Biology subjects

Liang, F.

Publications and source records attributed to Liang, F..

At least 19 recordsLinked to original sources

bioRxiv2026

A General Mathematical Model of Symport Based on Conformational Transitions

General mathematical modeling of symport faces two fundamental challenges: (i) a unified kinetic description independent of protein-specific structural details; and (ii) quantitative cross-scale mapping between microscopic conformational transitions and macroscopic physiological observables. Grounded in the fundamental physiological principle of cellular homeostasis, we propose a unifying hypothesis for symporter gating: symporters actively regulate intracellular concentrations of specific solutes within thermodynamically feasible bounds. Based on this hypothesis, we construct a universal mathematical model of symporters, employing a minimal conformational cycle as the topological scaffold and probabilistic transition rates to quantitatively describe conformational interconversion kinetics. Model simulations of experimental data from the SGLT, NaPi-II, NKCC, and NBC transporter families yield consistent fits. The resulting parameters not only reproduce experimentally observed transport behaviors---but also reveal underlying mechanistic principles of symporter function.

physiology↗

bioRxiv2026

Ultrafast and Accurate Selection of High-Quality Protein Complex Models from Large-Scale Prediction

In the post-AlphaFold era, advances in protein complex structure prediction have enabled the generation of thousands of candidate models per target, making the accurate and efficient selection of high-quality models from large candidate pools a critical challenge. Existing model-selection approaches commonly employ estimated model accuracy (EMA) methods, which include single-model and consensus-based methods. The former lack cross-model comparative information, whereas the latter often incur high computational costs from pairwise structural alignments and are influenced by candidate-pool quality. Here, we present DeepUMQA-Selection, a two-stage framework combining single-model accuracy estimators for preliminary selection with Ultrafast Shape Recognition (USR)-based structural alignment for consensus selection. Preliminary selection enriches the candidate pool with high-quality models and reduces subsequent structural comparisons, while USR-based structural alignment enables efficient consensus selection without explicit structural superposition. On the retrospective CASP16 QMODE3 benchmark dataset, DeepUMQA-Selection outperformed all participating methods and predictor-derived confidence metrics, as measured by mean Top-5 weighted penalty. The advantage was particularly pronounced for heteromeric targets, with a 13.9% improvement in model-selection performance relative to the best-performing CASP16 participating method. Furthermore, a confidence-assisted strategy enabled the framework to accommodate larger protein complexes while maintaining superior model-selection performance over competing methods, supporting its scalability. Runtime benchmarking showed that the proposed USR-based structural alignment achieved a substantial 317-fold speedup over US-align for candidate pools containing 1,000 models, demonstrating its computational efficiency for large-scale model selection. Our results demonstrate that DeepUMQA-Selection enables accurate and computationally efficient selection of high-quality protein complex models from large-scale candidate pools.

bioinformatics↗

bioRxiv2026

The Structural Code of Breast Cancer Proteoform: Alternative Splicing-driven Protein Isoform Variation and Functional Diversification

Alternative splicing generates extensive transcript diversity, but the extent to which this diversity contributes to the translated proteome and reshapes protein function remains unclear. Here, we develop 3DisoGalaxy, an atlas integrating transcript reconstruction, ribosome profiling, structural modelling and regulatory annotation in breast cancer. We find that 58,292 of 90,929 transcripts are linked to translation-supported ORFs, 71.9% of which arise from non-canonical transcript structures. These products are broadly accommodated within established protein fold space, indicating that alternative isoforms frequently preserve recognizable protein architectures despite substantial sequence variation. Functional divergence is instead concentrated in domains, intrinsically disordered regions, localization determinants and regulatory motifs. Motif remodelling is biased towards gains and is more extensive in cancer-driver genes than in other genes, linking isoform-associated regulatory variation to cancer-relevant proteins. As an example of domain remodelling, we identify an AKT1-{Delta}PH isoform that lacks the N-terminal PH domain while retaining the kinase core, with immunoblotting revealing a lower-molecular-weight AKT1 species consistent with this isoform. Together, our results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.

cancer biology↗

bioRxiv2026

An Isoform-Centric, Structure-Aware Framework for Protein Function Prediction and Evaluation, Instantiated in 3DisoDeepPF

Understanding and accurately predicting function across protein isoforms has been a long-standing challenge with profound implications for both biological and translational research. However, most functional annotations and benchmarks remain tied to genes or reference protein sequences, leaving limited support for distinguishing protein isoforms from the same gene whose sequence, structure and domain composition may lead to different functions. To address this gap, we developed an isoform-centric framework for protein function and domain annotation that integrates a dense graph of sequence and structure similarity with protein features. We implemented this framework as 3DisoDeepPF, a graph-based multimodal model, and applied it to a breast cancer isoform atlas. Across canonical benchmarks and evaluations at isoform resolution, 3DisoDeepPF showed strong performance in predicting GO terms and Pfam domains and remained robust in tests with homology control. It further captured changes in Pfam domain composition among isoforms from the same gene, including reference-relative domain gain and loss. An evidence tracing module links predicted labels to supporting proteins in the graph, as illustrated by the calcium and integrin binding protein 1 (CIB1). Together, this study provides a framework informed by protein structure for function and domain annotation at isoform resolution, converting human protein isoform diversity into traceable functional evidence for cancer atlas interpretation.

cancer biology↗

bioRxiv2026

Highly Accurate Estimation of the Fold Accuracy of Protein Structural Models

BackgroundThe function of a protein is intrinsically linked to its three-dimensional fold, and deep learning has revolutionized the field by enabling high-accuracy structure prediction at an unprecedented scale. Nevertheless, the growing deployment of these predictive pipelines in drug discovery and structural biology reveals a critical bottleneck that lies in the lack of independent and rigorous estimation of model accuracy (EMA) methodologies. ResultsHere we present DeepUMQA-Global, a single-model deep learning framework for estimating accuracy of protein structure models. Our method employs a structure-sequence cross-consistency mechanism to evaluate the bidirectional compatibility between the predicted structure and the input sequence, enabling comprehensive characterization of fold accuracy. DeepUMQA-Global outperforms the self-assessment confidence scores of AlphaFold3, achieving improvements of 57.8% in Pearson correlation and 49.0% in Spearman correlation. With respect to the CASP16 retrospective benchmark, DeepUMQA-Global outperforms all single-model accuracy estimation methods that participated in CASP16 and achieves performance comparable to that of the top consensusObased methods. A lightweight consensus strategy built upon DeepUMQA-Global ranks first among all CASP16 participants, surpassing all other methods, including consensus approaches, and highlighting the strength of our method. Remarkably, DeepUMQA-Global demonstrates a strong ability to discriminate between alternative conformational states of proteins, as evidenced in the CASP unique alternative conformation protein complex target and the CoDNaS benchmark. ConclusionsOur results indicate that DeepUMQA-Global can be extended to broader protein modeling tasks, moving beyond static evaluation to offer a foundation for dynamic conformation EMA, where it accurately discriminates alternative conformational states and demonstrates reliable predictive fidelity in model accuracy estimation.

bioinformatics↗

bioRxiv2025

Dynamic alterations of DNA methylation and transcriptome in adaptation to and recovery from the space environment

Space exploration presents tremendous health challenges. Here, we report time series of multi-omic and phenotypic profiles of seventeen astronauts from six China Manned Space missions with continuous spaceflight durations ranging from 13 to 180 days. We revealed a key role of DNA methylation regulation in reshaping gene expression patterns to adapt to the space environment. Long-duration spaceflight showed more alterations in epigenetic modifications correlated with alternative splicing and protein acetylation. During recovery, an "overrange rebound" phenomenon was observed, furthermore, a mathematical model was established to describe this implying important phenomenon. Moreover, we revealed the correlations between molecular alterations and phenotypic changes such as coagulation activation and bone intensity loss. Additionally, we performed ground-based simulation experiments to estimate the impacts of individual stressors in the space environment on DNA methylation. In summary, our study highlights the importance and complexity of epigenetic regulation in adaptation to and recovery from the space environment.

genomics↗

bioRxiv2025

PLI Analyzer for Data-driven Validation of AI Predicted Biomolecular Interfaces

PLI-Analyzer is a computational tool for detailed analysis of protein, RNA, and DNA interaction interfaces, combining atomic-level contact detection with domain annotations from UniProt and InterPro. It offers customizable interaction thresholds, residue-level output, and compatibility with AI-generated structures, enabling precise validation and interpretation of contact dynamics. We applied PLI-Analyzer to evaluate high-quality protein-protein complexes predicted by AlphaFold-3 and Boltz-2, revealing notable differences in predicted interfaces and confidence scores. These findings highlight current limitations in generative structure models specifically for macromolecular complexes and underscore the need for robust, domain-informed evaluation frameworks in structural bioinformatics.

bioinformatics↗

bioRxiv2025

A Tissue Proteolysis Activity Mapping and Substrate Discovery Platform for Identifying Novel Tumor-Activated Biosensors

Dysregulated extracellular proteolytic activity is a prominent hallmark of cancer and can thus be exploited for tumor detection and therapeutic development. However, the discovery of tumor-responsive probes has been hindered by the lack of methods capable of capturing proteolytic events directly in tissue samples. Here, we report PSurf, a platform that enables the identification of tissue-specific protease sensors with tissue specimens. Through differential selection of tumor-specific sequences over healthy tissue, PSurf identified context-specific tumor-activated probes that precisely distinguish metastatic lesions in lung tissue slices. Using these substrates, we engineered nanobody-targeted biosensors that release urinary reporters upon tumor-specific cleavage in vivo, enabling precise noninvasive tumor detection in a murine lung metastasis model. PSurf provides a foundation for developing conditionally activated agents through tissue-specific activity mapping and probe discovery.

bioengineering↗

bioRxiv2025

MViewEMA: Efficient Global Accuracy Estimation for Protein Complex Structural Models Using Multi-View Representation Learning

Estimation of model accuracy (EMA) is crucial for the reliable application of protein structure models in biological research. With the rapid advancement of protein structure prediction techniques and the explosive growth of predicted structural data, existing EMA methods struggle to balance computational efficiency with estimation performance. Here, we present MViewEMA, a single-model EMA method that leverages a multi-view representation learning framework to integrate residue-residue interaction features from micro-environment, meso-environment, and macro-environment levels for global accuracy assessment of protein complex models. Benchmark results demonstrate that MViewEMA outperforms state-of-the-art EMA methods in global accuracy assessment, achieving more than a 10-fold improvement in computational efficiency compared to our previous method, DeepUMQA3. This method enables efficient selection of high-quality protein complex models from large-scale structural datasets and achieved top performance in model selection tracks during the CASP16 blind test, demonstrating its potential to enhance the accuracy of complex structure prediction when integrated into modern frameworks such as AlphaFold-Multimer, AlphaFold3, and DiffDock-PP.

bioinformatics↗

bioRxiv2025

Intracellular imaging of MGMT and FTO

Investigations into epigenetic modifications have underscored the pivotal roles demethylases play in modulating the dynamics of RNA and DNA. Abnormal demethylase expression is closely related to the occurrence and development of many diseases. Unraveling the individual activity of different demethylases is essential to study the underlying mechanisms. In this paper, we report the development of demethylase-responsive DNAzyme-powered walkers designed for the simultaneous imaging of two important demethylases: O6-methylguanine-DNA methyltransferase (MGMT) and fat mass and obesity-associated protein (FTO). Epigenetically inactivated DNAyzme-based DNA walker-functionalized gold nanoparticles were employed to orthogonally visualize MGMT and FTO activities in various live cancer cell lines with high sensitivity. This method offers a direct way for the comprehensive evaluation of multiple demethylase activities, and the understanding of epigenetic regulation.

molecular biology↗

bioRxiv2024

Uncovering Ancient DNA in Petroleum: Insights into Earth Hidden Life Events and Geological History

Specific macromolecules in petroleum, preserved through geological processes from ancient organisms, are recognized as molecular fossils or geochemical markers (GMs). Our selected GMs indicate that the source rocks of Nanyang Oilfield formed in an anoxic, saline, and stratified lacustrine environment with marine influence. Contrary to science fiction notions that oil originates from ancient large animals, mainstream academia has consistently asserted that oil is derived from the organic matter of lower life forms, formed over extended geological processes, with intact DNA no longer persisting in oil post-formation. However, this study successfully extracted 3,159,020 DNA fragments from the petroleum samples using the nanoparticle affinity bead technology, followed by sequencing and classification via the mega screen method. These fragments, categorized as original in situ DNA (oriDNA), recent environmental DNA (preDNA), and paleo-environmental DNA (paeDNA), exhibit a "Genome Accumulated over Time" (GAT) pattern of "old-less, new-many". This aligns with findings from GMs while offering more specific genetic information. The analysis reveals evidence of historical events, including animal extinctions, marine invasions, ancient bird species presence, Asian Homo erectus activities, and modern human influences in preDNA. Notably, the mitogenomic data positions Asian Homo erectus closer to modern humans than to chimpanzees at the maternal basis. The absence of deamination in petroleum ancient DNA (aDNA) fragments is likely due to the anaerobic, anhydrous environment and the screening process that excludes degraded fragments. Consequently, the authenticity criteria and scope of application of traditional aDNA methods require reevaluation. Surprisingly, the near-absence of oriDNA has impeded our efforts to determine the specific biological origins of the oil. These findings position petroleum as a novel, non-skeletal source of aDNA, offering insights into ancient animal activities, geological changes, and human origins while underscoring its potential as an untapped resource for studying genetic preservation across geological timescales.

paleontology↗

bioRxiv2024

The ZIP8 A391T Crohn's disease-linked risk variant induces colonic metal ion dyshomeostasis, microbiome compositional shifts, and inflammation

The pathogenesis of Crohns disease involves genetic and environmental factors, with the gut microbiome playing a crucial role. The Crohns disease-associated variant rs13107325 in the SLC39A8 gene results in an A391T substitution in the ZIP8 metal ion transporter and has previously been linked to alterations in the colonic microbiome in variant carriers. We hypothesized that the A391T substitution alters metal ion homeostasis in the colonic mucosal-luminal interface, thereby inducing dysbiosis which may promote intestinal inflammation. To evaluate this hypothesis, we generated a SLC39A8 A393T mouse model (matching human A391T). Consistent with an effect of the variant on ZIP8 function, homozygous A393T mice exhibited increased cobalt in the colonic mucosa, but reduced iron, zinc, manganese, cobalt, copper, and cadmium in the colonic lumen. We performed 16S rRNA gene sequencing of colon samples and histological scoring of colon tissue collected from the SLC39A8 A393T mouse model at different ages. We identified variant-linked effects on microbiome beta diversity in 2-month, 3-4 month, and 12-month old mice and spontaneous intestinal inflammation in 10-month but not 5-month old mice. Predicted pathway analysis of the microbiome samples revealed differential enrichment of iron-, zinc- and cobalt-dependent pathways in A393T mice compared to wild-type controls. These results suggest that the variant in SLC39A8 primarily restricts metal availability to the microbiota, resulting in compositions that can adapt to the environment, and that A393T-linked dysbiosis occurs prior to the onset of inflammation. This study paves the way for future studies investigating risk variants as microbiome-disease modifiers. NEW & NOTEWORTHYMice recapitulating the human A391T Crohns disease-linked risk variant in the SLC39A8-encoded ZIP8 transporter exhibit reduced luminal trace metals and an altered microbiome composition. The microbiome compositional shift occurs prior to the onset of spontaneous colonic inflammation. This study supports an emerging paradigm by which genetic risk for inflammatory bowel disease may confer disease susceptibility through modulation of the gut microbiome.

genomics↗

bioRxiv2024

Beta-frequency sensory stimulation enhances gait rhythmicity through strengthened coupling between striatal networks and stepping movement

Stepping movement is delta (1-4 Hz) rhythmic and depends on sensory inputs. In addition to delta rhythms, beta (10-30 Hz) frequency dynamics are also prominent in the motor circuits and are coupled to neuronal delta rhythms both at the network and the cellular levels. Since beta rhythms are broadly supported by cortical and subcortical sensorimotor circuits, we explore how beta-frequency sensory stimulation influences delta-rhythmic stepping movement, and dorsal striatal circuit regulation of stepping. We delivered audiovisual stimulation at 10 Hz or 145 Hz to mice voluntarily locomoting, while simultaneously recording stepping movement, striatal cellular calcium dynamics and local field potentials (LFPs). We found that 10 Hz, but not 145 Hz stimulation prominently entrained striatal LFPs. Even though sensory stimulation at both frequencies promoted locomotion and desynchronized striatal network, only 10 Hz stimulation enhanced the delta rhythmicity of stepping movement and strengthened the coupling between stepping and striatal LFP delta and beta oscillations. These results demonstrate that higher frequency sensory stimulation can modulate lower frequency dorsal striatal neural dynamics and improve stepping rhythmicity, highlighting the translational potential of non-invasive beta-frequency sensory stimulation for improving gait.

neuroscience↗

bioRxiv2023

Nanoscale imaging of pT217-tau in aged rhesus macaque entorhinal and dorsolateral prefrontal cortex: Evidence of interneuronal trafficking and early-stage neurodegeneration

Structured Abstract INTRODUCTIONpT217-tau is a novel fluid-based biomarker that predicts onset of Alzheimers disease (AD) symptoms, but little is known about how pT217-tau arises in brain, as soluble pT217-tau is dephosphorylated postmortem in humans. METHODSWe utilized multi-label immunofluorescence and immunoelectron-microscopy to examine the subcellular localization of early-stage pT217-tau in entorhinal and prefrontal cortices of aged macaques with naturally-occurring tau pathology and assayed pT217-tau levels in plasma. RESULTSpT217-tau was aggregated on microtubules within dendrites exhibiting early signs of degeneration, including autophagic vacuoles. It was also seen trafficking between excitatory neurons within synapses on spines, where it was exposed to the extracellular space, and thus accessible to CSF/blood. Plasma pT217-tau levels increased across the age-span and thus can serve as a biomarker in macaques. DISCUSSIONThese data help to explain why pT217-tau predicts degeneration in AD and how it gains access to CSF and plasma to serve as a fluid biomarker.

neuroscience↗

bioRxiv2023

Multimodal single cell-resolved spatial proteomics reveals pancreatic tumor heterogeneity

Despite the advances in antibody-guided cell typing and mass spectrometry-based proteomics, their integration is hindered by challenges for processing rare cells in the heterogeneous tissue context. Here, we introduce Spatial and Cell-type Proteomics (SCPro), which combines multiplexed imaging and flow cytometry with ion exchange-based protein aggregation capture technology to characterize spatial proteome heterogeneity with single cell resolution. The SCPro was employed to explore the pancreatic tumor microenvironment and revealed the spatial alternations of over 5,000 proteins by automatically dissecting up to 100 single cells guided by multi-color imaging of centimeter-scale formalin-fixed, paraffin-embedded tissue slide. To enhance cell-type resolution, we characterized the proteome of 14 different cell types by sorting up to 1,000 cells from the same tumor, which allows us to deconvolute the spatial distribution of immune cell subtypes and leads to the discovery of a novel subtype of regulatory T cells. Together, the SCPro provides a multimodal spatial proteomics approach for profiling tissue proteome heterogeneity.

systems biology↗

bioRxiv2023

Inhibition of miR-199b-5p reduces pathological alterations in Osteoarthritis by targeting Fzd6 and Gcnt2

Osteoarthritis (OA) is a degenerative disease with a high prevalence in the elderly population, but our understanding of its mechanisms remains incomplete. Analysis of serum exosomal small RNA sequencing data from clinical patients and gene expression data from OA patient serum and cartilage obtained from the GEO database revealed a common dysregulated miRNA, miRNA-199b-5p. In vitro cell experiments demonstrated that miRNA-199b-5p inhibits chondrocyte vitality and promotes extracellular matrix degradation. Conversely, inhibition of miRNA-199b-5p under inflammatory conditions exhibited protective effects against damage. Local viral injection of miRNA-199b-5p into mice induced a decrease in pain threshold and OA-like changes. In an OA model, inhibition of miRNA-199b-5p alleviated the pathological progression of OA. Furthermore, bioinformatics analysis and experimental validation identified Gcnt2 and Fzd6 as potential target genes of miRNA-199b-5p. Thus, these results indicated that miRNA-199b-5p/Gcnt2 and Fzd6 axis might be a novel therapeutic target for the treatment of OA.

molecular biology↗

bioRxiv2023

NextPolish2: a repeat-aware polishing tool for genomes assembled using HiFi long reads

The high-fidelity (HiFi) long-read sequencing technology developed by PacBio has greatly improved the base-level accuracy of genome assemblies, but these assemblies still contain some base-level errors, particularly within the error-prone regions of HiFi long reads. However, existing genome polishing tools usually introduce overcorrections and haplotype switch errors when correcting errors in genomes assembled from HiFi long reads. Here we describe an upgraded genome polishing tool - NextPolish2, which can fix base errors remaining in those "highly accurate" genomes assembled from HiFi long reads without introducing excess overcorrections and haplotype switch errors. We believe NextPolish2 has a great significance to further improve the accuracy of Telomere-to-Telomere (T2T) genomes. NextPolish2 is freely available at https://github.com/Nextomics/NextPolish2.

bioinformatics↗

bioRxiv2023

An efficient error correction and accurate assembly tool for noisy long reads

Long read sequencing data, particularly those derived from the Oxford Nanopore (ONT) sequencing platform, tend to exhibit a high error rate. Here, we present NextDenovo, a highly efficient error correction and assembly tool for noisy long reads, which achieves a high level of accuracy in genome assembly. NextDenovo can rapidly correct reads; these corrected reads contain fewer errors than other comparable tools and are characterized by fewer chimeric alignments. We applied NextDenovo to the assembly of high quality reference genomes of 35 diverse humans from across the world using ONT Nanopore long read sequencing data. Based on these de novo genome assemblies, we were able to identify the landscape of segmental duplications and gene copy number variation in the modern human population. The use of the NextDenovo program should pave the way for population-scale long-read assembly, thereby facilitating the construction of human pan-genomes, using Nanopore long read sequencing data.

bioinformatics↗