Biology subjects

Lu, M.

Publications and source records attributed to Lu, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Critical roles of MCM8 in meiotic recombination during mouse spermatogenesis

Meiotic DNA double-strand break (DSB) formation and repair by homologous recombination is crucial for ensuring proper chromosome segregation. In mice, the mini-chromosome maintenance family protein, MCM8, has been proposed to function in meiotic recombination and its loss leads to infertility, but the underlying mechanisms are poorly understood. Here we used cytological and genomic assays to infer the role of MCM8 during meiotic recombination in mouse spermatocytes. We show that MCM8-deficient spermatocytes exhibit increased levels of SPO11-dependent DSBs at recombination hotspots during early prophase. DSBs are resected normally and accumulate strand-exchange proteins. However, downstream recombination intermediates are barely detected and recombination intermediate-associated MutSgamma foci do not form efficiently. Consistent with a role in early recombination intermediate processing, MCM8 binds to displacement loop (D-loop) structures in vitro. We propose that MCM8 controls meiotic recombination in at least two ways. MCM8 participates in regulating meiotic DSB number. Further, MCM8 plays a role in the formation and/or stability of post-resection recombination intermediates, steps that are critical for DSB repair via recombination and for efficient synapsis of homologous chromosomes during mouse meiosis.

molecular biology↗

bioRxiv2026

A postnatal human lung developmental atlas reveals windows of genetic vulnerability to chronic lung disease

At birth, the lungs undergo an abrupt physiologic change, as the function of gas exchange transitions from the placenta to the lung. Subsequent postnatal development of the lungs is marked by a rapid and profound increase in the growth of the distal airways and alveolar gas exchange compartment. Insults during this period increase the risk of developing lung disease later in life, though how early-life events affect adult disease onset remains unclear. We generated a single-cell atlas of postnatal human lung development from birth through adulthood and mapped temporally regulated gene expression changes in each cell lineage. Using this atlas, we identified disease risk-associated genes with developmentally regulated expression. These analyses reveal cell type-specific and temporally restricted expression of genes associated with adult lung disease risk, including COPD. Heritability enrichment analysis demonstrated that COPD genetic risk is enriched in genes active during early postnatal endothelial development, linking early-life vascular maturation to adult disease susceptibility. These findings characterize the early window of susceptibility for adult chronic lung diseases and establish a framework to guide mechanistic studies of disease-associated genes.

developmental biology↗

bioRxiv2026

The m6A Landscapes on the RNA of Mumps Virus and the Host 3 Modulate the Viral Replication and Antiviral Innate Immunity

N6-methyladenosine (m6A) is the most prevalent internal modification in eukaryotic mRNA and has emerged as a critical regulator of RNA virus infection. However, its role in the mumps virus (MuV), a non-segmented negative-strand (NNS) RNA virus, remains undefined. Here, we comprehensively characterize the m6A epitranscriptome of MuV JL2 strain and its functional impact on viral replication and host innate immunity. Using single-base resolution GLORI-seq, we identified abundant m6A modifications on MuV genomic, antigenomic and messenger RNAs, with uneven distribution and non-canonical motif enrichment. Genetic depletion of METTL3 enhanced viral replication by facilitating RNA synthesis and nucleocapsid encapsidation in Vero-E6 cells. In epithelial A549 and monocytoid THP1-iDC cells, MuV infection triggered robust type I/III interferon and proinflammatory responses by activating multiple pattern recognition receptors in a m6A-dependent manner and induced incomplete iDC maturation characterized by downregulated HLA class II; however, the latter molecule can be partially restored by METTL3-knockdown. The MuV infection reshaped the host m6A landscape with a positive correlation between m6A enrichment and transcripts enhancement of numerous innate immune genes in a cell type-specific manner. Functional analyses revealed that host m6A machinery modulates antiviral signaling, which varies between viral infection and viral RNA-transfection due to the infection-induced host m6A machinery fluctuation. Collectively, our findings demonstrate that m6A serves as a bidirectional regulator during MuV infection, simultaneously constraining viral replication and modulating host immune recognition, thereby highlighting RNA methylation as a pivotal determinant of MuV pathogenesis and a potential target for optimized immunogenicity. ImportanceN6-methyladenosine (m6A) modification has emerged as a key regulator of RNA virus infection, yet its role in mumps virus (MuV) remains undefined. Here we map the single-base resolution m6A landscape of a recombinant MuV and demonstrate that viral m6A restricts genome encapsidation and replication while attenuating innate immune sensing. MuV infection extensively remodels host m6A profiles in epithelial and dendritic cells, preferentially enhancing methylation of innate immune transcripts. Strikingly, m6A-deficient MuV RNA exhibits increased affinity for RIG-I-like and Toll-like receptors, eliciting stronger interferon and proinflammatory responses. Our findings identify m6A as a bidirectional regulator of MuV replication and immunity and suggest an epitranscriptomic strategy to optimize live-attenuated vaccine design.

immunology↗

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

Chromosomal instability and chromosome 17p loss drive convergentNDE1 synthetic lethality in metastatic cancer cells

Recent studies have identified recurrent features of metastatic cancer cells such as their increased chromosomal instability (CIN) and frequent loss of the short arm of chromosome 17 (Chr17p). However, it remains unclear whether these features induce synthetic lethal vulnerabilities that can be used to specifically target metastatic disease. Using whole-genome CRISPR/Cas9 loss-of-function screens performed in matched primary and CIN-high brain-metastatic tumor models, we discovered that brain-metastatic cells exhibit increased sensitivity to the loss of diverse regulators of chromosome segregation. Knockout of one such regulator, NDE1, selectively inhibited the growth of brain-metastatic models in vitro and in vivo, an effect driven by the loss of STAG2 and consequent induction of CIN. Surprisingly, dependence on NDE1 was also highly correlated with loss of Chr17p across hundreds of cancer cell lines in DepMap, the result of losing the NDE1 paralog NDEL1, which resides at this locus. CIN and Chr17p loss are thus independently sufficient to drive NDE1 dependence in brain-metastatic cells, and the presence of both features increases NDE1 dependence additively. These findings demonstrate that metastasis evolution endows cancer cells with specific vulnerabilities, including one that is driven by two recurrently altered molecular features of metastatic disease.

cancer biology↗

bioRxiv2026

Single Plaque Proteomics Reveals the Composition and Dynamics of the Amyloid Microenvironment in Alzheimer's Disease

Alzheimers disease (AD) is characterized by amyloid plaques that form complex microenvironments in the brain. However, the molecular composition of these plaques and their temporal regulation are not well defined. Here, we developed a sensitive workflow for quantitative proteomic profiling of single plaques using refined laser capture microdissection and data-independent acquisition mass spectrometry (LCM-DIA-MS). From >200 plaques and control regions in AD mouse models (5xFAD and APP-KI) and human brains, we quantified >7,000 proteins, revealing stage-dependent, cell-type-related remodeling of the amyloid proteome (amyloidome). Temporal profiling uncovered early immune and lysosomal activation followed by engagement of RNA processing and synaptic pathways. Cross-model and cross-species analyses determined a conserved amyloidome including APOE, MDK, PTN, and HTRA1, validated by co-localization in imaging analysis. Network analysis highlighted modules in lipid transport, vesicle organization, and autophagy. These findings establish amyloid plaques as conserved, dynamic multicellular hubs that link amyloid accumulation to downstream cellular events.

neuroscience↗

bioRxiv2026

Polygenic and redundant architectures of climate-adaptive traits may complicate genomic predictions of maladaptation

SignificanceUnderstanding the genetic basis of local adaptation is an important step to predict species responses to climate change. Current predictions of maladaptation to climate in trees, however, rely mostly on genotype-environment associations, which overlooks the complexity of genetic architectures underpinning climate-adaptive traits. Based on genotype-phenotype associations, we unveil key aspects of the polygenic architecture of drought tolerance and cold hardiness in two lineages of a widespread conifer. Our results suggest that predictions based solely on climate-associated alleles may mischaracterize maladaptation to future climates due to mismatches between the distribution of climate-associated alleles and alleles contributing to adaptive traits. We also show that cold hardiness and drought tolerance evolved largely independently in the two lineages, and with little pleiotropy between traits. Understanding the genetic architecture of climate-adaptive traits can help predict responses to climate change and inform management strategies that mitigate the effects of future climates. By characterizing the genetic basis of adaptation to spatially varying climate conditions, models can predict response to temporal change in climate by extrapolating from spatial patterns of variation. However, such methods are predicated upon a simple genetic basis, with a linear relationship between allele frequency, phenotype, and environment. Here, we explore the nature of the mapping between genotype, phenotype, and climate adaptation in Douglas-fir, an important North American conifer. Using two large common garden experiments combined with exome sequencing and case-control genome-wide association tests, we found that drought tolerance and cold hardiness in two Douglas-fir varieties (Pseudotsuga menziesii var. menziesii and var. glauca) are highly polygenic with little pleiotropy between the two traits. The two varieties showed little repeated evolution in the genetic basis of drought tolerance and none for cold hardiness. Allelic clines were observed along geographic and climatic gradients across 74 natural populations, but their direction of effect was often inconsistent with phenotypic clines. Our findings reveal that the genomic variation underlying climate-adaptive traits is remarkably complex, with redundancy likely playing a key role in the evolution of the divergent polygenetic architectures of abiotic stress tolerance. This suggests that predicting maladaptation to climate based solely on climate-associated alleles may misrepresent future adaptive responses. Genomic predictions and management practices should focus on individual lineages and consider the particularities of the genetic architecture of climate-adaptive traits.

evolutionary biology↗

bioRxiv2026

Distinct allosteric remodeling of HIV-1 Env dynamics on virions by gp41-directed antibodies reveals two modes of neutralization

HIV-1 envelope glycoprotein (Env), a gp120-gp41 trimer, undergoes coordinated conformational changes that drive membrane fusion and allow immune evasion by transiently concealing neutralization-sensitive epitopes. Most broadly neutralizing antibodies (bNAbs) target gp120, whereas a distinct subset recognizes conserved gp41 regions, such as the fusion peptide and the membrane-proximal external region; however, their impact on Env dynamics and associated neutralization mechanisms remains unclear. Using bioorthogonal tagging for single-molecule FRET, we monitored real-time bNAb-induced conformational sampling of Env on intact virions. Most gp41-directed bNAbs allosterically stabilized the prefusion-closed (PC) state, whereas the bivalent 10E8.4/iMab favored both PC and CD4-bound open (predominant) states. Antibodies redistributed the conformational populations of Env with modest kinetic effects, preserving the sequential transition pathway. These findings reveal two modes of neutralization for gp41-directed antibodies: fixing the prefusion-closed conformation and opening it, in both cases via long-range allosteric control of Env dynamics.

microbiology↗

bioRxiv2026

Inositol hexakisphosphate Functions as a Cofactor and Modulator of ADAR1 Activity

Adenosine-to-inosine (A-to-I) RNA editing by ADAR1 is a key post-transcriptional modification, and mutations in ADAR1 lead to Aicardi-Goutieres syndrome (AGS), an autoimmune disorder. Despite its biological and clinical relevance, the regulation of ADAR1 activity remains incompletely understood. Using a combination of biochemical approaches, inositol-pentakisphosphate 2-kinase (IPPK)-knockout cells, molecular dynamics simulations, and a cell-permeable inositol hexakisphosphate (IP6) prodrug (Pro-IP6), we demonstrate that IP6 depletion drastically reduces global RNA editing, while supplementation with Pro-IP6 restores and even enhances editing levels. Furthermore, we identify the C6-phosphate of IP6 as a critical determinant of ADAR1 catalytic efficiency, functioning within a hydrogen-bonding network that indirectly coordinates a Zn{superscript 2}-ion. Finally, we show that the AGS-associated ADAR1 mutation N907S impairs RNA editing activity, most likely by altering the hydrogen-bond interaction network linking IP6 to the ADAR1 catalytic center. Together, these findings identify IP6 as an essential cofactor and regulator of ADAR1 activity and highlight cofactor availability and interaction networks as strategies for therapeutically modulating RNA editing.

molecular biology↗

bioRxiv2026

DIA-based quantitative proteomics reveal the protective effects of quercetin against atopic dermatitis via attenuating inflammation and modulating immune response

Atopic dermatitis is a common inflammatory skin disorder characterised by recurrent eczematous lesions and intense itch. Quercetin is a naturally occurring flavonoid, exhibits antioxidant and anti-inflammatory properties. Previous studies have indicated its beneficial role in managing atopic dermatitis (AD); however, the precise underlying mechanism remains unclear. This study aimed to investigate the protective effects of quercetin against AD and to elucidate its potential mechanisms. We demonstrated that quercetin effectively suppressed the overexpression of pro-inflammatory effector factors--including interleukin (IL)-1{beta}, thymic stromal lymphopoietin (TSLP) and chemokine (C-X-C motif) ligand 1/10/11 (CXCL1/10/11)--in immortalized human keratinocytes (HaCaT) stimulated by TNF-/IFN-{gamma}. Proteomic analysis revealed 88 differentially expressed proteins, suggesting that quercetins therapeutic action involves multiple pathways. Notably, the NOD-like receptor signaling pathway was identified as a key factor. The key proteins related to this pathway including inhibitor of nuclear factor kappa B kinase epsilon (IKBKE), indoleamine 2,3-dioxygenase 1 (IDO1) and chemokine (C-X-C motif) ligand 9 (CXCL9) showed a significant decrease in expression levels after quercetin treatment. Collectively, these results demonstrate that quercetin alleviates AD symptoms by attenuating inflammatory responses, likely through inhibition of the NOD-like receptor signaling pathway.

pharmacology and toxicology↗

bioRxiv2025

Carbon bias from grassy tree misclassification: revealing forest structural heterogeneity by integrating GEDI and Sentinel-2

Tropical forests store roughly half of terrestrial carbon, yet carbon estimates in regenerating and disturbed forests remain highly uncertain. A major source of bias is the prevalence of fast-growing, canopy-forming monocots--such as bamboo, palms, and bananas--that are often misclassified as trees. These "grassy trees" achieve canopy dominance but lack secondary growth, violating woody allometries used in most biomass models. Although NASAs GEDI mission has transformed large-scale biomass mapping with spaceborne LiDAR, its products rely on coarse plant functional types (PFTs), causing grassy-tree-dominated canopies to be absorbed into evergreen broadleaf tree (EBT) classes. Using a texture-based Sentinel-2 classifier, we isolated bamboo-dominated forests within GEDI EBT products in Xishuangbanna, China. GEDI observations show that bamboo canopies are structurally distinct from tree-dominated forests and lead to systematic carbon overestimation of 20-44 Mg C ha-{superscript 1} relative to empirical benchmarks. Our framework improves carbon accounting in structurally heterogeneous forests while remaining adaptable for place-based management.

ecology↗

bioRxiv2025

Building dynamical models of multi-step state transitions from single cell gene expression trajectories

Multi-step cell state transitions occur across biological processes, such as development and disease progression, yet the underlying gene regulation remains unclear. We introduce NetDes, a computational systems-biology method that infers core transcription factor (TF) regulatory networks and builds ODE-based dynamical models from single-cell gene expression trajectories. In benchmarks on synthetic trajectories with decoys and BEELINE scRNA-seq datasets, NetDes identifies regulatory interactions competitively with existing methods, and reconstructs a simulated cell-fate circuit. We applied it to time-series scRNA-seq data of iPSC-to-definitive-endoderm differentiation, epithelial-mesenchymal transition, erythropoiesis, and dendritic cell differentiation. NetDes has advantages over existing approaches in reconstructing a minimal network with a single model that reproduces observed expression dynamics and captures sequential state transitions. Network simulations predict TFs and their combinations driving each transition, recovering known master regulators, while network coarse-graining reveals the circuit logic of iPSC-to-DE differentiation. NetDes provides a general framework for mechanistic modeling of complex cell state transitions.

systems biology↗

bioRxiv2025

Structure-informed evolutionary analysis of the meiotic recombination machinery

Despite being essential for fertility, many proteins involved in meiotic homologous recombination have diverged rapidly. The evolutionary forces driving this divergence remain mostly unknown, in part because of challenges in accounting for the interplay of sequence changes with constraints imposed by proteins structures and physiological roles. Here, we explore strategies to more sensitively detect signatures of positive or relaxed selection by integrating evolutionary analyses with structural and functional information, using meiotic recombination proteins in four taxa--primates, rodents, birds and budding yeasts. By mapping selection rate estimates onto predicted protein structures, we characterized protein regions likely to have experienced positive selection. We further identified subtle sequence variation within protein domains that are well conserved generally because of structural constraints. To detect sequence variation masked by these constraints, we analyzed selection at structurally matched residues, comparing homologs across different lineages as well as between meiosis-specific and generalist paralogs. These approaches identified lineage- and paralog-restricted enrichment of non-synonymous substitutions that may indicate loss of functional constraints and/or adaptive innovation. Finally, we used cross-species complementation experiments in Saccharomyces cerevisiae to show that sequence variation in the pro-crossover factor MSH4 modulates recombination proficiency. We suggest that evolutionary plasticity per se is a key conserved characteristic of the meiotic recombination machinery. More generally, our approach provides a mechanistic framework to analyze protein evolution.

evolutionary biology↗

bioRxiv2025

Causal Modeling Reveals Cell-Cell Communication Dynamics in the Tumor Microenvironment During Anti-PD-1 Therapy in Breast Cancer Patients

BackgroundImmune checkpoint blockade (ICB) targeting PD-1/PD-L1 plays a crucial role in breast cancer treatment. Despite clinical success, how ICB reshapes the tumor microenvironment (TME) to enhance anti-tumor activity remains unclear. Anti-PD-1 therapy alters TME cells beyond PD-1+ T cells, with extensive cell-cell communication (CCC) playing a key role. Understanding the dynamic CCC changes upon anti-PD-1 treatment can illuminate ICB mechanisms of action and TME dynamics. MethodsWe analyzed single-cell RNA-seq data from 31 breast cancer patients before and after anti-PD-1 (pembrolizumab) treatment (Bassez et al., 2021). We identified differentially expressed genes (DEGs) induced by treatment in major cell types. We then applied an instrumental variable approach to uncover causal relationships between T-cell and non-T-cell DEGs. We further mapped ligand-receptor interactions mediating signal transduction between cells and constructed a CCC network from T to non-T cells. ResultsAnti-PD-1 therapy induced widespread transcriptional changes across multiple cell populations. Key pathways modulated in T cells included NF-{kappa}B, interferon-{gamma}, and interleukin signaling. CD4+ and CD8+ exhausted T cells engaged in distinct ligand-receptor interactions with tumor-associated macrophages (TAMs) and other types of cells, reshaping the TME. Our results indicated CD4+ exhausted T cells activated M1-like TAMs via TNF-TNFRSF1A and TNFSF14-LTBR, while CD8+ exhausted T cells engaged M1-like TAMs through ICAM1-ITGAL/ITGB2 and CCL8-CCR2, promoting anti-tumor immunity. Conversely, immunosuppressive interactions were also observed, such as TNF-TNFRSF1B (TNFR2) and TNFSF14-TNFRSF14 (HVEM) from CD4 T cells, as well as CSF1-CSF1R and RPS19-C5AR1 from CD8 T cells, which likely promote M2-like tumor-associated macrophage (TAM) polarization and contribute to pro-tumor immune regulation and resistance to therapy. Notably, key receptors in the causal CCC networks, such as C5AR1, TNFR2, and CSF1R, emerged as potential targets to enhance anti-PD-1 efficacy. ConclusionsThese findings elucidate TME remodeling during anti-PD-1 therapy and underscore the pivotal role of CCC in treatment response. Our study identifies critical communication networks that may be biomarkers for immunotherapy responsiveness and highlights novel therapeutic targets, including C5AR1 and HVEM. Furthermore, our application of causal inference methodologies provides a robust framework for dissecting CCC mechanisms in immunotherapy.

bioinformatics↗

bioRxiv2025

A co-evolved peptide-GPCR system senses host entry to drive fungal infection

A successful infection requires pathogens to recognize the specific host environment in order to reprogram their physiology accordingly. One major way in which eukaryotic cells sense their surroundings is via G-Protein Coupled Receptors (GPCRs), which share a seven-transmembrane architecture and G-protein-mediated downstream signaling. While mammalian GPCRs are well-characterized and represent important drug targets, their fungal counterparts remain poorly understood. In the corn pathogen Ustilago maydis, we now uncover a GPCR-based mechanism that allows the fungus to scout the host environment to sense whether it has entered into the plant tissue. During infection, the fungus secretes the protein Pit2, which is cleaved by host apoplastic-cysteine proteases, releasing a peptide ligand hidden within Pit2. This ligand activates the fungal GPCR Gpe1 strongly promoting fungal proliferation after initial host penetration. Comparative analyses reveal conservation of the Gpe1/Pit2 system, with co-evolutionary signatures preserving receptor-ligand specificity. Furthermore, this GPCR system recognizing hidden peptide ligands shows conceptual similarities to the fungal pheromone mating system, without sharing sequence similarity. Our findings reveal a co-evolved mechanism between fungus and host that encodes environmental context into a protein scaffold, establishing a novel paradigm for host-dependent signaling with implications for inter-organismic communication.

microbiology↗

bioRxiv2025

A Multi-Layered Atlas of Spatial Regulatory Programs and Therapeutic Vulnerabilities in Glioblastoma

Glioblastoma (GBM) is marked by profound spatial heterogeneity. This complexity fuels tumor progression and therapy resistance. Although recent spatial transcriptomics (ST) studies have defined transcriptional niches, or metaprograms, the systems level regulatory logic linking upstream signaling, transcriptional programs, and therapeutic vulnerabilities remains unresolved. Here, we introduce an integrated, multi layered framework that unifies transcription factor and pathway activity inference (STAN and SPAN) with ligand/receptor and drug target mapping, thereby constructing a systems-level regulatory atlas of GBM across 26 tumors. This atlas uncovers spatial niches organized around transcriptional hubs and signaling programs, including hypoxic mesenchymal regions coordinated by HIF1A and SOX2 with mTORC1 signaling, macrophage rich areas driven by STAT3 mediated immune modulation, and astrocyte-like states shaped by lipid metabolic regulators such as SREBF2. By coupling this regulatory atlas to drug target predictions, we identify niche specific therapeutic vulnerabilities, such as VEGF blockade in HIF1A high regions and MAO-B inhibition in mesenchymal states. Finally, we provide an open, interactive web resource to make these data broadly accessible. This work provides a generalizable blueprint for linking spatial regulation to therapeutic hypotheses across diverse human diseases.

bioinformatics↗

bioRxiv2025

PD-1 signaling is essential for the early accumulation of HBV-specific CD8+ T cells during HBV infection

Background & AimsProgrammed cell death Protein 1(PD-1) is one of the key inhibitory receptors that regulates CD8 T cell exhaustion during chronic viral infection. However, the role of PD-1 in modulating effector T cell differentiation and function during early phase of hepatitis B virus (HBV) infection remains poorly defined. MethodsUsing adoptive transfer of wild-type or PD-1 KO HBV-specific TCR transgenic (C93-TCRtg) CD8 T cells, flow cytometry, and transcriptome sequencing, we systematically profiled early PD-1 dynamics in splenic and intrahepatic T cells and evaluated how PD-1 deficiency shapes anti-HBV T cell responses in acute self-resolving (AR) and chronic (CH) HBV mouse models. ResultsAcute HBV infection induced sustained PD-1 upregulation on intrahepatic/splenic CD8 T cells, which predominantly exhibited an effector phenotype. PD-1 cells displayed enhanced proliferation, cytotoxicity, and effector cytokine production compared to PD-1- counterparts. Adoptive transfer of PD-1 KO C93-TCRtg CD8 T cells resulted in significantly impaired early expansion in both spleen and liver during acute infection, accompanied by reduced granzyme B expression while maintaining IFN-{gamma}, TNF-, or IL-2 production. Transcriptomic analysis revealed that PD-1 deficiency was associated with the upregulation of apoptosis gene signatures. In chronic HBV infection, PD-1 KO cells failed to expand long-term and exhibited exacerbated exhaustion evidenced by a loss of IFN-{gamma} production. ConclusionsPD-1 is essential for the early expansion and survival of HBV-specific CD8 T cells during acute infection and does not suppress their effector cytokine function. Its absence impairs proliferation and promotes exhaustion of HBV-specific CD8 T cell in chronic infections. Impact and implicationsOur study redefines PD-1s role in acute HBV infection. Rather than merely constraining effector function, PD-1 is essential for the early expansion and survival of HBV-specific CD8+ T cells, acting as a safeguard against activation-induced apoptosis. The context-dependent functions position PD-1 as a critical rheostat calibrating the magnitude and quality of the antiviral CD8+ T cell response, with significant implications for immunotherapeutic strategies targeting this pathway in hepatitis B.

immunology↗

bioRxiv2025

The anti-phage mechanism of a widespread trypsin-MBL module

Protease mediate activation of immune effectors is a conserved mechanism across life. This study identified a widespread and co-evolving trypsin-MBL module as a core effector in diverse bacterial immune systems (e.g., Hachiman, Argonaute, AVAST), protecting host via abortive infection. Focusing on Hachiman-trypsin-MBL, we demonstrated that, the protease activity of trypsin*HamAB is inhibited in the presence of ATP and MBL is an autoinhibited DNase with two inserted loops blocking the catalytic pocket. Upon infection, the HamB helicase senses invading nucleic acids and catalyzes the hydrolysis of ATP, activating the associated trypsin-like protease that cleaves specifically at two non-canonical KSS motif of MBL and releases its DNase activity. Cryo-EM structures of activated trypsin*HamAB bound with DNA reveal DNA binding and ATP hydrolysis lead to the release of the trypsin-like domain, enabling activation. Our work provides a comprehensive understanding on the mechanism of widely distributed trypsin-MBL module, wherein proteolytic activation of a toxic nuclease enables robust bacterial immunity while preventing self-toxicity through multi-layered control.

biochemistry↗