Biology subjects

Dai, Y.

Publications and source records attributed to Dai, Y..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Deep-learning-based interpolation of longitudinal microbiome data powers biologically informative discovery

The human microbiome is a foundational and dynamic foundation for several health-related functions and disease processes. Advances in microbiome sequencing have enabled the characterization of microbial communities in several niches. Longitudinal microbiome studies further strive to discover clinically informative microbial community trajectories. However, these data are fraught with dropout events, high noise, and irregular sampling that limit and prevent the use of many available longitudinal analysis tools. To address these challenges, we introduce Bidirectional GRU-ODE-Bayes (BGOB), a deep learning framework developed for longitudinal microbiome interpolation. BGOB combines bidirectional information flow and ODE-based continuous modeling to jointly interpolate and smoothen trends across individual participants, providing uniform, denoised time intervals across patients. BGOB enables vastly improved performance in differential abundance testing and time-to-event analysis, and makes possible longitudinal analyses requiring uniformity, such as lead-lag detection and temporal clustering. After interpolation, previously low-powered datasets are able to broadly recapitulate known microbiology and elucidate interacting microbial communities. We highlight several associations between microbial taxa and disease, including novel species associated with Early Childhood Caries and disruption of key healthy gut microbiota in Inflammatory Bowel Disease. The BGOB package is publicly available at https://github.com/Rachel-Lyu/BGOB_n_test.

microbiology↗

bioRxiv2025

A genetically-diverse mouse model reveals a complex gene-environment regulation of cognitive resilience and susceptibility to Alzheimer disease

Alzheimers disease (AD) has a complex etiology arising from largely unknown interactions between genetic and environmental (GxE) factors. Even in populations with causal familial Alzheimers disease mutations, there is variation in disease onset and progression, suggesting that clinical symptoms are modified by genetics and environment. Identification of such modifiers is critical, as mechanisms that promote resilience to high-risk AD mutations, unhealthy diet, or aging represent promising therapeutic targets for AD; global resilience factors that protect against multiple "hits" are among the highest priority for discovery. Both genetic and environmental protective factors in AD have been identified; however, GxE factors are incredibly difficult to study in human populations given complex genomes, poor self-reporting, limited data from underrepresented groups, and incompletely documented exposomes. Here, we (1) validate novel GxE tools using population of mouse strains that model the polygenic nature of human AD, (2) characterize individuals with cognitive resilience to high-risk genetic and dietary perturbations, (3) define and quantitate roles for genetics, sex, age, and diet, and (4) present data for the discovery of complex interactions that are nearly impossible to elucidate from humans or inbred mice. We found that a high-fat high-sugar (HFHS) diet is not universally damaging, as some strains showed an improved AD-related cognitive outcome when fed a HFHS diet, suggesting the need for personalized recommendations for dietary interventions in AD. Cognitive resilience to AD is polygenic; however, we found a locus on Chr 10 that was modestly associated with cognitive resilience to AD in females, and this association was strengthened by HFHS diet, pointing to an unexpected interaction between specific genetic loci and unhealthy diet in AD risk and resilience. This study is the first of its kind to explore characteristics of AD resilience and GxE interactions in a genetically diverse mouse model. We present a subset of strains that exemplify global cognitive resilience to be leveraged for deep mechanistic studies aimed toward development of resilience-based, personalized therapeutic interventions. HighlightsO_LIAD-BXD mouse models and data repository provide unprecedented tools for understanding individual differences arising from Gene x Environment factors in aging and AD. C_LIO_LIEvidence of global cognitive resilience to AD-relevant outcomes that is partially mediated by a resilience to aging and dietary risk factors. C_LIO_LICognitive resilience in AD-BXDs its polygenic nature, with a modest locus on Chr 10 whose association with resilience was amplified by a high-fat/high-sugar diet. C_LIO_LIThe genetic factors mediating resilience to AD in humans also predict cognitive resilience in AD-BXDs, suggesting robust, translatable global resilience factors. C_LI

neuroscience↗

bioRxiv2025

mRNA lipid nanoparticle-incorporated nanofiber-hydrogel composite generates a local immunostimulatory niche for cancer immunotherapy

Hydrogel materials have emerged as versatile platforms for various biomedical applications. Notably, the engineered nanofiber-hydrogel composite (NHC) has proven effective in mimicking the soft tissue extracellular matrix, facilitating substantial recruitment of host immune cells and the formation of a local immunostimulatory microenvironment. Leveraging this feature, here we report an mRNA lipid nanoparticle (LNP)-incorporated NHC microgel matrix, termed LiNx, by incorporating LNPs loaded with mRNA encoding tumour antigens. Harnessing the potent transfection efficiency of LNPs in antigen-presenting cells (APCs), LiNx demonstrates remarkable immune cell recruitment, antigen expression and presentation, and cellular interaction. These attributes collectively create an immunostimulating milieu and yield a potent immune response achievable with a single dose, comparable to the conventional three-dose LNP immunization regimen. Further investigations reveal that the LiNx not only generates heightened Th1 and Th2 responses but also elicits a distinctive Type 17 T helper cell-mediated response pivotal for bolstering antitumour efficacy. Our findings elucidate the mechanism underlying LiNxs role in potentiating antigen-specific immune responses, presenting a new strategy for cancer immunotherapy.

bioengineering↗

bioRxiv2025

AAVone: A Cost-Effective, Single-Plasmid Solution for Efficient AAV Production with Reduced DNA Impurities

Currently, the most common approach for manufacturing GMP-grade adeno-associated virus (AAV) vectors involves transiently transfecting mammalian cells with three plasmids that carry the essential components for production. The requirement for all three plasmids to be transfected into a single cell and the necessity for high quantities of input plasmid DNA, limits AAV production efficiency, introduces variability between production batches, and increases time and labor costs. Here, we developed an all-in-one, single-plasmid AAV production system, called AAVone. In this system, the adenovirus helper genes (E2A, E4orf6, and VA RNA), packaging genes (rep and cap), and the vector transgene cassette are consolidated into a single compact plasmid with a 13-kb backbone. The AAVone system achieves a two- to four-fold increase in yields compared to the traditional triple-plasmid system. Furthermore, the AAVone system exhibits low batch-to-batch variation and eliminates the need for fine-tuning the ratios of the three plasmids, simplifying the production process. In terms of vector quality, AAVs generated by the AAVone system show similar in vitro and in vivo transduction efficiency, but a substantial reduction in sequences attributed to plasmid backbones and a marked reduction in non-functional snap-back genomes. In Summary, the AAVone platform is a straightforward, cost-effective, and highly consistent AAV production system - making it particularly suitable for GMP-grade AAV vectors.

bioengineering↗

bioRxiv2024

Transcriptional landscape of the archaeal cell cycle is broadly conserved in eukaryotes

The cell cycle is a series of events that occur from the moment of cell birth to cell division. In eukaryotes, cell growth, genome replication, genome segregation, and cytokinesis are strictly coordinated, defining discrete cell cycle phases. In contrast, these key processes may occur concurrently in bacteria. Thermoacidophilic archaea in the genus Saccharolobus follow a defined cell cycle program, with the first pre-replicative growth (G1) phase, followed by the chromosome replication (S) phase, the second growth (G2) phase, and rapid genome segregation (M) and cytokinesis (D) phases. However, whether other processes, such as metabolism, catabolism, protein translation, and antiviral defense also occur at specific cell cycle phases, as in eukaryotes, or are active throughout the cell cycle, as in bacteria, remains unclear. To address this question, we synchronized cultures of S. islandicus and performed an in-depth transcriptomic analysis of samples enriched in cells undergoing the M-G1, S, and G2 phases. Differential gene expression and consensus gene co-expression network analyses provided a holistic view of the S. islandicus cell cycle. In addition to the core transcriptome network, which is expressed throughout the cell cycle, we show that diverse metabolic pathways, protein synthesis, cell motility and even antiviral defense systems, are expressed in a cell cycle dependent fashion. Our data also refines understanding of the processes previously known to be linked to the cell cycle, such as DNA replication. We show that most DNA replication genes are expressed prior to the S phase, during the M-G1, whereas expression of the major chromatin genes, and accordingly, chromatinization are concomitant with replication. A statistical model was used to define sets of signature genes characteristic of each of the analyzed cell cycle phases, emphasizing transcriptional stratification of the phases. Signature genes are more conserved across Thermoproteota than non-signature genes and their peak expression, especially for the M-G1 and G2 specific genes, matches that of homologs in yeast. Collectively, our data elucidate the complexity of the S. islandicus cell cycle and suggest that it more closely resembles the cell cycle of eukaryotes than previously appreciated.

microbiology↗

bioRxiv2024

TiFM2.0 - Versatile mechanical measurement and actuation in live embryos

During development, spatial-temporally patterned tissue-level stresses and mechanical properties create diverse tissue shapes. To understand the mechanics of small-scale embryonic tissues, precisely controlled sensors and actuators are needed. Previously, we reported a control-based approach named tissue force microscopy (TiFM1.0), which combines dynamic positioning and imaging of an inserted cantilever probe to directly measure and impose forces in early avian embryos. Here we present an upgraded system (TiFM2.0) that utilises interferometer positioning to minimise probe holder footprint, enhancing accessibility and imaging signal. This new design enables a double-probe configuration for bidirectional stretching, compression and stress propagation experiments. As proof-of-concept, we showcase a variety of examples of TiFM2.0 applications in chicken and zebrafish embryos, including the characterization of mechanical heterogeneities important for the morphogenesis of the chicken posterior body axis. We also present simplified designs and protocols for the replication of TiFM systems with minimal custom engineering for developmental biology labs.

developmental biology↗

bioRxiv2024

Identification of molecular and functional subtypes using chronic pancreatitis patient-derived organoid models

Chronic pancreatitis (CP) affects [~]3 million people worldwide, yet altering the course of disease is challenging. We developed a patient-derived organoid (PDO) platform to investigate the molecular pathogenesis of this disease and identify therapeutic strategies. We generated 36 PDOs from patients with idiopathic, hereditary, and alcohol-related CP with high genetic concordance. PDOs retained inflammation-associated transcriptional and proteomic features. Transcriptomic profiling revealed three molecular subtypes of CP independent of etiology. We discovered widespread dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR) in half of the CP PDOs, including those with wildtype CFTR. Clinically available CFTR modulators stabilized mutant or wildtype CFTR, restored CFTR function, and decreased mitogenic and inflammatory signaling. This work provides the first comprehensive PDO platform for modeling CP. We demonstrate the utility of this platform for precision therapeutic investigations. Our findings reveal CFTR modulators as a broadly applicable and effective therapeutic strategy.

cell biology↗

bioRxiv2024

LP-Micro Offers Interpretable Disease Outcome Prediction by Leveraging Microbial Biomarkers and Their Time-Varying Effects

Information generated from longitudinally-sampled microbial data has the potential to illuminate important aspects of development and progression for many human conditions and diseases. Identifying microbial biomarkers and their time-varying effects can not only advance our understanding of pathogenetic mechanisms, but also facilitate early diagnosis and guide optimal timing of interventions. However, longitudinal predictive modeling of highly noisy and dynamic microbial data (e.g., metagenomics) poses analytical challenges. To overcome these challenges, we introduce a robust and interpretable machine-learning-based longitudinal microbiome analysis framework, LP-Micro, that encompasses: (i) longitudinal microbial feature screening via a polynomial group lasso, (ii) disease outcome prediction implemented via machine learning methods (e.g., XGBoost, deep neural networks), and (iii) interpretable association testing between time points, microbial features, and disease outcomes via permutation feature importance. We demonstrate in simulations that LP-Micro can not only identify incident disease-related microbiome taxa but also offers improved prediction accuracy compared to existing approaches. Applications of LP-Micro in two longitudinal microbiome studies with clinical outcomes of childhood dental disease and weight loss following bariatric surgery yield consistently high prediction accuracy. The identified critical early predictive time points are informative and aligned with clinical expectations.

bioinformatics↗

bioRxiv2024

Multi-modal profiling identifies CD4+CXCR5+PD-1- Tfh cells as prognostic and predictive biomarkers for response to R-CHOP therapy in human DLBCL

Despite the improvements in clinical outcomes for patients with Diffuse Large B-Cell Lymphoma (DLBCL), a significant proportion of those patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. Characterizing the heterogeneity of the tumor microenvironment (TME) in diffuse large B cell lymphoma (DLBCL) is crucial for understanding relapsed/refractory disease. However, the complex and diverse nature of the TME has impeded progress. Here, using single-cell RNA sequencing(scRNA-seq), we explored the DLBCL landscape at single-cell resolution, profiling 77,344 cells from both primary and relapsed DLBCL patients. We further investigated the shared and distinct molecular and cellular features of tumor microenvironment in both primary and relapsed DLBCL tumors by integrating next-generation DNA sequencing data and multiple scRNA-seq datasets from total 72,351 cells. Our results demonstrated that there was a significant decrease of CD4+CXCR5+PD-1- Tfh cells, along with excessive activation of the TNF-NF{kappa}B signaling pathways in malignant B cells in R/R disease. Furthermore, by using multiplex IHC, we confirmed that CD4+CXCR5+PD-1- Tfh cells are prognostic and predictive biomarkers for response to R-CHOP treatment. As a proof of concept, we successfully generated mutilplexed images of CD4+CXCR5+PD-1- Tfh cells from a single DAPI staining in human DLBCL tissues through using generative artificial intelligence. Our study offers critical insights into the heterogeneity and molecular features of DLBCL, shedding light on the crucial role of CD4+CXCR5+PD-1- Tfh cells in the recurrent process. HighlightsO_LIShared and distinct molecular and cellular features of tumor microenvironment in both primary and relapsed DLBCL tumors; C_LIO_LIThe characteristic of relapsed DLBCL TME is a dysfunctional immune microenvironment with a significant decrease of CD4+CXCR5+PD-1- Tfh cells. C_LIO_LICD4+CXCR5+PD-1- Tfh cells are prognostic and predictive biomarkers for response to R-CHOP treatment C_LIO_LIDetermination of CD4+CXCR5+PD-1- Tfh cells in human DLBCL tissues through using generative artificial intelligence. C_LI

immunology↗

bioRxiv2024

High-dimensional Biomarker Identification for Scalable and Interpretable Disease Prediction via Machine Learning Models

Omics data generated from high-throughput technologies and clinical features jointly impact many complex human diseases. Identifying key biomarkers and clinical risk factors is essential for understanding disease mechanisms and advancing early disease diagnosis and precision medicine. However, the high-dimensionality and intricate associations between disease outcomes and omics profiles present significant analytical challenges. To address these, we propose an ensemble data-driven biomarker identification tool, Hybrid Feature Screening (HFS), to construct a candidate feature set for downstream advanced machine learning models. The pre-screened candidate features from HFS are further refined using a computationally efficient permutation-based feature importance test, forming the comprehensive High-dimensional Feature Importance Test (HiFIT) framework. Through extensive numerical simulations and real-world applications, we demonstrate HiFITs superior performance in both outcome prediction and feature importance identification. An R package implementing HiFIT is available on GitHub (https://github.com/BZou-lab/HiFIT).

bioinformatics↗

bioRxiv2024

scEMB: Learning context representation of genes based on large-scale single-cell transcriptomics

BackgroundThe rapid advancement of single-cell transcriptomic technologies has led to the curation of millions of cellular profiles, providing unprecedented insights into cellular heterogeneity across various tissues and developmental stages. This growing wealth of data presents an opportunity to uncover complex gene-gene relationships, yet also poses significant computational challenges. ResultsWe present scEMB, a transformer-based deep learning model developed to capture context-aware gene embeddings from large-scale single-cell transcriptomics data. Trained on over 30 million single-cell transcriptomes, scEMB utilizes an innovative binning strategy that integrates data across multiple platforms, effectively preserving both gene expression hierarchies and cell-type specificity. In downstream tasks such as batch integration, clustering, and cell type annotation, scEMB demonstrates superior performance compared to existing models like scGPT and Geneformer. Notably, scEMB excels in silico correlation analysis, accurately predicting gene perturbation effects in CRISPR-edited datasets and microglia state transition, identifying a few known Alzheimers disease (AD) risks genes in top gene list. Additionally, scEMB offers robust fine-tuning capabilities for domain-specific applications, making it a versatile tool for tackling diverse biological problems such as therapeutic target discovery and disease modeling. ConclusionsscEMB represents a powerful tool for extracting biologically meaningful insights from complex gene expression data. Its ability to model in silico perturbation effects and conduct correlation analyses in the embedding space highlights its potential to accelerate discoveries in precision medicine and therapeutic development.

bioinformatics↗

bioRxiv2024

A secondary β-hydroxybutyrate metabolic pathway linked to energy balance

{beta}-hydroxybutyrate (BHB) is an abundant ketone body. To date, all known pathways of BHB metabolism involve interconversion of BHB and primary energy intermediates. Here we show that CNDP2 controls a previously undescribed secondary BHB metabolic pathway via enzymatic conjugation of BHB and free amino acids. This BHB-ylation reaction produces a family of endogenous ketone metabolites, the BHB-amino acids. Genetic ablation of CNDP2 in mice eliminates tissue amino acid BHB-ylation activity and reduces BHB-amino acid levels. Administration of BHB-Phe, the most abundant BHB-amino acid, to obese mice activates neural populations in the hypothalamus and brainstem and suppresses feeding and body weight. Conversely, CNDP2-KO mice exhibit increased food intake and body weight upon ketosis stimuli. CNDP2-dependent amino acid BHB-ylation and BHB-amino acid metabolites are also conserved in humans. Therefore, the metabolic pathways of BHB extend beyond primary metabolism and include secondary ketone metabolites linked to energy balance.

biochemistry↗

bioRxiv2024

Dynamic convergence of autism disorder risk genes across neurodevelopment

Over three hundred and seventy-three risk genes, broadly enriched for roles in neuronal communication and gene expression regulation, underlie risk for autism spectrum disorder (ASD) and developmental delay (DD). Functional genomic studies of subsets of these genes consistently indicate a convergent role in neurogenesis, but how these diverse risk genes converge on a smaller number of biological pathways in mature neurons is unclear. To uncover shared downstream impacts between neurodevelopmental disorder (NDD) risk genes, here we apply a pooled CRISPR approach to contrast the transcriptomic impacts of targeting 29 NDD loss-of-function genes across human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells, glutamatergic neurons, and GABAergic neurons. Points of convergence vary between the cell types of the brain and are greatest in mature glutamatergic neurons, where they broadly target not just synaptic and epigenetic, but unexpectedly, mitochondrial biology. The strongest convergent networks occur between NDD genes with common co-expression patterns in the post-mortem brain, biological annotations, and clinical associations, suggesting that convergence may one-day inform patient stratification and treatment. Towards this, ten out of eleven drugs tested that were predicted to reverse convergent signatures in human cells and/or arousal and sensory processing behaviors in zebrafish ameliorated at least one behavioral phenotype in vivo. Altogether, robust convergence in post-mitotic neurons represents a clinically actionable therapeutic window.

genetics↗

bioRxiv2024

Evaluation of vectors for gene expression in Pseudovibrio bacteria and their application in Aplysina marine sponge studies

-Proteobacteria belonging to the Pseudovibrio genus have been isolated from different marine organisms including marine sponges, corals and algae. This genus was first described in 2004 and has since garnered attention due to the potential ecological relevance and biotechnological application of its metabolites. For instance, we recently reported specialized metabolites we named pseudovibriamides from Pseudovibrio brasiliensis Ab134. The pseudovibriamide encoding ppp gene cluster is found in two thirds of Pseudovibrio genomes. Pseudovibriamides coordinate motility and biofilm formation, behaviors that are known to be important for host colonization. Although we previously established reverse genetics methods to delete genes via homologous recombination, no self-replicative vectors have been reported for Pseudovibrio. We show that plasmid vectors containing two different broad-host-range replicons, RSF1010 and pBBR1, can be used in P. brasiliensis. The efficiency of vector transfer by electroporation averaged [~] 3 x 103 CFU/{micro}g plasmid DNA whereas the conjugation frequency from E. coli ranged from 10-3 to 10-6. We then tested the vectors for fluorescent protein expression and consequent labeling, which allowed us to observe their effects on swarming motility and to compare plasmid stability. This study expands the genetic toolbox available for Pseudovibrio which is expected to enable future ecological and biotechnological studies. ImportanceThe genus Pseudovibrio of -Proteobacteria has consistently been isolated from marine sponges and other marine organisms such as corals and algae. Pseudovibrio bacteria are a source of antibiotics and other secondary metabolites with the potential to be developed into pharmaceuticals. Moreover, the secondary metabolites they produce are important for their physiology and for interactions with other organisms. Here we expand the genetic tool box available for Pseudovibrio bacteria by establishing self-replicative vectors that can be used for the expression of e.g., fluorescent proteins. The availability of genetic tools is important to enable us to explore the emerging ecological and biotechnological potential of Pseudovibrio bacteria.

genetics↗

bioRxiv2024

Nuclear FAK aggravates CD8+ T cell exhaustion via the SP1-IL-6 axis in colorectal cancer

Nuclear abnormalities such as nuclear deformation are hallmarks of many diseases, including cancer. Accumulating evidence suggests that the dense and mechanically stiff tumor microenvironment promotes nuclear deformation in cancer cells. However, little is known about how nuclear deformation in neoplastic cells regulates immune exhaustion in the tumor microenvironment. Here, we found that lamin A/C-mediated nuclear stiffening in neoplastic cells promotes the nuclear translocation of phosphorylated focal adhesion kinase (pFAK), which is strongly correlated with the heterogeneity and exhaustion of CD8+ T cells within the spatial context of the tumor microenvironment in human colorectal cancer. Mechanistically, we revealed that increased nuclear tension within tumor cells promotes pFAK nuclear translocation, where nuclear pFAK was found to regulate SP1/IL-6-mediated T-cell exhaustion and the transcription of proinflammatory cytokines/chemokines. Pharmacological inhibition or disruption of pFAK nuclear translocation enhanced antitumor immune responses and synergistically potentiated PD-1 and TIM-3 immunotherapy by increasing CD8+ T-cell cytotoxicity and restoring exhaustion in preclinical models of colorectal cancer. These findings highlight the pivotal role of nuclear tension-mediated pFAK translocation into the tumor cell nucleus in regulating CD8+ T-cell exhaustion, suggesting that pFAK is a promising target for advancing cancer immunotherapy.

immunology↗

bioRxiv2024

Sympathetic Nervous System Overactivation Induces Colonic Eosinophil-Associated Microinflammation and Contributes to the Pathogenesis of Irritable Bowel Syndrome

ObjectiveMucosal microinflammation is a characteristic clinical manifestation of irritable bowel syndrome (IBS), and its symptoms are often triggered by psychological stress. In the present study, we aimed to investigate the impact of early life stress-associated dysfunction of the sympathetic nervous system (SNS) on mucosal immune changes in the gastrointestinal tract (GI) and its contribution to IBS pathogenesis. DesignWe utilised a traditional animal model of IBS with maternal separation (MS) and evaluated colorectal hypersensitivity, immune alterations, and SNS activity in adult rats with MS. We conducted a series of experiments to manipulate peripheral SNS activity pharmacologically and chemogenetically to explore the interaction between SNS activity and GI events. ResultsThe MS-induced IBS model exhibited visceral hypersensitivity and eosinophilic infiltration in the colonic mucosa, along with SNS overactivation. Degeneration of the SNS using 6-OHDA neurotoxin decreased eosinophil infiltration and visceral hypersensitivity in the MS model. Notably, specific chemogenetic activation of the peripheral SNS induced eosinophil infiltration in the intestinal mucosa through the noradrenergic signalling-mediated release of eotaxin-1 from mesenchymal cells. ConclusionThis study highlights the critical role of SNS overactivation in eotaxin-1-driven eosinophil infiltration in the colon, leading to the development of visceral hypersensitivity in IBS. The results provide important insights into the mechanistic links among increased sympathetic activity, mucosal microinflammation, and visceral hypersensitivity in individuals with IBS, suggesting potential therapeutic approaches. What is already known on this topicO_LIA subgroup of patients with irritable bowel syndrome (IBS) presents with microinflammation in the gastrointestinal tract (GI). C_LIO_LIEarly life stress is recognised as a major risk factor for the development of IBS in adulthood. C_LIO_LIOveractivation of the sympathetic nervous system (SNS) is frequently associated with IBS. C_LI What this study addsO_LIMaternal separation (MS) stress induces eosinophil-associated microinflammation in the colonic mucosa of adult rats. C_LIO_LIInhibition of SNS activity suppresses eosinophil infiltration and mitigates visceral hypersensitivity in the MS model. C_LIO_LINoradrenergic signalling within the peripheral sympathetic activation stimulates mesenchymal cells to release eotaxin-1, leading to substantial eosinophil-predominant immune alterations in the colon. C_LI How this study might affect research, practice, or policyO_LITreatment with fibroblast-derived eotaxin-1 and targeting eosinophil-associated microinflammation could be a potential strategy to alleviate visceral pain in patients with IBS. C_LIO_LIThe chemogenomic method specifically manipulates peripheral SNS and provides a valuable tool for future research. C_LI

neuroscience↗

bioRxiv2024

Biomolecular condensates can function as inherent catalysts

We report the discovery that chemical reactions can be catalyzed by condensates formed by intrinsically disordered proteins (IDPs). The proteins themselves lack any catalytic activities. Catalytic functions of condensates emerge as a consequence of sequence-dependent mesoscale electrochemical microenvironments created by phase separation. Stimulated Raman spectroscopy suggests that the catalytic behaviors of condensates are attributable to the spatial variations of water activities across condensate interiors and interfaces. We show that condensates are capable of catalyzing diverse cellularly relevant hydrolysis reactions. Through sequence design, the electrochemical properties of condensates can be programmed to exert control over catalytic behaviors. Incorporation of synthetic condensates into live cells alters transcription profiles and enables the activation of gene circuits that depend on products of hydrolysis reactions catalyzed by condensates. Our discovery of suggests that condensates, depending on their composition-dependent electrochemical properties, can be "Condenzymes", which contribute unexpected emergent chemical functions in cells.

biophysics↗

bioRxiv2024

Biomolecular condensates are characterized by interphase electric potentials

Biomolecular condensates form via processes that combine phase separation and reversible associations of multivalent macromolecules. Condensates can be two- or multi-phase systems defined by coexisting dense and dilute phases. Here, we show that solution ions can partition asymmetrically across coexisting phases defined by condensates formed by intrinsically disordered proteins or homopolymeric RNA molecules. Our findings were enabled by direct measurements of the activities of cations and anions within coexisting phases of protein and RNA condensates. Asymmetries in ion partitioning between coexisting phases vary with protein sequence, condensate type, salt concentration, and ion type. The Donnan equilibrium set up by asymmetrical partitioning of solution ions generates interphase electric potentials known as Donnan and Nernst potentials. Our measurements show that the interphase potentials of condensates are of the same order of magnitude as membrane potentials of membrane-bound organelles. Interphase potentials quantify the degree to which microenvironments of coexisting phases are different from one another. Importantly, and based on condensate-specific interphase electric potentials, which are membrane-like potentials of membraneless bodies, we reason that condensates are mesoscale capacitors that store charge. Interphase potentials lead to electric double layers at condensate interfaces. This helps explain recent observations of condensate interfaces being electrochemically active.

biophysics↗