Biology subjects

Dong, A.

Publications and source records attributed to Dong, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Selective GRAB sensors reveal distinct endocannabinoid dynamics in vivo

The endocannabinoid system modulates diverse physiological processes via two endogenous lipid ligands, 2-arachidonoylglycerol (2-AG) and anandamide (AEA); however, their specific spatiotemporal dynamics remain poorly understood owing to the lack of selective probes. Here, we developed GRAB2-AG2.0 and GRABAEA2.0, two genetically encoded fluorescent sensors that selectively detect 2-AG and AEA, respectively. Both sensors exhibited high apparent affinity and molecular specificity for their respective ligands, enabling the real-time detection of 2-AG and AEA release evoked by electrical stimulation in cultured neurons and acute brain slices. In freely behaving mice, these sensors revealed ligand- and context-specific eCB dynamics: aversive stimulation preferentially evoked 2-AG, whereas psychoactive drugs produced distinct 2-AG and AEA responses. Notably, {Delta}9-THC elicited a sustained 2-AG signal in the nucleus accumbens shell, and local deletion of Dagla markedly attenuated both this signal and {Delta}9-THC-induced hypolocomotion. These sensors therefore enable detecting 2-AG and AEA signaling seperately and reveal an endogenous 2-AG component of the behavioral response to {Delta}9-THC.

neuroscience↗

bioRxiv2026

A lateral linker histone binding mode scaffolds dinucleosome stacking in chromatin fibers

Linker histones are essential for chromatin compaction, yet how they contribute to higher-order fiber assembly remains poorly understood. Here, we determined cryo-electron microscopy structures of Arabidopsis dodeca-nucleosome fibers containing distinct H2A/H3 variants and linker histone H1.3, revealing a noncanonical binding mode that a laterally positioned H1.3 connects the acidic patch of one nucleosome and the DNA of the neighboring nucleosome, thereby scaffolding dinucleosomes into two-start chromatin fibers. This noncanonical binding mode is structurally conserved when H1.3 is replaced by Gallus gallus H5. Furthermore, incorporation of H2A.W and H3.3 further induces back-to-back fiber dimerization. Cryo-electron tomography and in vivo cross-linking mass spectrometry analyses support the physiological relevance of H1 lateral engagement. Our findings establish that linker histones act as active architectural scaffolds in higher-order chromatin organization.

molecular biology↗

bioRxiv2026

Transformation and recombination of neural information in a brain network

Mammalian brain function relies on integrated interactions among interconnected neural structures. The principles by which regional activity is transformed into projection-specific signals and then recombined at targets elsewhere in the brain are fundamental to brain processing, but remain poorly understood. Here we study these phenomena using a genetically encoded probe that provides neurophysiological readouts from virally labeled projections on a brain-wide scale via functional magnetic resonance imaging (fMRI). By analyzing outputs from thalamic and cortical somatosensory processing regions in rats, we find that projection-specific neural population activity undergoes shifts in tuning and temporal characteristics as it emanates from source regions. Patterns of neural information flow to targeted brain structures reconfigure under different conditions of stimulation and rest, contrasting with intrinsic fMRI functional connectivity profiles, which remain constant. Excitatory and inhibitory projections are coactivated during stimulation, but their relative response amplitudes change dynamically between stimulus conditions and across repeated stimuli, suggesting mechanistic roles for network-wide shifts in excitation/inhibition balance. Our results thus reveal how information flow throughout a neural system reshapes to promote stimulus selectivity and provide underpinnings of large-scale brain phenomena.

neuroscience↗

bioRxiv2025

Multi-modal choroid plexus pathology in aging and Alzheimer's disease

Brain barriers, cerebrospinal fluid (CSF) dynamics, and peripheral factors are implicated as significant contributors to Alzheimers disease (AD). The choroid plexus (ChP) is a blood-brain interface that produces CSF and forms the blood-CSF barrier. However, how ChP pathology develops across the lifespan and contributes to AD has not been systematically characterized. Here, we report a multi-modal ChP atlas integrating single-nucleus transcriptomics from 49 individuals, AI-assisted quantitative histopathology across >500 postmortem samples age 16 to 105, spatial transcriptomics, and functional studies in 5xFAD mice. We identify fibrosis, calcification, and macrophage abnormalities as hallmarks of ChP aging, with AD pathology conferring additional effects, including expansion of a pro-inflammatory fibroblast-macrophage signaling niche. In 5xFAD mice, macrophage dysfunction is associated with impaired epithelial barrier maintenance and repair. Together, these data provide a foundational resource for understanding ChP dysfunction in aging and AD and propose the macrophage-fibroblast-epithelial barrier axis as a driver of ChP pathology.

neuroscience↗

bioRxiv2025

Unraveling Candidatus Dermatophostum as a Novel Genus of Polyphosphate-Accumulating Organisms for High-Strength Wastewater Treatment

Dermatophilaceae polyphosphate-accumulating organisms (PAOs), formerly classified as Tetrasphaera PAOs, play pivotal roles in enhanced biological phosphorus removal (EBPR). However, their phylogenetic diversity, ecological preferences, and metabolic traits remain poorly characterized, and a robust marker gene for their classification is lacking. Here, we performed an extensive phylogenomic and metabolic analysis of Dermatophilaceae PAOs utilizing 46 newly recovered metagenome-assembled genomes (MAGs) from a laboratory-scale EBPR reactor treating high-strength wastewater and full-scale wastewater treatment plants. These analyses revealed a previously uncharacterized PAO genus, named Candidatus Dermatophostum, which is adapted to high-phosphorus environments. Its representative species, Ca. D. ammonifactor, was enriched in the EBPR reactor and its PAO phenotype was confirmed by polyphosphate staining and fluorescence in situ hybridization. Genomic, transcriptomic, and protein structure analyses revealed its specialized metabolic capabilities for phosphate metabolism, glycogen synthesis and dissimilatory nitrate reduction to ammonium. Moreover, Ca. Dermatophostum was found to be widely distributed across WWPTs worldwide, underscoring both its ecological importance and its potential role in mitigating nitrous oxide (N2O) emissions. Finally, we propose a ppk1-based classification framework that resolves Dermatophilaceae PAOs into six distinct clades, consistent with whole-genome phylogeny, and demonstrates that ppk1 can serve as a reliable marker gene for tracking these populations. Together, these findings expand the ecological and functional understanding of Dermatophilaceae PAOs and highlight their promise for advancing sustainable wastewater treatment and resource recovery.

microbiology↗

bioRxiv2025

Substrates Coupling and Inhibition of the human Na+- dependent Cl-/HCO3-exchanger

Maintaining pH homeostasis is essential for neuronal excitability and for regulating cerebrospinal fluid (CSF). The Na+-dependent Cl-/HCO3- exchanger, NCBE (SLC4A10), abundant in the choroid plexus, contributes to CSF pH control by mediating bicarbonate flux, yet its molecular mechanism has remained unclear. Here we report cryo-EM structures of human NCBE in multiple functional states, revealing conserved binding sites for Na+, Cl-, and HCO3-, as well as an unexpected K+ site indicating relaxed cation selectivity. The inhibitor DIDS binds above the substrate cavity, locking NCBE in an outward-facing conformation and defining a subfamily-selective inhibitory mechanism. Functional assays and molecular dynamics simulations validate ion coordination and inhibitor effects. Comparison of cryo-EM structures with an AlphaFold3 inward-facing model supports an elevator-like mechanism and completes the conformational cycle of Na+-coupled HCO3- transporters. Together, these findings define the structural basis of NCBE and provide a framework for understanding ion coupling and pharmacological modulation within the SLC4 family.

biophysics↗

bioRxiv2025

Expanding the RNA Virus Universe by Scalable Structure-Guided Discovery

The discovery of RNA viruses from metatranscriptomic data remains challenging due to their extreme sequence divergence and frequent lack of conserved motifs. We present Rider, a lightweight two-stage framework that couples fast, structure-informed sequence screening with targeted structural validation. Stage 1 uses a compact 35M-parameter protein language model to prioritize RdRp-like fragments at whole-sample scale, achieving over 44x higher end-to-end screening throughput on commodity hardware. Stage 2 applies structure prediction and Foldseek-based alignment against a dedicated RdRp structure resource ([~]200k ESMFold-predicted structures), providing orthogonal evidence for remote homologs. Applied to >10,000 metatranscriptomes spanning marine, freshwater, soil and host-associated microbiomes, Rider matches or outperforms leading tools (e.g., LucaProt, PalmScan) and additionally recovers divergent and truncated sequences. Multiple orthogonal indicators, including structure consistency and low DNA read mapping to corresponding contigs, support genuine RNA origin. In a human IBD cohort, Rider agrees with state-of-the-art calls for clinically relevant RNA viruses while extending discovery to divergent lineages. Rider turns structure-guided homology search into a practical, scalable pipeline for RNA virome discovery. HighlightO_LIA two-stage framework enables structure-guided RNA virus discovery at sample scale, achieving up to 44-fold higher throughput on standard computing hardware. C_LIO_LIThe method matches or surpasses LucaProt and PalmScan across >10,000 metatranscriptomes from diverse environments, while recovering RdRp fragments missed by existing tools. C_LIO_LIStructural validation using [~]200,000 ESMFold-predicted RdRp models and Foldseek alignment supports the detection of remote homologs with high confidence. C_LIO_LIOrthogonal evidence, including low DNA read mapping, strand-specific expression, and ORF metrics, confirms RNA origin and reduces false positives.. C_LIO_LIOpen-source code and an openly released RdRp structure database enable scalable, reproducible RNA virome discovery in environmental and clinical settings. C_LI

bioinformatics↗

bioRxiv2025

A Machine Learning Approach to Predicting Dyspnea with Noninvasive Biomarkers

RationaleDyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in patients with chronic and critical illness, and its presence is associated with poor clinical outcomes and long-term psychological trauma. The multidimensional nature of the neurophysiological mechanisms underlying dyspnea, paired with individual variation in its presentation, makes identifying and monitoring this symptom difficult, particularly in non-communicative patients. ObjectiveUndetected and untreated dyspnea in critically ill patients is a significant problem contributing to patient suffering. Therefore, the objective of this study was to investigate the feasibility of machine learning methods for assessing and continuously monitoring dyspnea using easily obtained noninvasive biomarkers. MethodsWe recruited healthy participants (N = 60, 35 women) and stimulated dyspnea using a forced end-tidal semi-rebreathing circuit to modulate arterial oxygen and carbon dioxide levels while collecting non-invasive biomarker data and continuous self-reported dyspnea severity scores. This data was used to train machine-learning models to predict the presence or absence of significant dyspnea (Numeric Rating Scale [≥] 3). We then compared the performance of our final model to observational estimates by trained healthcare providers. Measurements and Main ResultsThe final model (Random Forest) performed well (PR-AUC=0.832) and exceeded the accuracy of observation estimates made on the same participants using the Respiratory Distress Observational Scale (RDOS) (accuracy=54%). ConclusionsThese results indicate that machine learning models can utilize non-invasive biomarker inputs to accurately predict carbon dioxide- and hypoxia-induced dyspnea in a healthy population during spontaneous breathing.

physiology↗

bioRxiv2025

H3K4me1 directs H3K36me2 and H3K36me3 deposition in land plants

Monomethylation of histone H3 lysine 4 (H3K4me1) marks enhancers in mammals. However, the function of H3K4me1 in plants remains largely unclear. Here, we analyzed the genome-wide distribution of H3K4me1 in diverse species across evolution, revealing a distinctive H3K4me1 distribution pattern in land plants. To explore the function of H3K4me1 in plants, we identified an H3K4me1-specific reader protein, Early heading date 3 (Ehd3), and solved the structure of Ehd3 in complex with the H3K4me1 peptide, revealing a unique binding module differing from the previously reported PHD finger proteins. We further identified an Ehd3-binding protein, SET domain group 724 (SDG724), and the deletion of either Ehd3 or SDG724 caused similar defects in plant phenotype and changes in transcriptome and epigenome profiles. Both Ehd3 and SDG724 are enriched at chromatin regions marked by H3K4me1 but not H3K4me2 or H3K4me3. Ehd3 activates the H3K36 methyltransferase SDG724, and H3K36me2/me3 are colocalized with H3K4me1 in the genomes of land plants. Collectively, our results reveal that H3K4me1 directs the establishment of H3K36me2 and H3K36me3 in land plants.

molecular biology↗

bioRxiv2025

High-throughput protein target mapping enables accelerated bioactivity discovery for ToxCast and PFAS compounds

Chemical pollution is a global threat to human health, yet the toxicity mechanism of most contaminants remains unknown. Here, we applied an ultrahigh-throughput affinity-selection mass spectrometry (AS-MS) platform to systematically identify protein targets of prioritized chemical contaminants. After benchmarking the platform, we screened 50 human proteins against 481 prioritized chemicals, including 446 ToxCast chemicals and 35 per-and polyfluoroalkyl substances (PFAS). Among 24,050 interactions assessed, we discovered 35 novel interactions involving 14 proteins, with fatty acid-binding proteins (FABPs) emerging as the most ligandable protein family. Given this, we selected FABPs for further validation, which revealed a distinct PFAS binding pattern: legacy PFAS selectively bound to FABP1, whereas replacement compounds, PFECAs, unexpectedly interacted with all FABPs. X-ray crystallography further revealed that the ether group enhances molecular flexibility of alternative PFAS, to accommodate the binding pockets of FABPs. Our findings demonstrate that AS-MS is a robust platform for the discovery of novel protein targets beyond the scope of the ToxCast program and highlight the broader protein-binding spectrum of alternative PFAS as potential regrettable substitutes.

pharmacology and toxicology↗

bioRxiv2025

Enantioselective Protein Affinity Selection Mass Spectrometry (EAS-MS)

We report an enantioselective protein affinity selection mass spectrometry screening approach (E-ASMS) that enables the detection of weak binders, informs on selectivity, and generates orthogonal confirmation of binding. After method development with control proteins, we screened 31 human proteins against a designed library of 8,210 chiral compounds. 16 binders to 12 targets, including many proteins predicted to be "challenging to ligand", were discovered and confirmed in orthogonal biophysical assays. 7 binders to 6 targets bound in an enantioselective manner, with KD values ranging from 3 to 20 {micro}M. Binders for four targets (DDB1, WDR91, WDR55, and HAT1) were selected for in-depth characterization using X-ray crystallography. In all four cases, the mechanism for enantioselectivity was readily explained. We conclude E-ASMS can be used to identify and characterize selective and weakly-binding ligands for novel protein targets with unprecedented throughput and sensitivity.

pharmacology and toxicology↗

bioRxiv2025

Developmentally cascading structures do not lose evolutionary potential, but compound developmental instability in rat molars

Increasing variability down serially segmented structures, such as mammalian molar teeth and vertebrate limb segments, is a much-replicated pattern. The same phenotypic pattern has conflicting interpretations at different evolutionary scales. Macroevolutionary patterns are thought to reflect greater evolutionary potential in later-forming segments, but microevolutionary patterns are thought to reflect less evolutionary potential and greater phenotypic plasticity. We address this conflict by recalculating evolutionary potential (evolvability) from a systematic review of published mammalian molar sizes, then directly measure phenotypic plasticity from a controlled feeding experiment. Effects on lengths and widths are discordant in a way that suggests general growth pathways have a role in phenotypically plastic dental responses to nutrition. Effects on successive trait means do not necessarily increase downstream, contrary to long-standing hypotheses. We confirm prior findings of increasing non-inherited variance downstream, showing decoupling between effects on trait mean and variance. These patterns can be explained by a cascading model of tooth development compounding the effect of developmental instability as an influence separate from general environmental effects on the developing embryo. When evaluated in terms of evolvability, later-developing molars are equally or more evolvable than earlier-developing molars, aligning their microevolutionary potential with macroevolutionary patterns in other serially segmented structures.

evolutionary biology↗

bioRxiv2024

Structural and functional interrelationship of histone H2A and its variants H2A.Z and H2A.W in Arabidopsis

Multiple histone H2A variants are known in eukaryotes. However, the functional relationship between H2A and its variants in plants remains largely obscure. Using CRISPR/Cas9 editing, we generated a mutant lacking four H2A isoforms in Arabidopsis and analyzed the functional and structural relationship between H2A and its variants H2A.Z and H2A.W. RNA-sequencing and phenotype analyses revealed mild changes in gene transcription and plant development in the mutants lacking H2A, H2A.Z, or H2A.W compared with the wild-type plants. Chromatin immunoprecipitation sequencing analysis showed that H2A is able to substitute for both H2A.Z and H2A.W across the genome, including in euchromatin and heterochromatin regions. However, H2A.Z replaced both H2A and H2A.W primarily within the euchromatin regions. By using DNA and histones derived from Arabidopsis, we constructed nucleosomes containing H2A, H2A.Z, or H2A.W and resolved their cryogenic electron microscopy structures at near-atomic resolution. Collectively, the results reveal the structural similarity and functional redundancy of H2A and H2A variants in Arabidopsis.

plant biology↗

bioRxiv2024

Fentanyl reinforcement history has sex-specific effects on multi-step decision-making

It is commonly thought that drug addiction involves a transition to habitual control of action, where the choice to consume drugs becomes automatized and reflects a failure to deliberate over possible negative outcomes. Determining whether the pursuit of addictive drugs is habitual is hampered by a lack of behavior assessments suitable for use during a bout of actual drug seeking. Therefore, to understand how variable histories of drug reinforcement might affect goal-directed and habitual pursuit of drug, we trained rats to perform a multi-step decision-making task to earn oral fentanyl and sucrose rewards following extensive pretraining with either fentanyl or sucrose. Importantly, this task allowed for independent measurements of goal-directed and habitual choice characteristics during online pursuit of rewards, and habitual choice could be further categorized into perseverative and reward-guided components. Chronic fentanyl led to a bias for reward-guided habitual choice specifically in females, and a high degree of perseveration in both sexes. These behavioral changes after chronic fentanyl pretraining generalized across fentanyl and sucrose seeking. In contrast, acute fentanyl selectively increased perseveration in females, and blunted the gradual within-session improvement in goal-directed choice in both sexes. These results show that chronic fentanyl reinforcement promotes habits that generalize across drug and non-drug reward seeking, and that female rats are especially susceptible to habitual control induced by both chronic and acute fentanyl reinforcement.

animal behavior and cognition↗

bioRxiv2024

Structural basis of TMPRSS11D specificity and autocleavage activation

Transmembrane Protease, Serine-2 (TMPRSS2) and TMPRSS11D are human proteases that enable SARS-CoV-2 and Influenza A/B virus infections, but their biochemical mechanisms for facilitating viral cell entry remain unclear. We demonstrate these proteases can spontaneously and efficiently cleave their own zymogen activation motifs, thereby activating their wider protease activity on other cellular substrates. We determined TMPRSS11D co-crystal structures in complexes with a native TMPRSS11D zymogen activation motif and with an engineered activation motif, providing insights into TMPRSS11D autocleavage activation and revealing unique regions of its substrate binding cleft. We further show that a protease inhibitor that underwent clinical trials for TMPRSS2-targeted COVID-19 therapy, nafamostat mesylate, was rapidly cleaved by TMPRSS11D and converted to low activity derivatives. These insights into human protease viral tropism and into liabilities with existing human serine protease inhibition strategies will guide future drug discovery campaigns for these targets.

biochemistry↗

bioRxiv2024

Pan-Cancer Genetic Analysis of Mitochondrial DNA Repair Gene Set

BackgroundThe mitochondrial DNA repair has gained attention for its potential impact on pan-cancer genetic analysis. This study investigates the clinical relevance of mitochondrial DNA repair genes: PARP1, DNA 2, PRIMPOL, TP53, MGME1. MethodsUsing multi-omics profiling data and Gene Set Cancer Analysis (GSCA) with normalized SEM mRNA expression, this research analyzes differential expression, gene mutation, and drug correlation. ResultsTP53 was the most commonly mutated mitochondrial-related gene in cancer, with UCS and OV having the highest mutation rates. CPG mutations linked to lowest survival rates. Breast cancer, with various subtypes, was potentially influenced by mitochondrial DNA repair genes. ACC was shown to be high in gene survival analysis. BRCA, USC, LUCS, COAD, and OV showed CNV levels impacting survival. A negative gene expression-methylation correlation was observed and was weakest in KIRC. Mitochondrial DNA repair genes were linked to Cell cycle_A activation. A weak correlation was found between immune infiltration and mitochondrial genes. Few drug compounds were shown to be affected by mitochondrial-related genes. ConclusionUnderstanding mitochondrial-related genes could redefine cancer diagnosis, and prognosis, and serve as therapeutic biomarkers, potentially altering cancer cell behavior and treatment outcomes.

bioinformatics↗

bioRxiv2024

CACHE Challenge #1: targeting the WDR domain of LRRK2, a Parkinson's Disease associated protein.

The CACHE challenges are a series of prospective benchmarking exercises meant to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE #1 challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinsons disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods. Seventy-three of the 1955 procured molecules bound LRRK2 in an SPR assay with KD lower than 150 M and were advanced to a hit expansion phase where computational teams each selected up to 50 analogs each. Binding was observed in two orthogonal assays with affinities ranging from 18 to 140 M for seven chemically diverse series. The seven successful computational workflows varied in their screening strategies and techniques. Three used molecular dynamics to produce a conformational ensemble of the targeted site, three included a fragment docking step, three implemented a generative design strategy and five used one or more deep learning steps. CACHE #1 reflects a highly exploratory phase in computational drug design where participants sometimes adopted strikingly diverging screening strategies. Machine-learning accelerated methods achieved similar results to brute force (e.g. exhaustive) docking. First-in-class, experimentally confirmed compounds were rare and weakly potent, indicating that recent advances are not sufficient to effectively address challenging targets.

biochemistry↗

bioRxiv2024

A resource to enable chemical biology and drug discovery of WDR Proteins

Protein class-focused drug discovery has a long and successful history in pharmaceutical research, yet most members of druggable protein families remain unliganded, often for practical reasons. Here we combined experiment and computation to enable discovery of ligands for WD40 repeat (WDR) proteins, one of the largest human protein families. This resource includes expression clones, purification protocols, and a comprehensive assessment of the druggability for hundreds of WDR proteins. We solved 21 high resolution crystal structures, and have made available a suite of biophysical, biochemical, and cellular assays to facilitate the discovery and characterization of small molecule ligands. To this end, we use the resource in a hit-finding pilot involving DNA-encoded library (DEL) selection followed by machine learning (ML). This led to the discovery of first-in-class, drug-like ligands for 9 of 20 targets. This result demonstrates the broad ligandability of WDRs. This extensive resource of reagents and knowledge will enable further discovery of chemical tools and potential therapeutics for this important class of proteins.

biochemistry↗