Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

An Injectable Antisense Oligonucleotide (ASO) Approach to Treat Obesity in Preclinical Models

Obesity leads to metabolic dysregulation and thus drives complications including type 2 diabetes, cardiovascular disease, steatotic liver disease and some cancers. Obesity is primarily driven by lifestyle factors, which impacts individuals differently depending on their genetic susceptibility. Studies on this genetic risk have provided major insights into gene networks that modulate obesity development, including incretins and their regulatory circuits. Indeed, incretin-based therapeutics (i.e. GLP1 RA) have proven to be enormously successful in promoting weight loss, but do so with several ongoing challenges including significant weight rebound upon cessation, loss of lean mass, and side effects that reduce therapeutic longevity. Thus, ongoing research is necessary to identify additional interventions that overcome or minimise these concerns. To this end, in our previous work we have identified a novel lipid regulatory protein with potential to influence lipid storage. In the current study, we use antisense oligonucleotides (ASO) to silence this protein in mouse models of diet induced obesity, and demonstrate that once weekly IP injections of ASO prevents the development of obesity, and defends against the progression of existing obesity. This is shown to be effective in multiple mouse strains fed different diets over various time frames, with gene targeting ASOs leading to reductions in fat mass, no change in lean mass, along with improvements in whole body glucose tolerance and steatotic liver disease. Additional studies demonstrate that this phenotype is likely driven by effects in adipose tissue, but not liver, and is not linked to activation of the Type 1 Interferon response, a previously implicated off target effect of ASO administration. Thus, these studies demonstrate that our injectable ASO approach in mice can successfully treat obesity in the absence of major change in lean mass, thus positioning this intervention as a therapeutic program that works alternatively to, or in conjunction with current weight loss medicines.

physiology↗

bioRxiv2026

LongVerse: verified AI agents for Nanopore and PacBio DNA methylation analysis

AI agents now run sequencing pipelines, but their outputs are checked by proxy, with rubrics or language-model judges. LongVerse turns one English sentence into haplotype-resolved DNA methylation from Nanopore or PacBio reads, through agents that read the data, supply arguments to a pinned pipeline and never write code. On HG002, a healthy reference genome, agent and human expert produced byte-identical calls (r = 1.000) that agreed with bisulfite sequencing (r = 0.943, 0.884), at $0.12 to $0.54 of conversation per run. A consensus agent that admits any per-site caller reduced error 10.7 percent against the best published caller.

bioinformatics↗

bioRxiv2026

Effects of Alternating Polarity Frequency on the Assembly of Electro-Methanogenic Microbial Communities

Electro-methanogenesis can enhance methane production and has attracted extensive interest, but the current strategies for building electro-methanogenic microbial communities suffer from several limitations. Alternating polarity has been shown as a new strategy to build electro-methanogenic communities, but the impact of alternation frequency on community assembly remains to be understood. In this study, the impact was evaluated using bioelectrochemical systems amended with granular activated carbon, and the working-electrode potential was alternated between +0.4 and -0.4 V vs. SHE at six frequencies ranging from 0.5 to 12 days. Among the tested conditions, 4-d alternation led to the best overall performance, producing approximately 250 L/L/kg cumulative biogas, 96% methane content, and a 45% methane yield, while preserving a stable and reproducible community structure. The community contained two Methanobacterium populations, two putatively electroactive Geobacter populations, and one putatively electroactive Pseudomonas population, together with diverse fermentative and syntrophic bacteria. Transcript-based analyses revealed clear frequency- and potential-dependent shifts in the activity of these functional groups. Redundancy analysis associated the Methanobacterium formicicum-related population with cathodic current and methane production, whereas the Geobacter sulfurreducens-related population was linked to anodic current and methane production. Bayesian and local-similarity networks further connected methanogen dynamics with specific electroactive, fermentative, and syntrophic partners. Collectively, these results establish alternating polarity frequency as a critical parameter for building robust communities capable of high-rate, high-quality methane production.

microbiology↗

bioRxiv2026

LineageFlow: Growth-Corrected State Dynamics for Probabilistic Cell-Fate Prediction

Single-cell lineage tracing links early transcriptional states to the fates of their descendants, but forecasting clonal fate remains challenging because differentiation and unequal cell expansion jointly shape descendant populations. Here we introduce LineageFlow, a computational framework that combines continuous-time cell-state transitions, relative net growth and state-conditioned generative flows to predict future fate distributions and transcriptional profiles from early single-cell measurements. In clone-disjoint evaluations of lineage-traced hematopoiesis, LineageFlow improves fate prediction and expression-distribution accuracy over matched computational baselines. A separately retrained analysis of cord-blood lineage data shows a similar advantage at a longer prediction horizon. Controlled simulations show that accounting for differential growth improves fate prediction when descendant states expand at different rates, while offering little benefit under equal growth. These findings highlight the importance of modeling state transitions and relative expansion together when predicting the fate of unseen clones.

bioinformatics↗

bioRxiv2026

Human brain white matter charts in international populations

Brain charts provide normative references for identifying neurodevelopmental milestones and clinically meaningful deviations. Existing white matter (WM) charts are derived predominantly from European and North American populations, limiting generalizability. Here, we established the first set of population-specific WM charts of 198 morphological and microstructural phenotypes for both Chinese (N=19,215) and Western (N=15,584) populations across the human lifespan. Developmental trajectories and spatial organization of WM maturation and degeneration were broadly conserved across the populations, whereas maturational timing varied across pathways and metrics. The Chinese population showed earlier maturation in several projection and sensorimotor pathways, but more protracted maturation in higher-order association and limbic pathways. Chinese population-matched charts more accurately predicted WM phenotypes and detected more extreme disease-related deviations in brain health in the Chinese population than Western-derived models. Individual deviation patterns further discriminated patients from healthy controls and predicted cognitive performance and plasma biomarkers. Our findings reveal population-specific WM maturation and show that reference-population mismatch can reduce the accuracy and clinical sensitivity of normative brain charts.

neuroscience↗

bioRxiv2026

Spatially resolved host-fungal transcriptomics profiling by fungal-DBiT

Hosts and their associated fungi coexist within a shared tissue environment, engaging in dynamic interactions that influence immune regulation, tissue homeostasis, and disease progression. Dissecting these interactions requires spatially resolved and unbiased approaches capable of capturing gene expression from both host and fungal cells within intact tissue architecture. Here, we present fungal-DBiT, a spatial transcriptomic platform that enables simultaneous, high-resolution mapping of host and fungal RNAs, directly in tissue sections. Using fungal-DBiT, we profiled the spatial distribution of host and fungal transcripts in a fungal infection mouse model, and review pronounced spatial heterogeneity in fungal localization and activity, accompanied by region-specific host transcriptional responses. We further applied fungal-DBiT to intestinal tissues under physiological conditions, demonstrating its sensitivity in detecting low-abundance fungal species in the absence of overt inflammation. Together, these results demonstrate the ability of fungal-DBiT to resolve host-fungal interactions in situ and highlight its utility for studying mycobiome associated immune responses and disease processes with spatial precision.

microbiology↗

bioRxiv2026

Hierarchical distribution matching enables comprehensive characterization of common and condition-specific cell niches in spatial omics data

Deciphering cell niches in complex tissues is essential for understanding tissue structure and disease. Recent advances in spatial omics have enabled subcellular resolution and accurate cell identity mapping. However, robust delineation of cell niches and disease-associated spatial patterns remains difficult. We introduce Harmonics, a novel computational framework that systematically identifies both common and condition-specific cell niches from spatial omics data through hierarchical distribution matching. Harmonics also includes a suite of downstream modules that facilitate comprehensive niche characterization. We demonstrate its scalability, accuracy and generalizability across datasets spanning diverse species, tissues, diseases, spatial modalities, and technological platforms. For condition-agnostic datasets, Harmonics outperforms baseline methods in both accuracy and robustness, and further demonstrates the capability to resolve niche structures at finer granularity. Across diverse diseases including pulmonary fibrosis, triple-negative breast cancer, and colorectal cancer, Harmonics enables precise identification of condition-specific niches and reveals disease-associated dynamics, subtype-specific spatial patterns, and structured immune architectures. We envision Harmonics as a practical and versatile tool for spatial niche analysis that can be applied across a wide range of biological contexts and seamlessly integrated with existing spatial omics workflows.

bioinformatics↗

bioRxiv2026

Longitudinal Metaproteomic and Lysine Crotonylation Remodeling Defines Clinical Response to Fecal Microbiota Transplantation in Ulcerative Colitis

Background Fecal microbiota transplantation (FMT) can induce steroid-free clinical remission in a subset of patients with ulcerative colitis (UC), but treatment responses remain heterogeneous and are not fully explained by taxonomic microbiome shifts. To define functional molecular features associated with FMT efficacy, we performed integrated longitudinal fecal metaproteomic and lysine crotonylation (Kcr) profiling. Methods We analyzed 87 fecal samples from 23 patients with active UC collected at baseline and at weeks 1, 8, and 12 after FMT. Patients were classified as responders (n = 13) or non-responders (n = 10) according to steroid-free clinical remission at week 12. Across samples, we identified an average of 3,682 proteins and 562 Kcr sites per sample. Results Responders showed greater metaproteomic and meta-crotonylomic complexity at week 12, sustained enrichment of Prevotella and Faecalibacterium, and eight directionally consistent baseline-altered proteins with candidate prognostic value. After FMT, responders exhibited coordinated microbial functional remodeling, including increased proteins involved in short-chain fatty acid (SCFA) metabolism, acyl-CoA-centered pathways, nutrient transport, and polysaccharide degradation, together with attenuation of host neutrophil-related inflammatory protein and Kcr signatures. Non-responders showed minimal or opposing molecular changes. Conclusions: These findings nominate longitudinal fecal metaproteomic and Kcr remodeling as functional molecular readouts of clinical response to FMT in UC and highlight lysine crotonylation as an underexplored metabolite-sensitive layer linking microbial metabolic restoration with host inflammatory resolution.

microbiology↗

bioRxiv2026

Cortex-wide single-cell activity mapping in freely moving mice

How the cortex supports complex, naturalistic behavior can be revealed only in freely moving animals. Although head-mounted microscopes promise access to the neural dynamics underlying such behavior, fundamental trade-offs among field of view, spatial resolution, device weight, and background contamination have prevented cortex-wide single-neuron recording, leaving distributed cortical coordination largely inaccessible. To meet these challenges, we introduce COMET (Cortex-wide Observational Miniature Epifluorescence Technique), a 3.75-g head-mounted mesoscope that integrates an aberration-controlled wide-field optical design, uniform high-efficiency excitation and single-coaxial power-and-data transmission with an end-to-end denoising and signal-extraction pipeline. This enables cortex-wide calcium imaging at single-cell resolution in freely moving mice. COMET captures activity from >15,000 layer 2/3 neurons per 5-min recording over fields of view up to 10 mm in diameter while preserving natural behavior. Benchmarking against benchtop two-photon microscopy demonstrates high spatial concordance of detected neurons and matched event-level calcium dynamics. We apply COMET to social interaction to quantify region-specific engagement and to an auditory trace fear-conditioning task that requires natural movement and behavioral expression, revealing time-ordered changes in regional firing-rate structure and functional connectivity preceding a global conditioned response. COMET provides an open, lightweight hardware-software framework for linking single-neuron activity to cortex-scale network dynamics during freely expressed behaviors under changing internal or external conditions.

neuroscience↗

bioRxiv2026

Regional macrophage specialization shapes intestinal neuroimmune function

Tissue-resident macrophages adapt to local environments to support organ-specific functions, but whether their regulation differs across regions of the same organ is poorly understood. The gastrointestinal tract provides an ideal system to address this question because its anatomically distinct regions perform specialized physiological functions and contain different cellular environments. Here, we found that intestinal muscularis macrophages (MMs) exhibited distinct regional trophic requirements and neuroimmune functions across the gut. Small-intestinal MMs were highly sensitive to CSF1 neutralization but recovered robustly, whereas colonic MMs were less sensitive to CSF1 depletion yet showed limited recovery. Disruption of CSF1-dependent MMs selectively reduced nitrergic neurons and altered motility in the small intestine, whereas the colonic neuronal compartment was comparatively preserved. Csf1 was enriched in small-intestinal nNOS+ neurons, and neuron-specific Csf1 deletion reduced both MMs and nitrergic neurons and altered small-intestinal transit, with limited effects in the colon. Together, these findings reveal that macrophage trophic requirements and neuroimmune functions are regionally specialized within the intestine and identify neuronal CSF1 as a key component of the trophic relationship between nitrergic neurons and MMs in the small intestine.

neuroscience↗

bioRxiv2026

Targeted RNA degradation of HIV-1 TAR element at 5'UTR by CRISPR-Cas13X blocks HIV-1 lytic reactivation

Human immunodeficiency virus type 1 (HIV-1) latency remains a major barrier to a cure. Here, we developed a hypercompact CRISPR-Cas13X.1 system to target the HIV-1 5' untranslated region (5'UTR), focusing on the transactivation response (TAR) RNA element required for Tat-dependent transcription. Following validation of a single-vector system, we screened CRISPR RNAs (crRNAs) targeting distinct 5'UTR elements and identified crRNA-TAR-2 as the most effective inhibitor of Tat-dependent reporter activity. Mechanistic analyses demonstrated that TAR targeting disrupted Tat-TAR interactions. In HIV-1 infection models, Cas13X.1-mediated TAR targeting reduced HIV-1 Gag precursor (p55) and capsid (p24) protein expression, as well as gag and tat transcript levels, accompanied by activation of the PKR-eIF2a; antiviral pathway. TAR targeting also suppressed viral gene expression and reactivation in multiple latency models and reduced viral load in HIV-1-infected primary peripheral blood mononuclear cells (PBMCs). These findings establish HIV-1 TAR RNA as a target for Cas13X.1-mediated antiviral activity and support RNA-targeting CRISPR systems as a potential strategy to suppress HIV-1 infection and reactivation.

microbiology↗

bioRxiv2026

DiffRhyShiny: A Benchmarking-Informed Platform for Differential Rhythmicity Analysis with Dependence-Aware Evidence Integration

Motivation: Differential rhythmicity analysis identifies condition-specific changes in biological oscillations, but diverse algorithmic assumptions complicate method selection. Furthermore, integrating complementary evidence across different tools while accounting for statistical dependence remains an unresolved challenge. Results: We benchmarked seven algorithms across diverse rhythmic scenarios, revealing that optimal selection depends heavily on specific biological variations and experimental designs. To overcome single-algorithm limitations, we introduced Kost's Method, a dependence-aware p-value integration approach. Building on this framework, we developed DiffRhyShiny, an interactive web platform that automates robust differential rhythmicity analysis, consensus evaluation, and visualization. Furthermore, we validated the platform's performance and statistical rigor using both extensive simulated scenarios and real-world transcriptomic datasets. Availability and implementation: DiffRhyShiny is freely available at https://omicsai.shinyapps.io/diffrhyshiny, with the latest source code at https://github.com/liuchuan111/diffrhyshiny. The code and data to reproduce all benchmarking results are archived on Figshare at https://doi.org/10.6084/m9.figshare.33070100.

bioinformatics↗

bioRxiv2026

Charting sex divergence in the human brain across the lifespan

Biological sex fundamentally shapes human brain organization, but sex-specific normative neuroanatomical trajectories across the lifespan remain largely uncharted. Here, we constructed independent, sex-specific lifespan brain charts using structural neuroimaging data from 59,915 healthy individuals (29,760 males and 30,155 females) ranging in age from 266 postconception days to 100 years. By examining 296 structural phenotypes across global, cortical, and subcortical measures, these models revealed widespread sex differences in maturational timing, with males reaching peak milestones later than females. These trajectories demonstrate that sex differences evolve dynamically, with phenotype-specific windows of emergence and maximal separation. Compared with conventional sex-pooled references, sex-specific models achieved superior predictive accuracy and reduced misestimation of individual deviations in healthy populations. Across five neuropsychiatric conditions, sex-specific models improved the detection of extreme deviations and revealed both shared and sex-dependent patterns of disorder-related neuroanatomical abnormalities. These sex-specific charts establish tailored normative references for assessing brain development, ageing, and disease.

neuroscience↗

bioRxiv2026

LuTuFlow: a deep learning-based pipeline for quantitative characterization of mouse lung tumors in CT imaging

Computed tomography (CT) is a widely used, non-invasive imaging tool to monitor tumor growth. Tumor identification and volumetric quantification are crucial for assessing tumor burden, whereas tracking individual tumors by aligning scans from multiple time points reveals disease progression. However, these processes remain largely dependent on manual analysis, limiting the accuracy, reproducibility, objectivity, and scalability of tumor characterization. Several deep learning models have enabled automated segmentation and object identification. However, open-source, integrated software platforms that cover the entire workflow - including processing raw CT images, annotating and tracking tumors through time, and generating data reports and visualizations - are still needed. Here, we present LuTuFlow, a computer vision pipeline incorporating a nnU-Net-based deep learning model, configured for murine lung segmentation and tumor analysis. We integrated these modules into a Napari plugin, allowing researchers to apply the entire automated workflow to transform raw CT scan datasets into quantitative readouts and interactive visualizations in a simple graphical user interface. The resulting model, iteratively refined using expert-corrected annotations, generated reliable quantitative estimates of tumor burden.

cancer biology↗

bioRxiv2026

A split-control criterion for few-shot adaptation in single-cell perturbation prediction

Few-shot adaptation can help or harm single-cell perturbation prediction, but conventional evaluation shares a control estimate between calibration responses and held-out targets. We show how methods carry control error into their predictions and derive its contribution to score inflation. Nested control-depth experiments support inverse-depth scaling of inner-product inflation; correlation inflation also depends on the control noise-to-signal ratio. Independent-control scoring changed the rank of 40 of 52 configuration-dataset entries. We introduce SafeDelta, a split-control criterion that uses calibration data to decide whether to adapt. Across six datasets, mean gated gain was non-negative under the original two-control evaluation. On a deep plate, fixed predictions and decisions retained positive mean gains under three additional independent control references. The same reproducibility principle identified a fibrosis programme that localises to scar in human liver. These results inform adaptation decisions and control-depth planning.

bioinformatics↗

bioRxiv2026

Scan field rotation with a K-mirror for fast two-photon imaging along curved planes

In contrast to the curved geometry of biological structures, the imaging plane of conventional microscopes is flat. In principle, axial scanning can adjust the focus to follow curved structures. In resonant scanning microscopes, which are broadly used for video-rate functional imaging, however, such focus adjustment is typically possible at rates faster than the slow (~30 Hz) scan axis but not as fast as the fast (~8000 Hz) resonant axis. The fixed direction of the fast resonant axis therefore constrains how the imaging plane can be tilted or curved using axial scanning, and limits how well it can be aligned with biological structures of interest. Here, we present an optical modification that overcomes this constraint. Specifically, we combine scan field rotation using a K-mirror with fast axial scanning using an electrically tunable lens. We demonstrate the versatility of our approach for calcium imaging by aligning the imaging plane with the curved pyramidal cell layer in mouse hippocampus, increasing the number of simultaneously imaged neurons. In addition, we image dendritic arbors of hippocampal and cortical pyramidal neurons that would otherwise be only partially accessible for fast imaging, and we apply our method to the curved layers of cerebellar Purkinje cells. Furthermore, we demonstrate how scan field rotation can be used to optimally orient a dendritic branch for high-speed subcellular glutamate imaging. Our approach is based on a single module and can therefore be retrofitted to standard two-photon systems. We openly share design specifications, 3D-printed parts, and custom ScanImage-compatible code to facilitate rapid adoption.

neuroscience↗

bioRxiv2026

FLASH X-rays preserve neutrophil chromatin to boost antitumor immunity

Ultrahigh dose-rate FLASH radiotherapy spares normal tissue while preserving antitumor activity, positioning it as a promising technology in radiation oncology, but its immunomodulatory mechanisms remain elusive. Here, using a bilateral subcutaneous tumor model in mice, we show that 8-Gy FLASH X-rays, versus an equal dose of conventional dose-rate (CONV) X-rays, elicit a robust abscopal antitumor effect with anti-PD-1 therapy. Single-cell transcriptome and T cell receptor (TCR) profiling reveal that FLASH X-rays plus anti-PD-1 enhance antitumor immune infiltration and TCR clonal expansion in both irradiated and abscopal tumor lesions. Mechanistically, the ultrashort temporal continuity of FLASH dose delivery conserves chromatin compaction in neutrophils during exposure and inhibits neutrophil extracellular trap (NET) formation, thereby dismantling NET-mediated CD8+ T-cell exclusion within primary tumors. Conversely, CONV or split-dose FLASH X-rays induce marked chromatin modifications prior to dose completion, leading to chromatin hyper-relaxation which promotes NETosis and consequently abrogates systemic antitumor immunity. Notably, this detrimental effect can be reversed by pharmacologically suppressing PARylation-mediated chromatin modification and decondensation in neutrophils. These findings identify radiation-induced aberrant chromatin relaxation in neutrophils as a critical determinant of radioimmunotherapy outcomes, providing a rationale for redefining the FLASH effect and advancing its clinical translation.

cancer biology↗

bioRxiv2026

Cyclic Hypoxia drives Wnt5a-ROR1 stroma-tumor crosstalk promoting breast cancer growth

Tumor hypoxia can be stable, or cyclic based on proximity to vasculature, and affects not just the cancer cells, but also other cells in the tumor microenvironment (TME). Although cyclic hypoxia can affect cells in the tumor microenvironment differently from stable hypoxia, its effect on non-malignant cells in the tumor microenvironment (TME) is unclear. Here, using single cell RNA ATAC sequencing of multicellular co-culture model of triple-negative breast cancer (TNBC), comprising MDA-MB-231 cells, fibroblasts (Fbs), mesenchymal stromal cells (MSCs), endothelial cells, and macrophages, we systemically map the transcriptomic response shaped by dynamic oxygen regimes. Cyclic hypoxia induced a distinct transcriptional program compared to stable hypoxia in a cell type specific manner, regulating cell subpopulation proportions with key phenotypic implications. In TNBC, cyclic hypoxia reversed chronic hypoxia-induced cell cycle arrest, and reversed the enrichment of a highly mesenchymal WNT5A+/COL6+ subpopulation stabilized in hypoxia. Furthermore, cyclic hypoxia increased fibroblast activation, but suppressed MSC proliferation. Mechanistically, cyclic hypoxia coordinated paracrine WNT5A/B-ROR1 signaling between fibroblasts and TNBCs. In a mouse breast CAF-TNBC co-xenograft model, disrupting this cyclic hypoxia driven WNT5A-ROR1 stroma-cancer crosstalk reduced tumor growth in vivo. Together, our findings highlight dynamics in oxygen regimen as distinct microenvironmental cues, reprograming the TME compartments to accelerate cancer growth and invasion.

cancer biology↗