Biology subjects

Duan, D.

Publications and source records attributed to Duan, D..

13 recordsLinked to original sources

bioRxiv2025

MetaboliteChat: A Unified Multimodal Large Language Model for Interactive Metabolite Analysis and Functional Insights

Accurately characterizing the mechanisms and properties of metabolite molecules is essential for advancing metabolomics and systems biology. Yet most existing approaches are narrow, task-specific models that do not transfer across tasks and cannot express the richer, multimodal biological context of a metabolite in natural language. To address these challenges, we introduce MetaboliteChat, a multimodal ChatGPT-like large language model (LLM) that provides a unified and interactive framework for metabolite analysis. MetaboliteChat integrates molecular-graph and image reasoning with natural language understanding to generate comprehensive, free-form predictions about metabolite mechanisms and properties. The MetaboliteChat architecture consists of a graph neural network (GNN), a convolutional neural network (CNN), a large language model (LLM), and adapters, all trained end to end. This unified, multimodal design enables interactive reasoning over unseen metabolites, allowing the model to integrate structural and contextual cues and support discovery and translational insights across diverse biological systems.

bioinformatics↗

bioRxiv2025

Novel Function of Arylalkalamine N-acetyltransfe- rase-1 in Modulating Host Coagulation and Blood Feeding in Aedes aegypti

During blood feeding, mosquitoes introduce substantial quantities of salivary proteins into their hosts to facilitate feeding. Arylalkylamine N-acetyltransferase-1 (aaNAT1) is a salivary protein prominently produced in the salivary glands of Aedes aegypti. Previous research has demonstrated that mosquitoes with AaaaNAT1 mutations fail to efficiently inhibit host blood coagulation; however, the precise regulatory mechanisms remain unknown. This study identified the primary metabolites and proteins interacting with AaaaNAT1 through integrated transcriptomic, proteomic, and metabolomic analyses. Combined with isothermal titration calorimetry (ITC), immunohistochemistry, ELISA, platelet function assays, and coagulation tests, we further established that AaaaNAT1 binds norepinephrine, reducing host platelet aggregation and thereby limiting activation of the host coagulation cascade and fibrinolytic system. Additionally, behavioral investigations showed that AaaaNAT1 knockdown in Aedes aegypti significantly prolonged the time required for female mosquitoes to locate a host and successfully obtain blood, while also markedly reducing blood consumption. This effect may stem from the inability of aaNAT1-depleted mosquitoes to effectively suppress host blood aggregation during feeding, as well as the downregulation of octopamine following AaaaNAT1 knockdown. Therefore, this study reveals a novel role for aaNAT1 distinct from its known functions in pigmentation and immunity, advancing our understanding of aaNAT1s role in insects.

molecular biology↗

bioRxiv2024

Interleukin-1 prevents SARS-CoV-2-induced membrane fusion to restrict viral transmission via induction of actin bundles

Innate immune responses triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection play pivotal roles in the pathogenesis of COVID-19, while host factors including pro-inflammatory cytokines are critical for viral containment. By utilizing quantitative and qualitative models, we discovered that soluble factors secreted by human monocytes potently inhibit SARS-CoV-2-induced cell-cell fusion in viral-infected cells. Through cytokine screening, we identified that interleukin-1{beta} (IL-1{beta}), a key mediator of inflammation, inhibits syncytia formation mediated by various SARS-CoV-2 strains. Mechanistically, IL-1{beta} activates RhoA/ROCK signaling through a non-canonical IL-1 receptor-dependent pathway, which drives the enrichment of actin bundles at the cell-cell junctions, thus prevents syncytia formation. Notably, in vivo infection experiments in mice confirms that IL-1{beta} significantly restricted SARS-CoV-2 spreading in the lung epithelia. Together, by revealing the function and underlying mechanism of IL-1{beta} on SARS-CoV-2-induced cell-cell fusion, our study highlights an unprecedented antiviral function for cytokines during viral infection.

immunology↗

bioRxiv2024

Machine learning-inferred and energy landscape-guided analyses reveal kinetic determinants of CRISPR/Cas9 gene editing

The CRISPR/Cas nucleases system is widely considered the most important tool in genome engineering. However, current methods for predicting on/off-target effects and designing guide RNA (gRNA) rely on purely data-driven approaches or focus solely on the systems thermal equilibrium properties. Nonetheless, experimental evidence suggests that the process is kinetically controlled rather than being in equilibrium. In this study, we utilized a vast amount of available data and combined random forest, a supervised ensemble learning algorithm, and free energy landscape analysis to investigate the kinetic pathways of R-loop formation in the CRISPR/Cas9 system and the intricate molecular interactions between DNA and the Cas9 RuvC and HNH domains. The study revealed (a) a novel three-state kinetic mechanism, (b) the unfolding of the activation state of the R-loop being the most crucial kinetic determinant and the key predictor for on- and off-target cleavage efficiencies, and (c) the nucleotides from positions +13 to +16 being the kinetically critical nucleotides. The results provide a biophysical rationale for the design of a kinetic strategy for enhancing CRISPR/Cas9 gene editing accuracy and efficiency.

biophysics↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

magpie: a power evaluation method for differential RNA methylation analysis in N6-methyladenosine sequencing

MotivationRecently, novel biotechnologies to quantify RNA modifications became an increasingly popular choice for researchers who study epitran-scriptome. When studying RNA methylations such as N6-methyladenosine (m6A), researchers need to make several decisions in its experimental design, especially the sample size and a proper statistical power. Due to the complexity and high-throughput nature of m6A sequencing measurements, methods for power calculation and study design are still currently unavailable. ResultsWe propose a statistical power assessment tool, magpie, for power calculation and experimental design for epitranscriptome studies using m6A sequencing data. Our simulation-based power assessment tool will borrow information from real pilot data, and inspect various influential factors including sample size, sequencing depth, effect size, and basal expression ranges. We integrate two modules in magpie: (i) a flexible and realistic simulator module to synthesize m6A sequencing data based on real data; and (ii) a power assessment module to examine a set of comprehensive evaluation metrics. AvailabilityThe proposed power assessment tool magpie is publicly available as a R/Bioconductor package at: https://bioconductor.org/packages/magpie/.

bioinformatics↗

bioRxiv2023

Development of Sensorimotor-Visual Connectome Gradient at Birth Predicts Cognitive Outcomes at 2 Years of Age

Functional connectome gradients represent fundamental brain organizing principles. Here, we investigate the maturation of the macroscopic connectome gradients in a task-free functional MRI dataset consisting of 39 preterm and term babies aged 31-42 postmenstrual weeks and its connection with postnatal cognitive growth. We show that the principal sensorimotor-to-visual gradient is present in baby connectomes around 35.6 postmenstrual weeks and continuously develops towards a more term-like pattern. The gradients global topographical structure undergoes progressive maturation with age, characterized by increases in explanation ratio, gradient range and gradient variation. The development of focal gradients is mostly localized in primary regions serving sensory, motor and visual functions. Machine learning approaches revealed that the connectome gradient at birth significantly predicts individual cognitive outcomes at 2-y follow-up. These findings highlight the early emerging rules of functional connectome gradients and have implications for understanding how the connectome gradients at birth underlies cognitive growth in later life. HighlightsO_LISensorimotor-to-visual gradient is present around 35.6 postmenstrual weeks C_LIO_LIGlobal gradient structure undergoes substantial changes during the third trimester C_LIO_LIRegional gradient develops mostly in primary sensory, motor, and visual regions C_LIO_LISensorimotor-to-visual gradient at birth predicts cognitive outcomes at age 2 C_LI

neuroscience↗

bioRxiv2022

Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence

Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Using neuroimaging, connectome, transcriptome, and computational modeling, we mapped cortical thinning patterns primarily located in lateral frontal and parietal heteromodal nodes during childhood and adolescence, which is structurally constrained by white matter network architecture and is particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible while using another independent dataset. Our findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

neuroscience↗

bioRxiv2022

Abl2 mediates microtubule nucleation and repair via tubulin co-condensation.

Abl family kinases are evolutionarily conserved regulators of cell migration and morphogenesis. Genetic experiments in Drosophila suggest that Abl family kinases interact functionally with microtubules to regulate axon guidance and neuronal morphogenesis. Vertebrate Abl2 binds to microtubules and promotes their plus-end elongation both in vitro and in cells, but the molecular mechanisms by which Abl2 regulates microtubule (MT) dynamics were unclear. We report here that Abl2 regulates MT assembly via condensation and direct interactions with both the MT lattice and tubulin dimers. We find that Abl2 promotes MT nucleation, which is further facilitated by the ability of the Abl2 C-terminal half to undergo phase separation and form co-condensates with tubulin. A naturally occurring tubulin binding-deficient Abl2 splice isoform fails to promote nucleation. Abl2 binds to regions adjacent to MT damage and facilitates their repair via fresh tubulin recruitment and increases MT rescue frequency and lifetime. MT recovery after nocodazole treatment is greatly slowed in Abl2 knockout COS-7 cells compared to wild type cells. We propose a model in which Abl2 locally concentrates tubulin and recruits it to MT tips or to defects in the MT lattice to promote MT repair, rescue, and nucleation.

biochemistry↗

bioRxiv2022

Structural insight into the individual variability architecture of the functional brain connectome

Human cognition and behaviors depend upon the brains functional connectomes, which vary remarkably across individuals. However, whether and how the functional connectome individual variability architecture is structurally constrained remains largely unknown. Using tractography- and morphometry-based network models, we observed the spatial convergence of structural and functional connectome individual variability, with higher variability in heteromodal association regions and lower variability in primary regions. We demonstrated that functional variability is significantly predicted by a unifying structural variability pattern and that this prediction follows a primary-to-heteromodal hierarchical axis, with higher accuracy in primary regions and lower accuracy in heteromodal regions. We further decomposed group-level connectome variability patterns into individual unique contributions and uncovered the structural-functional correspondence that is associated with individual cognitive traits. These results advance our understanding of the structural basis of individual functional variability and suggest the importance of integrating multimodal connectome signatures for individual differences in cognition and behaviors.

neuroscience↗

bioRxiv2020

Integrating protein copy numbers with interaction networks to quantify stoichiometry in mammalian endocytosis

Proteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at various copy numbers within a cell, from hundreds (e.g. auxilin) to millions (e.g. clathrin). Between cell types with identical genomes, copy numbers further vary significantly both in absolute and relative abundance. These variations contain essential information about each proteins function, but how significant are these variations and how can they be quantified to infer useful functional behavior? Here, we address this by quantifying the stoichiometry of proteins involved in the CME network. We find robust trends across three cell types in proteins that are sub- vs super-stoichiometric in terms of protein function, network topology (e.g. hubs), and abundance. To perform this analysis, we first constructed the interface resolved network of 82 proteins involved in CME in mammals, plus lipid and cargo binding partners, totaling over 600 specific binding interactions. Our model solves for stoichiometric balance by optimizing each copy of a protein interface to match up to its partner interfaces, keeping the optimized copies as close as possible to observed copies. We find highly expressed, structure-forming proteins such as actin and clathrin do tend to be super-stoichiometric, or in excess of their partners, but they are not the most extreme cases. We test sensitivity of network stoichiometry to protein removal and find that hub proteins tend to be less sensitive to removal of any single partner, thus acting as buffers that compensate dosage changes. As expected, tightly coupled protein pairs (e.g. CAPZA2 and CAPZB) are strongly correlated. Unexpectedly, removal of functionally similar cargo adaptor proteins produces widely variable levels of disruption to the network stoichiometry. Our results predict that knockdown of the adaptor protein DAB2 will globally impact the stoichiometry of most other cargo adaptor proteins in Hela cells, with significantly less impact in fibroblast cells. This inexpensive analysis can be applied to any protein network, synthesizing disparate sources of biological data into a relatively simple and intuitive model of binding stoichiometry that can aid in dynamical modeling and experimental design.

systems biology↗

bioRxiv2020

Ultra-sensitive nanozyme-based chemiluminescence paper test for rapid diagnosis of SARS-CoV-2 infection

The recently emerged coronavirus disease COVID-19 has now evolved into a global pandemic. Early detection is crucial for its effective control. Nucleic acid testing for viral pathogen and serological testing for host antibodies are playing important roles in current COVID-19 diagnosis. However, while nucleic acid testing is complicated, facility-restricted and time-consuming, antibody testing may result in high rates of false-negative diagnoses, especially during the early stages of viral infection. Thus, a more rapid and reliable test for both early COVID-19 diagnosis and whole-population screening is urgently needed. Here, we developed a novel nanozyme-based chemiluminescence paper assay for rapid and high-sensitive testing of SARS-CoV-2 spike antigen. Our paper test uses a newly established peroxidase-mimic Co-Fe@hemin nanozyme instead of natural HRP that catalytically amplifies the chemiluminescent signal, allowing for target concentrations to be as low as 0.1 ng/ml. Furthermore, our nanozyme-based chemiluminescence test exhibits a linear range that is 32-fold wider compared to ELISA tests. Importantly, testing is completed in less than 16 min, compared to 1-2 h required for ELISA or nucleic acid tests. Critically, signal detection is feasible using a smartphone camera. Ingredients for our test are simple and readily available, rendering overall cost considerably lower than those used in current diagnoses. In conclusion, our novel test provides a high-sensitive, point-of-care testing (POCT) approach for SARS-CoV-2 antigen detection, which should greatly increase current early screening capacities for suspected infections, and considerably lower demand for national healthcare resources.

microbiology↗

bioRxiv2020

Late-life restoration of mitochondrial function reverses cardiac dysfunction in old mice

Diastolic dysfunction is a prominent feature of cardiac aging in both mice and humans. We show here that 8-week treatment of old mice with the mitochondrial targeted peptide SS-31 (elamipretide) can substantially reverse this deficit. SS-31 normalized the increase in proton leak and reduced mitochondrial ROS in cardiomyocytes from old mice, accompanied by reduced protein oxidation and a shift towards a more reduced protein thiol redox state in old hearts. Improved diastolic function was concordant with increased phosphorylation of cMyBP-C Ser282 but was independent of titin isoform shift. Late-life viral expression of mitochondrial-targeted catalase (mCAT) produced similar functional benefits in old mice and SS-31 did not improve cardiac function of old mCAT mice, implicating normalizing mitochondrial oxidative stress as an overlapping mechanism. These results demonstrate that pre-existing cardiac aging phenotypes can be reversed by targeting mitochondrial dysfunction and implicate mitochondrial energetics and redox signaling as therapeutic targets for cardiac aging.

physiology↗