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Biology subjects

Yu, B.

Publications and source records attributed to Yu, B..

At least 55 records · Page 3Linked to original sources
bioRxiv2025

Ethylene signal-driven plant-multitrophic synergy boosts crop performance

Efficient nutrient use in agriculture depends on the dynamic interplay between plant roots, soil, and microbial communities. The root-rhizosphere interface is central to nutrient uptake and serves as a key hub for interactions with beneficial microbes. Arbuscular mycorrhizal (AM) fungi, positioned at the nexus between plant roots and soil microbiota, play a critical role in enhancing crop performance under nutrient-limited conditions. In this study, we dissected the genetic and molecular basis of AM fungi-induced lateral root development in maize (Zea mays), focusing on the role of ethylene-responsive transcription factors (ERFs). We identified ERF genes as essential regulators of pericycle cell division, acting downstream of ethylene biosynthesis genes (ACS6 and ACS7) and AM fungal signaling. Our findings reveal that AM fungi promote lateral root initiation by activating ERF expression and reprogramming flavonoid metabolism, particularly reducing the accumulation of flavonols such as kaempferol and quercetin, which otherwise inhibit root development when over-accumulated. Furthermore, we demonstrated that Massilia, a beneficial rhizobacterium, synergizes with AM fungi to enhance lateral root formation by colonizing fungal hyphae, degrading flavonoids, and contributing to auxin production. Together, our results uncover a tripartite signaling network linking ethylene signaling, flavonoid-mediated microbial recruitment, and AM symbiosis. This study highlights ERFs as central integrators of plant-microbe interactions and provides a molecular framework for engineering root architecture and microbiome assembly to improve nutrient acquisition and support sustainable crop productivity.

plant biology↗
bioRxiv2025

Hepatocyte FGFR2 Mediates the Antifibrotic Effects of FGF10 in Advanced Liver Fibrosis.

Fibroblast growth factor 10 (FGF10) supports epithelial repair, but its role in liver fibrogenesis remains uncertain. Here we found that hepatic FGF10 and its receptor FGFR2 decline with progression to advanced fibrosis in patient biopsies and in carbon tetrachloride (CCl4)- and diet-induced mouse models. Restoring hepatic FGF10 with recombinant human FGF10 or adeno-associated virus mediated liver-targeted expression attenuated and partially reversed established advanced bridging fibrosis, reduced inflammation, and decreased hepatocyte apoptosis, and these benefits required hepatocyte FGFR2 because hepatocyte-specific Fgfr2 deletion abolished protection. In primary hepatocytes, FGF10 activated FGFR2-FRS2, increased inhibitory GSK3{beta}(Ser9) phosphorylation, and suppressed NF-{kappa}B activation, reducing TGF-{beta}1 and other cytokines and thereby limiting paracrine hepatic stellate cells activation. The molecular and histologic benefits extended to metabolically primed steatohepatitis, supporting translatability beyond toxicant injury. Mechanistic signaling readouts confirm FGFR2 engagement, while the main text centers on the hepatocyte FGF10-FGFR2 axis as an intrinsic brake on fibrogenesis. Together, these data identify a hepatocyte-centric FGF10-FGFR2 axis as a negative regulator and potential regressor of fibrogenesis, highlighting it as a tractable therapeutic target in advanced liver fibrosis.

pharmacology and toxicology↗
bioRxiv2025

Characterization of Cancer-Reactive T Cells and Neoantigen-specific T Cell Receptors

Not all tumor-infiltrating T cells are cancer-reactive (CR). Several studies have reported gene expression signatures associated with CR-T cells. To integrate these findings, we developed a computational workflow, CAT (Cancer-Associated T cells), which harmonizes existing CR-T cell signatures and applies them to identify CR-T cells across an atlas of one million T cells. Our findings reveal that the abundance of CR-T cells varies across cancer types and that baseline levels of CR-T cells predict patients responses to immunotherapy. In parallel, we established a high-throughput computational platform, Neo-TCR, for systematic screening of neoantigen-specific TCRs and their cognate neoantigens. The efficacy of Neo-TCR is validated by cross-validation studies and replications in two independent datasets. Together, our findings suggest a new direction for developing biomarkers for cancer detection and monitoring: integrating CR gene expression signatures with neoantigen-specific TCRs.

cancer biology↗
bioRxiv2025

A stress-dependent postembryonic role for the core CPA factor CFIM-1 in germline integrity

Post-transcriptional processing of pre-mRNAs generates a diversity of 3 UTR transcript isoforms that can vary in their function and stability. The differential enrichment of transcript isoforms has been implicated in diseases ranging from cancer to neurodevelopmental disorders. However, the post-embryonic developmental roles of the core ensemble of cleavage and polyadenylation (CPA) factors that mediate these post-transcriptional changes remain poorly characterized. Here, we report a stress- dependent role for the core CPA factor CFIM-1 in germline integrity in Caenorhabditis elegans. Total loss-of-function of cfim-1 elicits a temperature-sensitive sterile phenotype in hermaphrodites. These changes in brood size are accompanied by broad sperm, oocyte and germline morphology defects. Surveying the transcriptome of cfim-1(lf) worms, we uncover changes in transcript isoform abundance for dozens of genes with known functions related to the development and maintenance of these structures, consistent with a model in which post-transcriptional regulation of target genes via cfim- 1 is crucial to the development and maintenance of germline integrity. Our findings collectively define a novel post-embryonic role for a core CPA factor in tissue-specific development.

developmental biology↗
bioRxiv2025

Uncovering smooth structures in single-cell data with PCS-guided neighbor embeddings

Single-cell sequencing is revolutionizing biology by enabling detailed investigations of cell-state transitions. Many biological processes unfold along continuous trajectories, yet it remains challenging to extract smooth, low-dimensional representations from inherently noisy, highdimensional single-cell data. Neighbor embedding (NE) algorithms, such as t-SNE and UMAP, are widely used to embed high-dimensional single-cell data into low dimensions. But they often introduce undesirable distortions, resulting in misleading interpretations. Existing evaluation methods for NE algorithms primarily focus on separating discrete cell types rather than capturing continuous cell-state transitions, while dynamic modeling approaches rely on strong assumptions about cellular processes and specialized data. To address these challenges, we build on the Predictability-Computability-Stability (PCS) framework for reliable and reproducible data-driven discoveries. First, we systematically evaluate popular NE algorithms through empirical analysis, simulation, and theory, and reveal their key shortcomings such as artifacts and instability. We then introduce NESS, a principled and interpretable machine learning approach to improve NE representations by leveraging algorithmic stability and to enable robust inference of smooth biological structures. NESS offers useful concepts, quantitative stability metrics, and efficient computational workflows to uncover developmental trajectories and cell-state transitions in single-cell data. Finally, we apply NESS to six single-cell datasets, including those about pluripotent stem cell differentiation, organoid development, and multiple tissue-specific lineage trajectories. Across these diverse contexts, NESS consistently yields useful and verifiable biological insights, such as identification of transitional and stable cell states and quantification of transcriptional dynamics during development. Notably, NESS resolves distinct neuronal subpopulations during embryoid formation and provides a deeper understanding of their cell-state dynamics.

bioinformatics↗
bioRxiv2025

TIR immune signaling is blocked by phosphorylation to maintain plant growth

Toll/interleukin-1 receptor (TIR) domain proteins are immune signaling components and function as NAD+-cleaving enzymes to activate defense responses. Activation of TIRs represses growth and drives cell death in plants and promotes axon degeneration in animals, but how plant TIRs are repressed remains unclear. Here, we show that TIR NADase activity requires a conserved serine residue spatially close to the catalytic glutamate. The plant Ca2+-dependent protein kinases (CPKs), the mammalian Ca2+/calmodulin-dependent protein kinase II delta (CAMK2D) and TANK binding kinase 1 (TBK1) phosphorylate TIR domains at this conserved serine, which blocks TIR NADase activities and functions and thus maintains growth in plants and suppresses SARM1 TIR signaling in animals, respectively. Our findings define a fundamental molecular mechanism by which phosphorylation at a conserved serine residue blocks TIR signaling to balance growth and defense trade-offs.

plant biology↗
bioRxiv2025

An exonuclease safeguards cGAS immune signaling by degrading its 2'-5' phosphodiester intermediate

Excessive activation of cyclic GMP-AMP synthase (cGAS) drives inflammatory and autoimmune diseases, but complete inhibition of cGAS signaling can compromise host defence. Here we show that cGAS signaling can be tuned through a previously unrecognized regulatory checkpoint. Bacterial cGAS generates cGAMP through a two-step mechanism involving release and rebinding of a 2'-5'-linked linear dinucleotide intermediate. We identify a CBASS-associated exonuclease (Exo) that selectively degrades this catalytic intermediate, establishing a threshold for cGAS activation while preserving immune function. This thresholding mechanism is conserved across domains of life: Exo suppresses human cGAS activity in vitro and in mammalian cells and attenuates cGAS-driven pathology in vivo. Our findings identify the catalytic intermediate surveillance as a conserved strategy for safeguarding cGAS signaling.

biochemistry↗
bioRxiv2025

Old vs. New Local Ancestry Inference in HCHS/SOL: A Comparative Study

Hispanic/Latino populations are admixed, with genetic contributions from multiple ancestral populations. Studies of genetic association in these admixed populations often use methods such as admixture mapping, which relies on inferred counts of "local" ancestry, i.e., of the source ancestral population at a locus. Local ancestries are inferred using external reference panels that represent ancestral populations, making the choice of inference method and reference panel critical. This study used a dataset of Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) to evaluate the "old" local ancestry inference performed using the state-of-the-art inference method, RFMix, alongside "new" inferences performed using Fast Local Ancestry Estimation (FLARE), which also used an updated reference panel. We compared their performance in terms of global and local ancestry correlations, as well as admixture mapping-based associations. Overall, the old RFMix and new FLARE inferences were highly similar for both global and local ancestries, with FLARE-inferred datasets yielding admixture mapping results consistent with those computed from RFMix. However, in some genomic regions the old and new local ancestries have relatively lower correlations (Pearson R < 0.9). Most of these genomic regions (86.42%) were mapped to either ENCODE blacklist regions, or to gene clusters, compared to 7.67% of randomly-matched regions with high correlations (Pearson R > 0.97) between old and new local ancestries.

genetics↗
bioRxiv2025

5' UTR-mediated retention of eIF3 on 80S ribosomes promotes co-translational folding of ER membrane proteins

Co-translational folding of nascent polypeptides is essential for protein function and cellular homeostasis. Ribosome-associated chaperones assist in this process, but coordination between their recruitment and translation initiation remains poorly understood. We report here that specific binding sites for eukaryotic translation initiation factor eIF3 within the 5 untranslated regions (5UTRs) of mRNAs promote its retention on 80S ribosomes during the synthesis of select endoplasmic reticulum (ER) membrane proteins. Disruption of these eIF3 binding sites leads to misfolding and sequestration of newly synthesized membrane proteins into ER whorls. Sequestration into ER whorls is exacerbated by HSP70 inhibition but can be rescued by overexpressing HSPA8 and HSPA1. Cross-linking assays reveal that 5UTR binding sites stabilize eIF3-80S interactions during early elongation, facilitating recruitment of HSPA8 to ribosomes. These findings indicate that genetic instructions within 5UTRs direct eIF3-mediated chaperone recruitment, ensuring proper co-translational folding of ER membrane proteins.

cell biology↗
bioRxiv2025

Targeted stimulation of motor cortex neural ensembles drives learned movements

During the execution of learned motor skills, the neural population in the layer 2/3 (L2/3) of the primary motor cortex (M1) expresses a reproducible spatiotemporal activity pattern. It is debated whether M1 actively participates in generating this activity pattern and whether this learned pattern causally drives the learned movement. To address these questions, we utilized in vivo two-photon calcium imaging combined with holographic optogenetic stimulation of functionally defined M1 L2/3 neuronal ensembles in mice performing a skilled lever-pressing task. A brief and synchronous stimulation of [~]20 neurons whose activity onset in voluntary trials precedes movement onsets induced movements that resembled the learned movement, while producing spatiotemporal activity patterns in other M1 neurons that resembled those during the voluntary learned movement. Moreover, trial-by-trial variability of optogenetically triggered population activity correlated with the variability in the induced movements. These trial-by-trial variabilities were predicted by the initial state of M1 population activity immediately preceding the stimulation. In some trials, the stimulation induced the learned activity without inducing overt movements, indicating that the learned activity is not simply a reflection of movements and instead can be induced internally. The stimulation failed to generate movements or learned activity when mice were disengaged from the task. Stimulation of the neurons whose activity followed voluntary movement onsets failed to induce the learned movement in task-engaged mice. Taken together, the learned activity pattern in M1 L2/3 can be generated when the M1 network is prepared at the optimal initial state and receives precise triggering inputs, supporting the active role of M1 in the generation of learned activity and learned movements.

neuroscience↗
bioRxiv2024

Identification of Covalent Cyclic Peptide Inhibitors Targeting Protein-Protein Interactions Using Phage Display

Peptide macrocycles are promising therapeutics for a variety of disease indications due to their overall metabolic stability and potential to make highly selective binding interactions with targets. Recent advances in covalent macrocycle peptide discovery, driven by phage and mRNA display methods, have enabled the rapid identification of highly potent and selective molecules from large libraires of diverse macrocycles. However, there are currently limited examples of macrocycles that can be used to disrupt protein-protein interactions and even fewer examples that function by formation of a covalent bond to a target protein. In this work, we describe a directed counter-selection method that enables identification of covalent macrocyclic ligands targeting a protein-protein interaction using a phage display screening platform. This method utilizes binary and ternary screenings of a chemically modified phage display library, employing the stable and weakly reactive aryl fluorosulfate electrophile. We demonstrate the utility of this approach using the SARS-CoV-2 Spike-ACE2 protein-protein interaction and identify multiple covalent macrocyclic inhibitors that disrupt this interaction. The resulting compounds displayed antiviral activity against live virus that was irreversible after washout due to the covalent binding mechanism. These results highlight the potential of this screening platform for developing covalent macrocyclic drugs that disrupt protein-protein interactions with long lasting effects.

microbiology↗
bioRxiv2024

Mapping AAV capsid sequences to functions through function-guided in silico evolution

Artificial intelligence (AI) offers significant potential to accelerate the functional engineering of adeno-associated virus (AAV) capsids in a time- and cost-efficient manner. However, existing approaches lack the ability to systematically map capsid sequences to multifunctional properties. To address this challenge, we developed ALICE, a knowledge-driven platform for in silico AAV capsid engineering that directly maps sequence to multiple functions. Our method incorporating a heuristic algorithm with contrastive learning principles, termed function-guided evolution (FE), to iteratively optimize high-performing capsid sequences generated by a naive language model toward desired functions. We elucidate FEs evolutionary mechanism, demonstrating its ability to navigate a function-guided landscape and generate capsids with tailored properties. After validating ALICEs ability to design murine-specific AAV capsids targeting Ly6a/Ly6c1 with limited training data, we developed ALICE-X by integrating a curriculum learning strategy. This upgrade facilitated exploration of sequence space beyond existing wet-lab datasets, enabling successful targeting of the human transferrin receptor 1 (hTfR1). The resulting engineered AAV variant, AAV.ALICE-H3, demonstrated improved viability, specific receptor targeting, and [~] 251-fold enhanced CNS tropism in human TFRC knock-in (hTFRC KI) mice compared to wildtype controls. This interpretable, knowledge-driven framework advances in silico AAV capsid design, offering broad applicability for translational gene therapy.

bioengineering↗
bioRxiv2024

Novel and optimized mouse behavior enabled by fully autonomous HABITS: Home-cage Assisted Behavioral Innovation and Testing System

Mice are among the most prevalent animal models used in neuroscience, benefiting from the extensive physiological, imaging and genetic tools available to study their brain. However, the development of novel and optimized behavioral paradigms for mice has been laborious and inconsistent, impeding the investigation of complex cognitions. Here, we present a home-cage assisted mouse behavioral innovation and testing system (HABITS), enabling free-moving mice to learn challenging cognitive behaviors in their home-cage without any human involvement. Supported by the general programming framework, we have not only replicated established paradigms in current neuroscience research but also developed novel paradigms previously unexplored in mice, resulting in more than 300 mice demonstrated in various cognition functions. Most significantly, HABITS incorporates a machine-teaching algorithm, which comprehensively optimized the presentation of stimuli and modalities for trials, leading to more efficient training and higher-quality behavioral outcomes. To our knowledge, this is the first instance where mouse behavior has been systematically optimized by an algorithmic approach. Altogether, our results open a new avenue for mouse behavioral innovation and optimization, which directly facilitates investigation of neural circuits for novel cognitions with mice.

animal behavior and cognition↗
bioRxiv2024

Cholinergic feedback for context-specific modulation of sensory representations

The brains ability to prioritize behaviorally relevant sensory information is crucial for adaptive behavior, yet the underlying mechanisms remain unclear. Here, we investigated the role of basal forebrain cholinergic neurons in modulating olfactory bulb (OB) circuits in mice. Calcium imaging of cholinergic feedback axons in OB revealed that their activity is strongly correlated with orofacial movements, with little responses to passively experienced odor stimuli. However, when mice engaged in an odor discrimination task, OB cholinergic axons rapidly shifted their response patterns from movement-correlated activity to odor-aligned responses. Notably, these odor responses during olfactory task engagement were absent in cholinergic axons projecting to the dorsal cortex. The level of odor responses correlated with task performance. Inactivation of OB-projecting cholinergic neurons during task engagement impaired performance and reduced odor responses in OB granule cells. Thus, the cholinergic system dynamically modulates sensory processing in a modality-specific and context-dependent manner, providing a mechanism for a flexible and adaptive sensory prioritization.

neuroscience↗
bioRxiv2024

Reciprocal regulation of m6A modification and miRNA production machineries via phase separation-dependent and -independent mechanisms

Methyltransferase complex (MTC) deposits N6-adenosine (m6A) onto RNA, whereas microprocessor produces miRNA. Whether and how these two distinct complexes cross-regulate each other has been poorly studied. Here we report that the MTC subunit B (MTB) tends to form insoluble condensates with poor activity, with its level monitored by 20S proteasome. Conversely, the microprocessor component SERRATE (SE) forms liquid-like condensates, which in turn promotes solubility and stability of MTB, leading to increased MTC activity. Consistently, the hypomorphic lines expressing SE variants, defective in MTC interaction or liquid-like phase behavior, exhibit reduced m6A level. Reciprocally, MTC can recruit microprocessor to MIRNA loci, prompting co-transcriptional cleavage of primary miRNA (pri-miRNAs) substrates. Additionally, pri-miRNAs carrying m6A modifications at their single-stranded basal regions are enriched by m6A readers, which retain microprocessor in the nucleoplasm for continuing processing. This reveals an unappreciated mechanism of phase separation in RNA modification and processing through MTC and microprocessor coordination.

plant biology↗
bioRxiv2024

A biodegradable and restorative peripheral neural interface for the interrogation of neuropathic injuries

Monitoring the early-stage healing of severe traumatic nerve injuries is essential to gather physiological and pathological information for timely interventions and optimal clinical outcomes. While implantable peripheral nerve interfaces provide direct access to nerve fibers for precise interrogation and modulation, conventional non-degradable designs pose limited utilization in nerve injury rehabilitation. Here, we introduce a biodegradable and restorative neural interface for wireless real-time tracking and recovery of long-gap nerve injuries. Leveraging machine learning techniques, this electronic platform deciphers nerve recovery status and identifies traumatic neuroma formation at the early phase, enabling timely intervention and significantly improved therapeutic outcomes. The biodegradable nature of the device eliminates the need for retrieval procedures, reducing infection risks and secondary tissue damage. This research sheds light on bioresorbable multifunctional peripheral nerve interfaces for probing neuropathic injuries, offering vital information for early diagnosis and therapeutic intervention.

bioengineering↗
bioRxiv2024

Genetic Architecture and Analysis Practices of Circulating Metabolites in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. We provided a set of reasonable strategies for outlier and imputation handling to process metabolite data. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole genome sequencing data from 16,359 individuals passing the quality control filters, and discovered 1,778 independent loci associated with 667 metabolites. Among 108 novel locus-metabolite pairs, we detected not only novel loci within previously implicated metabolite associated genes but also novel genes (such as GAB3 and VSIG4 located in the X chromosome) that have putative roles in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, including well-known metabolic genes such as FADS2, D2HGDH, SUGP1, UTG2B17, strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

bioinformatics↗