Biology subjects

Liu, Z.

Publications and source records attributed to Liu, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Disease-associated NK-cell state remodeling reveals transcriptional profiles predictive of clinical phenotypes

Natural killer (NK) cells adapt their cellular states to diverse tissue and inflammatory environments, yet how this plasticity manifests across pathological contexts and relates to patient-level disease phenotypes remains poorly defined. Here we established the Human NK-cell Atlas (HNKA) from over 1 million NK cells, including samples from 1,632 donors spanning 50 diseases. Within a shared NK-cell state architecture, analyses of state abundance and matched-reference exceedance distinguished disease-biased redistribution from transcriptional displacement. Fine-grained analyses localized disease-associated remodeling to specific NK-cell states, including CD56dim NK ISG15 in infection and autoimmunity and CD56bright NK ITM2C in tumors. These patterns were accompanied by recurrent interferon responses and state-specific regulatory activity. Cytokine perturbations recapitulated key transcriptional features of disease-associated NK-cell states. We developed NKceiver, a model based on state-specific NK-cell expression profiles for patient-level prediction. It distinguished 18 diseases and predicted COVID-19 severity and response to immune checkpoint inhibitors, with predictive performance retained in unseen patients and studies. Collectively, our results reveal that disease-associated remodeling within the diverse NK-cell state repertoire resolved by HNKA is biologically interpretable and clinically informative, supporting disease discrimination and prediction of clinical phenotypes.

immunology↗

bioRxiv2026

ProtCell: a foundation model for single-cell proteomics

Single-cell proteomics provides a direct functional readout of cellular states, but targeted assays measure limited and non-identical protein panels, fragmenting information across experiments. Here, we present ProtCell, a foundation model developed using approximately 380 million cells from 98 datasets for pretraining and evaluation. ProtCell combines protein-identity and continuous-abundance embeddings in a transformer encoder and learns cell- and protein-level representations through masked abundance modeling. ProtCell first connects fragmented profiles through transferable annotation and batch correction while preserving biological organization. It then extends limited profiles through abundance reconstruction and inference of an unmeasured cytotoxic protein program enriched in natural killer cells and memory CD8$^+$ T cells. The learned protein dependencies further guide the selection of compact panels that retain information for profile reconstruction and biological classification. ProtCell thus provides a framework for connecting fragmented proteomic profiles, extending information beyond measured panels and guiding more informative measurements.

bioinformatics↗

bioRxiv2026

Erythrocyte extravasation drives ferroptosis and inflammatory amplification in eccentric contraction-induced skeletal muscle injury via the heme-HO-1-iron axis

Eccentric contraction-induced skeletal muscle injury is a common sports-related condition characterized by pain, impaired muscle function, slow recovery, and frequent recurrence, yet treatment remains symptomatic and mechanism-based targets are lacking. Although microvascular disruption and erythrocyte extravasation characterize severe muscle strain, the metabolic fate of extravasated erythrocytes has received little attention. In hemorrhagic and hemolytic conditions, erythrocyte-derived heme can activate heme oxygenase-1 (HO-1)-mediated iron release and ferroptosis, potentially amplifying inflammation; however, whether this pathway contributes to eccentric muscle injury remains unknown. To address this gap, we established a parameter-controlled rat model in which the gastrocnemius underwent 0, 50, 100, or 150 eccentric stretch repetitions. Muscle torque, gait, weight-bearing, endurance, pain threshold, histopathology, microcirculatory perfusion, macrophage polarization, and heme, ferrous iron, glutathione (GSH), malondialdehyde (MDA), glutathione peroxidase 4 (GPX4), and pro-inflammatory cytokine levels were assessed. Increasing repetitions produced graded functional impairment, myofiber damage, erythrocyte extravasation, inflammatory infiltration, and microcirculatory disturbance. Heme accumulation was accompanied by HO-1 upregulation in perivascular CD68-positive (CD68) macrophages, muscle iron accumulation, GSH and GPX4 depletion, elevated MDA, and increased M1 macrophage and cytokine levels. These findings suggest a potential heme-HO-1-iron-ferroptosis-associated inflammatory mechanism in eccentric muscle injury, providing a rationale for mechanistic validation and targeted therapeutic development. Keywords: Eccentric contraction-induced muscle injury; Erythrocyte extravasation; Heme oxygenase-1; Ferroptosis; Macrophage polarization

immunology↗

bioRxiv2026

Genome-wide LD scores enable robust heritability and genetic correlation estimation from summary statistics across genetic ancestries

Our knowledge of human complex trait architecture across diverse populations remains limited. Estimating SNP heritability and genetic correlation from GWAS summary statistics - successful in revealing genetic architecture in homogeneous cohorts - is challenging in structured and admixed populations due, in part, to the difficulty of representing long-range LD. We present SUMMIT, a statistical framework that combines genome-wide LD scores, efficiently estimated using random projections, with GWAS summary statistics to estimate genome-wide and annotation-specific heritability and genetic correlation. In simulations that explore diverse aspects of genetic architecture across European (EUR), South Asian (SAS), and admixed African-European cohorts (AFR) in the UK Biobank (UKB), SUMMIT had increased accuracy and reduced bias compared to prior methods, with the largest gains in non-European ancestries reflecting improved modeling of long-range LD. Across 40 UKB traits, SUMMIT produced estimates of genome-wide common-SNP heritability (h_g^2) and heritability enrichments in genomic annotations that were broadly concordant across ancestries with the SUMMIT h_g^2 estimates more closely matching recent whole-genome sequencing based estimates. SUMMIT substantially improved genetic correlation analysis recovering more significant findings across ancestries (23 SAS and 3 AFR at FDR < 0.05 compared with none and two for cov-LDSC) with the non-European discoveries showing concordant effects in Europeans suggesting that, like heritability, global patterns of pleiotropy are largely shared across ancestries. By combining accurate genome-wide LD and efficient moment estimation, SUMMIT enables investigation into how heritability and genetic correlation vary across populations and genomic annotations, including in structured and admixed cohorts, at the genome-wide, annotation-specific, and cross-trait levels.

genomics↗

bioRxiv2026

Distinct spatial organization of human hippocampal perfusion and microvascular pulsatility across age

Arterial pulsation can modulate neuronal activity through mechanosensitive pathways in mice, but whether vascular pulsatility is similarly related to neural organization in humans remains unclear. Here, using 7T MRI in 35 young and older adults, we mapped cerebral perfusion and microvascular volumetric pulsatility index (mvPI) across the unfolded hippocampus and integrated these measures with histological, electrophysiological, and transcriptomic reference maps. Perfusion and mvPI exhibited distinct spatial organization and age-related differences. In young adults, perfusion preferentially corresponded to parvalbumin-interneuron density and beta/gamma distribution, whereas mvPI was associated with theta-band distribution. A number of associations detected in young adults were not detected in the older adults maps. Spectral simulations showed qualitative similarity to heartbeat-related phase resetting as one possible explanation for the mvPI-theta relationship, while spatial transcriptomics revealed perivascular enrichment of PIEZO2, a candidate mediator of vascular mechanotransduction. Together, these findings establish perfusion and tissue-level pulsatility as distinct dimensions of human hippocampal vascular organization and provide a framework for investigating their relationships with neural dynamics across aging.

neuroscience↗

bioRxiv2026

Selectivity Dilution in Three-Factor Learning: A Finite-Population Model with Potential Implications for Motor Development and Post-Stroke Motor Rehabilitation

Motor development and post-stroke motor recovery may share underlying learning mechanisms, but the early mechanical environments of the two processes differ strikingly. During early development the fetus moves within amniotic fluid, where buoyancy substantially reduces gravitational load and enables spontaneous low-resistance movement; in contrast, post-stroke motor reconstruction occurs without this fluid low-resistance phase. Whether and how the absence of a fluid low-resistance phase influences post-stroke functional recovery is the central testable question raised by the selectivity dilution framework. Three-factor learning rules use broadcast neuromodulatory signals to convert eligibility traces into lasting synaptic changes. Because the signal is broadcast, it may reinforce all eligible synapses that are active during reinforcement without obvious deviation, not only those that caused the successful outcome. This framework offers a testable mechanistic principle for early motor learning and neurorehabilitation, and may inform the design of biologically plausible, non-backpropagation learning algorithms in artificial systems.

neuroscience↗

bioRxiv2026

A community benchmark enables high-resolution, cross-lab quantification of mouse social behavior

Social behavior is a sensitive readout of brain state, but quantifying rodent social behavior at scale has relied on siloed, lab-specific tools. We assembled Days of our Mice (DooM), a benchmark of manually annotated video and pose tracking spanning 15 laboratories and 33 social and solitary behaviors, and hosted a community behavior classification challenge. We built on challenge solutions to develop the High-Dimensional Rodent Annotator (HiDRA), a behavior classification tool that generalizes to labs unseen during training and learns cross-lab movement features. Applied without retraining to experimental data, HiDRA resolves line-specific and state-dependent behavioral fingerprints with strong generalizability and reproducibility, establishing high-resolution, shareable social phenotyping as a scalable readout of brain and internal state. We release the DooM dataset and HiDRA classifiers as open resources.

neuroscience↗

bioRxiv2026

Pan-cancer nucleosome landscapes reveal tumor heterogeneity and inform cell-free DNA-based detection

Background: Nucleosome positioning and occupancy are fundamental features of chromatin organization, yet their variation across human cancers and potential utility for noninvasive cancer detection remain poorly characterized. Methods: We systematically characterized nucleosome organization across 410 primary tumors spanning 23 cancer types using ATAC-seq, establishing a high-confidence pan-cancer nucleosome atlas validated by independent MNase-seq data. We characterized shared and cancer-type-enriched nucleosome patterns, investigated their associations with tumor heterogeneity and regulatory alterations, and evaluated tissue-derived nucleosome signatures for cancer classification and detection using circulating cell-free DNA (cfDNA). Results: The atlas identified shared and cancer-type-enriched nucleosomes associated with distinct regulatory programs. Notably, nucleosome occupancy provided information complementary to chromatin accessibility for tumor stratification and revealed molecular heterogeneity within individual cancers, including subgroups associated with Basal-like breast cancer. In hepatocellular carcinoma, differential nucleosome analysis revealed cancer-associated chromatin remodeling involving regulatory pathways, transcription factor motifs, and candidate genes. Importantly, tissue-derived nucleosome signatures were detectable in cfDNA, enabling classification among three cancer types (AUROC = 0.877) and colorectal cancer detection (AUROC = 0.930), with an AUROC of 0.773 in an independent validation cohort. We also developed OncoNucAtlas, a publicly accessible database facilitating exploration of these nucleosome landscapes. Conclusions: Our study cancer-associated nucleosome organization as a complementary source of epigenomic information and demonstrates the potential of tissue-derived nucleosome signatures for cfDNA-based cancer detection. The pan-cancer atlas provides a resource for investigating tumor heterogeneity and developing noninvasive cancer detection approaches.

bioinformatics↗

bioRxiv2026

Mechanical characterization of human centromeres

Centromeres must withstand high pulling forces in metaphase, yet allow rapid and complete chromosome segregation in anaphase. Using optical tweezers measurements on isolated human metaphase chromosomes, we find that centromeres are stiffer at low forces and more frequently exhibit pronounced softening compared to whole chromosomes, while displaying a similar stiffening response at high forces. We capture these mechanical properties by establishing a softened hierarchical worm-like chain model. Cohesin cleavage alters the mechanical properties of centromeres but does not lead to chromosome segregation in vitro. Topoisomerase II is recruited to centromeric regions under significant tension, likely to resolve the persistent centromeric DNA entanglements that provide additional sister chromatid cohesion. These findings advance our understanding of the mechanical resilience and regulation of centromeres during mitosis.

biophysics↗

bioRxiv2026

AMPK-dependent brain-wide norepinephrine release promotes recovery from metabolic coma in mice

Coma is a pathological brain state characterized by loss of consciousness. How the brain recovers from coma remains largely unknown. Using mouse models of metabolic coma, we identified an endogenous neuromodulatory pathway that actively promotes coma recovery. In mice subjected to hypoglycemic coma, hypoglycemia triggered AMPK-dependent excitation of nucleus tractus solitarius (NTS) neurons, which activated locus coeruleus (LC) norepinephrine neurons through a glutamatergic NTS-LC circuit. LC activation drives widespread norepinephrine release across cortical and subcortical regions, thereby promoting post-coma arousal. Notably, coma-associated brain-wide norepinephrine release was unconventional in both scale and duration, with a magnitude approximately 10-fold higher than physiological norepinephrine release during sleep-wake cycles. This neuromodulatory process also operated during hypercapnic coma. Vagus nerve stimulation accelerated coma recovery by engaging this endogenous anti-coma mechanism. Our findings uncover an AMPK-dependent brainstem circuit that actively restores arousal from metabolic coma, revealing a neural defense strategy against profound metabolic stress.

neuroscience↗

bioRxiv2026

scPRIME-seq uncovers synchronized multimodal molecular collapse facilitated by pre-neoplastic epigenetic burden in prostate cancer

Tumorigenesis involves alterations across the genome, epigenome and transcriptome, yet how these layers interact to drive malignant transformation remains unclear, largely due to the lack of scalable multimodal single-cell approaches. Here, we developed scPRIME-seq, a high-throughput platform for simultaneous single-cell profiling of transcriptome, genome and DNA methylome, and applied it to 436,908 cells from 29 prostate cancers and 15 benign tissues. This multimodal atlas resolved dynamic changes across 30 cell types and a unified tumorigenic trajectory. Integrated analysis revealed a cell-state transition tipping point, where the onset of aneuploidy is temporally coupled with global methylomic alterations and transcriptomic rewiring. Early focal epigenetic alterations, including TMEM106A promoter hypermethylation and the emergence of hypomethylated domains, were present in founder aneuploid clones and benign tissues, indicating a pre-neoplastic origin of epigenetic burden. These pre-neoplastic alterations coincide with transcriptomic changes that affect epithelial interactions with stromal and immune compartments, promoting a putative tumor-permissive microenvironment. scPRIME-seq provides a high-throughput multimodal framework for identifying conserved, cell-intrinsic molecular programs underlying tumorigenesis.

cancer biology↗

bioRxiv2026

Defense-associated reverse transcriptases synthesize DNA in a telomerase-like manner

Defense-associated reverse transcriptases (DRTs) constitute an emerging class of bacterial defense systems that harness reverse-transcriptase activity to generate cDNA products and counter phage infection. A distinct subset of DRT10 systems evolutionarily related to telomerase generates tandem-repeat DNA to confer antiphage immunity. Here, we biochemically characterize the reverse transcription activity of DRT10 and determine cryo-EM structures of DRT10-ncRNA complex in three functional states, revealing an unanticipated 2:1 RT:ncRNA assembly mode. Two DRT10 protomers dimerize through a central pair of interlocked {beta}-hairpins and are further embraced by a single ncRNA. This architecture distinguishes DRT10 from previously characterized DRT complexes, which either lack an ncRNA component or exhibit an equivalent stoichiometry of RT:ncRNA. Strikingly, despite the nearly identical conformations of the two DRT10 protomers, cDNA product density was resolved in only one catalytic pocket, revealing different product occupancy within the dimer. Moreover, along with flanking linkers, the stem loops of the ncRNA as fixed points to supply steric barriers help define the template boundary. These findings reveal a distinctive ncRNA-mediated DRT10 dimeric assembly and establish a mechanistic framework for protein-primed reverse transcription constrained by the length of the RNA flanking linker.

biochemistry↗

bioRxiv2026

Tractable and Thermodynamically Consistent pKa Prediction via First-Dissociation Aggregation

Ionization governs molecular behavior, yet predicting aqueous pKa accurately and tractably remains a fundamental challenge. Rigorous ensemble methods require enumerating a protonation-state space that grows exponentially with the number of ionizable sites, while fast graph predictors return numbers without thermodynamic consistency. Here we derive an exact thermodynamic identity showing that the macroscopic first-dissociation constant is fully determined by protonated-microstate populations and unique first-deprotonation events, eliminating the deprotonated ensemble algebraically and reducing aggregation to O(n+E) operations. We implement this identity in DTi-pKa, a dual-head graph neural network whose free-energy and dissociation heads are coupled by thermodynamic constraints. On four external benchmarks (355 molecules), DTi-pKa achieves a pooled MAE of 0.5665 pKa units, with 0.6285 on the 169 records lacking training-cache matches, while providing site-resolved micro-pKa values and protonation-state populations. Controlled ablations show that constraint placement at the level of the reported macroscopic equilibrium matters more than microscopic label precision--a design principle transferable to physics-informed machine learning beyond chemistry. Closure diagnostics expose numerical self-consistency as an open frontier, which we report transparently. By replacing an intractable computation with a physical identity, DTi-pKa unifies macroscopic accuracy and microscopic interpretability in a single framework.

bioinformatics↗

bioRxiv2026

A learned oral signal drives long-lasting thirst satiation

Drinking quenches thirst long before the ingested water has been absorbed. Here we investigate the mechanism by combining sham drinking, which uncouples water ingestion from rehydration, with recordings of thirst-promoting neurons in the brain. We show that sham drinking suppresses thirst and rapidly inhibits thirst-promoting neurons despite no water absorption. Remarkably, this suppression of thirst neurons in the absence of rehydration is proportional to the amount of water consumed and persists for tens of minutes after drinking has stopped. This sustained inhibition is triggered by passage of water through the oral cavity, but not licking or swallowing alone, and undergoes extinction with repeated sham drinking, indicating it is learned. Complementary experiments using hypertonic saline demonstrate this learning is bidirectional. These findings reveal that the experience of rapid thirst quenching is not a hard-wired response to the consumption of water, but rather a learned prediction of future bodily state.

neuroscience↗

bioRxiv2026

Beyond RMSD: Deterministic Dlow Matching for Ultrafast and Physically Validated Transition-State Generation

Transition state (TS) generation is typically evaluated by geometric similarity, yet low root-mean-square deviation (RMSD) does not establish first-order saddle-point character or reaction-path connectivity. Here we introduce Kairos-GFM, a deterministic equivariant flow-matching model that combines a two-dimensional reaction graph with the Kabsch-aligned mean of three-dimensional reactant and product geometries. Using 881 Transition1x reactions whose reference TSs passed strict saddle-point and bidirectional intrinsic reaction coordinate validation, Kairos-GFM generates one candidate in 0.0118 s with a median RMSD of 0.14 [A]. A hierarchical physical-validation framework--spanning reaction-center geometry, raw single-point energy, DFT saddle-point optimization, harmonic frequency analysis, and IRC endpoint matching reveals that low RMSD and saddle-point convergence do not guarantee the intended reaction channel. Kairos-GFM recovers the target channel in 75.94% of reactions, outperforming diffusion-based baselines but remaining below transport-based methods. These results position Kairos-GFM as a rapid initial-geometry generator for quantum-chemical refinement and provide a transferable validation standard that distinguishes geometric similarity from physical fidelity.

biochemistry↗

bioRxiv2026

Early dynamics of a neutrophil interferon program drive immunotherapy resistance and limit durable anti-tumor immunity

Despite the remarkable success of immune checkpoint blockade (ICB), durable clinical benefit remains limited to a subset of patients, highlighting the need for predictive biomarkers and new therapeutic targets. Here, we investigated the early immune dynamics associated with anti-PD1 responsiveness using longitudinal single-cell transcriptomics, spatial transcriptomics, and neutrophil-specific genetic perturbations in preclinical models of triple-negative breast cancer. We identified a conserved neutrophil interferon-stimulated gene (ISG) program that emerges before overt tumor divergence and predicts resistance to anti-PD1 therapy. Successful treatment was associated with an early reduction of IFN-responsive neutrophils in both blood and tumor tissues, whereas persistent neutrophil IFN signaling correlated with therapeutic resistance. Mechanistically, genetic disruption of either type I or type II interferon signaling in neutrophils enhanced anti-PD1 efficacy and promoted durable anti-tumor immune memory. Spatial analyses further revealed an inverse association between IFN-responsive neutrophils and tertiary lymphoid structure-enriched regions during effective therapy. Together, these findings identify IFN-responsive neutrophils as early determinants of immunotherapy outcome and establish dynamic neutrophil interferon programs as candidate blood-based biomarkers and therapeutic targets for cancer immunotherapy.

cancer biology↗

bioRxiv2026

From Ligand Binding to Pore Opening in the Mosquito Odorant Receptor AaegOR10

Mosquito olfaction is central to host seeking and other behaviors relevant to vector ecology and disease transmission. Mosquito odorant receptors (ORs) are ligand-gated ion channels, yet how ligand binding is coupled to pore opening remains poorly understood. Here, we combine more than 400 $\mu$s of aggregate molecular dynamics simulations and adaptive sampling with Markov state models (MSMs) and electrophysiological measurements to characterize the gating dynamics of \textit{Aedes aegypti} odorant receptor 10 (AaegOR10). Interaction analysis identifies M288 as a persistent contact between $o$-cresol and S6, connecting the orthosteric pocket to a conformation-dependent hydrophobic network involving I293, F294, and F356 at the S6-S7b interface. The MSMs place the experimentally determined open and closed structures within a multistate conformational landscape and identify a principal intermediate along the dominant gating pathway. A localized S6 kink in this state is associated with weakened S6-S7b coupling and increased flexibility of the pore-lining S7b helix. Ligand binding shifts the conformational equilibrium toward open states and shortens the transition times from the closed state to both the intermediate and open states. We also identify an off-path closed state characterized by a pronounced inward displacement of S6, with phospholipid headgroup insertion observed in some sampled conformations. Mutational analysis and voltage-clamp recordings support the functional relevance of M288, the S6-S7b interface, and the kink-prone S6 region. Together, these results describe a multistate pathway linking ligand recognition to AaegOR10 pore gating.

biophysics↗

bioRxiv2026

Pair-complete structural gating enables Pareto optimization of de novo cyclic peptides with preserved binding geometry and improved developability

Cyclic peptides can engage extended protein interfaces, but sequence changes that improve developability often disrupt the selected target-bound geometry. Existing property-guided design methods lack a principled way to preserve this geometry during local multiproperty optimization. Here we present RF-PepTune, which separates structural eligibility from property prioritization. Before any property score is queried, RF-PepTune evaluates single substitutions and all position-distinct pairs induced by admitted substitutions to build a parent-specific, pair-complete admission graph. Pareto Monte Carlo tree search then optimizes predicted permeability, solubility, non-fouling, and low-haemolysis scores exclusively within this graph, and selected sequences undergo full structural re-evaluation. In a matched three-arm comparison of 334 parents across MDM2, GABARAP, and MCL1, joint property-structure success rose from 10.2% without admission to 51.5% with single-substitution admission and 77.5% with pair-complete admission; pair-complete gating improved success by 26.0 percentage points over single-substitution gating (95% CI, 20.7-31.4). Property-positive but structure-failing endpoints fell from 88.3% to 9.3%. In a separate target-balanced set, all 90 prioritized outputs improved all four model-native scores while satisfying prespecified structural criteria. This work establishes pairwise structural gating as a general strategy for constrained multi-objective molecular optimization.

bioinformatics↗