Biology subjects

Luo, N.

Publications and source records attributed to Luo, N..

At least 19 recordsLinked to original sources

bioRxiv2026

A MET-Targeted Variable New Antigen Receptor Theranostic for Non-Small Cell Lung Cancer

The MET receptor tyrosine kinase is mutated or amplified in [~]6% of non-small cell lung cancer (NSCLC) and overexpressed in [~]80% of all NSCLC cases. A theranostic agent that can both see and treat MET-altered NSCLC has never been described before in the literature. Here, we report a shark-derived single-domain variable new antigen receptor (VNAR) for MET with theranostic applications. Following the immunization of a juvenile nurse shark (Ginglymostoma cirratum) with the extracellular domain of human MET, we identified a VNAR clone that specifically engaged MET with high affinity. Engineering the lead VNAR into a bivalent human Fc, vMET1-Fc, yielded a construct that selectively targeted and was internalized by MET-positive cells without affecting cell viability or downstream MET signaling. When radiolabeled with the positron emitting isotope Zr-89, [89Zr]Zr-vMET1-Fc enabled longitudinal PET/CT imaging. High tumor uptake with low background was observed in MET-positive NSCLC xenografts administered [89Zr]Zr-vMET1-Fc. As a targeted beta-particle radiotherapy, [{superscript 1}Lu]Lu-vMET1-Fc resulted in marked tumor-growth delay and exhibited a favorable toxicity profile, collectively improving progression-free survival in NSCLC mouse models. Non-human primate PET/CT imaging studies with ([Zr]Zr-vMET1-Fc in healthy rhesus macaques confirmed favorable biodistribution and dosimetry, predictable clearance, and minimal off-target uptake. Additional blood chemistry analysis found no significant immune response or cytotoxicity. Together, these findings establish vMET1-Fc as a theranostic agent for imaging and treating MET-altered NSCLC. Statement of SignificanceA shark-derived antibody selectively targeting MET shows preclinical efficacy as a theranostic agent for MET-altered cancer.

cancer biology↗

bioRxiv2025

Transport of endo-β-mannosidase AtEBM from cytoplasm to the vacuole through autophagy pathway in Arabidopsis

Autophagy is a conserved eukaryotic intracellular degradation pathway that exhibits specialized forms, such as the biosynthetic cytoplasm-to-vacuole targeting (Cvt) pathway in yeast. This pathway selectively delivers several hydrolase precursors to the vacuole. While the core autophagy machinery is highly conserved between yeast and plants, the existence of a similar Cvt-like pathway for vacuolar hydrolase trafficking in plants remains unclear. Here, we found that Arabidopsis thaliana endo-{beta}-mannosidase (AtEBM), a glycosidase involved in degrading vacuolar N-glycans released from glycoproteins, is selectively transported to the vacuole via autophagy. Further analyses revealed that AtEBM directly interacts with the core autophagy protein ATG8 through an ATG8-interacting motif (AIM). This interaction is essential for sequestering AtEBM into autophagosomes. Remarkably, the AIM is conserved among EBM orthologs across the green plant lineage. In addition, several phenotypic studies showed that atebm mutants generated through CRISPR-Cas9 editing did not exhibit autophagy defects, including early senescence and hypersensitivity to nutrient starvation, but rather had reduced fecundity. Thus, these findings reveal a Cvt-like pathway in plants that fulfills a biosynthetic role by selectively delivering the glycosidase AtEBM to the vacuole.

cell biology↗

bioRxiv2025

AAV11 mediates efficient retrograde trans-neuronal transduction of astrocytes

Understanding the mechanisms by which astrocytes regulate neural circuits is crucial for elucidating the mechanisms underlying cognitive and behavioral abnormalities in psychiatric disorders and for exploring potential therapeutic or intervention strategies. Viral tracers are powerful vehicles for comprehending the complex relationship between neurons and astrocytes. Despite adeno-associated virus 1 (AAV1) based anterograde trans-neuronal tools have been successfully applied for identifying astrocytes connected with presynaptic neurons, analogous retrograde trans-neuronal tools for labeling astrocytes connected to postsynaptic neurons remain under development. Here, we first demonstrate that GfaABC1D promoter embedding AAV11 can transfer retrogradely from axons of postsynaptic neurons to astrocytes. Furthermore, we established an AAV11-based dual-viral recombination strategy for labeling astrocytes connected to specific postsynaptic neurons. Finally, by employing targeted neuronal ablation technology to ablate neurons in a specific brain region, we observed that injection of AAV11 into the downstream brain region of this targeted area exhibited minimal labeling of astrocytes functionally associated with the ablated neurons. This finding indicates that AAV11 holds utility for deciphering pathological alterations in disease-related astrocyte-neuron connectivity networks. This work fills a key gap in tools used for studying astrocyte-neuron connectivity networks.

neuroscience↗

bioRxiv2025

Digital Twin Brain Predicts rTMS Effects on Brain State Dynamics in Chronic Tinnitus

Predicting repetitive transcranial magnetic stimulation (rTMS) effects on whole-brain dynamics in clinical populations is crucial for developing personalized therapies and advancing precision medicine in brain disorders. This study provides the first proof-of-concept demonstrating that the Digital Twin Brain (DTB) can forecast rTMS effects on brain state dynamics in individuals with brain disorders (chronic tinnitus). First, we identified two aberrant brain states that predominantly overlapped with the somatomotor and default mode networks, respectively. Subsequently, we developed DTB for patients and derived regional responses for each brain region, revealing distinct roles of the parieto-occipital and frontal regions. Mechanistically, we examined the biological plausibility using tinnitus-specific risk genes and investigated the multi-scale neurobiological relevance. Clinically, we found that DTB can predict rTMS effects in an independent, longitudinal dataset (all r > 0.78). Particularly, the predictive capacity exhibits a state-specific nature. Overall, this work proposes a novel DTB-based framework for predicting rTMS effects in clinical populations and provides the first empirical evidence supporting its clinical utility. This approach may be generalizable to other brain disorders and neuromodulation techniques, promoting broader advancements in brain health.

neuroscience↗

bioRxiv2025

Energy inefficiency underpinning brain state dysregulation in individuals with major depressive disorder

Disruptions in brain state dynamics are a hallmark of major depressive disorder (MDD), yet their underlying mechanisms remain unclear. This study, building on network control theory, revealed that decreased state stability and increased state-switching frequency in MDD are driven by elevated energy costs and reduced control stability, indicating energy inefficiency. Key brain regions, including the left dorsolateral prefrontal cortex, exhibited impaired energy regulation capacity, and these region-specific energy patterns were correlated with depressive symptom severity. Neurotransmitter and gene expression association analyses linked these energy deficits to intrinsic biological factors, notably the 5-HT2a receptor and excitatory-inhibitory balance. These findings shed light on the energetic mechanism underlying brain state dysregulation in MDD and its associated biological underpinnings, highlighting brain energy dynamics as a potential biomarker by which to explore therapeutic targets and advance precise interventions for restoring healthy brain dynamics in depression.

neuroscience↗

bioRxiv2025

Physical Activity and Depressive Mood Shared the Structural Connectivity between Motor and Reward Network: a population-based study from the UK Biobank

BackgroundExercise has been revealed to leave a positive effect on alleviating depressive symptoms by various existing studies. However, the neural basis behind this phenomenon remains unknown, as well as its underlying biological mechanism.AimsUsing a large neuroimaging cohort from UK Biobank, this study aimed to identify structural connectivity (SC) patterns simultaneously linked with physical activity and depression, as well as its biological interpretation.Method492 participants with major depression disorder (MDD) and 535 healthy controls (HC) were extracted from the UK Biobank dataset. Partial least squares regression was first utilized to explore a replicable SC pattern simultaneously associated with physical activity and depressive mood. The neuromaps toolbox was applied to interpret the biological ontologies of the identified SC pattern. Neuroimaging-transcriptome association and enrichment analyses were conducted to explore its underlying genetic basis, pathways and cell types. The reproducibility and generalizability were tested on another independent MDD dataset (N=3,496) and bipolar disorder (BD) dataset (N=81).ResultsA SC pattern linked with exercise was identified to be both significantly correlated with depressive mood and group discriminative between MDDs and HCs, which primarily located between the motor-related regions and reward-related regions. This pattern was associated with multiple neurotransmitter receptors, such as serotonin and GABA receptors, and enriched in pathways like synaptic signaling and astrocytes cell type. The SC pattern and genetic results were also replicated in another independent MDD dataset and present commonalities with BD.ConclusionsThis study not only initially identified a reproducible shared SC pattern between physical activity and depressive mood, but also elucidated the underlying biological mechanisms, which enhanced our understanding of how exercise helps alleviate depression and may inform the development of novel neuromodulation targets.

neuroscience↗

bioRxiv2025

Keystone engineering enables collective range expansion in microbial communities

Keystone engineers profoundly influence microbial communities by altering their shared environment, often by modifying key resources. Here, we show that in an antibiotic-treated microbial community, bacterial spread is controlled by keystone engineering affecting dispersal--an effect hidden in well-mixed environments. Focusing on two pathogens, non-motile Klebsiella pneumoniae and motile Pseudomonas aeruginosa, we found that both tolerate a {beta}-lactam antibiotic, with Pseudomonas being more resilient and dominating in well-mixed cultures. During range expansion, however, the antibiotic inhibits Pseudomonas ability to spread unless it is near Klebsiella--Klebsiella degrades the antibiotic to create a "clear zone" that allows Pseudomonas to expand, at the expense of Klebsiellas own growth, thus acting as a keystone engineer. As Pseudomonas spreads, it competitively suppresses Klebsiella. Our modeling and experimental analyses reveal that this keystone effect operates at a millimeter scale. We also observed similar keystone engineering by a Bacillus species isolated from a hospital sink, in both pairwise and eight-member bacterial communities with its co-isolates. These findings suggest that spatially explicit experiments are essential to understand certain keystone engineering mechanisms and have implications for surface-associated microbial communities like biofilms, as well as for diagnosing and treating polymicrobial infections involving drug-degrading, non-motile (e.g., Klebsiella), and drug-tolerant, motile (e.g., Pseudomonas) bacteria.

ecology↗

bioRxiv2024

Decoding pattern formation rules by integrating mechanistic modeling and deep learning

Predictive programming of self-organized pattern formation using living cells is challenging in major part due to the difficulty in navigating through the high-dimensional design space effectively. The emergence and characteristics of patterns are highly sensitive to both system and environmental parameters. Often, the optimal conditions able to generate patterns represent a small fraction of the possible design space. Furthermore, the experimental generation and quantification of patterns is typically labor intensive and low throughput, making it impractical to optimize pattern formation solely based on trials and errors. To this end, simulations using a well-formulated mechanistic model can facilitate the identification of optimal experimental conditions for pattern formation. However, even a moderately complex system can make these simulations computationally prohibitive when applied to a large parameter space. In this study, we demonstrate how integrating mechanistic modeling with machine learning can significantly accelerate the exploration of design space for patterning circuits and aid in deriving human-interpretable design rules. We apply this strategy to program self-organized ring patterns in Pseudomonas aeruginosa using a synthetic gene circuit. Our approach involved training a neural network with simulated data to predict pattern formation 10 million times faster than the mechanistic model. This neural network was then used to predict pattern formation across a vast array of parameter combinations, far exceeding the size of the training dataset and what was computationally feasible using the mechanistic model alone. By doing so, we identified many parameter combinations able to generate desirable patterns, which still represent an extremely small fraction of explored parametric space. We next used the mechanistic model to validate top candidates and identify coarse-grained rules for patterning. We experimentally demonstrated the generation and control of patterning guided by the learned rules. Our work highlights the effectiveness in integrating mechanistic modeling and machine learning for rational engineering of complex dynamics in living cells.

synthetic biology↗

bioRxiv2024

Microglia-specific transduction via AAV11 armed with IBA1 promoter and miRNA-9 targeting sequences

Microglia, as resident immune cells in the central nervous system (CNS), are closely related to human health and the pathogenesis of various CNS diseases, making them compelling targets for therapeutic interventions. However, functional and therapeutic studies of microglia remain significant challenges largely due to the lack of tools capable of efficiently and specifically transducing microglia. Herein, we evaluated the specificity and efficiency of various adeno-associated virus (AAV) vectors armed with the mIBA1 promoter and miRNA-9 targeting sequences in transducing microglia within the caudate putamen (CPu) brain region, and found that AAV11 mediates more specific and efficient transduction of microglia. Subsequently, we further demonstrated that AAV11 also exhibits high transduction specificity for microglia across various brain areas and within the spinal cord. Finally, by reducing the injection dosage, we employed AAV11 for sparse labeling of microglia. This work provides a promising tool for advancing both the functional investigation and therapeutic targeting of microglia.

neuroscience↗

bioRxiv2023

FFCM-MRF: An accurate and generalizable cerebrovascular segmentation pipeline for humans and rhesus monkeys based on TOF-MRA

PurposeCerebrovascular segmentation and quantification of vascular morphological features on humans and rhesus monkeys are essential for prevention, diagnosis, and treatment of brain diseases. However, current automated whole-brain vessel segmentation methods are often not generalizable to independent datasets, limiting their usefulness in real-world environments with their heterogeneity in participants, scanners, and species. Materials and MethodsIn this study, we proposed an automated, accurate and generalizable segmentation method for magnetic resonance angiography images called FFCM-MRF. This method integrates fast fuzzy c-means clustering and Markov random field optimization using blood vessel shape priors and spatial constraints. We used a total of 123 human and 44 macaque MRA images scanned at 1.5 T, 3 T, and 7 T MRI from 9 datasets to develop and validate the method. ResultsThe average Dice score coefficients for multiple independent datasets were 69.16-89.63%, with the improvements in FFCM-MRF ranged from 0.16-16.14% compared with state-of-the-art machine learning methods. Quantitative analysis showed that FFCM-MRF can accurately segment major arteries in the Circle of Willis at the base of the brain and smaller distal pial arteries while effectively suppressing noise. Test-retest analysis showed that the model yielded high vascular volume and diameter reliability. ConclusionsOur results demonstrate that the proposed method is highly accurate and reliable and largely independent of variations in field strength, scanner platforms, acquisition parameters, and species. The macaque MRA data and user-friendly open-source toolbox are freely available at OpenNeuro and GitHub to facilitate studies of imaging biomarkers for cerebrovascular and neurodegenerative diseases.

neuroscience↗

bioRxiv2023

Osteocalcin of maternal and embryonic origins synergize to establish homeostasis in offspring

Many physiological functions regulated by osteocalcin are affected in adult offspring of mothers experiencing an unhealthy pregnancy. Furthermore, osteocalcin signaling during gestation influences cognition and adrenal steroidogenesis in adult mice. Together these observations suggest that osteocalcin functions during pregnancy may be a broader determinant of organismal homeostasis in adult mammals than previously thought. To test this hypothesis, we analyzed in unchallenged wildtype and Osteocalcin-deficient, newborn, and adult mice of various genotypes and origin, and that were maintained on different genetic backgrounds, the functions of osteocalcin in the pancreas, liver and testes and their molecular underpinnings. This analysis revealed that providing mothers are themselves Osteocalcin-deficient, Osteocalcin haploinsufficiency in embryos hampers insulin secretion, liver gluconeogenesis, glucose homeostasis, testes steroidogenesis in adult offspring; inhibits cell proliferation in developing pancreatic islets and testes; and disrupts distinct programs of gene expression in these organs and in the brain. This study indicates that through their synergistic regulation of multiple physiological functions, osteocalcin ofmaternal and embryonic origins contributes to the establishment and maintenance of organismal homeostasis in newborn and adult offspring.

physiology↗

bioRxiv2022

Macaque Brainnetome Atlas with Fine-grained Parcellations and Reliable Connections

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas that identifies anatomically and functionally distinct regions is fundamental to biomedical and evolutionary research. However, even though connectivity information is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were comprehensively evaluated with multi-contrast MRI, invasive neuronal-tracing, and Nissl-stained images collected from a single subject and with open-access datasets from other cohorts. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, block-face, and section images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

neuroscience↗

bioRxiv2022

Distributed information encoding and decoding using self-organized spatial patterns

Dynamical systems often generate distinct outputs according to different initial conditions, and one can infer the corresponding input configuration given an output. This property captures the essence of information encoding and decoding. Here, we demonstrate the use of self-organized patterns, combined with machine learning, to achieve distributed information encoding and decoding. Our approach exploits a critical property of many natural pattern-formation systems: in repeated realizations, each initial configuration generates similar but not identical output patterns due to randomness in the patterning process. However, for sufficiently small randomness, different groups of patterns that arise from different initial configurations can be distinguished from one another. Modulating the pattern generation and machine learning model training can tune the tradeoff between encoding capacity and security. We further show that this strategy is applicable to non-biological dynamical systems and scalable by implementing the encoding and decoding of all characters of the standard English keyboard. Significance StatementSelf-organized patterns are ubiquitous in biology. They arise from interactions in and between cells, and with the environment. These patterns are often used as a composite phenotype to distinguish cell states and environment conditions. Conceptually, pattern generation under an initial condition is encoding; discerning the initial condition from the pattern represents decoding. Inspired by these examples, we develop a scheme, integrating mathematical modeling and machine learning, to use self-organization for secure and accurate information encoding and decoding. We show that this strategy is applicable to non-biological dynamical systems. We further demonstrate the scalability of the scheme by generating a complete mapping of the standard English keyboard, allowing encoding of English text. Our work serves as an example of nature-inspired computation.

systems biology↗

bioRxiv2022

Improved production and expanded application of CVS-N2c-ΔG virus for retrograde tracing

Neurotropic virus tracers, particularly those with low toxicity and high efficient tracing, are powerful tools for structural and functional dissections of neural circuits. The retrograde trans-mono-synaptic technology based on rabies virus CVS-N2c strain has reduced cytotoxicity and enhanced efficiency, attains long-term gene manipulation for functional studies, but suffers from difficult preparation and low yield. To overcome these shortcomings, an improved production system was established for rapid rescue and preparation of CVS-N2c-{Delta}G virus, CVS-N2c-{Delta}G with the same titer as SAD-B19-{Delta}G can be prepared within a short time. Meanwhile, we found that N2cG coated CVS-N2c-{Delta}G allows efficient retrograde access to projection neurons, and further expand its application in VTA/SNc to DLS pathway that unaddressed by rAAV9-Retro, and the efficiency is 6 folds higher than that of rAAV9-Retro. Then the trans-synaptic efficiency of CVS-N2c-{Delta}G virus was evaluated. Results showed that the trans-mono-synaptic efficiency of oG-mediated CVS-N2c-{Delta}G was 2-3 folds higher than that of oG-mediated SAD-B19-{Delta}G, but there was no difference between oG-mediated and N2cG-mediated CVS-N2c-{Delta}G system. In addition, codon modified N2cG (optiG) did not increase the efficiency of CVS-N2c-{Delta}G tracing. Finally, we found that the CVS-N2c-{Delta}G produced by the improved method can be used for monitoring neural activity of projection neurons, and the time window can be maintained for 3 weeks, and it can also express sufficient recombinases for efficient transgene recombination. That is, the virus produced by the improved production system does not affect its own function, paving the way for its further optimization, popularization and application in structural and functional studies of neural circuits.

neuroscience↗

bioRxiv2022

AAV11 permits efficient retrograde targeting of projection neurons

Viral tracers that permit efficient retrograde targeting of projection neurons are powerful vehicles for structural and functional dissections of the neural circuit and for the treatment of brain diseases. Recombinant adeno-associated viruses (rAAVs) are the most potential candidates because they are low-toxic with high-level transgene expression and minimal host immune responses. Currently, some rAAVs based on capsid engineering for retrograde tracing have been widely used in the analysis and manipulation of neural circuits, but suffer from brain area selectivity and inefficient retrograde transduction in certain neural connections. Here, we discovered that the recombinant adeno-associated virus 11 (rAAV11) exhibits potent retrograde labeling of projection neurons with enhanced efficiency to rAAV2-retro in some neural connections. Combined with calcium recording technology, rAAV11 can be used to monitor neuronal activities by expressing Cre recombinase or calcium-sensitive functional probe. In addition, we further showed the suitability of rAAV11 for astrocyte targeting. These properties make rAAV11 a promising tool for the mapping and manipulation of neural circuits and gene therapy of some neurological and neurodegenerative disorders. HighlightsO_LINaturally occurring AAV serotype capsid exhibits robust retrograde functionality C_LIO_LIImproved distribution properties and retrograde transport efficiency C_LIO_LICan express Cre recombinase or calcium-sensitive functional probe for neural circuits monitoring C_LIO_LICan specifically target astrocytes C_LI

neuroscience↗

bioRxiv2021

Daily oscillation of the excitation/inhibition ratio is disrupted in two mouse models of autism

Alterations to the balance between excitation and inhibition (E/I ratio) are postulated to underlie behavioral phenotypes in autism spectrum disorder (ASD) patients and mouse models. However, in wild type mice the E/I ratio is not constant, but instead oscillates across the 24h day. Therefore, we tested whether the E/I oscillation, rather than the overall E/I ratio, is disrupted in two ASD-related mouse lines: Fmr1 KO and BTBR, models of syndromic and idiopathic ASD, respectively. The E/I ratio is dysregulated in both models, but in different ways: the oscillation is lost in Fmr1 KO and reversed in BTBR mice. In both models these phenotypes associate with differences the timing of excitatory and inhibitory synaptic transmission and endocannabinoid signaling compared to wild type mice, but not with altered sleep. These findings raise the possibility that ASD-related phenotypes may be produced by a mismatch of E/I to the appropriate behavioral state, rather than alterations to overall E/I levels per se.

neuroscience↗

bioRxiv2021

Engineered AIM-based Selective Autophagy to Degrade Proteins and Organelles

Techniques for disrupting of protein function are essential for biological researches and therapeutics development. Though well-established, genetic perturbation strategies may have off-target effects and/or trigger compensatory mechanisms, and cannot efficiently eliminate existing protein variants or aggregates1, 2. Therefore, precise and direct protein-targeting methods are highly desired. Here we describe a novel method for targeted protein clearance by engineering an autophagy receptor with a binder to provide target specificity and an ATG8-binding motif (AIM) to link the targets to nascent autophagosomes, thus harnessing the autophagy machinery for degradation. We demonstrate its specificity and broad potentials by degrading various fluorescent-tagged proteins and peroxisome organelle, using a tobacco-based transient expression system, and by degrading endogenous proteins in transgenic Arabidopsis expressing engineered receptors. With the wide substrate scope and specificity of selective autophagy, our method provides a convenient and robust strategy for eliminating proteins and aggregates, and may enable developing new treatments for protein-related disorders.

cell biology↗

bioRxiv2020

TipQAD: an automated tool for quantifying apical fluorescence dynamics in tip-growing cells

Cell polarity is a fundamental property essential for the function and development of all cellular organisms. Tip growth is an extreme form of polar growth requiring spatiotemporally dynamic but highly coordinated cellular activities. Quantification of these dynamic activities is important for the systematic study of the mechanisms controlling cell polarity, but an automated and unbiased method for analyzing and quantification of tip-growing cells has been missing. In this paper, we developed a computational model and an associated tool called TipQAD for quantifying the spatiotemporal dynamics of fluorescence protein (FP) labeled molecules or structures in tip-growing cells. This tool robustly and accurately measured the spatial distribution and temporal dynamics of FP-labeled proteins in the cytoplasm or the plasma membrane at the tip region of several types of tip-growing cells. We also demonstrated its ability to analyze data from FRAP experiments. In conclusion, this tool showed great potential for automated measurements of the spatiotemporal dynamics of fluorescent-labeled cellular molecules and structures.

plant biology↗