Biology subjects

Hu, W.

Publications and source records attributed to Hu, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Intrinsic immune receptor triggering mechanism informs rational chimeric receptor design

The T cell receptor (TCR) couple antigen recognition to T-cell activation and immune homeostasis. As an eight-subunit assembly, TCR activation operates as a highly coordinated, multi-subunit signaling event. However, which subunit serves as the primary trigger upon ligand engagement still remains unresolved. we identify CD3{varepsilon} as a triggering subunit whose intracellular domain (ICD) is released from the plasma membrane during TCR activation. Elevated membrane tension facilitates this transition from a membrane-proximal to a membrane-distal conformation. The released ICD forms condensates through phase separation with free or co-receptor-associated Lck. These condensates recruit additional CD3{varepsilon} ICDs from neighboring TCRs, triggering resting receptors and promoting further recruitment of TCRs and Lck to amplify proximal signaling. The CD3{varepsilon} ICD alone support robust T cell activation independently of its own ITAM. We observe a similar triggering mechanism in several activating receptors in T and nature killer (NK) cell. These findings support a unifying model in which designated subunits initiate multi-subunit immune receptor activation through phase separation with key kinases. Guided by this model, we engineered triggering molecules (TRIG) that lack canonical intracellular signaling modules. These TRIG molecules recruit endogenous immune receptors in a ligand-dependent manner and efficiently activate both T cells and NK cells. This mechanism provides a basis for designing chimeric receptors that activate immune cells through endogenous receptor signaling.

immunology↗

bioRxiv2026

AI-guided discovery of natural pocket proteins for portable small-molecule sensing

Recognition-element development remains an important practical challenge in small-molecule biosensing. Here, we present DWCLASS, an AI-guided workflow that combines screening of natural pocket proteins, molecular dynamics simulations, experimental binding assessment, and portable metasurface plasmonic sensing. Using thiamine (vitamin B1, thiamine) and 25-hydroxyvitamin D3 [25(OH)D3] as model analytes, the workflow identified binding responses in 7 of 16 tested analyte-protein pairs (43.8%). Selected proteins were incorporated into a competitive MetaSPR assay with gold nanoparticle amplification and acoustic mixing. The portable device provided a 240 s measurement step for prepared samples. Serum LODs were 2.98 ppt for thiamine and 3.82 ppt for 25(OH)D. Preliminary measurements of human serum specimens were compared with commercial ELISA to explore performance in biological samples. This study establishes an integrated route from AI-assisted screening of natural proteins to portable assay development for two chemically distinct vitamin analytes. Applicability to additional targets and clinical reference accuracy remain to be established.

bioinformatics↗

bioRxiv2026

METTL1 gene dosage and catalytic activity define a targetable vulnerability in pediatric cancers

METTL1 is responsible for catalyzing N7-methylguanosine (m7G) methylation of tRNAs. METTL1-dependent oncogenic mechanisms include both its methyltransferase catalytic activity and, in specific instances, non-catalytic interactions that maintain aminoacylated tRNA levels in malignant cells. We show that METTL1 copy number gain and elevated expression are a feature of pediatric tumors that are METTL1 dependent, using Cas13-mediated RNA to reduce the threshold of METTL1 mRNA and protein, which disrupts both catalytic and non-catalytic functions. In cell lines with METTL1 gene amplification, specific degradation of METTL1 mRNA impaired colony formation, triggered cell death, and decreased the translation efficiency of a subset of genes enriched for codons decoded m7G-modified tRNAs. METTL1 inhibition was accompanied by downregulation of c-MYC, n-MYC and MCL-1 protein expression. METTL1 silencing synergizes with drugs targeting anti-apoptotic members of the BCL2 family, notably BCL-xL. Importantly, the catalytic activity of METTL1 was required to rescue cells from the deleterious consequences of METTL1 silencing. We conclude that inhibiting the catalytic activity of METTL1 has potential therapeutic efficacy, particularly in tumors with METTL1 amplification. Synergistic combinations with BH3-mimetic drugs may be a promising therapeutic combination.

cancer biology↗

bioRxiv2026

Lineage tracing reveals asynchronous fate restriction in mouse embryos and stem cell-derived embryo models

How a flexible mammalian embryo gives rise to a reproducible body plan remains unclear, partly because cell lineages cannot be followed continuously in vivo. We combined DNA Typewriter lineage recording with tetraploid complementation to reconstruct high-resolution single-cell genealogies across mouse development and built FateVec, an analysis framework that infers fate-bias dynamics and lineage-associated transcriptional programs from reconstructed phylogenies. Loss of developmental potential proved progressive and asynchronous, with multiple lineages acquiring detectable fate bias before morphological diversification at gastrulation. Within the neural crest, most cells remained multipotent over an extended window, while independent founder clades differed markedly in restriction timing. Extending lineage recording to a stem-cell-derived embryo model revealed that cells with shared transcriptional identities can arise from distinct lineage relationships. We further found embryonic-lineage contributions to extraembryonic-like states, exposing an unexplored lineage plasticity. This lineage-resolved view of embryogenesis reveals that cell identity alone predicts neither developmental ancestry nor the timing of fate restriction.

developmental biology↗

bioRxiv2026

Olfactory-mediated host tracking and rapid local adaptation in a seed-feeding wasp

Understanding how specialized herbivores track divergence among their hosts is central to evolutionary biology. Congruent genetic structure between hosts and herbivores is often interpreted as evidence of long-term codivergence, but similar patterns may also arise when herbivores rapidly adapt to pre-existing host differentiation. Here, we integrate population genomics, host volatile profiling, and behavioral assays to examine host-associated divergence in the obligate seed-feeding wasp Megastigmus daduheensis and its conifer host Cupressus chengiana across three river valleys on the eastern Qinghai-Tibet Plateau. Despite strong phylogeographic congruence between each of the three wasp and host lineages, calibrated demographic analyses indicate that wasp divergence occurred during the early Holocene, substantially later than the Pliocene-Pleistocene divergence of host lineages. This temporal mismatch is inconsistent with strict long-term codivergence and instead supports rapid host tracking in a topographic complex region. Host lineages differed in volatile organic compound profiles, and behavioral assays showed that wasps were preferentially attracted to volatiles from their local host lineages. These results identify olfactory-mediated host recognition as a plausible mechanism promoting host fidelity and reinforcing host-associated genomic and behavioral differentiation. Our findings show that apparently concordant host-herbivore divergence can emerge over compressed evolutionary timescales through rapid local adaptation, highlighting how ecological differentiation can accumulate within species through host tracking.

evolutionary biology↗

bioRxiv2026

Biologically grounded cell profiling across microscopy modalities

Microscopy-based cell profiling has broad applications in biological discovery, disease characterization, and phenotypic drug screening. Modern microscopy continues to push the limits of resolution, speed, depth and throughput, but better imaging does not automatically lead to better biomedical discovery and translation. A key bottleneck is feature representation: existing features are either handcrafted or learned as black-box embeddings and often lack explicit biological meaning. Here we propose biological grounding as a first principle for cell profiling and implement it through MorphAgent, an AI agent framework in which each quantitative feature originates from a biological hypothesis and is anchored to a cellular structure or process. By integrating biological knowledge, multimodal reasoning and automated validation, MorphAgent makes biologically grounded feature design systematic and scalable. We show biological grounding fundamentally changes the properties of cell profiling features. Across three microscopy modalities, MorphAgent produces compact, expressive and transferable features for drug screening, cell state characterization and disease morphology analysis. In wide-field Cell Painting, a common assay for phenotypic drug screening, it improves perturbation-retrieval mean average precision by 48% over CellProfiler and 20% over DeepProfiler while using substantially fewer dimensions. In confocal mitochondrial imaging, biologically grounded features transfer across independently acquired datasets and imaging resolutions, supporting accurate aging-state classification. In structured illumination microscopy (SIM) imaging of Tau-labeled samples, biologically grounded super resolution features reveal nanoscale morphologies inaccessible at conventional resolution, enhancing the discrimination of disease-associated mutations. Moreover, biologically grounded features provide a hierarchical organization of cellular morphology, enabling multilevel alignment with transcriptomics data and facilitating mechanistic understanding. Biologically grounded cell profiling thus brings AI reasoning closer to biological mechanisms, advancing biomedical discovery and translation.

bioinformatics↗

bioRxiv2026

BLTP3A dysfunction unleashes lysosomal stress-induced antitumor immunity through STING

High-grade serous ovarian cancer progresses within a lipid-rich ascites microenvironment that engages stress-adaptation programs supporting malignant growth, yet how failed stress resolution influences tumor progression remains incompletely defined. Here, we show that unresolved lysosomal stress restrains tumor progression by sustaining tumor cell-intrinsic STING activity and reorganizing antitumor immunity. We identify BLTP3A as a lysosomal stress-resolution factor in ovarian cancer and show that the common germline missense variant BLTP3A M1098T increases stress-induced lysosomal damage. Patients carrying M1098T had longer overall survival and tumors enriched for cytotoxic T cell-myeloid neighborhoods. In syngeneic tumors, Bltp3a loss or orthologous variant expression delayed progression and generated Cxcl9+ antigen-presenting macrophage niches; M1098T-expressing human tumors similarly promoted interferon-responsive myeloid and T-cell enrichment in humanized mice. Mechanistically, ascites-induced lysosomal stress activated a STING-ATF4-BLTP3A feedback program. BLTP3A dysfunction disrupted CASM-associated lysosomal stress resolution, resulting in prolonged STING activity and sustained tumor-derived IFN-{lambda} without increased cGAMP. Tumor-cell STING and IFN-{lambda} were required for immune remodeling and tumor control. Thus, BLTP3A-dependent lysosomal stress resolution constrains the persistence of stress-induced STING signaling, whereas failure of this response sustains a tumor-intrinsic inflammatory program that organizes protective antitumor immunity.

cancer biology↗

bioRxiv2026

β-arrestin1 directly engages Gαs to sustain endosomal GPCR signaling

{beta}-arrestins ({beta}arrs) are canonical terminators of G protein-coupled receptor (GPCR) signaling, yet internalized receptors paradoxically sustain {beta}arr-dependent Gs/cAMP signaling from endosomes. How a desensitizing scaffold can instead promote G protein activation has remained unresolved, because the receptor-{beta}arr-G protein assemblies described so far position the two transducers on opposite faces of the receptor, with no contact between them. Using the parathyroid hormone type 1 receptor (PTH1R), we show that {beta}arr1 binds Gs directly, engages its nucleotide-free state, and does so far more strongly than it engages G{beta}{gamma}. A cryo-EM structure of the agonist-bound PTH1R-{beta}arr1-Gs complex at ~3.1 &Aring resolution reveals how: {beta}arr1 anchors to the phosphorylated receptor C-tail, leaving the transmembrane core free for Gs, and reorients to build a direct, three-node interface in which its finger, C- and back loops clamp the Switch I, Switch II and 3/{beta}5 regions of Gs. Disrupting either side of this interface abolishes complex assembly and selectively collapses the internalization-dependent phase of cAMP production, and the same interface governs {beta}arr1-Gs coupling at the glucagon-like peptide-1 receptor. {beta}-arrestin1 therefore acts as a positive regulator that holds Gs in a signaling-competent state, providing a unifying structural basis for sustained endosomal GPCR signaling.

biochemistry↗

bioRxiv2026

Unifying physical and molecular coordinate systems across modalities in spatial biology

Establishing a unified physical and molecular coordinate system from fragmented multi-modal data is a longstanding challenge in biology. Here, we present MAPS, a modality-agnostic platform for spatial biology comprising (1) MAPS-alignment for ultrafast alignment of any modality, (2) MAPS-integration for both anchored and unanchored integration across orthogonal modalities for 3D multi-modal reconstruction, and (3) MAPS-Explorer for large-scale interactive 3D analysis. MAPS outperformed existing methods across extensive benchmarks on 34 datasets spanning 16 technology platforms and 6 modalities, while delineating fine-grained multi-modal tissue architectures across diverse biological systems in mouse and human. At cross-consortium scale, MAPS integrated 434 slices comprising 21 million cells from 18 atlases and 5 modalities to construct the most comprehensive 3D multi-modal mouse brain atlas. At individual laboratory scale, MAPS empowered routine 2D spatial assays to reconstruct continuous 3D multi-modal landscapes of human hepatocellular carcinoma, revealing the limitations of 2D spatial relationships and uncovering depth-dependent immune-state transitions.

bioinformatics↗

bioRxiv2026

Molecular principles for graded activation of dopamine D1 receptor

G protein-coupled receptors (GPCRs) signal across a continuum of activation states, yet how ligands encode distinct signaling efficacies remains poorly understood. Here, we define the molecular mechanism underlying graded activation of the dopamine D1 receptor (D1R), a major therapeutic target for neuropsychiatric disorders. Functional analyses reveal that two widely used pharmacological tools, LE300 and SCH23390, possess intrinsic efficacy as an inverse agonist and a weak partial agonist, respectively, rather than the efficacy-silent neutral antagonists. Structural, molecular dynamics and mutagenesis analyses capture previously unrecognized inactive and intermediate receptor activation states that bridge known active conformations, and reveal that ligand efficacy is encoded through the progressive engagement of a conserved activation pathway centered on the W6.48 toggle switch. Guided by this mechanism, a single chemical modification markedly increases the agonist efficacy of SCH23390. Comparison with dopamine D2 receptor structures further reveals a conserved mechanism of inverse agonism despite distinct subtype-specific recognition. Together, these findings establish a structural framework for graded agonism at D1R and provide general principles for the rational design of efficacy-tuned therapeutics at dopamine receptors and related GPCRs.

biochemistry↗

bioRxiv2026

FXR-mediated recruitment of PPP1CB suppresses SMAD2/3 phosphorylation to mitigate pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease with limited treatment options and poorly understood molecular underpinnings. Dysregulated TGF-{beta}/SMAD signaling is a key driver of fibrotic remodeling, promoting persistent myofibroblast activation and excessive extracellular matrix deposition. Here we identify the Farnesoid X receptor (FXR), a bile acid activated nuclear receptor, as a previously unrecognized suppressor of pulmonary fibrosis. FXR expression is significantly reduced in lung tissues from patients with PF and in myofibroblasts derived from BLM-induced mouse models, correlating inversely with fibrosis severity. Genetic ablation of FXR exacerbates BLM-induced pulmonary fibrosis by promoting fibroblast hyperactivation and dysregulation of the TGF-{beta}/SMAD signaling pathway. Mechanistically, we identify PPP1CB as a previously unrecognized FXR-interacting protein in primary myofibroblasts derived from IPF patients. We further show that FXR both increases chromatin accessibility at the PPP1CB locus and assembles a functional complex with PPP1CB, which in turn promotes SMAD2/3 dephosphorylation and suppresses their nuclear translocation. Notably, the clinical-stage FXR agonist TERN101 exhibits potent therapeutic efficacy in a BLM-induced mouse pulmonary fibrosis model. These findings establish FXR as a critical antifibrotic regulator in lung tissue and suggest that pharmacological activation of FXR may offer a promising therapeutic strategy for IPF.

cell biology↗

bioRxiv2026

The secreted elastase SjCE2b drives host skin penetration by Schistosoma japonicum

Cercarial elastase is the most abundant protease secreted by Schistosoma mansoni and plays a critical role in cercarial invasion. Although Schistosoma japonicum encodes only a single elastase, SjCE2b, its secretion by cercariae and its specific function in skin penetration have remained elusive. Here, we report the first proteomic analysis of S. japonicum cercarial excretory-secretory products (ESPs) induced by linoleic acid or mouse skin, confirming the presence of SjCE2b in both ESPs preparations. Recombinant SjCE2b expressed in Pichia pastoris was characterized as a trypsin-like serine protease whose activity is entirely abolished by the elastase inhibitor MeoSuc-AAPF-CMK. Furthermore, SjCE2b expression was detected exclusively in cercarial extracts and localized specifically to the cercarial acetabular glands and ducts. Subsequent proteomic analysis indicates that SjCE2b can degrade numerous human epidermal proteins, including ten isoforms of type I and type II keratins. In vitro digestion assays further demonstrated that SjCE2b can digest key structural components of the dermis, including elastin, collogen, and fibronectin. Additionally, the cleavage of complement component C3 and immunoglobulins (IgA and IgG) suggests that SjCE2b may facilitate immune evasion by newly transformed schistosomula. Critically, the incubation of cercariae with anti-rSjCE2b antibody reduced the worm burden by 80.85%, confirming the essential role of SjCE2b in the skin penetration of S. japonicum cercariae and highlighting it as a compelling candidate for vaccine or therapeutic development. Author SummarySchistosomiasis constitutes a major global health burden caused by parasitic flatworms of the genus Schistosoma. Proteolytic and histolytic enzymes secreted by cercarial pre- and post-acetabular glands facilitate disruption of the host skin barrier and protect the parasite from localized dermal inflammatory response. Although cercarial elastase is a well-characterized invasion enzyme in Schistosoma mansoni, its role in Schistosoma japonicum remains poorly defined; consequently, S. japonicum cercariae have been hypothesized to rely on distinct repertoire of proteolytic enzymes during skin penetration. In the present study, we showed that SjCE2b was localized to the cercarial acetabular glands and ducts, and was secreted upon stimulation with linoleic acid or mouse skin. Functionally, SjCE2b can disrupt host skin integrity by degrading epidermal and dermal components, and may promote immune evasion through cleavage of complement component and immunoglobins. Furthermore, the antibody-mediated neutralization of secreted SjCE2b significantly impaired parasite penetration by greater than 80%. Together, these findings establish SjCE2b as a critical enzyme required for S. japonicum cercariae invasion and highlight its potential as a promising target for novel therapeutic interventions.

microbiology↗

bioRxiv2026

Humanized tauopathy chimeras uncover microglial and lncRNA strategies for neuroprotection

Human genetics implicates innate immunity as a key modifier of tau toxicity, yet human-specific neuroimmune mechanisms remain difficult to test in vivo. Here, we developed HuMiNAX, the first humanized iPSC-based neuroimmune xenograft model of tau-associated neurodegeneration, enabling human microglia to interact with human neurons and astrocytes in the adult mouse brain. In HuMiNAX, tau seeding induced aggregation only in mutation-carrying human neural grafts, causing neuron loss and inflammatory activation of human microglia. Progranulin-overexpressing human microglia dampened tau-associated inflammation, preserved neurons, and restored neuronal gene-expression and RNA-splicing programs, supporting microglial control of neuronal resilience. CRISPRi knockdown of the human-specific lncRNA HNRNPK-AS1 also protected neurons in HuMiNAX. These findings establish HuMiNAX as a human neuroimmune model of tauopathy and identify microglial and RNA-mediated strategies of neuronal resilience.

neuroscience↗

bioRxiv2026

Statistical tests for bivariate spatial association across multi-omics data with disjoint coordinates

Spatial biology has entered a new era of multimodal profiling, with multiple, high-dimensional spatial omics types being measured on consecutive tissue slices, or co-assayed on the same slice. Interest then lies in statistical testing for spatial association between the features of the different modalities, to gain insight in biological processes. One major challenge is the multitude of bivariate combinations, leading to high computational demands. Another difficulty is the difference in spatial resolution between technologies, implying no one-to-one matching between the measurement spots of the different modalities, even after alignment. As a result, common statistical measures such as joint distributions and correlations are not defined, and tests need to rely on spatial vicinity only. Moreover, we argue that many existing bivariate association tests address an inappropriate null hypothesis, or make inappropriate assumptions, both implying absence of spatial autocorrelation in any of the features and leading to misleading conclusions. As a remedy, we modify tests for the detection of spatially variable genes (Morans I, Gaussian processes and generalized additive models) to derive bivariate spatial association tests across modalities with non-overlapping coordinate sets, and provide variance estimators that do account for spatial autocorrelation. We develop inference methods for single sections as well as for replicated experiments with multiple sections, and compare their performance in nonparametric and parametric simulations. Finally, we apply the newly developed methods to two co-assayed spatial transcriptomics and metabolomics datasets from mouse and human. The full suite of tests is available from github.com/sthawinke/sbivar as the R-package sbivar. Author summarySpatial biology investigates molecules and cells in their spatial context in living tissues. For this purpose, recent technologies measure different classes of biomolecules on the same or adjacent tissue sections. Here we focus on methods to detect colocalisation of molecule pairs, which may provide clues on their biological function, e.g. involvement in the same pathways. Many existing tests for identifying such colocalized pairs rely on the two technologies being measured on the exact same locations, which is often not the case due to differences in resolution. Hence they first require location matching by granulating the technology with the best resolution to that of the worst, discarding information and failing to exploit the full spatial resolution of the data. Moreover, existing methods ignore spatial patterning or autocorrelation naturally present in spatial omics data, leading to many false findings. As a remedy, we present a suite of scalable methods that work directly on disjoint coordinate sets and do account for spatial autocorrelation, and confirm their validity in simulation studies. Next we apply the new methods to metabolite and gene expression measurements of mouse and human datasets, uncovering interesting colocalized gene-metabolite pairs. The methods presented are available in the sbivar R-package from github.com/sthawinke/sbivar.

bioinformatics↗

bioRxiv2026

A glycoRNA switch for malignancy: SNORA73B activates TIAR-dependent oncogenic signaling in lung adenocarcinoma

Although glycosylated small non-coding RNAs are emerging players in cancer, their functions in lung adenocarcinoma (LUAD) are largely unknown. We identify SNORA73B as a glycosylated small nucleolar RNA (glycol-snoRNA) that carries sialic acid-capped O-glycans in both normal lung epithelial and LUAD cells. SNORA73B is markedly elevated in LUAD, and its plasma levels distinguish early-stage LUAD from healthy controls with an area under the curve (AUC) of 0.7903. Subcellular fractionation reveals predominant nuclear localization. Functional assays demonstrate that SNORA73B depletion curbs LUAD cell proliferation, migration, and invasion, whereas its overexpression fosters these malignant phenotypes and accelerates tumor growth. Mechanistically, SNORA73B directly binds the T-cell-restricted intracellular antigen-related protein (TIAR), thereby enhancing TIAR protein abundance without affecting its mRNA levels. TIAR then recognizes the 3-untranslated region (3-UTR) of MYC mRNA to upregulate c-Myc, which subsequently augments AKT phosphorylation. Importantly, c-Myc knockdown largely rescues the oncogenic phenotypes and tumorigenesis induced by SNORA73B overexpression. Collectively, our data unveil a glycoRNA-dependent oncogenic axis SNORA73B-TIAR-c-Myc-AKT that drives LUAD progression. These findings position SNORA73B as a promising early diagnostic biomarker and a candidate therapeutic target in LUAD.

Cancer Biology↗

bioRxiv2026

Structural Basis of Nidovirus Replication Organelle Evolution Revealed by the Arterivirus DMV Pore Complex

Positive-strand RNA viruses of the order Nidovirales - which include coronaviruses and arteriviruses - remodel host membranes into double-membrane vesicles (DMVs) as replication organelle to shield viral RNA synthesis from immune sensors. In coronaviruses, newly synthesized RNA is exported to the cytoplasm through a massive DMV pore complex formed by viral non-structural proteins (nsps). However, it remains unknown whether this elaborate architecture is unique to large-genome coronaviruses or a universal hallmark of the order. Here, we integrate in situ cryo-electron tomography and single-particle cryo-electron microscopy to resolve the atomic structure of DMV pore complex within its native membrane environment, from Equine Arteritis Virus (EAV), a prototype arterivirus with small genome. Despite lacking obvious sequence homology, the minimal EAV pore shares conserved architectural principles with its elaborate coronavirus counterpart. EAV pore complex is formed by a 12:12 stoichiometry of nsp2 and nsp3 protomers organized into four stacked concentric rings on double-membrane, yet generating pronounced structure symmetry mismatch. Functionally, the complex displays a distinct pore profile while preserving a positively charged central channel, essential for viral replication and transport. These findings demonstrate that, despite diversity in genome size and virion morphology, nidovirus replication organelles exhibit striking evolutionary conservation at the atomic structural level. Collectively, we propose that the order Nidovirales can be unified at the ultrastructural level by this conserved signature pore complex on the DMV-based replication organelle.

microbiology↗

bioRxiv2026

Singlet-states-mediated highly efficient two-photon fluorescence in organic dyes

This study reports a brand-new continuous-wave-excited (CW-excited) two-photon fluorescence emission mechanism in indocyanine green (ICG), an organic fluorescent dye widely used in clinical practice. This mechanism is based on the excited state absorption (ESA) process of the first singlet excited state. Intramolecular electrons sequentially absorb two photons to reach a high-energy singlet excited state, followed by direct radiative transition to the ground state to generate fluorescence. The entire process is exclusively mediated by singlet states. We further summarize the essential requirements for organic dyes to realize this luminescence mechanism. First, the dye must possess at least two well-separated singlet excited states with distinct energies, corresponding to two absorption peaks at different wavelengths in the absorption spectrum. The wavelength of the high-energy singlet excited state is about half that of the first singlet excited state. Second, the peak in the absorption spectrum corresponding to the transition from the ground state to the first singlet excited state has a sufficiently large molar extinction coefficient. Third, the first singlet excited state exhibits the capability of ESA. Fourth, electrons at the high-energy singlet excited state can directly transit to the ground state and emit fluorescence. We validated this mechanism in a variety of organic dyes satisfying the above conditions, confirming its universality. Using CW laser as the excitation source, we achieved two-photon fluorescence imaging of mouse cerebral blood vessels at a depth of 400 m, which clearly resolves three-dimensional vascular networks with high resolution. We also performed two-photon fluorescence imaging on human gastric cancer tissue samples at a depth of around 150 m, which provides a low-cost strategy for clinicians to rapidly acquire high-contrast tumor tissue images.

bioengineering↗

bioRxiv2026

Annotation-free sequence-level multimodal graph learning reveals gut microbiome signatures of atherosclerotic cardiovascular disease

BackgroundAtherosclerotic cardiovascular disease (ACVD) remains one of the leading causes of mortality, and the gut microbiome has been implicated in ACVD-related metabolic and inflammatory processes. However, current microbiome-based disease prediction frameworks predominantly rely on annotation-dependent taxonomic or pathway-level abundance profiles. While effective for community-level association analysis, these approaches compress metagenomic information into predefined biological categories and may consequently obscure fine-grained sequence variation, uncharacterized microbial fragments, regulatory sequence signals and sequence-based structure information embedded within metagenomic DNA. Whether disease-relevant microbiome information can be directly learned from raw metagenomic sequences without prior annotation remains incompletely explored. ResultsWe developed MLMGCN-CVD, an annotation-free sequence-level multimodal graph-learning framework for ACVD prediction directly from gut metagenomic DNA fragments. Rather than relying on taxonomic aggregation, MLMGCN-CVD integrates pretrained genomic language-model embeddings, sequence-derived structural priors, and read-mapping quantitative evidence to learn disease-associated representations at the DNA fragment level. In a primary cohort comprising 218 ACVD patients and 187 healthy controls, MLMGCN-CVD achieved an area under the receiver operating characteristic curve (AUC) of 0.978 under grouped 10-fold cross-validation. External validation on an independent cohort (PRJNA615842) yielded an AUC of 0.940, outperforming relative- abundance-, pathway-, and sequence-only reference frameworks. Importantly, model-prioritized fragments independently recovered multiple microbiome-associated functions previously implicated in ACVD, including trimethylamine (TMA) metabolism, O-antigen of lipopolysaccharide (LPS) biosynthesis, phosphotransferase systems (PTS), and Enterobacteriaceae-associated modules. Beyond these established signatures, Rfam-supported analyses identified candidate regulatory RNA-associated signals, including riboswitches and Bacterial small RNAs, suggesting that regulatory sequence information may contribute previously underexplored discriminatory signals within the ACVD gut microbiome. Several representative sequence elements further showed significant correlations with host cardiometabolic indicators. ConclusionsOur findings suggest that microbiome-associated disease signals extend beyond conventional taxonomic or pathway abundance summaries and can be directly inferred from raw metagenomic sequences. By shifting microbiome modelling from annotation-dependent community aggregation toward annotation-free sequence-level representation learning, MLMGCN-CVD provides a framework for uncovering biologically informative regulatory and functional signals embedded within metagenomic data.

bioinformatics↗