted context-specific susceptibility genes, especially from alveolar cells of lung, contributing to lung cancer etiology.

genetics↗

bioRxiv2026

Coronavirus envelope protein drives iron sensing disorder by hijacking the TAp73-FDXR axis

Iron overload is increasingly recognized as a critical contributor to coronavirus pathogenesis1, yet the underlying induction mechanisms remain unclear. Here, we uncover a fundamental pathway by which coronavirus drives IRP1 RNA-binding activity to induce iron accumulation2 via targeting the TAp73-FDXR axis. Specifically, coronavirus infection represses transcription of FDXR (encoding the key rate-limiting enzyme in host iron-sulfur cluster synthesis3), thereby impairing host iron-sulfur cluster generation to trigger the functional conversion of the cytosolic aconitase 1 (ACO1) into iron-regulatory protein 1 (IRP1)4, ultimately leading to the hosts persistently false perception of iron deficiency. We identify TAp73 as the primary transcription factor governing FDXR expression, and demonstrate that the coronavirus envelope protein (CoV-E) orchestrates TAp73 nuclear export. Subsequently, CoV-E binds TAp73 through a critical valine residue within its C-terminal PBM domain, inducing the K48-linked ubiquitination and proteasomal degradation of TAp73. Furthermore, we developed a CoV-E-targeting molecule, DPTP-FC, which blocks CoV-E-TAp73 interaction via forming steric hindrance and effectively alleviates iron accumulation and tissue damage caused by PEDV, PDCoV, and SARS-CoV-2 infection. Our study reveals the central role of the TAp73-FDXR axis in CoV-induced iron accumulation, highlighting CoV-E as an attractive antiviral target and DPTP-FC as a promising therapeutic candidate.

microbiology↗

bioRxiv2026

Isoform-resolved spatial transcriptomics on a lab-made high-density array via a single-chip NGS-TGS workflow

High-resolution spatial transcriptomics is still cost-prohibitive and dominated by short-read sequencing, limiting in situ detection of transcript structures. Here we present a low-cost, lab-made, high-density bead-in-microwell chip assembled by routine centrifuge and decoded by a tri-part combinatorial long-barcode strategy. The design provides 5.6x107 barcode combinations across 4.1x10{square} capture sites, reducing collisions while remaining tolerant to third-generation sequencing raw errors. Using a single-chip, dual-platform workflow, we split full-length cDNA for next-generation and third-generation sequencing within the same spatial coordinates. In an incompatible tomato-pepper graft, we identified interface-associated splicing reprogramming, including thousands of unannotated isoforms, enriched novel CaGRP1 isoforms, and SlPIP2 intron retention, supported by individual long-read sequences. In mouse embryos, we further demonstrate cross-species applicability by resolving unannotated Col1a2 isoforms in oligodendrocyte progenitors and spatially restricted Dalrd3 intron retention. This cost-efficient system broadens access to spatial full-length transcriptomics and may support diverse biological studies.

plant biology↗

bioRxiv2026

IgG Propels Atherosclerosis by Noncanonically Activating Macrophages

Despite being a central component of adaptive immunity and a highly abundant serum protein, the contribution of IgG to the milieu of atherosclerosis remains unappreciated. Here, we identify a pro-atherogenic role for IgG as it activates an innate immune cascade, independent of its classical antigen-neutralizing function. Analyses of human coronary artery plaques reveal a positive correlation between IgG and cardiovascular and cerebrovascular disease severity. Integrated single-cell plaque analyses localize IgG, coinciding with its recycling receptor FcRn, to pro-inflammatory and foamy macrophages. Genetic ablation of FcRn in myeloid cells prevents IgG from accumulating in mouse atherosclerotic lesions, diminishing plaque size and inflammation. Mechanistically, IgG acts as an endogenous ligand for TLR4, triggering NF-{kappa}B-NLRP3 inflammasome signaling without requiring its antigen-binding domain. Additionally, IgG accelerates macrophage foam cell formation through upregulation of downstream effector LCN2. Our work uncovers a role for previously overlooked adaptive immune molecules in the pathogenesis of atherosclerosis through a noncanonical mechanism linked with innate immunity.

immunology↗

bioRxiv2026

CHPT1-LCAT rewires lipolysis towards ferroptosis

Ferroptosis is driven by iron-dependent lipid peroxidation, yet how metabolic flux through central lipid pathways is selectively routed towards pro-ferroptotic lipid species remains unclear. Here, through an unbiased chemical-genetic screen targeting core metabolic enzymes, we identify diacylglycerol (DAG) as a licensing lipid intermediate whose pro-ferroptotic activity depends on its intracellular routing. Systematic manipulation of lipolytic flux reveals that ferroptotic vulnerability is not determined by bulk lipolytic output or downstream intermediates, but by the selective channelling of DAG into a distinct metabolic fate. Mechanistically, DAG is selectively routed through a previously unrecognized intracellular metabolic axis composed of choline phosphotransferase 1 (CHPT1) and lecithin-cholesterol acyltransferase (LCAT). We uncover an enzymatically active intracellular pool of LCAT (iLCAT) that cooperates with CHPT1 on Golgi-trans-Golgi network membranes to generate polyunsaturated cholesteryl esters that execute ferroptosis. Functionally, enforced DAG routing through this axis suppresses tumour growth via ferroptosis in vivo, whereas hepatocyte-specific inhibition of the CHPT1-iLCAT axis attenuates lipid peroxidation and disease progression in metabolic dysfunction-associated steatohepatitis. Together, these findings establish subcellular lipid routing, rather than lipid abundance per se, as a fundamental determinant of ferroptotic vulnerability.

cell biology↗

bioRxiv2026

A bacterial effector blocks SUMOylation by steric occlusion of UBC9 via arginine-GlcNAcylation

The post-translational modifier SUMO is crucial for host antimicrobial defense. Here, we discover that Salmonella employs a unique strategy to dismantle the host SUMOylation machinery. Salmonella infection robustly inhibits global SUMOylation, particularly SUMO2/3 conjugation, without altering the expression of SUMO-cycle enzymes. Genetic screening identified the T3SS-2 effector SseK1 as both necessary and sufficient for this suppression. SseK1, an arginine-GlcNAcyltransferase, directly binds and specifically modifies the SUMO E2-conjugating enzyme UBC9 at arginine 17 (R17). Structural and biophysical analyses revealed that GlcNAcylation at R17 sterically hinders UBC9s interaction with SUMO, thereby inactivating the entire SUMOylation cascade. A unique C-terminal lid domain (ARHVQ motif) in SseK1 confers substrate specificity for UBC9, representing an evolutionary innovation within Salmonella genus. Quantitative SUMOylome profiling demonstrated that SseK1-mediated UBC9 inactivation reprograms the host SUMOylation landscape, impairing the modification of key immune regulators such as MyD88, Hspa8 and destabilizing proteins like PDCD4. Consequently, this mechanism is critical for Salmonella intracellular survival and systemic virulence in mice. Our study unveils a unique bacterial strategy to dismantle the host SUMOylation machinery via precise enzymatic inactivation of its central hub.

biochemistry↗

bioRxiv2026

Reprogramming of neuronal genome function and phenotype by astrocytes

Heterotypic cell-cell interactions are critical to governing cellular physiology, disease progression, and responses to the environment and pharmacologic interventions. For example, neurons and astrocytes engage in intricate interactions that are essential for brain development and function1-3. However, the transformation of these extracellular signals into epigenomic regulation that governs cell function is poorly understood. Here, we report that weeks of co-culture between human induced pluripotent stem cell (hiPSC)-derived neurons and mouse cortical astrocytes extensively reprograms gene expression and the chromatin accessibility landscape in neurons, affecting thousands of genes and putative gene regulatory elements (REs), including many transcription factors (TFs). These genes are enriched for functions implicated in neuronal differentiation and maturation, and tend to be impacted in schizophrenia, and autosomal dominant Alzheimers disease. Through complementary CRISPR interference and activation screens, we recapitulated hundreds of astrocyte-induced transcriptional and chromatin remodeling events in mono-cultured neurons at both promoters and distal regulatory elements (REs) of TF genes. We discovered functional REs for [~]50 astrocyte-responsive TF genes, providing a map of gene regulatory network control. Astrocyte-responsive TF genes fall into groups that exert independent or counter-balancing transcriptional effects, highlighting the complex coordination of the neuronal response to astrocytes. Functional effects of specific TFs, including POU3F2 and TFAP2E, on neurite morphology and neuronal electrophysiology are consistent with transcriptional effects, demonstrating the capacity of direct epigenetic control to mimic heterotypic cellular signals. This work illuminates the regulation of neurodevelopment-and disease-relevant gene modules by neuron-astrocyte interactions, and provides a blueprint for applying modern functional genomics to uncover the links between cell microenvironment and epigenomic programming. HighlightsO_LINeuronal gene expression and chromatin accessibility landscape are profoundly remodeled by astrocytes over weeks of co-culture C_LIO_LIAstrocyte-responsive neuronal gene modules and neuron-responsive astrocytic gene modules are enriched for genes associated with schizophrenia and familial Alzheimers Disease C_LIO_LISingle-cell CRISPR interference and activation screens of astrocyte-responsive gene regulatory elements identified dozens of functional regulatory elements of TF genes in neurons C_LIO_LISingle-cell CRISPR interference and activation screens of >200 astrocyte-responsive TF genes uncovered discrete functional clusters that promote neuronal maturity or stemness C_LIO_LIAstrocyte-responsive TF genes reprogram neuronal electrophysiology and neurite morphology C_LI

genomics↗

bioRxiv2026

MetaSAG: A Tool for Multi-level Exploration and Taxonomic Analysis of Microbial Single-Amplified Genomes

Microbial single-amplified genome (SAG) sequencing technologies have elevated microbial research resolution to the single-cell level. However, neither upstream data processing nor downstream analysis has been fully developed, greatly limiting the research in strain level. Herein, we developed MetaSAG (Multi-level Exploration and Taxonomic Analysis of microbial Single-Amplified Genomes), which enables accurate and rapid taxonomic classification of microbial SAGs. MetaSAG outperforms existing method in species classification certainty, computational efficiency, and sensitivity of low abundance species identification. In addition, MetaSAG enables species-level functional analysis, as well as strain-level evolutionary analysis. With the help of MetaSAG, we discovered the parasitic relationship between phages and bacteria, identifying multiple susceptible bacteria and a broad spectrum of phages. Furthermore, we developed MetaK-Lytic (k-mer-based meta-learning framework to predict phage lytic ability) to achieve accurate prediction of phage lytic activity based on 31-mer short sequences, which is well adapted to the characteristics of incomplete SAG sequences. Overall, we offer a comprehensive integrated tool that can parse microbial SAG data from raw data to the strain level to decipher the functional ecology of microbial dark matter, with broad implications for microbial ecology and phage therapy (https://github.com/liangcheng-hrbmu/MetaSAG). Significance StatementThis work provides a comprehensive framework for high-resolution SAG data analysis. The developed pipeline improves taxonomic annotation sensitivity and speed. Strain-level tracking enables dynamic evolutionary and functional insights, while single-cell bacterial-virus network reconstruction reveals precise interaction patterns. The novel annotation-free short sequence-based MetaK-Lytic facilitates functional prediction of uncharacterized phage sequences. Integrated into the MetaSAG platform, these tools deliver a streamlined, multi-level solution for interpreting SAG data, advancing studies in microbial ecology, evolution, and virology.

microbiology↗

bioRxiv2026

Using peptide-exchange systems to interrogate peptide-specific KIR binding to HLA Class -I

The killer-cell immunoglobulin-like receptors (KIR) are a family of activating and inhibitory HLA class I (HLA-I) binding receptors expressed on natural killer (NK) cells and subsets of T cells. The KIR detect HLA-I molecules in a peptide-dependent manner, with some KIR displaying exquisite peptide-specificity. Studying peptide recognition by KIR often uses TAP-deficient cell lines expressing single HLA-I alleles, which are heterogenous and time consuming to generate. Here, we established an alternative approach using peptide-exchange technologies hitherto developed for studying T cell recognition of HLA-I. We tested two methods; dipeptide-mediated peptide exchange and open-HLA-I, HLA-I molecules consisting of heavy chain-{beta}2m disulphide bonded dimers. We combined peptide-exchange technologies with SpyTag-SpyCatcher chemistry to allow rapid detection of KIR binding via HLA-I displayed on plates or cells. We demonstrated the fidelity of this system with peptides of known KIR specificity bound to HLA-C*05:01. We then screened a peptide library to identify novel strong KIR2DS4 binding peptides presented by HLA-C*04:01. Peptide-exchanged HLA-C was functionally competent, promoting activation of KIR2DS4+ NK cells and inhibiting activation of KIR2DL1+ NK cells. Together, we show that peptide-exchangeable HLA-I molecules are ligands for KIR, presenting a flexible, efficient system for examining the peptide-sequence dependent recognition of HLA-I by KIR.

immunology↗

bioRxiv2026

Safety Signals Enable Single-Episode Active Avoidance paradigm and Expose Threat Generalization in Tuberous Sclerosis Complex

Animals must flexibly discriminate between threat and non-threat to deploy adaptive defensive strategies. We introduce a single-episode differential signaled active avoidance (DSAA) paradigm that temporally dissociates acquisition, consolidation, and retrieval of instrumental avoidance memory. Interleaving a behaviorally noncontingent neutral cue (CS-) with a threat-predictive, behaviorally contingent cue (CS+) enhanced long-term memory without altering acquisition, demonstrating that differential contingency structure selectively reinforces memory consolidation rather than influencing learning performance. Naive animals inferred contingencies within a single episode, and discrimination achieved during training predicted retrieval precision. However, discrimination operated within defined boundary conditions: overtraining or elevated threat intensity destabilized cue specificity and promoted persistent avoidance generalization. Under high-threat conditions, freezing and shuttling co-emerged as complementary defensive responses, indicating a shift from precise cue-based encoding to a generalized defensive state. Remote retrieval recruited oxytocin receptor-expressing cells in the medial prefrontal cortex and activated mTORC1-dependent translational signaling, implicating protein synthesis in maintenance of discriminative avoidance memory. In a Tuberous Sclerosis Complex model with Tsc2 haploinsufficiency in oxytocin-responsive cells, males displayed intact acquisition but generalized avoidance at both recent and remote time points, a deficit not rescued by additional training. These findings identify oxytocin-modulated translational control as a molecular gate stabilizing threat-safety discrimination and show that disruption of this axis - by excessive threat or reduced Tsc2 gene dosage - biases memory toward pathological generalization, providing a mechanistic framework for safety-learning deficits in neurodevelopmental and anxiety-related disorders.

animal behavior and cognition↗

bioRxiv2026

Sex-specific Genetic Regulatory Effects in Chickens

Sexual dimorphism is a defining vertebrate feature, yet its sex-specific molecular architecture remains poorly understood. Here we established a sex-balanced, uniformly reared chicken cohort to map this landscape, integrating individual whole-genome sequencing with 7,969 bulk and 779,380 single nucleus transcriptomes across 32 tissues from 280 birds. We identified 495,098 independent expression quantitative trait loci for 20,194 genes, including 10,937 loci modulated by cell-type composition. Notably, 340 genes were regulated by 449 loci in a sex-dependent manner, significantly enrichment in endocrine tissues like adipose and the adrenal gland. Furthermore, we fine-mapped 1,219 structural variants, demonstrating their unique roles to tissue- and sex-specific expression beyond SNPs. Ultimately, we showed the utility of these regulatory effects in elucidating the molecular basis of metabolism and complex traits in both chickens and humans. This comprehensive atlas of regulatory effects provides profound insights into the genomic and molecular basis of sexual dimorphism in vertebrates.

genomics↗

bioRxiv2026

Eubiota: Modular Agentic AI for Autonomous Discovery in the Gut Microbiome

The gut microbiome regulates many aspects of human biology, including immunity and inflammatory diseases, yet mechanistic discovery and translation remain constrained by fragmented workflows and manual hypothesis integration. Here, we present Eubiota, an open-source modular agentic framework that decomposes microbiome inquiry using specialized agents for planning, execution, verification, and grounded synthesis. Coordinated through shared memory and domain-specific tools, Eubiota employs reinforcement learning to optimize multi-turn reasoning, achieving 87.7% benchmark accuracy and outperforming GPT-5.1 by 10.4%. Across four case studies, Eubiota enabled end-to-end discovery with experimental validation. Screening nearly 2,000 bacterial genes, Eubiota identified the uvr-ruv DNA repair axis as a fitness determinant under inflammatory stress, validated using transposon mutants and IBD metagenomes. It further designed a four-strain consortium that attenuated colitis severity in mice and generated a commensal-sparing antibiotic cocktail, demonstrating its utility in addressing community-level design challenges at cellular and molecular levels. Finally, Eubiota discovered diet-associated metabolites that suppress NF-{kappa}B signaling. Together, these results establish Eubiota as a scalable, tool-grounded scientific copilot for mechanistically driven microbiome discovery.

bioinformatics↗

bioRxiv2026

Local Motion Is Sufficient for Human Body Movement Perception in High-Level Visual Cortex

Perceiving the movements of other living organisms is a fundamental ability across species. Although several cortical regions are selective for static body features, it is unclear whether these areas also encode motion cues independently of body shapes. Here, we isolated optical flow patterns from naturalistic body movements using synthesized videos that eliminate explicit body shape information. Behavioral results suggest that participants successfully recognized walking directions from the shape-free flow motion stimuli. Using ultra-high field fMRI, we found that three body-motion-related areas, fusiform gyrus (FG), lateral occipitotemporal cortex (LOTC), and posterior superior temporal sulcus (pSTS), were sensitive to both the amount and the spatiotemporal structure of flow motion. Critically, the flow motion effects were significantly correlated to voxel-wise body motion selectivity in FG and LOTC, but not to body shape selectivity in any of the ROIs. These findings identify flow motion as a distinct and behaviorally sufficient cue for body perception, which could dissociate the neural mechanism underlying motion and shape encoding in FG and LOTC.

neuroscience↗

bioRxiv2026

KRT17 stabilizes EPN1 via inhibiting SMURF1-mediated ubiquitination to modulate Wnt/β-catenin signaling output and stem-like traits in ovarian cancer

BackgroundOvarian cancer (OC) progression and chemoresistance are closely linked to dysregulated oncogenic signaling, including Wnt/{beta}-catenin pathways that contribute to cancer stem-like traits. However, the upstream mechanisms connecting cytoskeletal regulation to Wn/{beta}-catenin signaling in OC remain incompletely understood. Keratin 17 (KRT17), a type I intermediate filament protein, has been implicated in tumor progression, but its mechanistic role in OC requires clarification. MethodsGene Expression Omnibus (GEO) datasets and clinical specimens were analyzed to assess KRT17 and EPN1 expression and prognostic significance. Functional assays, xenograft models, co-immunoprecipitation, ubiquitination analyses, and rescue experiments with wild-type and ubiquitination-resistant EPN1 mutants were performed to investigate molecular mechanisms. ResultsKRT17 expression was elevated in OC tissues and correlated with poor patient survival. KRT17 depletion suppressed proliferation, migration, stem-like properties, tumor growth, and cisplatin resistance. Mechanistically, KRT17 interacted with EPN1 and weakened its association with the E3 ligase SMURF1, reducing SMURF1-mediated ubiquitination at lysine 107 and preventing proteasomal degradation. Stabilized EPN1 was associated with increased {beta}-catenin abundance and stemness-associated markers, and enhanced self-renewal capacity. ConclusionsThese findings identify a KRT17-EPN1 axis that links intermediate filament dynamics to ubiquitin-dependent regulation of EPN1 stability and Wnt/{beta}-catenin signaling outputs in ovarian cancer.

cancer biology↗

bioRxiv2026

Super-resolution single-cell spatial atlas of plant de novo regeneration

Plant de novo regeneration, a capacity absent in animals, relies on stem-cell-niche formation rather than pre-existing reservoirs. Growth hormones such as auxin and cytokinin, together with numerous genetic regulators, participate in regeneration, but the architectural principles coordinating extensive cellular reprogramming at the individual-cell scale remain elusive. Using super-resolution multimodal spatial transcriptomics to 1.16 million cells, we tracked tomato regeneration across temporal intervals from wounding to organogenesis. Datasets are available at http://www.single-cell-spatial.com.

cell biology↗

bioRxiv2026

CLM-X: A multimodal single-cell foundation model with flexible multi-way Transformer for unified scRNA-seq and scATAC-seq analysis

AO_SCPLOWBSTRACTC_SCPLOWAdvances in single-cell multimodal profiling have enabled a more systematic analysis of cellular biology, yet the rapid accumulation of large-scale, heterogeneous datasets poses substantial challenges for integrative analysis. Recently, Transformer-based cell language models (CLMs) are becoming powerful foundational tools for learning transferable cell representations from unimodal single-cell datasets. However, a unified and flexible multimodal foundation model for joint modeling of scRNA-seq and scATAC-seq datasets remains underexplored. Here, we present CLM-X, a multimodal single-cell foundation model built on multiway Transformer architecture. CLM-X employs a harmonized tokenization design together with a stage-wise masked reconstruction pretraining strategy, enabling unified modeling of RNA-only, ATAC-only, and paired RNA-ATAC input within a single Transformer-based framework. We pretrain CLM-X on million-scale unimodal and multimodal datasets, and systematically evaluate its transferability on five downstream tasks including batch correction, modality integration, cross-modal translation, cell type annotation, and perturbation prediction. Across comprehensive benchmarks on 10 datasets, CLM-X consistently outperforms existing multimodal methods and unimodal foundation models, with particularly clear advantages in RNA-ATAC cross-modal translation and genetic-perturbation-response prediction. Overall, CLM-X establishes a unified and flexible multimodal foundation model for integrative analysis of scRNA-seq and scATAC-seq datasets, advancing a more robust, comprehensive, and biological interpretable single-cell analysis beyond current multimodal fusion approaches and unimodal foundation models.

genomics↗

bioRxiv2026

Z-RNA-ZBP1 axis drives Tau-mediated neurodegeneration

Although the causes of Tau aggregates vary, once Tau aggregates are formed, their neurotoxicity significantly contributes to neuronal death and cognitive decline in tauopathies, with Alzheimers disease (AD) being the most well-known example. Despite its central pathogenic role, however, effective therapeutic strategies targeting neurotoxicity of Tau remain poor. Here we demonstrate the pathogenic role of neuronal cell death in Tau-related neurodegeneration. Tau-expressing neurons undergo cell death through Z-DNA-binding protein 1 (ZBP1) activation triggered by endogenous Z-RNAs. These Z-RNAs are derived from reactivated transposable elements (TEs) that are typically silenced within heterochromatin. Tau aggregates show a strong affinity for H3K9me3-modified chromatin, effectively sequestering these epigenetic marks from Heterochromatin Protein 1 (HP1), thereby disrupting the condensation of constitutive heterochromatin. Clinically, an inverse correlation between ZBP1 expression levels in excitatory neurons and cognitive performance in AD patients was observed. Importantly, Zbp1 haploinsufficiency significantly ameliorated cognitive deficits in aged Tau-transgenic mice (24-month-old), highlighting the therapeutic potential of ZBP1 inhibition to strive against neurodegeneration in tauopathies.

neuroscience↗

bioRxiv2026

Salmonella exploits metal-responsive UMPylation to enable intracellular biphasic growth and antibiotic tolerance

Salmonella develops profound antibiotic tolerance during in vivo infection, directly contributing to antimicrobial treatment failure. Although phenotypic heterogeneity in bacterial growth rates underlies this tolerance, the exact mechanisms remain elusive. Here, we reveal that Salmonella exhibits a biphasic growth pattern within macrophages, with initial antibiotic levels modulating lag phase duration. Crucially, this growth plasticity is orchestrated by metal ion homeostasis and a reversible PTM-mediated protein phase transitions. Mechanistically, under stress conditions, enhanced Mn2+ uptake activates the UMPylator YdiU, which modifies critical translational machinery components such as elongation factor TufA. These modifications induce protein aggregation, leading to translational arrest and growth stasis. Conversely, upon stress alleviation, Salmonella accumulates Mg2+ and effluxes Mn2+, then the de-UMPylase YdiV is activated, which resolves protein aggregates to enable rapid bacterial resuscitation and proliferation. This metal-responsive proteostatic switch represents an evolutionarily conserved strategy for bacterial stress adaptation, with broad implications for combating antimicrobial tolerance. SIGNIFICANCE STATEMENTAntibiotic tolerance, a key cause of treatment failure in chronic infections, is often linked to bacterial phenotypic heterogeneity, yet the underlying regulatory mechanisms remain largely understood. This study uncovers a fundamental survival strategy employed by intracellular pathogen Salmonella, where host-derived manganese acts as a critical signal to induce a reversible, dormant state. We demonstrate that stress-induced Mn2+ influx activates widespread protein UMPylation, which functions as a molecular glue to drive the aggregation of essential proteins, thereby halting bacterial growth and conferring antibiotic tolerance. Crucially, this state is reversible upon stress relief through Mn2+ efflux and subsequent de-UMPylation, enabling rapid bacterial resuscitation. As an evolutionarily conserved mechanism of adaptive tolerance, this metal-ion-responsive switch, mediated by reversible protein UMPylation, identifies a key target for developing therapeutics against persistent bacterial infections.

microbiology↗