Biology subjects

Zhu, B.

Publications and source records attributed to Zhu, B..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Endogenous mutational mechanisms and metabolic context shape endometrial cancer

Uterine corpus endometrial carcinoma (UCEC) is a common gynecologic malignancy with rising mortality, yet its genome-wide mutational architecture remains incompletely understood. Here we analyze deep whole-genome sequencing data from 440 UCEC tumors from The Cancer Genome Atlas, integrated with transcriptomic and clinical data, to define subtype-specific mutational processes and genomic architectures. We uncover pronounced molecular subtype-specific differences in endogenous mutational mechanisms, retrotransposition activity, structural variation, and chromosomal instability. LINE-1 retrotransposition emerges as a key contributor to genome instability in UCEC, acting as a prominent source of structural variation in copy-number stable tumors and associating with chromothripsis and ecDNA-mediated oncogene amplification in copy-number high tumors. Mutational signature SBS28 contributes significantly to mutations in POLE-deficient tumors and is strongly correlated with SBS10a and SBS10b. Mismatch repair-deficient tumors exhibit a previously unrecognized doublet base substitution signature and a defining imbalance between ID2 and ID1 indel processes, reflecting pervasive DNA template-strand replication slippage and associated with increased tumor immunogenicity. Copy-number low tumors follow a distinct low-mutagenesis evolutionary trajectory characterized by reduced replication stress, low proliferative activity, genomic stability and enrichment of SBS18 associated with oxidative damage. Notably, we identify a consistent inverse association between body mass index and tumor mutational burden in UCEC, suggesting that host metabolic state may influence fundamental cellular processes governing mutation accumulation, promoting tumor development through non-mutagenic mechanisms rather than elevated genomic instability. Together, these findings establish a mutagenesis-centric framework for UCEC that links endogenous mutational mechanisms to tumor architecture and host metabolic context, uncovering previously unrecognized subtype-specific genomic features with important implications for refined risk stratification and therapeutic strategies.

genomics↗

bioRxiv2026

Early immune responses anticipate HIV rebound and precede viral control

Sustained viral suppression following antiretroviral treatment (ART) cessation is a major goal of HIV cure research1. Rare individuals mount immune responses able to control viral rebound without intervention2,3, however, the earliest moments in which these responses form remain poorly defined. We performed an intensively sampled, prospective analytical treatment interruption (ATI) to study the initial immune response to rebound and to understand its role in defining subsequent virus control. Profiling of peripheral blood mononuclear cells and plasma revealed consistent immune activation prior to systemic rebound, including upregulation of antiviral transcriptional pathways, expansion of CD16++ non-classical monocytes, and increases of inflammatory and antiviral soluble plasma proteins. Individuals with prior viral control (controllers) diverged from non-controllers with a slower slope of rebound, a longer period of immune activity prior to rebound, and engagement of a multifaceted immune program with less systemic inflammation. An intermediate immune signature emerged in a separate ATI cohort of individuals who experienced delayed rebound after receiving broadly neutralizing antibodies4, suggesting that immunotherapy can induce a potentially protective pre-rebound immune response. Together, these data resolve the earliest systemic host immune responses to HIV rebound and demonstrate broad immune differences associated with HIV control phenotypes.

immunology↗

bioRxiv2026

Single-Cell and Spatial Methods for Multimodal Functional Glycan Profiling in Tissues

Glycans regulate multiple physiological processes, including immune recognition and cancer progression. In disease, altered glycan landscapes are interpreted by human lectins. Functional glycan-lectin interactions are difficult to profile because glycans are not genome-encoded and their changes are poorly captured by existing multimodal methods. We present two platforms, single-cell outlining and transcriptome sequencing (scGOAT-seq) and GlycoScope, which use human lectins to enable functional glycan accessibility into single-cell and spatial multiomic measurements. ScGOAT-seq quantifies lectin-accessible glycan states with gene expression, while GlycoScope enables multiplexed in situ co-detection of glycans and proteins in tissues. Applying these approaches to immune cells, we identify stimulus-specific glycan remodeling and show that distinct Siglec-ligand-defined programs stratify immune activation states not captured by traditional methods; in follicular lymphoma, GlycoScope, resolves spatial glycan programs associated with malignant B cells and localized immune microenvironments. The presented methods provide a general framework for integrating functional glycan accessibility into single-cell and spatial multiomics.

molecular biology↗

bioRxiv2026

Spatial immune hubs defined by conserved activated dendritic cells are remodeled by immunotherapy

Dendritic cells (DCs) orchestrate anti-tumor immune responses, yet the full extent of their phenotypic diversity, and spatial dynamics within the tumor microenvironment (TME) remains incompletely understood. Here, we constructed an integrated atlas of tumor-infiltrating DCs by harmonizing single-cell transcriptomic data from 12 murine tumor studies and 28 published human cancer datasets, together with newly generated single-cell-resolved multiplexed tissue imaging across immunotherapy conditions in a murine model. We noted conserved transcriptional states across species, including canonical conventional type 1 DCs (cDC1s), diverse type 2 DC (cDC2) subpopulations, and two activation states characterized by CCR7 expression (CCR7+ DCs) or interferon-stimulated gene expression (ISG DCs). Spatial transcriptomics analyses from human TMEs revealed that CCR7+ DCs and ISG DCs reside in distinct T cell-enriched regions that are embedded within distinct signaling environments. High-dimensional multiplexed proteomic imaging demonstrated that these DC-T cell niches undergo divergent remodeling across multiple immunotherapy conditions. Notably, this spatial reorganization occurred despite minimal detectable changes in DC transcriptional states. This study delineates conserved DC activation states and their spatial organization within tumors and captures the therapy-dependent remodeling, providing a framework for studying therapy-associated remodeling of DC immune programs in cancer.

immunology↗

bioRxiv2026

A spatiotemporal immune atlas of subarachnoid hemorrhage from single-cell and spatial transcriptomics

Background and PurposeSubarachnoid hemorrhage (SAH) triggers a complex immune response that critically influences early brain injury (EBI) and long-term outcomes. However, the precise spatiotemporal dynamics and heterogeneity of immune cell infiltration and microglial reprogramming remain poorly understood. We aimed to construct a high-resolution immune atlas to delineate cell states, lineage trajectories, and spatial niches following SAH. MethodsWe integrated single-cell RNA sequencing (scRNA-seq) of CD45+ immune cells with spatial transcriptomics (ST) in a murine endovascular perforation SAH model. Immune landscapes were profiled at 24 hours (acute phase) and 72 hours (subacute phase) post-injury, compared with sham controls. Advanced bioinformatics integrated transcriptional signatures with spatial localization to map macrophage, neutrophil, and microglial dynamics. ResultsOur atlas reveals a coordinated immune transition from acute inflammation to reparative processing. We identified five macrophage, four neutrophil, and eight microglial subsets with distinct spatiotemporal patterns. Notably, we discovered a SAH-specific inflammatory microglial population (MG_03; Spp1+/Lpl+) that clusters at the rupture site during the acute phase. This subset is transcriptionally distinct from disease-associated microglia (DAM) in other neurodegenerative conditions. Trajectory analysis suggests MG_03 acts as a signaling hub for immune recruitment before transitioning toward proliferative and reparative states (MG_06-08) that disperse into the parenchyma by 72 hours. ConclusionsThis study provides the first comprehensive spatiotemporal immune atlas of SAH, highlighting the distinct role of the Spp1+ MG_03 subpopulation in early injury sensing. These findings offer a roadmap for identifying precise therapeutic windows and targeting specific immune subsets to mitigate EBI. Graphical AbstractExperimental workflow for single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) in a mouse SAH model induced by endovascular perforation. Brain tissue from the ipsilateral (injured) hemisphere was collected from sham and at 24 h and 72 h post-SAH. For scRNA-seq, CD45 immune cells were isolated prior to library preparation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/703421v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@4a1bc9org.highwire.dtl.DTLVardef@16664c4org.highwire.dtl.DTLVardef@1619725org.highwire.dtl.DTLVardef@a0d34_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

Early microglial priming in Alzheimer's disease revealed by ME-seq

Epigenetic modifications, particularly DNA methylation, change dynamically with aging and are implicated in Alzheimers Disease (AD), yet how methylation interfaces with transcriptional and chromatin regulation at single-cell resolution remains poorly understood. Progress has been limited by a lack of scalable technologies capable of jointly profiling these regulatory layers. Here, we present ME-seq, a highly scalable technologies capable of simultaneously profiling DNA methylation, gene expression, and chromatin accessibility, while achieving a 100-fold reduction in cost. We generated over 400,000 single-nucleus trimodal profiles from the aging and AD mouse brain across ages, producing the first such atlas of neurodegeneration. We found AD progression triggers pronounced, disease-specific shifts in cellular composition, characterized by accelerated epigenetic aging and the expansion of disease-associated microglia (DAM). Integrative analyses, including aging clocks, revealed that DNA methylation acts as an early priming layer preceding transcriptional activation with IRF1 identified as a methylation-sensitive transcription factor serving as a gatekeeper for DAM activation. Our results establish ME-seq as a transformative tool for large-scale epigenomic dissection, revealing DNA methylation as a primary coordinator of cell-state transitions in the aging brain. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/702946v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@67435dorg.highwire.dtl.DTLVardef@177c22aorg.highwire.dtl.DTLVardef@16c6fd9org.highwire.dtl.DTLVardef@231b92_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Wetness modulates the effects of grazing on net ecosystem productivity in global grasslands

Overgrazing has induced widespread grassland degradation globally. However, how grazing intensity affects ecosystem carbon dioxide (CO2) fluxes with wetness fluctuations in grasslands at a global scale remains poorly understood. Here we measured ecosystem CO2 fluxes covering the 7th to 11th years of a continuous grazing experiment in a typical steppe, and conducted a meta-analysis of 585 observations by collecting relevant data in global grasslands. Our experimental results showed that mean gross primary productivity (GPP) and ecosystem respiration (ER) were decreased under heavy grazing (HG) compared with control without grazing (CK), whereas net ecosystem productivity (NEP) was not different between HG and CK in the typical steppe. The NEP was higher under light grazing in the wetter years, but it was not different between LG and CK under drier years in the typical steppe. The structural equation model showed that grazing altered NEP by increasing soil temperature and relative growth rate, while decreasing AGB. In contrast, grazing decreased GPP, ER and NEP, respectively, in global grasslands. Both our field experiment and the meta-analysis revealed that the response of NEP to light grazing, rather than heavy grazing, was lineally correlated with the wetness index. Higher wetness and aboveground biomass (AGB) increased the response of NEP to grazing in global grasslands. However, heavy grazing reduced NEP and AGB even under higher wetness indices in global grasslands, resulting from a loss of their resilience in long-term heavy grazing. These findings indicate that light grazing appears to be a promising management to promote plant relative growth rate and carbon sequestration. Overall, the meta-analysis and field experiment jointly provide global perspectives on the response of ecosystem CO2 fluxes to grazing intensity and improve our understanding of the factors influencing the response of ecosystem CO2 fluxes to grazing intensity.

ecology↗

bioRxiv2026

Ybx1 Deficiency Causes ROS-Driven IBD-Like Intestinal Inflammation and Postnatal Lethality

Y box-binding protein 1 (YB-1; Ybx1/ybx1) is essential for zebrafish development. Maternal ybx1-/- mutants exhibited embryonic lethality, whereas zygotic mutants (Zybx1-/-) showed high postnatal mortality between 10 and 20 dpf, although a small fraction survived to adulthood. Western blot and immunohistochemical analysis revealed strong, transient expression of Ybx1 in intestinal enterocytes from 3 to 5 days post-fertilization (dpf), followed by rapid ubiquitin-mediated degradation at 6 dpf, coinciding with defective intestinal development and compromised gut homeostasis. RNA-seq analysis identified elevated reactive oxygen species (ROS) and upregulation of matrix metalloproteinases mmp9 and mmp13a in Zybx1-/- larvae. Antioxidant treatment with ascorbic acid rescued postnatal lethality and alleviated intestinal defects, whereas prooxidant exposure exacerbated them. Pharmacological inhibition of Mmp9 or Mmp13a similarly prevented lethality, highlighting a ROS-MMP axis driving tissue damage. By 30 dpf, surviving mutants exhibited progressive intestinal impairment and severe pathology. These findings demonstrate that Ybx1 deficiency triggers ROS-dependent intestinal inflammation, MMP-mediated gut damage, and postnatal lethality, establishing Ybx1-deficient zebrafish as a robust model for studying inflammatory bowel disease (IBD)-like intestinal disorders.

developmental biology↗

bioRxiv2026

Pre-myelinating oligodendrocyte ADGRG1 is required for axon ensheathment and CNS myelin formation

Myelin is essential for axonal health and rapid propagation of action potentials. In the central nervous system (CNS), myelination is initiated with axon ensheathment by pre-myelinating oligodendrocytes (preOLs), followed by iterative membrane wrapping and longitudinal extension along the axon. The molecular mechanisms that govern preOL development remain largely unknown. In this study, we identify the adhesion G protein-coupled receptor ADGRG1 (also called GPR56) as a key, evolutionarily conserved regulator of this process. We show that ADGRG1 is highly expressed in preOLs and that its conditional deletion in mouse preOLs leads to simplified preOL morphology and defective axon ensheathment, resulting in CNS hypomyelination. Live imaging in zebrafish demonstrated conserved function of Adgrg1 in axon ensheathment. Mechanistically, we show that ADGRG1 promotes preOL maturation by RhoA activation. Collectively, these findings reveal an ADGRG1-mediated RhoA signaling pathway that governs axon ensheathment and myelin formation.

neuroscience↗

bioRxiv2026

Protein-peptide Interaction Representation Learning with Pretrained Language Models

Protein-peptide Interactions (PpIs) paly essential roles in diverse cellular processes, yet their systematic identification remains challenging due to the limited availability of experimentally annotated protein-peptide interaction data. To address this challenge, we present PepInter, a sequence-based Deep Learning (DL) framework that leverages large-scale pretraining on structurally derived pseudo protein-peptide pairs to learn interaction-relevant representations. Specifically, energy-dominant peptide fragments are extracted from protein complexes curated from non-redundant Protein Data Bank (PDB) structures, enabling the construction of pseudo protein-peptide interaction pairs that capture interface interaction patterns shared with canonical protein-protein interactions. This strategy allows the model to acquire interaction-aware priors in the absence of large-scale annotated protein-peptide complex datasets. Built upon the ESM-Cambrian (ESMC) architecture, PepInter adopts a two-stage pretraining strategy. In the first stage, masked language modeling is used to learn general protein sequence representations. In the second stage, the model is further trained to predict Rosetta-derived energetic scores, explicitly incorporating structural interaction signals into the learned embeddings. Following pretraining, PepInter is fine-tuned for both protein-peptide interaction classification and peptide bioactivity regression tasks. Across multiple benchmark datasets, including protein-peptide binding affinity prediction, PepInter consistently outperforms existing baseline methods and demonstrates strong generalization in identifying biologically meaningful PpIs. Case studies further highlight its ability to recover known interaction patterns and predict novel protein-peptide interactions. Together, these results establish PepInter as a scalable and effective framework for protein-peptide interaction prediction, with strong potential to accelerate peptide-based drug discovery.

bioinformatics↗

bioRxiv2025

Multimodal AI for Single cfDNA Profiling and Cancer Screening

Cell-free DNA (cfDNA) serves as a non-invasive biomarker for cancer detection, but conventional methods face challenges due to the ultra-low abundance of tumor-derived cfDNA (ctDNA) among normal cfDNA. Though nucleosome-bound cfDNA harbors rich epigenomic features that could enable ctDNA identification by single-molecule multi-omics cross-validation, this remains unexplored due to methodological limits. Here, we developed a cfDNA sequencing approach integrating methylation, fragmentomics, and histone modifications at the single-molecule level; together with gene semantics and epigenomic annotations, these modalities were vectorized and fused to represent each cfDNA molecule. We trained a Transformer-based model (cfAI) to profile and evaluate ctDNA likelihood at molecule, gene, and sample levels. cfAI achieved [~]10-fold enrichment of cancer-derived signals over noise and reached 72.6% sensitivity at 93.1% specificity for multi-cancer detection. Our study establishes an innovative framework that overcomes the inherent signal-to-noise limitations of conventional assays and reveals biological features at molecular resolution for cancer detection.

bioinformatics↗

bioRxiv2025

Revealing the Drivers Underlying Distinct Evolutionary Trajectories in Lung Adenocarcinoma

Elucidating the evolution of cancers allows us to understand their key events, and the order in which they occur. To chart and interpret these evolutionary trajectories, we leverage whole-genome sequencing of lung tumours, including those from the largest cohort to date of lung cancers in subjects who have never smoked. Through ordering frequent genomic alterations, we discover three distinct evolutionary paths taken by lung adenocarcinomas; two dominated by tumours from people who have never smoked (NS-LUAD), and one followed by the vast majority of those who have smoked (S-LUAD). However, one in six NS-LUAD follow the smoking-dominant trajectory. These tumours, surprisingly, have fewer somatic alterations than the other NS-LUAD, and have shorter latency. They are strongly enriched for KRAS mutations. Our results suggest that gaining KRAS mutations allows these tumours to evolve more rapidly, acquiring a set of smoking-associated key alterations, with less need for genomic instability to progress. These tumours are three times more frequent in subjects of European vs. East Asian ancestry. These findings could shape clinical management strategies for lung adenocarcinoma patients, particularly for tumours driven by smoking-like evolutionary trajectories.

cancer biology↗

bioRxiv2025

Identifying High-Dimensional Genomic Factors Modulating Biological Networks Across Multi-Omics Data

Biological traits such as genes, metabolites, and microbial taxa interact within complex networks, yet how genomic factors shape these interactions remains poorly understood. Here, we introduce GFBioNet, a computationally efficient method for identifying factors that modulate direct associations between biological traits within network models. Our two-stage strategy first estimates a baseline network using Gaussian graphical models and then tests whether genomic factors modulate specific network edges (trait-trait relationships), enabling scalable analysis of high-dimensional multi-omics data while explicitly controlling the false discovery rate (FDR). Simulations demonstrate reliable FDR control and high statistical power across a broad range of settings. Applied to multiple datasets, GFBioNet reveals host genetic variants influencing oral microbiome relationships, gut microbial taxa modulating metabolite networks in colorectal cancer, and somatic mutations and copy-number alterations reshaping gene expression networks in lung adenocarcinoma. By expanding network analysis to evaluate modifiers of trait-trait relationships, GFBioNet offers a versatile tool for uncovering the genomic architecture of biological networks across multi-omics studies.

genomics↗

bioRxiv2025

Temporal single-cell profiling uncovers age-associated delays in immune resolution to respiratory viral infection

Aging is a major risk factor for increased morbidity and mortality following acute respiratory virus infections. To elucidate the immune determinants underlying viral pathogenesis and delayed lung repair in the aged lung, a comprehensive time-course study was conducted. Single-cell RNA sequencing (scRNAseq) and high-dimensional flow cytometry were utilized to compare lungs from young and aged mice infected with influenza A virus (IAV). Aged hosts displayed diminished alveolar macrophage (AM) and dendritic cell (DC) but elevated monocyte-derived macrophage (MoM) and interstitial macrophage (IM) presence following infection. Additionally, enhanced accumulation of adaptive immune cells, including CD4+ tissue-resident helper (TRH) cells, CD8+ tissue-resident memory (TRM) cells, and a B cell subset resembling age-associated B cells, was observed in the memory phase. Pathway analysis revealed that elevated type I and II interferon (IFN/{gamma}) signaling, especially in MoM/IM subsets, distinguished the aged hosts from the young. Inhibition of IFN/{gamma} signaling after viral clearance improved long-term respiratory outcomes and reduced both IM and TRH populations in aged mice. These findings highlight the pivotal role of IFN/{gamma} signaling, likely within MoM/IM subsets, in driving the exuberant persistence of adaptive immune cells and chronic immunopathology in the aged lung following acute viral infection.

immunology↗

bioRxiv2025

A transcription factor-responsive enhancer discovery platform for targeted immunotherapy

Synthetic enhancers with high specificity are crucial for therapeutic gene control. However, experimental screens and machine learning-guided design typically require context-specific datasets, limiting generalizability. Because transcription factor (TF) activity reflects cellular state, TF-responsive enhancer libraries offer a universal starting point. Here, we developed TREND (transcription factor-responsive enhancer discovery), a massively parallel reporter assay of [~]2.7 million enhancer-barcode constructs representing 57,715 designs. TREND covers 1,068 motif-annotated proteins, including 729 confirmed TFs across 49 DNA-binding domain families. Applied to ovarian cancer, TREND identified enhancers that discriminate cancer from normal epithelial cells. These enhancers enabled protein-interaction-based AND-gate circuits with reduced OFF-state leakage and amplified ON-state output, driving tumor-restricted expression of combinatorial immune effectors and robust antitumor responses in murine ovarian cancer models. TREND also identified T-cell activation-responsive enhancers with greater inducibility and lower basal activity than conventional NFAT-motif-based elements. Together, TREND provides a generalizable framework for context-specific enhancer discovery and therapeutic gene regulation.

synthetic biology↗

bioRxiv2025

ROSIE-Enabled Spatial Mapping Reveals Architectural Fragmentation and Immune Reprogramming in Lung Adenocarcinoma Evolution

The earliest steps of lung adenocarcinoma (LUAD) evolution remain poorly resolved because existing spatial-omics technologies cannot scale to the large archival cohorts required to capture rare transitional states. Here, we reconstructed a stage-resolved spatial atlas of LUAD progression using ROSIE, a deep-learning framework inferring 50-plex protein expression from routine H&E slides (114 specimens; 3.8 million cells). Using a pathology-defined precursor continuum (Normal[->]AAH[->]AIS[->]MIA[->]IAC) as a pseudotemporal axis, this scalable virtual multiplexing approach reveals a previously unrecognized two-phase immune reprogramming cascade tightly coupled to a measurable structural transition we term architectural fragmentation. During the AAH[->]AIS transition, transient adaptive immune engagement collapses, marked by a 48.4% loss of CD8 + T cells and the emergence of microfragmented epithelial-stromal interfaces. Subsequent AIS[->]MIA[->]IAC transitions are dominated by myeloid-driven immunosuppression, expansion of CD163 + macrophage niches, and the establishment of an immune-excluded architecture. Fragmentation severity in AIS strongly predicts downstream invasive potential, positioning it as an early, quantifiable hallmark of malignant transition. These findings define a mechanistic sequence linking structural disintegration, immune collapse, and invasive outgrowth and demonstrate that H&E-based virtual multiplexing enables cohort-scale dissection of early cancer evolution and identification of actionable windows for immunoprevention. The ROSIE predictions were validated against imaging mass cytometry (IMC) across 25 precursor samples, achieving concordance up to r [≥] 0.90 (93% of marker-cell-type pairs at r [≥] 0.80). A complementary comparison against MIPHEI-ViT, an independent virtual multiplexing framework, corroborated the structural and pan-immune components of this signature across all stages, while highlighting fine-grained immune-lineage resolution as a shared open challenge for H&E-based virtual multiplexing.

cancer biology↗

bioRxiv2025

Engineering magnetically guided bacteriophages for precision antimicrobial therapy and targeted biofilm eradication

Viruses, including bacteriophages, rely on passive diffusion to reach their hosts, limiting the efficacy of virus-based therapies and leading to off-target accumulation with systemic effects. Here, we present a strategy to confer controllable motility to bacteriophages by incorporating iron nanoparticles (FeNPs) into their head structures while preserving infectivity. Cryo-electron microscopy (Cryo-EM) and transmission electron microscopy-energy dispersive spectroscopy (TEM-EDS) confirmed the FeNP presence in the phages head. FeNP-tagged phages can be magnetically enriched and isolated from bacterial prey cultures, eliminating the need for ultracentrifugation. Under magnetic guidance, these engineered phages exhibit rapid and directed movement through complex microenvironments, including mazes and polymer barriers, enabling precise bacterial targeting and biofilm eradication in a microfluidic system. In an in vivo wound infection model, magnetically guided phages successfully navigated from the peritoneum to the biofilms on the wound, thus selectively eliminating biofilms while minimizing systemic exposure to other organs. Hence, our approach confers viral mobility, thus enhancing the precision and efficacy of bacteriophage-based biotechnological and therapeutic applications.

microbiology↗

bioRxiv2025

A microfluidic rheometer for tumor mechanics and invasion studies

Clinically, the feel, touch, and shape of a solid tumor are important diagnostic methods for determining the malignant state of the disease. However, there are limited tools for quantifying the mechanics and the malignancy of the tumor in a physiologically realistic setting. Here, we developed a microfluidic rheometer - termed the microrheometer - that enables simultaneous measurements of tumor spheroid mechanics and their invasiveness into a 3D extracellular matrix (ECM). The microrheometer consists of a pneumatic pressure control unit for applying controlled static or cyclic compression to tumor spheroids, and a sample chamber for containing spheroid embedded ECM. The innovation here lies in the integration of a polyacrylamide membrane force sensor within the sample chamber, enabling a direct force measurement in a physiologically relevant setting. We found that both tumor stiffness and the viscoelastic properties of the tumor are closely correlated with tumor invasiveness. The microrheometer allowed us to measure tumor mechanics in a short time (less than a minute) and has the potential to be used clinically in the future. We note that the microrheometer here can be easily extended to studies of mechanics of single cell, nucleus, as well as other cell/tissue types.

bioengineering↗