Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 433 records · Page 24Linked to original sources

bioRxiv2026

Nab-paclitaxel fused with the de novo designed receptor binder exhibits enhanced tumor targeting and therapeutic efficacy

Chemotherapy has been widely used in cancer treatment, but most of the chemotherapeutic drugs rely mainly on passive accumulation due to lack of target specificity, which may lead to systemic toxicity and limited clinical utility. Recent advances in artificial intelligence-based protein design provide new opportunities for developing precision therapeutics. Here we modify the albumin-bound paclitaxel (Nab-PTX), one of the most widely used drugs in chemotherapies, by applying the fusion proteins of albumin with the de novo designed protein binders targeting human EGFR or HER2. The resulting particles, EGFRmb-Nab-PTX and HER2mb-Nab-PTX, retain the similar physicochemical properties of Nab-PTX while acquiring the receptor-specific binding capacities. The in vitro assays show that both binder-modified Nab-PTX particles have increased uptake and inhibitory effects significantly in the cancer cell lines with high receptor expression levels. Furthermore, the data from a xenograft model, including tumor growth, excised tumor analysis, organ histology, and fluorescence imaging, show that the binder-modified Nab-PTX enhances tumor accumulation, improves tumor suppression, and reduces off-target toxicity compared with the conventional Nab-PTX, suggesting that they may have promising clinical potential in cancer treatment. Overall, this strategy provides an adaptable modular platform for generating albumin-based chemotherapeutic drugs with target specificities, which can be readily customized with diverse target binders to enable precise cancer therapies.

cancer biology↗

bioRxiv2026

FluNexus: a versatile web platform for antigenic prediction and visualization of influenza A viruses

Influenza A viruses continuously undergo antigenic evolution to escape host immunity induced by previous infections or vaccinations, consequently causing seasonal epidemics and occasional pandemics. Antigenic prediction and visualization of influenza A viruses are crucial for precise vaccine strain selection and robust pandemic preparedness. However, a user-friendly online platform for these capabilities remains notably absent, despite widespread demand. Here, we present FluNexus (https://flunexus.com), the first-of-its-kind, one-stop-shop web platform designed to facilitate the prediction and visualization of the antigenic change in emerging variants. FluNexus features a data preprocessing module for hemagglutinin subunit 1 (HA1) and hemagglutination inhibition (HI) data across three major public health threat subtypes (H1, H3 and H5). Meanwhile, FluNexus provides an interactive interface for online antigenic prediction and offers practical guidance for researchers. Most notably, FluNexus offers the visualization of influenza A virus antigenic evolution, providing intuitive insights into its antigenic dynamics. Specially, FluNexus proposes a novel manifold-based method for positioning antigens and antisera, generating accurate antigenic cartographies even with sparse HI data. By alleviating the programming burden on biologists, FluNexus supports more informed decision-making in vaccine strain selection and strengthens surveillance and pandemic preparedness. HighlightsO_LIFluNexus features a data preprocessing module for HA1 and HI data spanning the H1, H3, and H5 subtypes. C_LIO_LIFluNexus facilitates online antigenic prediction utilizing ten state-of-the-art antigenic prediction tools, and offers practical guidance based on a comparative evaluation of their performance. C_LIO_LIFluNexus provides a visualization module for mapping antigenic evolution of influenza A viruses, incorporating a novel manifold-based method for antigenic cartography. C_LI

bioinformatics↗

bioRxiv2026

YY1-Mediated Polycomb Group Function Safeguards Hematopoietic Stem Cells from Premature Aging

Hematopoietic stem cells (HSCs) undergo functional decline with age, characterized by myeloid-biased differentiation, loss of quiescence, and altered metabolic homeostasis. The molecular mechanisms driving these changes remain incompletely understood. Yin Yang 1 (YY1) is a multifunctional transcription factor and mammalian Polycomb group (PcG) protein that recruits PcG complexes to specific genomic loci via its 26-amino acid REPO (Recruitment of Polycomb) domain. To define the role of YY1 PcG function in adult HSCs, we generated a conditional YY1 REPO domain knockout mouse model (Yy1-/{Delta}REPO). Deletion of the REPO domain led to premature HSC aging, with expansion of immunophenotypic HSCs but loss of long-term self-renewal capacity. Yy1-/{Delta}REPO HSCs exhibited myeloid-biased output, expansion of myeloid-primed multipotent progenitors, increased myeloid colony formation, and an elevated myeloid-to-lymphoid ratio in peripheral blood. These cells displayed reduced quiescence, elevated reactive oxygen species, increased mitochondrial oxidative capacity, and enhanced {beta}-galactosidase activity--hallmarks of cellular aging. RNA-seq demonstrated dysregulation of gene networks governing HSC metabolism. Together, these findings establish YY1 PcG activity as a key epigenetic mechanism that preserves metabolic quiescence, sustains long-term self-renewal, and delays HSC aging. Our studies reveal a fundamental PcG-dependent epigenetic mechanism that dictate cell fate decisions and function decline during HSC aging.

molecular biology↗

bioRxiv2026

Indole-3-acetic acid production is rare among gut bacteria and reflects OFOR-driven amino acid oxidation in acetogens

Indole-3-acetic acid (IAA) is a tryptophan-derived gut microbial metabolite with reported anti-inflammatory activities, but the organisms and anaerobic pathways that support robust production remain unclear. Screening 206 human gut bacterial isolates by LC-MS revealed that IAA production is rare: only five strains exceeded the limit of quantitation, and high-capacity production was confined to the acetogens Blautia hydrogenotrophica and Intestinibacter bartlettii. Across growth conditions, IAA was a minor product that rose alongside carbohydrate-sensitive, OFOR-linked catabolism of multiple amino acids, generating abundant branched-chain and aromatic organic acids. In gnotobiotic mice mono-colonized with I. bartlettii, these metabolites were produced in vivo but showed distinct host handling, with branched-chain fatty acids largely extracted between portal and peripheral plasma, whereas aromatic acids and their glycine conjugates appeared in plasma and urine. Genomic analyses and heterologous enzyme assays identified expanded repertoires of 2-oxoacid:ferredoxin oxidoreductases (OFORs) with activities spanning pyruvate/oxaloacetate, branched-chain, and aromatic 2-oxoacids, including indolepyruvate conversion to indoleacetyl-CoA, a putative intermediate en route to IAA. Finally, position-specific 13C tracing showed that CO2 released during amino acid oxidation is reassimilated into acetate via reductive acetogenesis, indicating that gut acetogens can maintain redox balance without fermenting partner strains. Together, these findings show that high IAA output is restricted to select gut acetogens and linked to a broader OFOR-driven anaerobic metabolism that generates additional metabolites that are absorbed by the host.

microbiology↗

bioRxiv2026

EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery

Pathogenic variants in EXOSC3, a noncatalytic subunit of the RNA exosome, cause pontocerebellar hypoplasia type 1B (PCH1B), yet substantial variability in disease severity is observed among individuals carrying different EXOSC3 alleles. The molecular mechanisms of RNA exosome dysfunction in individuals carrying EXOSC3 p.G191 variants remains unresolved. To address this, we generated CRISPR/Cas9-engineered human cell models harboring EXOSC3 p.G191 variants and performed integrated transcriptomic, proteomic, and computational structural analyses. EXOSC3 p.G191 variants produced extensive, allele- and dosage-dependent alterations in gene expression and splicing, with heterozygous variants causing broad but attenuated disruption relative to homozygous EXOSC3 G191D/G191D cells. All EXOSC3 G191 variants promoted increased skipping of exon 3 in EXOSC3 transcripts, generating a short isoform predicted to encode an unstable proteoform. Molecular dynamics and {lambda}-dynamics simulations predicted substantial thermodynamic destabilization of all EXOSC3 G191 variant proteoforms, consistent with reduced protein abundance and thermal stability measured by global proteomics and PISA. At the protein complex level, EXOSC3 p.G191 variants were associated with coordinated decreases in all RNA exosome core subunits and the exonuclease EXOSC10, consistent with destabilization of RNA exosome assembly and orphan protein decay. In contrast, the catalytic exonuclease DIS3 and multiple independent RNA processing pathways were upregulated, indicating compensatory recalibration of RNA metabolism. Together, these findings link variant-induced alternative splicing, RNA exosome complex destabilization, and adaptive network responses to phenotypic variability in EXOSC3 p.G191-associated disease.

systems biology↗

bioRxiv2026

Inhibition of KDM5A/B promotes antitumor innate immune responses in HHV-8/KSHV2 positive B-cell lymphomas

Summary/AbstractHistone methylation is a dynamic and reversible epigenetic modification that critically controls the progression of human diseases, including infections and cancers. Here we reported that histone lysine demethylases (KDMs) in the KDM5 family KDM5A/B play profound roles in suppressing lytic reactivation of oncogenic human herpesvirus 8 (HHV-8), i.e., Kaposis sarcoma-associated herpesvirus (KSHV), as well as antiviral/antitumor innate immune responses in KSHV-infected B-cell lymphomas. We showed that KSHV lytic replication decreases KDM5A/B protein stability by enhancing their K-48 linked polyubiquitination while KDM5A/B depletion facilitates KSHV lytic reactivation. Mechanistic studies illustrated that KDM5A/B associate with KSHV LANA protein and dampen its chromatin association at both KSHV viral lytic promoter and promoters of antitumor immune-responsive genes (IRGs). In comparisons to normal B cells, KDM5A/B expression significantly increased in B-cell lymphoma cells, including KSHV-positive primary effusion lymphoma (PEL). We demonstrated that KDM5A/B inhibition remarkably induces both KSHV lytic reactivation and innate immune responses in PEL cells, resulting in a strong viral oncolytic effect, both in vitro in cell cultures and in vivo using a PEL xenograft mouse model. Overall, our studies identified the novel functions of KDM5A/B to silence KSHV lytic replication and antiviral/antitumor innate immune responses, which can be blocked to benefit the treatment of KSHV-associated B-cell lymphomas that are usually aggressive and difficult to treat.

microbiology↗

bioRxiv2026

Data-Driven Retrieval of Effective Point Spread Functions for Super-Resolution Optoacoustic Imaging

Localization-based super-resolution techniques have revolutionized biomedical imaging by surpassing classical diffraction limits. However, their performance is fundamentally constrained by distortions of the point spread function (PSF) induced by the system and the sample, which are particularly prominent in the case of spatially under-sampling. Here we introduce a data-driven effective point spread function retrieval (DEPR) method that directly learns continuous, field-dependent system responses from experimental point source datasets. Through statistical aggregation of thousands of targets and iterative self-supervised refinement, DEPR captures spatially variant imaging characteristics in situ without prior assumptions or external calibrations. When integrated into the localization optoacoustic tomography (LOT) pipeline, DEPR achieves accurate sub-pixel localization despite under-sampled conditions, thus enhancing resolution while reducing computational burden. We demonstrate its efficacy by in vivo imaging of the murine brain microvasculature using microparticle contrast agents in the first (NIR-I) and second (NIR-II) near-infrared windows, achieving significant improvement in data utilization efficiency and substantial reduction of gridded artifacts compared to conventional approaches. The method resolves vascular structures with [~]41 m separation across a [~]3 mm imaging depth range. This framework addresses fundamental challenges shared across diverse localization-based imaging modalities, offering a robust and generalizable strategy for high-precision imaging in complex biological systems.

neuroscience↗

bioRxiv2026

Dual-channel graph learning reveals similarity and complementarity in protein-protein interaction networks

Protein-protein interactions (PPIs) are governed by two fundamental interfacial mechanisms: similarity-driven, often involving symmetric structural motifs, and complementarity-driven, arising from geometric and physicochemical matching between binding surfaces. Despite their biological significance, computational models have largely overlooked the coexistence and interplay of these twofold interaction modes. Here, we introduce DMG-PPI, a dual-channel graph neural network framework that jointly models similarity and complementarity in PPI networks, extending prior heterophilous GNN concepts to explicitly disentangle these dual interaction modes. The model consists of two parallel message-passing pathways: Alignment Message Passing (AMP), which aggregates signals from similar neighbors to capture symmetric interfaces, and Divergence Message Passing (DMP), which contrasts node features to extract complementary binding patterns. The signals captured by AMP and DMP are integrated via an adaptive fusion strategy within each block, and the outputs of blocks are aggregated using the MixHop framework to encode higher-order interaction patterns. DMG-PPI substantially outperforms state-of-the-art methods on classical benchmark datasets, achieving a 7.19% improvement in Micro-F1 over the second-best method. Additionally, the dual-channel framework provides interpretable insights into key binding residues by identifying interfacial mechanisms. Overall, DMG-PPI serves as a powerful tool that reveals the mechanisms behind accurate PPI predictions and facilitates downstream biological analysis. Author summaryProteins interact through multiple interfacial principles rather than a single uniform mechanism, reflecting diverse modes of molecular recognition between binding partners. Accurately modeling this heterogeneity remains a central challenge in protein-protein interaction (PPI) prediction. Existing computational approaches often overlook such complexity and treat all interactions as arising from a dominant pattern. To address this limitation, we present DMG-PPI, a dual-channel graph neural network framework designed to account for distinct interaction principles within a unified model. By modeling both similarity-based and complementarity-based interaction signals, DMG-PPI enables a more comprehensive representation of interaction patterns in PPI networks. Evaluations on widely used benchmark datasets demonstrate that our approach achieves robust and consistent improvements over existing methods. Beyond prediction accuracy, DMG-PPI provides biologically meaningful interpretability by highlighting key residues and revealing distinct interfacial interaction mechanisms, offering valuable insights for downstream structural and functional studies.

bioinformatics↗

bioRxiv2026

Electro-Calcium uncoupling precedes neurodegeneration in Alzheimers disease

Alzheimers disease (AD) is categorized as a neurodegenerative disease, but there is a growing recognition of the vascular components in AD pathophysiology. Reduction in cerebral perfusion is routinely observed in AD patients and preclinical models prior to overt clinical symptoms. However, there is a limited mechanistic understanding of the early neurovascular deficits in AD, and how these may ultimately contribute to pathology. Here, we investigated the mechanisms of early neurovascular dysfunction in AD by using 3-month-old 5xFAD mice, a familial mouse model of AD. Functional hyperemia--the increase in cerebral blood flow (CBF) in response to neuronal activity--is driven by inward rectifier K+ (Kir2.1)-mediated hyperpolarizing (electrical) signals and Ca2+-dependent nitric oxide production within the capillary endothelial cells (cECs). Electrical and Ca2+ signals are tightly coupled through cECs membrane potential, referred to as Electro-Calcium (E-Ca) coupling. We hypothesize that E-Ca uncoupling contributes to impaired functional hyperemia in 5xFAD mice and that these neurovascular deficits precede the neurodegeneration and cognitive decline. At three months of age, 5xFAD mice did not exhibit any impairment in spatial learning and memory, or neuronal density. However, whisker stimulation-induced functional hyperemia was significantly reduced in 5xFAD mice compared to controls. Functional hyperemia exhibited a bimodal response in controls--consisting of fast and slow phases--with the slow phase being significantly reduced in 5xFAD mice. To identify mechanisms underlying these deficits, we measured cortical neuronal and endothelial Ca2+ activity using in-vivo imaging. Neuronal Ca2+ activity was comparable between controls and 5xFAD mice, while cECs Ca2+ activity was significantly reduced in 5xFAD mice. Moreover, Kir2.1 channel blocker, barium (100 M) significantly suppressed cECs Ca2+ activity in controls, but not in 5xFAD mice, consistent with crippled E-Ca coupling. Despite these vascular functional impairments, capillary density was preserved in 5xFAD mice. TRPV4 channels are one of the major Ca2+ entry pathways in cECs and potentiate E-Ca coupling. cECs TRPV4 current density was significantly reduced in 5xFAD mice while Kir2.1 current density was unchanged, indicating that impaired TRPV4 function underlies the E-Ca uncoupling. In summary, early E-Ca uncoupling leads to impaired functional hyperemia in 5xFAD mice and may contribute to later neuronal and cognitive decline.

neuroscience↗

bioRxiv2026

Basal ppGpp regulation by SpoT coordinates metabolic homeostasis and acid resistance

Bacteria maintain low basal levels of the alarmone ppGpp during steady-state growth, yet how this basal state is established and why it matters physiologically remain poorly understood. Here, we show that basal ppGpp represents an actively maintained regulatory state that coordinates metabolic homeostasis with stress resistance. Using a targeted perturbation of SpoT regulation in Escherichia coli, we uncover a sharp requirement for a sub-basal yet non-zero ppGpp pool to sustain growth in minimal medium and survival under extreme acid stress. Disruption of this basal state leads to misallocation of metabolic flux into arginine biosynthesis, depletion of glutamate, and collapse of the glutamate-dependent Gad acid resistance system. Through intragenic suppressor analysis, enzymatic perturbations, and protein-level feedback measurements, we further demonstrate that SpoT intrinsically tunes basal ppGpp through a distributed intramolecular regulatory network coupled to negative feedback control of SpoT abundance. This regulatory logic stabilizes ppGpp within a narrow physiological window, below the threshold of canonical stringent response activation. The requirement for SpoT-dependent basal ppGpp regulation is conserved in pathogenic Salmonella and Shigella. Together, our findings establish basal ppGpp as a distinct and actively regulated signaling regime that integrates metabolism and stress preparedness beyond acute starvation responses.

microbiology↗

bioRxiv2026

Biodistribution of mRNA vaccines in rats: Enrichment in injection site and lymph tissues and rapid clearance without tissue persistence

Messenger RNA (mRNA) vaccines using lipid nanoparticles (LNPs) are well-established and globally approved with acceptable safety profiles for preventing respiratory disease. Other mRNA-LNP product concepts are also emerging as novel treatments for broader clinical use. Here, we describe mRNA-LNP vaccine tissue distribution and kinetics after intramuscular dosing using three products formulated with same LNP matrix: mRNA-1273 (Spikevax), mRNA-1647 (a candidate cytomegalovirus [CMV] vaccine), and a reporter mRNA (nascent peptide-luciferase) drug product. Consistent biodistribution patterns were observed across studies: tissues with highest exposures were the injection site, draining lymph nodes, and spleen, with minimal distribution to non-lymphoid tissues. Vaccine components cleared rapidly from circulation and tissues, with complete elimination simulated to occur by [~]2 weeks. Following mRNA-1273 vaccination, Spike protein levels were transiently observed (elimination <5 days) and did not accumulate with repeated dosing. The ionizable lipid in the LNP matrix, Lipid H, underwent biotransformation and was excreted renally and hepatically, with no human-specific metabolites. Collectively, these results indicate that the LNP composition, not mRNA cargo, governs biodistribution. Furthermore, in a SARS-CoV-2 infection-free model, there was no evidence of Spike protein persistence. Overall, the data establish a framework that justifies leveraging biodistribution data across products and supports eliminating redundant animal studies.

pharmacology and toxicology↗

bioRxiv2026

AlphaGenome -enabled analysis of non-coding regulatory variants underlying RHD Expression

Systematic identification of functional non-coding regulatory variants remains a major challenge in human genetics. Conventional approaches such as large-scale CRISPR screening and genome-wide association studies (GWAS) are powerful but often prohibitively expensive, time-consuming, and experimentally intensive, limiting their scalability for locus-specific mechanistic studies. Recent advances in artificial intelligence offer the potential to partially replace or substantially augment these approaches by prioritizing regulatory variants with high functional likelihood. The RHD antigen, a major contributor to red blood cell alloimmunization, hemolytic transfusion reactions, and hemolytic disease of the fetus and newborn, serves as an excellent model for this paradigm, since coding variants alone do not fully account for differences in RHD expression. Here, we present an integrated artificial intelligence (AI)-guided and experimental framework to identify and validate functional non-coding regulatory variants governing RHD expression. We first applied AlphaGenome (AG), a deep-learning model released in 2025 for non-coding variant impact prediction, to systematically interrogate the RHD locus. By integrating multi-omics datasets, AG prioritized regulatory regions within the promoter, 5' untranslated region (5'UTR), and intragenic regions. In silico deletion- and Single Nucleotide Polymorphism (SNP)-based perturbation analyses consistently predicted that variants within the promoter and its proximal regions, as well as within intragenic regions, exert strong suppressive effects on RHD expression. To experimentally validate these predictions, we performed CRISPR-mediated base editing in K562 cells at AG-prioritized non-coding SNP sites. Editing of a high-score predicted variant (chr1:25272434 G>A) achieved efficient base conversion and was accompanied by additional nearby edits, all predicted by AG to downregulate RHD expression. In contrast, editing of low-score predicted sites (chr1:25272422 C>T) produced much smaller functional effects. Quantitative polymerase chain reaction (qPCR) analysis of full-length RHD transcripts, together with flow cytometry-based analysis of RHD expression, confirmed strong concordance between AI-based predictions and transcriptional as well as phenotypic outcomes. Taken together, our results demonstrate that the combination of AI-guided regulatory variant prioritization and targeted base editing provides a potentially scalable and cost-effective alternative to traditional CRISPR screening for decoding functional non-coding variants in blood group genes, with direct implications for genomics-based RHD typing and transfusion medicine. To our knowledge, this study also represents the first validation of AlphaGenome predictions at the phenotypic level using wet-lab experiments.

genomics↗

bioRxiv2026

BiHiTo: Biomolecular Hierarchy-inspired Tokenization

Three-dimensional atomic arrangements of biomolecules are key to demystifying biological functions. The rapid expansion of accessible structural data, driven by advances in AI for science, highlights the critical challenge of efficiently modeling large-scale biomolecular structures, which are high-dimensional systems shaped by biological assembly principles. To address this, we introduce BiHiTo, a multi-level Biomolecular Hierarchy-inspired Tokenizer that intrinsically mimics natural biological assembly hierarchies. Specifically, we design a multi-codebook quantizer that mirrors the natural hierarchy of biomolecular structure, enabling simultaneous capture of representations spanning atomic motifs to global conformational variations. This hierarchical alignment markedly improves the biological interpretability and reconstruction fidelity of biomolecular structure.Extensive experiments demonstrate that BiHiTo delivers state-of-the-art performance and robust generalization across molecular dynamics trajectories and macromolecular complexes, facilitating advances in structure generation and dynamic conformation exploration. In the reconstruction of the CASP14 and OOD test set FastFolding protein multi-conformation data, our method achieves a 17% and 51% reduction in RMSD compared to Bio2Token, respectively.

molecular biology↗

bioRxiv2026

High-Affinity Protein Binder Design via Flow Matching and In Silico Maturation

The de novo design of high-affinity protein binders remains a central challenge in protein engineering and therapeutic discovery. While deep generative models have advanced backbone generation and interface design, achieving picomolar or nanomolar binding affinities typically demands extensive experimental screening or iterative in vitro maturation. A general computational approach for the direct production of high-affinity binders has remained elusive. Here, we introduce an integrated framework that synergizes PPIFlow, a flow-matching-based generative model, with a novel in silico maturation strategy. PPIFlow employs a pairformer architecture to explicitly reason over pair-wise geometric and chemical interactions, modeling protein backbone rigid-body transformations as continuous flows. To bridge the affinity gap, we implement a dedicated in silico affinity maturation stage that combines interface rotamer enrichment with partial flow refinement to optimize energetic packing. This pipeline is further accelerated by AF3Score, a score-only adaptation of AlphaFold3 that enables high-fidelity and computationally efficient candidate prioritization. Across a diverse set of therapeutic targets, this synergistic approach consistently produces picomolar and nanomolar affinity binders without experimental affinity maturation. Notably, the framework proves highly effective for the de novo design of single-domain antibodies (VHHs), producing sub-nanomolar binders across multiple targets. These results establish that coupling robust backbone generation with focused in silico maturation renders the purely computational design of high-affinity binders feasible.

biochemistry↗

bioRxiv2026

Tonically active interneurons gate motor output in Drosophila larvae

Tonic inhibition and its transient removal are fundamental neural mechanisms for gating activity, suppressing out-of-phase excitation, and enhancing the temporal precision of behavior. However, their roles within locomotor central pattern generators (CPGs) remain poorly understood. Here, we identify A02l neurons--segmentally repeated excitatory interneurons in the Drosophila larval ventral nerve cord (VNC)--that regulate crawling behavior through tonic inhibition. A02l neurons exhibit high baseline activity and are transiently suppressed during motor output. They provide excitatory input to inhibitory premotor networks, enabling widespread silencing of motor neurons to maintain muscle relaxation. Optogenetic activation of A02l neurons reduced crawling frequency, whereas their inhibition induced transient whole-body contractions. Together, these findings reveal a cellular-resolution mechanism for tonic inhibition within the nerve cord and highlight its importance in gating motor output and maintaining motor quiescence.

neuroscience↗

bioRxiv2026

On the correctness of gene tree tagging and the consistency of ASTRAL-pro under a unified model of gene duplication, loss, and coalescence

AO_SCPLOWBSTRACTC_SCPLOWASTRAL-pro is the leading method for reconstructing species trees under complex evolutionary scenarios involving gene duplication, loss, and coalescence, commonly modeled by DLCoal. A unique aspect of A-pro is that it utilizes rooted gene trees, with internal vertices labeled as duplications or speciations, to modify its objective function compared to the traditional ASTRAL method. Although there is a natural event-based definition of correct tagging when genes evolve with only gene duplications and losses, it cannot be applied when there is deep coalescence. Here, we introduce a definition of correct tagging that is broadly applicable, proposing that a gene tree vertex is correctly tagged as a duplication if it is the most recent common ancestor of at least one pair of gene copies related via a duplication event. Using this definition, we study some statistical properties of ASTRAL-pros objective function under the DLCoal model and evaluate the accuracy of ASTRAL-pros tagging algorithm in simulations.

bioinformatics↗

bioRxiv2026

Bacteria-herpesvirus interaction reveals a proviral role of ISGylation in promoting herpesvirus capsid assembly

Herpesviruses are common pathogens of the oral cavity, yet how they interact with other oral microbes are poorly understood. Using murine gamma-herpesvirus 68 (MHV68) as a model for human gamma-herpesviruses, we discover that ISGylation is hijacked to facilitate viral capsid assembly and lytic replication. Co-infection with the oral Aggregatibacter actinomycetemcomitans (A.a.) and MHV68 synergistically induced interferon-stimulated gene 15 (ISG15) expression and global ISGylation. Proteomic profiling revealed viral structural proteins as the dominant targets of ISGylation in MHV68-infected cells. Genetic ablation of ISGylation, using ISGylation-resistant recombinant MHV68 and ISG15-deficient mouse embryonic fibroblasts (MEFs), demonstrated that ISGylation of the major capsid protein ORF25 is required for efficient capsid assembly and maturation into the infectious C-type virions. Strikingly, introduction of a de novo ISGylation site into the ISGylation-resistant MHV68 was sufficient to restore ISGylation, capsid assembly, and virion maturation. Consistent with these findings, A.a. failed to enhance MHV68 lytic replication in ISG15-deficient MEFs. Extending this mechanism to representative herpesviruses, we showed that ISGylation of major capsid proteins is broadly required for efficient lytic replication. Together, these findings uncover a previously unrecognized strategy by which herpesviruses exploit an ISG15 innate immune effector, amplified by microbial co-infection, to promote virion biogenesis and productive infection.

microbiology↗

bioRxiv2026

Iron Deficiency Drives Sarcopenia in the Elderly: HIF-1α-Mediated Fibro-Adipogenic Progenitor Differentiation Induces Fat Infiltration and Impairs Muscle Function

Abnormal iron metabolism is closely linked to sarcopenia; however, the specific iron metabolism features of fat-infiltrating sarcopenia remain poorly understood. Proteomic sequencing revealed that in skeletal muscle with severe fat infiltration, the expression of iron utilization-related proteins was significantly downregulated, whereas that of iron uptake and storage proteins was markedly upregulated, thereby presenting an abnormal iron deficiency (ID) phenotype. Nevertheless, the mechanism by which ID drives intramuscular fat infiltration has not been fully elucidated. Using clinical samples, aged murine ID models, and in vitro cell assays, this study is the first to demonstrate that ID stabilizes hypoxia-inducible factor-1 (HIF-1), promoting aberrant adipogenic differentiation of fibro-adipogenic progenitors (FAPs), disrupting the homeostatic balance between satellite cells (SCs) and FAPs, exacerbating skeletal muscle fat infiltration, and impairing muscle repair capacity. Notably, treatment with the HIF-1 inhibitor PX478 reversed these pathological alterations and improved muscle function. Collectively, our findings identify the ID-HIF-1-FAPs axis as a key driver of intramuscular fat infiltration, offering a novel therapeutic target for the clinical management of fat-infiltrating sarcopenia.

cell biology↗