Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

High-dimensional multiomics reveals perturbations to IL-6/IL-6R axis and RUNX3 in CD4+ T cells during third trimester pregnancy

ObjectivesCD4+ T cells play key roles in regulating immune responses during pregnancy, therefore we aimed to understand the CD4+ T cell surface proteome and transcriptome during pregnancy. MethodsCD4+ T cells were analysed in blood and decidua from term-pregnancies (>37 weeks), and non-pregnant blood. >350 surface proteins were screened via flow cytometry, and transcriptomes were analysed using single-cell RNA sequencing with >130 CITE-seq barcoded antibodies. ResultsSurface protein screening identified changes to ILT4/CD85d, CD9, IFN-{gamma} receptor {beta}-chain, CX3CR1 and CCR5 in the pregnant blood and decidual CD4+ T cells. CX3CR1 and CCR5 had the highest expression on the effector-memory T cell (TEM) subset in the blood, with expression consistent across subsets in decidua. CD126/IL-6R was lower in pregnant blood and decidual CD4+ T cells, while scRNAseq identified enrichment in the IL-6R signalling pathway in naive CD4+ T cells in pregnant blood. Both sIL-6R and IL-6 concentrations were increased in plasma during pregnancy, suggesting perturbations to the IL-6/IL-6R signalling axis. Meanwhile, decidual CD4+ T cells had increased expression of transcription factor RUNX3 in the CD69+ tissue-resident-like subset. ConclusionsOur findings demonstrate altered molecular expression in CD4+ T cells during pregnancy. This provides important mechanistic insight of their adaptation and regulation during placental development, which may drive placental dysfunction or pregnancy complications including preeclampsia, fetal growth restriction and stillbirth. These new data may inform future studies that focus on determining the significance of differentially- expressed immune features in pregnancy to identify potential targets for immune modulation to treat pregnancy complications and infections.

immunology↗

bioRxiv2026

Polyclonal-Monoclonal Transition in Lung Squamous Cell Carcinoma Evolution

The evolutionary trajectory of lung squamous cell carcinoma (LUSC) remains poorly defined, hindering the development of effective therapies. By integrating genomic and transcriptomic sequencing from human LUSC specimens, we delineated a polyclonal-to-monoclonal evolutionary trajectory during LUSC progression. This evolutionary pattern was corroborated by single-cell RNA sequencing, which revealed consistent tumor cell heterogeneity. Specifically, the SBS5 mutational signature was enriched and correlated with poor prognosis independent of tumor stage. By further utilizing the spontaneous LUSC mouse model to identify key genomic and genetic events in LUSC progression, we observed that the JNK pathway was inhibited and that cytoskeleton-related pathways were dysregulated during LUSC development, and identified the mutations in the JNK pathway (e.g., DACT1) and cytoskeletal regulators (e.g., KIF26A). Collectively, these findings established a polyclonal-monoclonal evolution paradigm for LUSC, potentially regulated by JNK pathways, which could benefit LUSC precision therapeutics.

genomics↗

bioRxiv2026

Single-Cell Profiling Reveals Developmental Trajectories and identifies SYK and TIM3 as Targets in some T Cell Lymphomas

T cell lymphomas (TCL) are a heterogeneous collection of malignancies whose origins and pathogenesis are poorly understood and for which few efficacious therapeutic options exist. Here, we conduct single-cell transcriptomic profiling spanning eight TCL entities and describe entity-associated programmes. We predict the cell of origin for these tumours through an integrative analysis of transcriptome and T cell receptor (TCR) maturation states. By identifying tumours with TCR states ranging from the pre-TCR through non-productive and productive TCR alpha and beta chain rearrangements we shed new light on their developmental origins. Furthermore, we apply our drug2cell computational drug target predictions with drug screens using patient-derived cell models, systematically benchmarking the performance of drug2cell and validating compounds and targets. This process identifies SYK inhibitors as a therapeutic opportunity and prioritises TIM3 for immunotherapy based on combined spatial transcriptomics analysis. Overall, our data provide a resource for diagnostics and therapies for tumours of critical unmet need.

cancer biology↗

bioRxiv2026

Identification of a somatic H3K23me3 methyltransferase SET-19 in C. elegans

Histone methylation plays essential roles in modulating chromatin organization and gene expression. H3K23 methylation is a conserved histone modification, yet its biological roles and the enzymes responsible for its deposition remain poorly understood. Here, we show that the loss of set-19 leads to a pronounced reduction in H3K23 methylation in C. elegans, as revealed by quantitative mass spectrometry, western blotting, and immunofluorescence staining. In vitro biochemical assays show that recombinant SET-19 proteins purified from E. coli directly catalyze H3K23 methylation. Genome-wide chromatin immunoprecipitation assays reveal that H3K23me3 is enriched at heterochromatic regions and that loss of set-19 alters H3K23me3 levels, accompanied by derepression of gene expression. Genetic analyses indicate that SET-19 is dispensable for both germline and somatic RNAi as well as transgenerational epigenetic inheritance of RNAi. SET-19 is predominantly expressed in somatic cells and specifically mediates H3K23me3 deposition in somatic tissues. The loss of set-19 causes a developmental delay without affecting fertility. Together, our results identify SET-19 as a somatic H3K23 methyltransferase and link H3K23me3 to gene repression in C. elegans.

genetics↗

bioRxiv2026

A Dynamic Oligomerization Network Coordinates Hemagglutinin-Mediated Membrane Fusion on Influenza Virions

Influenza A virus (IAV) entry is mediated by the trimeric glycoprotein hemagglutinin (HA), which undergoes low-pH-triggered conformational rearrangements to drive membrane fusion. Although biochemical and biophysical studies have long suggested that HA trimers function cooperatively, the structural basis for this cooperativity on intact virions has remained unclear. Here, using cryo-electron tomography (cryo-ET) and subtomogram averaging (STA), we determine the in situ structure of prefusion HA on native virions at 3.58 [A] resolution, enabling atomic modeling of membrane-anchored HA. We show that neighbouring HA trimers engage in lateral interactions mediated by HA1 subunits, assembling into flexible dimeric, pentameric, and hexameric organizations that form locally ordered lattices on the viral surface. A 6.0 [A] reconstruction of the HA-dimer reveals the molecular interfaces underlying these assemblies. Disruption of the dominant HA1-HA1 interaction markedly impairs viral entry and slows membrane fusion kinetics. Together, these findings define a virion-level mechanism for coordinated HA activation and establish a structural framework for understanding cooperative membrane fusion by class-I viral fusion proteins.

biophysics↗

bioRxiv2026

Improved Biosynthesis of Ethylene Glycol from Xylose in Engineered E. coli Utilizing Two-Stage Dynamic Control

In this study, we employ a two-stage dynamic metabolic control strategy to enhance the NADPH dependent biosynthesis of ethylene glycol from xylose in engineered E. coli. We evaluated the use of metabolic valves to dynamically reduce the enzymes involved in competitive pathways which compete for substrates with ethylene glycol biosynthesis, as well as regulatory pathways aimed at increasing NADPH fluxes. The performance of our initial strains with limits in pathway expression levels was improved by the addition of competitive valves, but not by increases in NADPH flux. In contrast, improving pathway expression levels, led to strains improved significantly by our regulatory valves which improved NADPH flux, but not by the competitive valves. This is consistent with a central hypothesis that faster pathways in and of themselves can compete with other metabolic fluxes by being faster and are better aided by regulatory changes capable of change rates elsewhere in metabolism. In this case in NADPH flux. Lastly, upon scale up to fed-batch bioreactors, our optimized strain, featuring dynamic control of two regulatory valves produced 140 g/L of EG in 70 hours at 92% of the theoretical yield.

synthetic biology↗

bioRxiv2026

Complete Genomes of Cultivated Gut Bacteria Reveal Mobile Genetic Element-Driven Functional Diversity with Therapeutic Implications

Cultivated bacterial isolates are essential for elucidating gut microbiota functions, yet reliance on fragmented draft genomes and limited mobile genetic element (MGE) annotation has constrained high-resolution analyses. Here, we present the Cultivated Complete Genome Reference (CCGR), a comprehensive compendium of 1,150 fully circularized human gut bacterial genomes. Overcoming draft limitations, CCGR achieves chromosome-scale resolution and reveals distinct evolutionary strategies shaping gene topological organization in response to bacterial growth. Furthermore, we decode the dynamic landscape of MGEs, demonstrating that broad-host-range phages follow strict positional patterns by integrating at conserved chromosomal hotspots flanked by nutrient transporter loci. Importantly, we provide mechanistic in vivo evidence that accessory genomic elements drive strain-level functional heterogeneity. Specifically, the plasmid-encoded scrK gene in Levilactobacillus brevis involved in fructose catabolism is required to mitigate fructose-diet-exacerbated colitis. Collectively, CCGR establishes a framework linking chromosomal architecture and MGEs to bacterial evolution and host health, enabling precise, strain-resolved functional investigations.

microbiology↗

bioRxiv2026

RiboPipe: efficient per-transcript codon-resolution ribo-seq coverage imputation for low-coverage transcripts

MotivationRibosome profiling (Ribo-seq) provides codon-resolution measurements of translation; however, many transcripts exhibit sparse or low read coverage, which limits downstream quantitative analyses. Reliable prediction and imputation of codon-resolution coverage for low-coverage transcripts remain computationally challenging. ResultsWe present RiboPipe, an efficient framework for per-transcript codon-resolution Ribo-seq coverage imputation for low-coverage transcripts. RiboPipe is designed around three key principles. First, it jointly optimizes transcript-level mean ribosome load (MRL) prediction and codon-level coverage modeling within a unified objective, enabling consistent learning across both local and transcript-level scales. Second, it introduces a peak-weighted loss that emphasizes high-signal codon positions associated with translational pausing, improving the recovery of functionally relevant coverage peaks. Third, the framework is lightweight and data-efficient, achieving stable performance even when trained on only a small fraction of high-coverage transcripts. Based on two publicly available Ribo-seq datasets (GSE233886 and GSE133393) as instances, we demonstrate stable convergence and consistent prediction accuracy across multiple train-test split ratios. Comparative evaluation of embedding strategies shows that simple one-hot representations achieve superior performance compared with pre-trained language model embeddings under identical training conditions. Overall, RiboPipe provides a computationally efficient and scalable framework for Ribo-seq coverage imputation in low-coverage transcripts. Availability and ImplementationThe source code and associated data can be accessed at https://github.com/yaozhong/riboPipe Contactyaozhong@ims.u-tokyo.ac.jp or imoto@hgc.jp

bioinformatics↗

bioRxiv2026

Social Functioning in Autism: A Systematic Review and Meta-analysis

Atypical social functioning is a core feature of autism, yet findings remain fragmented across components and development. We aimed to systematically integrate this literature and characterize the organization, development, and moderators of social functioning in autism. We conducted a systematic review and meta-analysis of behavioral studies published between January 1990 and August 2025, identified through PubMed, Web of Science, and prior reviews, including studies with clinically diagnosed autistic individuals and neurotypical controls. A qualitative synthesis and two complementary quantitative meta-analyses were performed, with risk of bias evaluated through study-level characteristics. A total of 2,622 studies (94,114 autistic and 172,847 neurotypical individuals across 32 countries) were included, covering 22 social components that clustered into five domains. Overall group differences were substantial (Hedges g = -0.744, 95% CI [-0.797, -0.690]). Differences emerged earliest in motivation-based processes ([~]6 months), followed by motor, emotion, and inference domains, and showed age-related divergence alongside improvement in some skills. Cross-domain analyses revealed stronger interdependencies in autism and an organizational pattern most consistent with serial relationships among domains. These findings should be interpreted in light of methodological heterogeneity, underpowered samples, and uneven cultural representation. Together, the results provide an integrative framework for understanding the organization and development of social functioning in autism, with implications for precision subtyping, developmentally timed interventions, and neurodiversity-informed research and policy. This study was pre-registered (PROSPERO: CRD42024566141).

developmental biology↗

bioRxiv2026

Defining influenza-specific B cells in vaccine responders, non-responders and influenza breakthrough infections

Although seasonal influenza vaccination programs are effective at a population level, our data from inactivated influenza vaccine (IIV) cohorts in years 2015-2022 reveal that 50-60% of individuals do not seroconvert following immunization. The underlying mechanisms of vaccine non-responsiveness are far from understood. In this study, we sought to define key determinants of optimal B cell immune responses elicited by seasonal influenza vaccination, and to explore why some individuals fail to elicit humoral immunity following immunization. Immune responses associated with seroconversion and vaccine failure from individuals immunized with IIVs were compared at cellular and molecular levels using single-cell transcriptomics. We analyzed HA-specific B cell immunity across vaccine-responders, breakthrough infections and patients hospitalized with acute influenza. Droplet-based single-cell RNA sequencing and VDJ-sequencing of influenza-specific B cells from stored PBMCs was performed using 10x Genomics. Our results show that atypical B cells are the major subset of B cell responses in vaccine non-responders on day 28 post-vaccination. Conversely, individuals who seroconvert had diverse B cell phenotypes. The use of recombinant influenza-specific HA probes allowed us to dissect expression patterns on influenza HA-specific B cells. We found that HA-specific B cells of vaccine non-responders for A/H1N1 and A/H3N2 components displayed elevated atypical-like markers (CD11c, FcRL-5) at baseline, compared to responders. Analysis of differentially expressed genes (DEGs) between responders and non-responders identified differential expression of HLA-DR, CD74, CD83, and CXCR3 genes. We subsequently demonstrated reduced frequencies of HLA-DR-, CD74- and CD83-expressing B cells in patients hospitalized with influenza, compared to healthy participants. Hospitalized influenza patients also had significantly higher proportions of atypical CD21-CD27- B cells. Overall, our data demonstrate an association between elevated frequencies of atypical-like B cells with both lack of seroconversion following immunization and severe influenza infection. These findings broaden our understanding of humoral immunity in influenza vaccination and infection, providing novel insights for vaccination strategies and design.

immunology↗

bioRxiv2026

Reassessment of RNF43 Function Reveals No Impact on Endogenous EGFR or BRAF Protein Stability

RNF43 is best known for removing the Wnt-receptor complex from the cell surface, thereby maintaining Wnt-signaling at minimal essential levels. Recent studies reported that RNF43-mutant colorectal cancers carrying the common BRAFV600E mutation, respond more effectively to combined BRAF/EGFR inhibition. To determine whether RNF43 directly regulates EGFR or BRAF protein abundance, multiple pancreatic and colorectal cancer cell line models were generated in which RNF43 was knocked out, repaired, or stably overexpressed. Total and cell surface EGFR levels, as well as endogenous BRAF expression, were quantified. Across all models, no consistent evidence emerges that RNF43 modulates endogenous EGFR or BRAF levels. R-spondins likewise fail to alter EGFR levels or internalization. Notably, elevated EGFR expression observed in a subset of RNF43 knockout clones is induced by unintended CRISPR/Cas9 vector integration rather than the absence of RNF43 itself, highlighting a previously underappreciated artefact that can confound interpretations of EGFR regulation in genome edited lines. Overall, the data argue against a direct and general role for RNF43 in controlling EGFR or BRAF protein abundance, contradicting recent reports that propose degradation of these targets. Further studies are required to resolve these discrepancies and clarify the mechanistic basis underlying these conflicting observations.

cell biology↗

bioRxiv2026

Differentiable Gene Set Enrichment Analysis for Pathway-Level Supervision in Transcriptomic Learning

In transcriptomics-driven drug discovery, upstream predictors of chemical-induced transcriptional profiles (CTPs) are typically trained with gene-wise objectives, whereas downstream interpretation relies on pathway-level, rank-based statistics such as Gene Set Enrichment Analysis (GSEA). This objective mismatch destabilizes pathway conclusions under prediction errors: small ranking perturbations can flip enrichment direction or distort pathway ordering. To bridge this gap, we present differentiable GSEA (dGSEA), a training-compatible surrogate that maps predicted gene-level scores to pathway enrichment with well-behaved gradients. Technically, dGSEA replaces discrete ranking operations with temperature-controlled soft sorting, smooth prefix accumulation, and differentiable extremum aggregation. Critically, to preserve the statistical semantics of classical GSEA, we introduce sign-specific robust permutation normalization (dNES) with optional{kappa} -calibration. For computational efficiency, a scalable Nystrom-window approximation (nyswin) reduces the quadratic bottleneck to near-linear complexity, enabling genome-scale evaluation. Empirically, across synthetic benchmarks and LINCS L1000 signatures, dGSEA matches classical GSEA accuracy with improved numerical stability. When incorporated as an auxiliary objective for SMILES-to-transcriptome prediction, dGSEA improves pathway-level agreement (macro correlation 0.257 [->] 0.306; sign accuracy 0.620 [->] 0.641) without compromising gene-level performance, providing a practical mechanism for pathway-aware optimization in transcriptomic prediction pipelines.

bioinformatics↗

bioRxiv2026

Stromal asparagine supports tumor adaptation to oxidative phosphorylation inhibition through SLC38A4-mediated metabolic coupling

PurposePancreatic ductal adenocarcinoma (PDAC) is characterized by a nutrient-deprived and hypoxic tumor microenvironment (TME) that imposes severe metabolic stress on cancer cells. Under these conditions, tumor cells frequently activate the integrated stress response (ISR) to adapt to TME and develop resistance to therapies. However, how TME components support tumor adaptation to mitochondrial metabolic stress remains incompletely understood. Here, we aimed to identify key metabolite involved in ISR adaptation under oxidative phosphorylation (OXPHOS) inhibition and to elucidate the metabolic symbiosis between cancer-associated fibroblasts (CAFs) and PDAC cells. MethodsWe integrated transcriptomic and metabolomic analyses with functional assays. ISR activation was evaluated by assessing the phosphorylation of eIF2 (p-eIF2) following treatment with carboxyamidotriazole orotate (CTO), an Complex I inhibitor. Metabolomic profiling was used to identify metabolites involved in ISR activation alleviation. Mouse models were used to assess therapeutic responses following depletion of the identified metabolite under CTO treatment. Genetic perturbation of Slc38a4 was performed to assess its functional role in tumor cell adaptation to metabolic stress. ResultsWe identified asparagine (ASN) as a critical metabolite supplied by CAFs to PDAC cells under OXPHOS inhibition. A minimum level of ASN is required for PDAC cells to execute ISR downstream adaptation. ASN depletion significantly enhanced the anti-tumor efficacy of OXPHOS inhibition both in vitro and in vivo. SLC38A4 emerged as a potential mediator of this interaction. SLC38A4 expression was associated with c-Myc, and its loss increased the sensitivity of PDAC cells to CTO-induced metabolic stress. ConclusionOur findings reveal a CAF-tumor metabolic crosstalk in which stromal-derived ASN supports PDAC cell adaptation to mitochondrial metabolic stress. Adaptive outcome of ISR signaling depends on the availability of key metabolic substrates such as ASN. When extracellular ASN supply is limited, the ATF4-dependent adaptive program collapses, converting ISR from a pro-survival response into a therapeutic vulnerability. SLC38A4 may function as a key mediator of this metabolic coupling and represents a potential target for enhancing the efficacy of OXPHOS inhibition in PDAC.

cancer biology↗

bioRxiv2026

Genetically Engineered Biomimetic Nanozymes Reprogram Immune Niches to Intercept Colitis-Carcinoma Transition

Colitis-associated colorectal cancer (CAC) arises from chronic inflammatory niches characterized by persistent oxidative stress and dysregulated immune cell recruitment. Current anti-inflammatory therapies provide only transient symptom relief and fail to prevent malignant progression due to their inability to simultaneously mitigate oxidative injury and immune chemotaxis. Our analysis of clinical samples revealed markedly elevated C-X-C motif chemokine ligand 2 (CXCL2) in intestinal tissues from patients with inflammatory bowel disease (IBD) and CAC, implicating the CXCL2-CXCR2 axis in driving excessive neutrophil and macrophage infiltration and fostering tumorigenesis. Herein, we report a biomimetic nanozymes (PB@ECM) that reprogram inflammatory immune niches to intercept CAC progression. PB@ECM integrates a Prussian blue nanozyme core with genetically engineered macrophage membranes, enabling concurrent scavenging of reactive oxygen species through superoxide dismutase- and catalase-like activities and sequestration of CXCL2 via membrane-displayed CXCR2 receptors. In murine models of colitis and CAC, PB@ECM significantly alleviated intestinal inflammation, suppressed neutrophil and macrophage infiltration, and effectively inhibited colitis-carcinoma transition. By disrupting the pathological crosstalk between oxidative stress and immune chemotaxis, this work establishes a biomimetic nanozyme strategy for preventing inflammation-driven carcinogenesis.

bioengineering↗

bioRxiv2026

DCS Tools: A high-performance, resource-efficient and scalable computing suite for population-scale genomic analysis and data compression

The advent of population-scale genomics has created significant bottlenecks in computational infrastructure and storage. Traditional BWA-GATK Best Practices require massive resources, while most existing acceleration solutions depend on specialized hardware like GPUs or FPGAs, increasing costs and limiting deployment. To address this, we developed DCS Tools, a high-performance suite optimized for standard CPU architectures. DCS Tools processes a 30X WGS sample from raw FASTQ to variant calls in just 1.79 hours on a 32-thread instance--a 16-fold speedup over traditional pipelines without additional hardware. The suite integrates DPGT for million-scale joint calling and introduces SeqArc and VarArc, which reduce storage footprints by up to 80% (FASTQ) and 66% (VCF) compared to GZIP. DCS Tools offers a cost-effective, hardware-agnostic solution for petabyte-scale genomic analysis.

bioinformatics↗

bioRxiv2026

Multi-component functionalized Bifidobacterium longum hydrogel for multi-target integrated therapy of colitis-associated anxiety and depression

Inflammatory bowel diseases (IBDs) are frequently accompanied by anxiety and depression, largely driven by perturbed gut-brain axis signaling. However, current oral therapies remain constrained by the spatial and functional separation between intestinal inflammation and central nervous system dysfunction. Here, we present a comprehensive gut-brain dual region integrated therapeutic strategy based on functionalized Bifidobacterium longum hydrogel (INPs@BL@Gel), in which baicalin and tyrosine are coordinated with Fe(III) to form infinite coordination polymers (ICPs), coated with inulin, assembled onto Bifidobacterium longum (BL), and subsequently encapsulated within a pH- and matrix metalloproteinase-responsive silk fibroin-gelatin hydrogel. INPs@BL@Gel exhibits high drug-loading, effective gastric protection, inflammation-triggered release, and long-term intestinal colonization. Within the inflamed intestine, BL and components synergistically suppress inflammatory responses, restore gut microbiota homeostasis, and promote intestinal barrier repair through multi-target integrated therapy. Importantly, BL combined with components markedly enhances the production of beneficial neuroactive metabolites such as homovanillic acid and short-chain fatty acids, which integrated regulate neuroinflammation, preserve synaptic function, and facilitate blood-brain barrier repair via the gut-brain axis. In vivo studies demonstrate that INPs@BL@Gel not only exert potent therapeutic efficacy against colitis and effectively alleviate associated depression, but also reshape the gut microbiota and restore barrier integrity, achieving an remarkable comprehensive therapeutic effect. O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/710940v1_fig1a.gif" ALT="Figure 11"> View larger version (59K): org.highwire.dtl.DTLVardef@1a831f3org.highwire.dtl.DTLVardef@1676617org.highwire.dtl.DTLVardef@15f99c1org.highwire.dtl.DTLVardef@1677cc4_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOScheme 1.C_FLOATNO (a) Schematic diagram of the design and preparation of functionalized Bifidobacterium longum hydrogel. (b) Exploration of the mechanism of INPs@BL@Gel in treating colitis-associated anxiety and depression through a dual-site multi-target synergistic strategy. C_FIG

pathology↗

bioRxiv2026

Learning the All-Atom Equilibrium Distribution of Biomolecular Interactions at Scale

Biomolecular functions are governed by dynamic conformational ensembles rather than static structures. While models like AlphaFold have revolutionized static structure prediction, accurately capturing the equilibrium distribution of all-atom biomolecular interactions remains a significant challenge due to the high computational cost of molecular dynamics (MD). We present AnewSampling, a transferable generative foundation framework designed for the high-fidelity sampling of all-atom equilibrium distributions, which is the first model to faithfully reproduce MD at the all-atom level. It uses a quotient-space generative framework to ensure mathematical consistency and leverages the largest self-curated database of protein-ligand trajectories to date, with over 15 million conformations. Statistically, AnewSampling consistently outperforms all prior generative methods on the ATLAS monomer benchmark, and the all-atom capabilities of AnewSampling enable close statistical alignment with ground-truth MD for evaluating atomic biomolecular interactions in protein-ligand dynamics. Furthermore, AnewSampling successfully recovers coupled ligand and side-chain motions in CDK2 systems, overcoming a major sampling hurdle inherent to conventional MD. AnewSampling enables rapid exploration of conformational landscapes prior to intensive simulations, elucidating fundamental biophysical mechanisms and accelerating the broader design of functional biomolecules.

bioinformatics↗

bioRxiv2026

Mature Citrus Leaves Undergo Coordinated Photosynthetic Downregulation to Support Flush-Driven Carbon and Nitrogen Sink Demand

The source{square}sink attenuation hypothesis suggests that plants regulate carbon fixation in response to fluctuations in sink demands. Many evergreen trees exhibit flushing growth patterns, where new shoot development generates a strong, transient demand for both carbon and nitrogen that may influence the function of mature leaves. This study examined the source-sink attenuation hypothesis in the context of vegetative sink growth by investigating the photosynthetic capacity and nitrogen dynamics in mature citrus leaves across three stages of flush development. In contrast to expectations, photosynthesis declined as flush growth progressed. Early flush initiation induced stomatal limitation in mature leaves, whereas as sink demand from further shoot growth continued carboxylation capacity and Rubisco abundance declined, despite relatively stable total leaf nitrogen. These results suggest that mature leaves undergo selective protein retooling under prolonged sink demand, constraining CO{square} fixation while maintaining C export. Overall, this study revealed that under strong combined N and C sink demands, mature citrus leaves function primarily as regulated carbon conduits rather than dynamically upregulating photosynthesis, providing new insight into source-sink coordination in woody perennial species. HighlightCitrus flush growth shows that mature leaves suppress photosynthesis through stomatal and biochemical regulation while reallocating carbon and nitrogen to support new shoot development, challenging classic source-sink theory.

plant biology↗