Biology subjects

Zeng, Q.

Publications and source records attributed to Zeng, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

Rotavirus NSP1 activates human NLRP1 inflammasome

While inflammasomes detect and defend against pathogens, the precise mechanisms by which enteric viruses trigger these complexes, and the specific viral components involved remain incompletely understood. In this study, we demonstrate that rotavirus infection robustly induced human NLRP1 inflammasome activation via p38 mitogen-activated protein kinase (MAPK)-dependent and -independent pathways. Utilizing cell lines reconstituted with NLRP1 signaling and reverse genetics-rescued recombinant rotaviruses, we identified non-structural protein 1 (NSP1), a well-characterized viral antagonist of host interferon signaling, as an activator of the NLRP1 inflammasome in the absence of double-stranded RNA. Domain mapping analysis revealed that the C-terminus of NSP1 but not the C-terminal IRF3-binding site was essential for triggering inflammasome activation. Mechanistically, we show that NSP1 induced the proteasomal degradation of NLRP1 to elicit its activation, a process dependent on host neddylation pathways and the Cullin-3/Elongin B/C ubiquitin ligase complex. Together, these findings suggest that RV engages parallel NLRP1 surveillance pathways, including a p38-dependent response to infection, and a novel NSP1-dependent pathway involving the ubiquitin-proteosome system, where a viral strategy aimed at host protein degradation inadvertently trips the human NLRP1 inflammasome wire.

microbiology↗

bioRxiv2026

Reinforcement learning with evolutionary priors unlocks multi-site enzyme optimization from sparse experimental feedback

Industrial enzymes underpin sustainable manufacturing, yet natural proteins rarely combine the activity, robustness and application compatibility required for practical use. Engineering such properties requires identifying beneficial combinations of interacting mutations within vast sequence spaces that are too large to search exhaustively and too sparsely sampled to model reliably. Here we introduce AlphaVariant, a reinforcement-learning (RL) framework that couples a generative evolutionary prior with iteratively updated low-N fitness models to enable feedback-driven search of large combinatorial protein sequence spaces. Across six experimentally measured protein fitness landscapes, AlphaVariant ranked first on the three large, non-enumerable multi-site landscapes. In two successive rounds of savinase activity optimization, AlphaVariant-designed libraries yielded 75.4% and 83.8% activity-improved variants among experimentally characterized candidates even as the accessible mutation space expanded from 25 to 67 positions. The search identified beneficial mutation combinations involving up to 17 structurally dispersed sites and produced a variant with 7.1-fold higher activity than wild type after only two design-test cycles. We then extended AlphaVariant to jointly optimize activity, thermostability and a patent-informed constraint for intellectual-property freedom. This multi-objective search yielded variants that outperformed the commercial protease Uno 100 L in both biochemical assays and application-relevant detergent washing tests. These results demonstrate that generative RL can efficiently navigate vast protein fitness landscapes, progressively incorporate multiple engineering objectives and convert sparse experimental feedback into enzyme variants with industrially relevant performance, effectively resolving the limits of biocatalyst engineering.

bioinformatics↗

bioRxiv2026

Assessing fish biodiversity and community structure in the Ganjiang River using eDNA metabarcoding

Hydropower development has emerged as a major driver of global environmental change, causing significant ecological damage to freshwater ecosystems and threatening aquatic biodiversity. However, the impact of cascade dams on fish communities in large river systems remains poorly understood, particularly in biodiversity hotspots such as China. Here, we used environmental DNA (eDNA) metabarcoding to assess the spatiotemporal patterns of fish diversity and community structure in the Ganjiang River, the largest tributary of the Yangtze River, in relation to cascade hydropower development. We collected water samples from 19 sites along the main stem and major tributaries in both wet and dry seasons, and analyzed the eDNA data using high-throughput sequencing and advanced bioinformatics pipelines. Our results revealed significant seasonal and spatial variations in fish diversity and community composition, with lower species richness and distinct assemblages in the impounded sections upstream of the dams compared to the downstream reaches. The fish communities were strongly influenced by environmental factors such as water temperature, pH, dissolved oxygen, and nutrients, which exhibited complex interactions with dam operation and land use practices. Spatial scale analyses further indicated that the impact of dams on fish diversity was most pronounced at the local scale, but also detectable at the regional scale. Our findings provide novel insights into the ecological consequences of cascade hydro-power development on fish communities and highlight the importance of considering spatial scales and environmental heterogeneity in assessing the impacts of human activities on freshwater biodiversity. Our study demonstrates the power of eDNA metabarcoding as a cost-effective and non-invasive tool for biodiversity assessment and conservation planning in large river systems facing multiple stressors and knowledge gaps.

ecology↗

bioRxiv2026

Liriodendrin Targets PFKFB3 to Suppress Inflammatory Phenotypic Transition and Vascular Remodeling in Pulmonary Hypertension

BackgroundPulmonary hypertension (PH) involves progressive vascular remodeling and perivascular inflammation. Despite modest clinical improvements with current therapies, their limited ability to reverse remodeling or restore immune homeostasis highlights the need for novel agents. Liriodendrin (Lidd), derived from Sargentodoxae caulis, exhibits anti-inflammatory and antiproliferative activities, but its efficacy and molecular targets in PH are unknown. MethodsTwo well-established PH animal models - the SU5416/hypoxia (SuHx) mice model and monocrotaline (MCT)-induced rat model - were employed for in vivo assessment of Lidd conducted pharmacological effects. Primary human pulmonary artery smooth muscle cells (hPASMCs) were utilized for mechanistic investigations. RNA-sequencing (RNA-seq) analysis was conducted to identify potential signaling pathways modulated by Lidd treatment. The direct molecular target of Lidd was determined through integrated application of drug affinity responsive target stability (DARTS) assay coupled with western blot validation. To delineate histone lactylation-mediated transcriptional regulation, we combined Cleavage Under Targets and Tagmentation (CUT&Tag) sequencing data analysis followed by chromatin immunoprecipitation quantitative PCR (ChIP-qPCR) verification. Genetic validation was achieved using PFKFB3-deficient murine models to verify the specificity of Lidd-mediated pharmacological actions. ResultsLidd administration attenuated pulmonary vascular remodeling, perivascular macrophage infiltration and PH progression in both SuHx and MCT models. Transcriptomic profiling of Lidd-treated hPASMCs revealed predominant enrichment of downregulated genes in inflammatory and cytokine-associated pathways. Mechanistically, Lidd directly bound PFKFB3 and enhanced its interaction with FZR1, promoting PFKFB3 ubiquitination and degradation, which reduced glycolysis-driven lactate and consequent histone lactylation. This, in turn, diminished transcriptional activation of proliferative and inflammatory mediators, including CCND1, TNC, and CCL2. Notably, exogenous lactate supplementation or endogenous lactate accumulation restored histone lactylation and paradoxically potentiated Lidds inhibitory effects on PASMC proliferation and migration, whereas p300 inhibition abrogated these lactate-mediated effects. Importantly, Lidd failed to confer additional protection in PFKFB3-deficient mice, confirming PFKFB3 as the primary target mediating its therapeutic action. ConclusionOur findings reveal that Lidd selectively targets the PFKFB3-mediated glycolytic-epigenetic axis to suppress PASMC phenotypic transformation and pulmonary vascular remodeling, positioning it as a promising therapeutic candidate for PH.

physiology↗

bioRxiv2026

BaiZe: A Multi-View Dynamic Framework for Simulating and Interpreting Cellular Responses Across Perturbation Contexts

Accurately predicting how cells respond to perturbations is important for understanding cellular regulation and prioritizing experimental interventions, yet existing models are often designed for specific perturbation types or biological contexts. Here we present BaiZe, a multi-view conditional state-transition framework that predicts the post-perturbation transcriptome from a control-state transcriptome together with genetic, chemical, temporal and optional chromatin-accessibility information. BaiZe models perturbation responses as context-dependent transitions between cellular states. BaiZe supports prediction across held-out cell states and genetic perturbations, unseen multi-gene combinations, chemical structures and doses, temporal stages and species contexts. Benchmarking across diverse perturbation settings demonstrates that BaiZe effectively recovers major transcriptional response programs under previously unseen conditions. Incorporating matched ATAC-seq context further improves selected state-transition predictions and enables model-based attribution of chromatin regions to response-associated genes and pathways. BaiZe also supports few-shot transfer of perturbation responses from human to mouse cellular systems and connects predicted transcriptomes to candidate morphology projections. To facilitate interpretation and use, BaiZe-Agent organizes response genes, pathways, chromatin evidence, cross-species predictions and projected phenotypes into traceable, queryable perturbation records. Together, BaiZe provides a broadly applicable framework for predicting and interpreting context-dependent cellular responses and for prioritizing hypotheses across diverse perturbation settings.

bioinformatics↗

bioRxiv2026

Light-dependent and predator inducible aldehyde synthesis in Prochlorococcus for specific defense against Uronema

Cyanobacteria as a primary producer provide energy and carbon sources for the marine food web, of which predation-interactions play central roles in regulating global element cycles and marine ecosystem stability. Here, we report the anti-predation activity of a typical marine cyanobacterium Prochlorococcus MED4 to defend the predation by Uronema marinum. MED4 synthesize formaldehyde as the anti-predation chemical, of which the synthesis was light-dependent and predator-inducible. Compared to other protists, both the higher concentration of accumulated formaldehyde in U. marinum and the lower formaldehyde tolerance of U. marinum resulted in the specific anti-predation of MED4 against U. marinum. This specific anti-predation could regulate the cyanobacterial growth and the U. marinum infection of marine fishes. Metadata analyses showed the mutually exclusion of Prochlorococcus and Uronema in global marine environments. These findings significantly advance our understanding of the marine food web and biogeochemical cycles. Significance StatementPredation-driven interactions in the ocean are critical regulators of global biogeochemical cycles, yet active defense mechanisms in marine picophytoplankton remain largely unknown. This study reveals that Prochlorococcus MED4 as the most abundant primary producer in the ocean synthesize light-driven and predator-inducible aldehydes to actively and specifically defend predation against the ciliate Uronema marinum. The anti-predation of Prochlorococcus against Uronema could have broad implications in biocontrol of Uronema infection in marine fishes and regulation of the marine food web.

microbiology↗

bioRxiv2026

Dynamic construction of subjective time through statistical learning of event structure

The perception of time is elastic, often deviating from physical intervals depending on how experience is structured. Yet, what determines how subjective time is constructed remains debated. Here, we tested whether perceived ongoing time is actively constructed from learned event representations rather than a dedicated internal clock. Using a novel pause-adjustment task across three statistical learning experiments, we measured temporal distortions during continuous listening to structured versus unstructured syllable streams. The presence of event structure systematically warped time: pauses were perceived as longer between pseudowords and shorter within pseudowords. This bidirectional temporal warping emerged online and remained stable across pause durations. Enriching these events with semantic meaning eliminated boundary-related dilation while preserving within-event compression. Moreover, physiological tracking of event structure, indexed by pupil dynamics, dissociated from the magnitude of temporal warping. These findings show that subjective time is constructed from hierarchical event representations and depends not only on where events are segmented, but also on how they are represented.

neuroscience↗

bioRxiv2026

High-throughput Single-cell Proteomics Enabled by Integrating nPOP-workflow with Quantitative Hyperplexing

Single-cell proteomics (scProteomics) has emerged as a powerful approach to dissect cellular heterogeneity and dynamic molecular mechanisms at unprecedented resolution. However, achieving high proteome coverage and quantitative accuracy while maintaining high-throughput remains a major challenge. In this study, we established a high-throughput scProteomics workflow that integrates a modified nano-proteomic sample preparation (nPOP) workflow with an IBT16 and TMT16 quantitative hyperplexing strategy. Through systematic optimization of chromatographic and mass spectrometric conditions, we established a label-free workflow for high-sensitivity and high quantification accuracy. On average, more than 3,000 protein groups were identified from individual 293T and HeLa cells on timsTOF SCP. When applied to single cholangiocarcinoma (CCA) cells and matched paracancerous cells dissociated from human fresh-frozen CCA tissue, approximately 2,000 protein groups were quantified per cell, revealing distinct metabolic and translational regulation patterns consistent with previously reported molecular features of CCA subtypes. To achieve high-throughput scProteomics, we then established an nPOP-based IBT16-TMT16 quantitative hyperplexing workflow. Across four human cell lines (293T, HeLa, A549, and LM3), our quantitative hyperplexing strategy achieved over 95% labelling efficiency and consistently identified 1,400 to 2,000 protein groups from single cells with a dynamic range spanning five orders of magnitude. In comparison to conventional multiplexing methods, our hyperplexing strategy not only enhanced proteome depth but also achieved ultrahigh-throughput ([~] 2,000 single cells per day if use Orbitrap Astral Zoom or timsUltra AIP etc.). Overall, our label-free and quantitative hyperplexing workflows provide an efficient and scalable platform for large scale scProteomics studies and clinical applications.

cell biology↗

bioRxiv2026

Transforming Histology into Virtual Multiplex Immunofluorescence to Decode Prognostic Spatial Immunity in Hepatocellular Carcinoma

The spatial organization of the tumor immune microenvironment (TIME) drives hepatocellular carcinoma (HCC) prognosis but remains unquantifiable on routine H&E slides. Here, we present HCCExplorer, a deep learning framework that translates H&E into virtual multiplex immunofluorescence (mIF) and uses multi-modal graph learning to decode spatial survival signals. Trained on 30 H&E-mIF slide pairs, HCCExplorer evaluated a 1,813-slide multi-center cohort. It achieved superior overall survival stratification over clinical indices and state-of-the-art pathology and protein foundation models, yielding a concordance index of 0.71 and a Hazard Ratio (HR) of 15.46 (P < 0.001), maintaining stability across three external cohorts. Beyond risk stratification, interpretation of model features identified M1 macrophage infiltration as a protective determinant (HR=0.40, P < 0.05). Furthermore, it uncovered a protective "Containment Niche" at the invasion frontier (HR=0.02, P < 0.01), featuring macrophages co-localizing with Foxp3+ Tregs and CD4+ T cells. Ultimately, HCCExplorer provides actionable, spatially-resolved biomarkers from conventional histology for precision HCC management.

pathology↗

bioRxiv2026

TRU-PE: A Universal, Trackable Prime Editor Toolkit for Robust Single- and Multi-Locus Genome Engineering

Prime editing (PE) holds immense promise for precise genome editing, but its wider adoption is constrained by large payloads and inefficient delivery in recalcitrant cell types. Here, we present TRU-PE (Trackable, Robust, and Universal Prime Editor), a toolkit that overcomes these barriers via a split-vector architecture coupled with fluorescence-guided enrichment. This design ensures stoichiometric component expression, yielding marked improvements in editing efficiency and accelerated workflows compatible with both plasmid and viral delivery. By integrating a polycistronic hCtRNA-sgRNA/pegRNA array, the derivative TRU-MPE system enables simultaneous editing of up to ten genomic loci. Furthermore, it enhances the performance of evolved PE editors, allows flexible vector stoichiometry and inspires novel editing reporters. Leveraging these capabilities, we successfully generated a combinatorial human iPSC-based platform for GATA2 deficiency, which accurately recapitulates genotype-specific hematopoietic defects. TRU-PE thus provides a user-friendly, scalable framework for robust single- and multi-locus genome engineering, accelerating functional genomics and therapeutic development.

genetics↗

bioRxiv2026

Epigenome-informed prioritization of bivalent chromatin SNPs enhances genomic prediction robustness: a proof-of-concept study in Pacific white shrimp (Litopenaeus vannamei)

BackgroundGenomic selection (GS) has revolutionized animal breeding, spanning livestock sectors such as pigs and cattle to aquatic species like fish and shrimp. However, its broader application across these industries is often constrained by high genotyping costs and reduced predictive reliability across divergent populations or generations. Developing cost-effective, biologically informed genotyping strategies to overcome these limitations remains a critical goal in animal agriculture. Epigenetic annotations, particularly histone modifications, provide direct functional insights into regulatory elements underlying complex trait variation and represent a promising but underexplored resource for marker prioritization. ResultsHere, using the Pacific white shrimp (Litopenaeus vannamei) as a model organism, we conducted a proof-of-concept study integrating resequencing and phenotypic data from 972 individuals. We generated high-resolution epigenomic maps by profiling four histone marks (H3K4me1, H3K4me3, H3K27me3, and H3K27ac) across multiple embryonic stages and adult muscle tissue using CUT&Tag. These functional annotations were then leveraged to prioritize single nucleotide polymorphism (SNP) subsets for genomic prediction. Among the tested strategies, SNPs located in the muscle-specific bivalent promoter/enhancer (E6) state--characterized by the co-occurrence of active and repressive marks--consistently maximized prediction accuracy under the BayesA model. Notably, even at a moderate density (15k), E6-derived SNPs achieved prediction accuracies exceeding those obtained using substantially larger genome-wide SNP sets. Most importantly, in a challenging cross-population validation using an independent strain, the E6-derived SNP subset significantly improved prediction accuracy by 47.6% (increasing from 0.21 {+/-} 0.05 to 0.31 {+/-} 0.04, p < 0.05) compared to random subsets at equivalent density. ConclusionsThese results demonstrate that epigenetic annotation-guided SNP prioritization provides a biologically informed and cost-effective strategy to enhance genomic prediction accuracy and stability. This framework is broadly transferable across species and offers a practical strategy for designing low-density genotyping panels that reduce costs while maintaining reliable selection outcomes in large-scale breeding programs.

genetics↗

bioRxiv2026

A Multimodal Single-Cell Epigenomic and 3D Genome Atlas of the Human Basal Ganglia

The basal ganglia (BG) underlie motor control, reward processing, and many neurological and psychiatric disorders, but a comprehensive epigenomic and 3D-genome atlas of the human BG is lacking. Here we present a multimodal single-cell atlas profiling DNA methylation and 3D chromatin conformation in 261,331 nuclei (snm3C-seq) across eight subregions, resolving 12 classes, 31 subclasses, and 59 groups. Harmonized under the HMBA basal-ganglia consensus taxonomy, this atlas integrates with matched RNA, ATAC-seq, and histone-modification data across five regulatory layers. We identify millions of cell-type- and region-specific differentially methylated regions enriched for distinct transcription factor motifs and link them to disease-associated heritability. Neuron-specific loops dominate cell-type-specific 3D contact remodeling, while most non-neuron-specific loops are constitutive. Among spiny projection neurons (SPNs), chromatin loops, rather than TAD boundaries, distinguish D1, D2, and eccentric SPN subclasses, with eccentric SPNs showing the most loop-level reorganization among the three. We characterize STR D2 SMYD2-HTR7 SPN, a newly recognized POU6F2 D2-SPN subtype, and reveal region-specific methylation and contact gradients of disease-associated genes, including CADM1 and PDE8B. Integrative gene-regulatory networks reconstruct cell-type-resolved enhancer-promoter links to interpret Parkinsons disease risk variants at SNCA. Finally, MERFISH spatial profiling combined with cross-species Patch-seq identifies non-SPN neuronal subtypes, including a MOXD1 striosomal STR FS PTHLH-PVALB GABA subtype with distinct electrophysiology, partitioning across the striatal matrix-striosome boundary. HighlightsO_LIA multimodal single-cell atlas maps DNA methylation and 3D genome architecture across human basal ganglia cell types and subregions. C_LIO_LINeuron-specific loops dominate cell-type-specific 3D contact remodeling in the human BG, whereas most non-neuron-specific loops are constitutive. C_LIO_LISpiny Projection Neuron (SPN) subtypes exhibit regionally organized epigenomic and 3D genome signatures that align with dorsal-ventral identities. C_LIO_LIChromatin loops are the primary distinguishing feature among D1, D2, and eccentric SPN subclasses, with eccentric SPNs being the most 3D-reorganized. C_LIO_LIIntegrated regulatory maps link cell-type-specific enhancers to disease-associated genetic risk in the human basal ganglia. C_LIO_LINon-SPN interneurons differ in distribution and in transcriptional and epigenetic identity across the matrix-striosome boundary. C_LI

neuroscience↗

bioRxiv2026

Single-Cell Raman Profiling Enables Rapid Precision Phage Therapy Against Multidrug-Resistant Hypervirulent Klebsiella pneumoniae

Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) poses a severe global health threat. Phage therapy is a promising alternative, but requires precise matching of phage to the bacterial strain. Here, we present a proof-of-concept method that integrates single-cell Raman spectroscopy with deep learning to enable rapid and precise selection of lytic phages against MDR-hvKP. By profiling Raman signatures of strains across multiple KL-types (capsule locus types), we trained three deep learning architectures for phage-host matching. Among them, the CNN_MLP-Transformer achieved the best performance (99.7%), slightly outperforming CNN_MLP (99.2%) and CNN_MLP-Attention (99.5%). Validation using 10 hvKP clinical isolates yielded an average phage selection accuracy of 78.3%. These findings demonstrate the feasibility and clinical potential of AI- augmented Raman spectroscopy as a rapid, label-free, precise strategy for guiding phage therapy against MDR-hvKP infections. TeaserAI-guided single-cell Raman profiling enables rapid precision phage selection against multidrug-resistant K. pneumoniae.

microbiology↗

bioRxiv2026

Interorganelle competition for linoleic acid underlies steatotic liver pathology

Lipid droplets (LDs) are traditionally viewed as protective organelles that sequester potentially cytotoxic lipids. However, whether and how LD biogenesis in pathological contexts actively rewires interorganelle lipid homeostasis to drive organelle dysfunction and disease progression remains unexplored. Here, we identify the adipocyte-enriched protein calsyntenin 3{beta} (CLSTN3B) as a critical promoter of metabolic dysfunction-associated steatotic liver disease (MASLD). CLSTN3B, an ER-LD contact protein previously shown to support LD maturation in adipocytes, is robustly induced in mouse hepatocytes by peroxisome proliferator-activated receptor {gamma} (PPAR{gamma}) in response to dietary caloric overload. CLSTN3B drives LD biogenesis and neutral lipid storage by stabilizing hemifusion-like ER-LD membrane bridges via its arginine-rich segment. These bridges preferentially recruit cone-shaped linoleoylated phosphatidic acid (PA), diverting linoleic acid (LA) into triacylglycerides (TAGs) rather than mitochondrial cardiolipin (CL), leading to disrupted cristae architecture, deficient ETC supercomplex assembly, elevated electron leak, and oxidative stress. Hepatocyte-specific CLSTN3B deletion impairs LD formation, reduces TAG accumulation, enhances fatty acid oxidation, restores CL maturation, and mitigates oxidative stress, collectively attenuating MASLD progression. Consistently, hepatic CLSTN3B expression correlates with fibrosis severity and progression in human MASLD. These findings position LDs as active regulators of interorganelle lipid partitioning and establish CLSTN3B as a key determinant of mitochondrial vulnerability, providing a general framework for how dysregulated organelle interfaces shape disease.

cell biology↗

bioRxiv2025

Somatic TYK2 activating mutations in tumor-infiltrating T cells promote anti-cancer immunity

Cancer cells evolve to increase fitness and evade the immune system, but it is not clear if tumor infiltrating lymphocytes (TILs) undergo selection for somatic mutations that augment anti-cancer immunity. Using single molecule whole exome sequencing in TILs, we identified somatic mutations in Tyrosine-protein kinase 2 (TYK2), several of which increased TYK2 phosphorylation, JAK-STAT signaling, and interferon gamma signaling. Among these mutations, TYK2D810V was recurrently observed in patients with diverse cancer types. In vitro, TYK2D810V enhanced T cells effector functions and cytokine production. We generated mice with a germline Tyk2D807V mutation that recapitulated the human TYK2D810Vmutation. These mice were healthy and did not develop autoimmune disorders. However, they possessed enhanced anti-tumor effects in the context of syngeneic and autochthonous cancer models. Adoptive therapy with Tyk2D807V CD8 T cells also decreased cancer growth. Thus, naturally occurring mutations in non-malignant lymphocytes can antagonize cancer and inspire new immunotherapies strategies.

cancer biology↗

bioRxiv2025

Cis-delivering releasable IL-15 superagonist enhances antitumor immunity in cold tumors by invigorating preexisting CD25+CD8+ T cells

Antibody-mediated cis-delivery and trans-delivery both direct cytokines to tumors and have been extensively investigated in clinical trials. However, a comparative analysis of their differential effects on cytokine activity is still lacking. In this study, we initially verify that cis-delivery of cytokine demonstrates a markedly stronger antitumor effect than trans-delivery, but it also exhibits certain drawbacks, including severe toxicity, insufficient activation of CD25+CD8+ T cells, and enhanced stimulation of intratumoral regulatory T cells (Tregs). To further address these issues, we developed a conditionally releasable and cis-delivering IL-15 immunocytokine (termed PMIS), which can selectively release a free IL-15 superagonist within tumors rather than immobilizing IL-15 to PD-1+ Tregs, thereby potently stimulating CD25+CD8+ T cells. Mice treated with PMIS showed significantly reduced systemic toxicities while achieving notably stronger antitumor effects. Administered either alone or in combination with other therapies, PMIS exhibits great potential for inhibiting orthotopic cold tumor and its metastases. Mechanistically, the significant activation of the pre-existing intratumoral CD25+CD8+ T cells and the improved CD25+CD8/Treg ratio contribute to the enhanced antitumor response of PMIS. These findings underscore the indispensable role of CD25+CD8+ T cells in cis-delivering IL-15 and provide a promising strategy for overcoming resistance to therapies and effectively controlling advanced cold tumors.

immunology↗

bioRxiv2025

Distinct microbial response to organic matter from nitrogen-starved and virus-infected phytoplankton

When phytoplankton die they release dissolved organic matter (DOM) that feeds co-occurring heterotrophic bacteria. We show that death due to phage infection and nitrogen starvation result in different changes to the macromolecular structure of Prochlorococcus, a globally abundant cyanobacterium, and that the resulting DOM elicits different microbial responses. Viral infection led to increased RNA and DNA content in Prochlorococcus whereas nitrogen starvation led to a lower protein content. DOM released from phage-infected cells induced high secondary (bacterial) production, while DOM from starved cells increased dark (heterotrophic) primary production in natural microbial communities from the oligotrophic Eastern Mediterranean Sea. Through 16S and 18S amplicon sequencing, metagenomics, and laboratory experiments we identify Alteromonadaceae and Rhodobacteraceae as heterotrophic taxa responding differently to the two DOM sources. We propose that distinct forms of phytoplankton mortality drive shifts in microbial community metabolism, including differential activity of pathways for heterotrophic carbon fixation, likely through anaplerotic reactions.

microbiology↗

bioRxiv2025

Programmable microparticles rewire CAR signaling to enable super-physiological expansion of human T cells in vitro

T cell proliferative capacity and persistence critically determine the therapeutic success of chimeric antigen receptor (CAR) T cells. However, it remains unknown if and how human CAR-T cells can be externally programmed to reach maximal proliferative capacity. Here, we use programmable PLGA microparticles functionalized with CAR-antigens and CD28-costimulatory antibodies (CAREp) to repeatedly stimulate human CD8+ CAR-T cells in vitro. CAREp-stimulated CAR-T cells expanded continuously for over 100 days--versus [~]30 days with tumor cell stimulation--and achieved up to 1018-fold cumulative expansion, greatly surpassing CD3/28-Dynabeads. Early-phase transcriptomic responses-- upregulation of DNA repair, cell cycle, telomere maintenance, and mitochondrial pathways--aligned with long-term outcomes: massive proliferation, telomere stability, robust respiration, and preserved progenitor phenotype by single-cell sequencing. Differentiation and exhaustion signals were broadly suppressed. Transient telomerase activity further supported physiologic expansion. These findings demonstrate that nanoscale-controlled extracellular cues can rewire intracellular signaling to drive durable, super-physiological expansion of functional CAR-T cells.

immunology↗