Biology subjects

Hu, X.

Publications and source records attributed to Hu, X..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

Development of a DNA-encoded library screening method DEL Zipper to empower the study of RNA-targeted chemical matter

To date, RNA-targeted chemical matter is under explored due to a lack of robust screening assays. In this study, we present a novel RNA-targeted small molecule screening approach using a specialized DNA-encoded library (DEL). Our findings reveal that the specialized DEL library, called "DEL Zipper", can significantly reduce single-stranded DNA-RNA region interaction signals during various kinds of RNA selection. By performing the selection against both G-quadruplex, we have identified novel hits that interact with RNA targets and the results are validated through binding. This study demonstrates that the "DEL Zipper" method is a robust screening assay that has potential for discovering small molecule ligands for diverse RNA targets.

molecular biology↗

bioRxiv2024

Role of AMPK in Atrial Metabolic Homeostasis and Substrate Preference

Atrial fibrillation is the most common clinical arrhythmia and may be due in part to metabolic stress. Atrial specific deletion of the master metabolic sensor, AMP-activated protein kinase (AMPK), induces atrial remodeling culminating in atrial fibrillation in mice, implicating AMPK signaling in the maintenance of atrial electrical and structural homeostasis. However, atrial substrate preference for mitochondrial oxidation and the role of AMPK in regulating atrial metabolism are unknown. Here, using LC-MS/MS methodology combined with infusions of [13C6]glucose and [13C4]{beta}-hydroxybutyrate in conscious mice, we demonstrate that conditional deletion of atrial AMPK catalytic subunits shifts mitochondrial atrial metabolism away from fatty acid oxidation and towards pyruvate oxidation. LC-MS/MS-based quantification of acyl-CoAs demonstrated decreased atrial tissue content of long-chain fatty acyl-CoAs. Proteomic analysis revealed a broad downregulation of proteins responsible for fatty acid uptake (LPL, CD36, FABP3), acylation and oxidation. Atrial AMPK deletion reduced expression of atrial PGC1- and downstream PGC1-/PPAR/RXR regulated gene transcripts. In contrast, atrial [14C]2-deoxyglucose uptake and GLUT1 expression increased with fasting in mice with AMPK deletion, while the expression of glycolytic enzymes exhibited heterogenous changes. Thus, these results highlight the crucial homeostatic role of AMPK in the atrium, with loss of atrial AMPK leading to downregulation of the PGC1-/PPAR pathway and broad metabolic reprogramming with a loss of fatty acid oxidation, which may contribute to atrial remodeling and arrhythmia.

physiology↗

bioRxiv2024

Slow-wave sleep and REM sleep differentially contribute to memory representational transformation

Memory transforms over time, gradually becoming less idiosyncratic and more gist-like. While sleep contributes to memory transformation, how different sleep stages and EEG activity influence memory transformation is far from clear. Applying representational similarity analysis to electroencephalogram (EEG) recordings, we examined memory representational transformation at both the idiosyncratic "item-level" and the generic "category-level". Our findings revealed that after an overnight sleep, item-level neural representations for post-sleep remembered items were abolished. In contrast, category-level representations remained prominent, but they became distinctive from pre-sleep. Across participants, more rapid eye movement (REM) sleep relative to slow-wave sleep (SWS) was associated with reduced item-level neural representational strength, increased category-level representational strength, as well as the decreased item-level representational similarity between pre-sleep learning and post-sleep retrieval sessions. Moreover, the theta and beta EEG power during REM sleep, and delta power during SWS differentially supported these representational transformations. These findings suggest that post-learning REM sleep and SWS play differential roles in supporting overnight memory transformation.

neuroscience↗

bioRxiv2024

Cholecystokinin modulates age-dependent Thalamocortical Neuroplasticity

The thalamocortical pathways exhibit neuroplasticity not only during the critical period but also in adulthood. In this study, we investigated how cholecystokinin (CCK) modulates age-dependent thalamocortical plasticity. Our findings demonstrated that CCK is expressed in thalamocortical neurons and that high-frequency stimulation (HFS) of the thalamocortical pathway triggers the release of CCK in auditory cortex (ACx), as detected by a CCK sensor. HFS of the medial geniculate body (MGB) induced thalamocortical long-term potentiation (LTP) in wild-type young adult mice. However, knockdown of Cck expression in MGB neurons or blockade of the CCK-B receptor (CCKBR) in the ACx abolished HFS-induced LTP. Interestingly, this LTP could not be elicited in juvenile (3-week-old) or aged mice (over 18-month-old) due to distinct mechanisms: the absence of CCKBR in juveniles and the inability to release CCK in aged mice. Notably, exogenous administration of CCK into the ACx rescued LTP in aged mice and significantly improved frequency discrimination. These findings highlight the potential of CCK as a therapeutic intervention for ameliorating neuroplasticity deficits associated with thalamocortical connectivity.

neuroscience↗

bioRxiv2024

Multimodal screen reveals noise regulatory proteins

Gene-expression noise can influence cell-fate choices across pathology and physiology. However, a crucial question persists: do regulatory proteins or pathways exist that control noise independently of mean expression levels? Our integrative approach, combining single-cell RNA sequencing with proteomics and regulator enrichment analysis, reveals 32 putative noise regulators. SON, a nuclear speckle-associated protein, alters transcriptional noise without changing mean expression levels. Furthermore, SONs noise regulation can propagate to the protein level. Long-read and total RNA sequencing shows that SONs noise regulation does not significantly change isoform usage or splicing efficiency. Moreover, SON depletion reduces state-switching in pluripotent mouse embryonic stem cells and impacts their fate choice during differentiation. Collectively, we discover a class of proteins that regulates noise orthogonally to mean expression levels. This work serves as a proof-of-concept that can identify other functional noise-regulators throughout development and disease progression.

systems biology↗

bioRxiv2024

SSRI antidepressant citalopram reverses the Warburg effect to inhibit hepatocellular carcinoma by directly targeting GLUT1

Although there is growing appreciation for effective repurposing of selective serotonin reuptake inhibitors (SSRIs) for cancer therapy, particularly hepatocellular carcinoma (HCC), efforts are hampered by limited knowledge of their molecular targets and mechanism of action. Global inverse gene-expression profiling method, drug affinity responsive target stability assay, and in silico molecular docking analysis was performed to identify the targets of SSRIs. Murine subcutaneous, orthotopic models, and patient-derived xenograft were employed to explore the therapeutic effects and underlying mechanisms of SSRIs in HCC. The clinical relevance of SSRI use was verified with real world data. SSRIs exhibit significant anti-HCC effects independent of their known target serotonin reuptake transporter. The glucose transporter 1 (GLUT1) is identified as a new target of SSRIs. Citalopram binds to and antagonizes GLUT1, resulting in reduced glycolytic flux and ATP generation. Mutant GLUT1 in the binding site E380 of citalopram compromises the inhibitory effects of citalopram on the Warburg effect and tumor growth. In preclinical models, citalopram dampens the growth kinetics of GLUT1high liver tumors and displays a synergistic effect with anti-PD-1 therapy. Retrospective analysis of health records found that SSRIs use is associated with a lower risk of metastasis among HCC patients. Our study reveals an unprecedented role of SSRIs in cancer metabolism, and establishes a rationale for repurposing SSRIs as potential anticancer drugs for HCC.

cancer biology↗

bioRxiv2024

MicroWorldOmics:A "One step for All" desktop application for comprehensive analysis in microbiome and virome and exploring "Dark Matter" from MicroWorld

A large amount of high-throughput sequencing data generated in ecology, medicine, and pharmacy has increasingly raised the complexity of data analysis and interpretation. However, the microbiome and virome field still lacks a convenient and programming-free desktop application for the comprehensive analysis in microbiome and virome data, particularly in virome analysis and Dark Matter exploration. Therefore, a plugin development mode desktop service, MicroWorldOmics, is proposed with a convenient and one-stop pipeline for life sciences and biomedical fields. Plugin development allows users to analyze data in parallel and interactively, while these tasks usually require advanced bioinformatician to achieve. MicroWorldOmics is a software widely used in microbiome and virome, containing 90 sub-applications, including four main functions: epidemiological analysis, metagenomic/amplicons and virome comprehensive analysis, and exploring Dark matter. More than 80 Python modules and 600 R packages are invoked in all aspects of bioinformatics analysis, statistical analysis, deep learning, and visualization. At the same time, the software supports multiple input and output results, such as GFF3, FASTA, CSV, PNG, JPG, JSON, and TXT, etc. Besides, to improve the efficiency for users, MicroWorldOmics supports being deployed in three mainstream systems: Windows, Linux, and Mac and also sets the demo/example data for users to test the benchmark easily. In summary, the development of MicroWorldOmics greatly facilitates the process of analyzing microbiome and virome data for researchers who have no programming foundation and are devoted to life science and biomedicine data analysis.

genomics↗

bioRxiv2024

Elucidating the kinetic and thermodynamic insight into regulation of glycolysis by lactate dehydrogenase and its impact on tricarboxylic acid cycle and oxidative phosphorylation in cancer cells

Lactate dehydrogenase (LDH) stands at the intersection of pyruvate metabolism. While it is believed that inhibition of LDH redirects pyruvate to mitochondrial metabolism, suppressing glycolysis and boosting oxidative phosphorylation, the mechanism remains largely unexplored. We found that individual LDH A or B knockouts had minimal impact on glycolysis, tricarboxylic acid cycle (TCA cycle), or oxidative phosphorylation (OXPHOS). However, combining LDH knockout with LDH inhibitor GNE-140 significantly suppressed these processes. Inhibition of LDH led to an increase in free NADH concentration and a decrease in free NAD+ concentration, the reduced free NAD+ concentration inhibited GAPDH, disrupting the balance of glycolytic intermediates, which were linked with thermodynamic shift of the Gibbs free energy of reactions between phosphofructokinase 1 (PFK1) and phosphoglycerate mutase (PGAM) in the glycolytic pathway, favoring their reverse direction. This disrupted glycolysis led to impaired TCA cycle and mitochondrial respiration due to reduced pyruvate and glutamine carbon influx into TCA cycle. Under hypoxia, LDH inhibition had a stronger effect, inducing energy crisis, redox imbalance, and cancer cell death. Our study reveals LDHs intricate control over glycolysis, TCA cycle, and mitochondrial respiration, highlighting the interplay of enzyme kinetics and thermodynamics in metabolic pathways, a crucial aspect for understanding metabolic regulation. Impact statementThis study elucidates a biochemical mechanism by which lactate dehydrogenase influences glycolytic flux in cancer cells, revealing a kinetic- thermodynamic interplay that contributes to metabolic regulation.

biochemistry↗

bioRxiv2024

Defining cellular determinants of resistance to PD-1 pathway blockade in non-small-cell lung cancer

Despite sustained clinical responses to immune-checkpoint blockade (ICB) therapies in non-small-cell lung cancer (NSCLC), the majority of patients derive no clinical benefits, and the cellular and molecular underpinnings of such resistance remain incompletely understood. To identify cell types that may influence immunotherapy responses, we first integrated newly generated and previously published single-cell RNA sequencing data from 110 treatment-naive patients with NSCLC. Among tumor-resident cell types, we identified MMP1+ cancer-associated fibroblasts (CAFs), which were inversely correlated with the level of tumor-reactive T cells--a key determinant of response to ICB. Further single-cell analysis for newly collected 21 tumor samples from NSCLC patients treated with anti-PD-1/PD-L1 agents revealed that MMP1+ fibroblasts were indeed enriched in treatment-refractory patients, and this observation was also validated in an independent dataset of bulk RNA sequencing from 344 NSCLC patients treated with PD-L1 agents. Examination of the spatial architecture showed that MMP1+ fibroblasts were located at the tumor-stroma boundary, forming a single-cell layer that encircled the cancer cell aggregates, and we hence defined MMP1+ fibroblasts as tumor-stroma boundary (tsb)CAFs. Such tsbCAFs likely promote resistance to ICB by functioning as a physical barrier that prevents tumor-reactive T cells from recognizing and killing cancer cells. Our study provides a new framework to identify cellular underpinnings of resistance to ICB and suggests new strategies to overcome ICB resistance. Highlights{lozenge} Identification and characterization of MMP1+ fibroblasts in lung cancer. {lozenge}Single-cell meta-analysis reveals cell populations impeding the accumulation of tumor-reactive T cells. {lozenge}MMP1+ fibroblasts correlate with the low infiltration of tumor-reactive T cells and the resistance to anti-PD-1/PD-L1 treatment. {lozenge}MMP1+ fibroblasts appear to form a space barrier between malignant and T cells.

immunology↗

bioRxiv2024

Signal transduction pathways controlling Ins2 gene activity and β cell state transitions

Pancreatic {beta} cells exist in low and high insulin gene activity states that are dynamic on a scale of hours to days. Here, we used live 3D imaging, mass spectrometry proteomics, and targeted perturbations of {beta} cell signaling to comprehensively investigate Ins2(GFP)HIGH and Ins2(GFP)LOW {beta} cell states. We identified the two Ins2 gene activity states in intact isolated islets and showed that cells in the same state were more likely to be nearer to each other. We report the proteomes of pure {beta} cells to a depth of 5555 proteins and show that {beta} cells with high Ins2 gene activity had reduced {beta} cell immaturity factors, as well as increased translation. We identified activators of cAMP signaling (GLP1, IBMX) as powerful drivers of transitions from Ins2(GFP)LOW to the Ins2(GFP)HIGH states. Okadaic acid and cyclosporine A had the opposite effects. This study provides new insight into the proteomic profiles and regulation of {beta} cell states.

cell biology↗

bioRxiv2024

RBET guides case-specific choice of batch correction methods for single-cell transcriptomic data with overcorrection awareness and large batch effect robustness

Integrating single-cell RNA-sequencing datasets from different sources is a common practice to empower in-depth interrogation for biological insights, where batch effect correction (BEC) is of vital importance. However, an inappropriate BEC may lead to overcorrection and report misleading results on downstream analyses including cell annotation, trajectory inference and cell-cell communication. Hence, we develop the Reference-based Batch Effect Testing (RBET), a novel statistical framework for evaluating the performance of different BEC methods by leveraging housekeeping-gene inspired reference genes and MAC statistics for distribution comparison. Comparing with existing methods, RBET is more powerful on detecting batch effect, overcorrection sensitive, computationally efficient, and robust to large batch effect sizes. Furthermore, extensive multi-scenario real examples show that RBET selects optimal BEC tools for consistent downstream analysis results, which confirm prior biological knowledge. This comprehensive BEC decision-making tool is available as an R package.

bioinformatics↗

bioRxiv2024

DENOISING: Dynamic Enhancement and Noise Overcoming in Multimodal Neural Observations via High-density CMOS-based Biosensors

Large-scale multimodal neural recordings on high-density biosensing microelectrode arrays (HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity across various brain networks. However, the fidelity of these recordings is frequently compromised by pervasive noise, which obscures meaningful neural information and complicates data analysis. To address this challenge, we introduce DENOISING, a versatile data-derived computational engine engineered to adjust thresholds adaptively based on large-scale extracellular signal characteristics and noise levels. This facilitates the separation of signal and noise components without reliance on specific data transformations. Uniquely capable of handling a diverse array of noise types (electrical, mechanical, and environmental) and multidimensional neural signals, including stationary and non-stationary oscillatory local field potential (LFP) and spiking activity, DENOISING presents an adaptable solution applicable across different recording modalities and brain networks. Applying DENOISING to large-scale neural recordings from mice hippocampal and olfactory bulb networks yielded enhanced signal-to-noise ratio (SNR) of LFP and spike firing patterns compared to those computed from raw data. Comparative analysis with existing state-of-the-art denoising methods, employing SNR and root mean square noise (RMS), underscores DENOISINGs performance in improving data quality and reliability. Through experimental and computational approaches, we validate that DENOISING improves signal clarity and data interpretation by effectively mitigating independent noise in spatiotemporally structured multimodal datasets, thus unlocking new dimensions in understanding neural connectivity and functional dynamics.

neuroscience↗

bioRxiv2024

Mapping Large-scale Spatiotemporal Dynamics of Synaptic Plasticity and LTP for Memory Encoding in the Hippocampal Network

Understanding memory formation requires elucidating the intricate dynamics of neuronal networks in the hippocampus, where information is encoded and processed through specific activity patterns and synaptic plasticity. Here, we introduce "EVOX," an advanced network electrophysiology platform equipped with high-density microelectrode arrays to capture critical network-level synaptic dynamics integral to learning and memory. This platform surpasses traditional methods by enabling label-free, high-order mapping of neural interactions, providing unprecedented insights into network Long-Term Potentiation (LTP) and evoked synaptic transmission within the hippocampal network. Utilizing EVOX, we demonstrate that high-frequency stimulation induces network-wide LTP, revealing enhanced synaptic efficacy in previously inactive cell assemblies in hippocampal layers. Our platform enables the real-time observation of network synaptic transmission, capturing the intricate patterns of connectivity and plasticity that underpin memory encoding. Advanced computational techniques further elucidate the mesoscale transmembrane generators and the dynamic processes that govern network-level memory encoding mechanisms. These findings uncover the complex dynamics that underlie learning and memory, showcasing EVOXs potential to explore synaptic and cellular phenomena in aging circuits. EVOX not only advances our understanding of hippocampal memory mechanisms but also serves as a powerful tool to investigate the broader scope of neural plasticity and network interactions in healthy and diseased states.

neuroscience↗

bioRxiv2024

Repression of PRMT activities sensitize homologous recombination-proficient ovarian and breast cancer cells to PARP inhibitor treatment

Therapeutic epigenetic modulation is currently being evaluated in the clinic to sensitize homologous recombination (HR)-proficient tumors to PARP inhibitors. To broaden its clinical applicability and identify more effective combination strategies, we conducted a drug screen combining PARP inhibitors with 74 well-characterized epigenetic modulators targeting five major classes of epigenetic enzymes. Notably, both type I PRMT inhibitors and PRMT5 inhibitors scored highly in combination efficacy and clinical prioritization. PRMT inhibition significantly enhanced PARP inhibitor-induced DNA damage in HR-proficient ovarian and breast cancer cells. Mechanistically, PRMT suppression downregulates DNA damage repair genes and BRCAness-associated pathways, while also modulating intrinsic innate immune responses within cancer cells. Integrative analysis of large-scale genomic and functional datasets from TCGA and DepMap further supports PRMT1, PRMT4, and PRMT5 as promising therapeutic targets in oncology. Importantly, dual inhibition of PRMT1 and PRMT5 synergistically sensitizes tumors to PARP inhibitors. Collectively, our findings provide strong rationale for the clinical development of PRMT and PARP inhibitor combinations in HR-proficient ovarian and breast cancers.

cancer biology↗

bioRxiv2024

MEA-seqX: High-resolution Profiling of Large-scale Electrophysiological and Transcriptional Network Dynamics

Concepts of brain function imply congruence and mutual causal influence between molecular events and neuronal activity. Decoding entangled information from concurrent molecular and electrophysiological network events demands innovative methodology bridging scales and modalities. Our MEA-seqX platform, integrating high-density microelectrode arrays, spatial transcriptomics, optical imaging, and advanced computational strategies, enables the simultaneous recording and analysis of molecular and electrical network activities at the level of individual cells. Applied to a mouse hippocampal model of experience-dependent plasticity, MEA-seqX unveiled massively enhanced nested dynamics between transcription and function. Graph-theoretic analysis revealed an increase in densely connected bimodal hubs, marking the first observation of coordinated spatiotemporal dynamics in hippocampal circuitry at both molecular and functional levels. This platform also identified different cell types based on their distinct bimodal profiles. Machine-learning algorithms accurately predicted network-wide electrophysiological features from spatial gene expression, demonstrating a previously inaccessible convergence across modalities, time, and scales.

neuroscience↗

bioRxiv2024

A single cell framework identifies functionally and molecularly distinct multipotent progenitors in adult human hematopoiesis

Hematopoietic multipotent progenitors (MPPs) regulate blood cell production to appropriately meet the biological demands of the human body. Human MPPs remain ill-defined whereas mouse MPPs have been well characterized with distinct immunophenotypes and lineage potencies. Using multiomic single cell analyses and complementary functional assays, we identified new human MPPs and oligopotent progenitor populations within Lin-CD34+CD38dim/lo adult bone marrow with distinct biomolecular and functional properties. These populations were prospectively isolated based on expression of CD69, CLL1, and CD2 in addition to classical markers like CD90 and CD45RA. We show that within the canonical Lin-CD34+CD38dim/loCD90CD45RA-MPP population, there is a CD69+ MPP with long-term engraftment and multilineage differentiation potential, a CLL1+ myeloid-biased MPP, and a CLL1-CD69-erythroid-biased MPP. We also show that the canonical Lin-CD34+CD38dim/loCD90-CD45RA+ LMPP population can be separated into a CD2+ LMPP with lymphoid and myeloid potential, a CD2-LMPP with high lymphoid potential, and a CLL1+ GMP with minimal lymphoid potential. We used these new HSPC profiles to study human and mouse bone marrow cells and observe limited cell type specific homology between humans and mice and cell type specific changes associated with aging. By identifying and functionally characterizing new adult MPP sub-populations, we provide an updated reference and framework for future studies in human hematopoiesis.

cancer biology↗

bioRxiv2024

Artesunate, EDTA and colistin work synergistically against MCR-negative and -positive colistin-resistant Salmonella

Discovering new strategies to combat the multi-drug resistance bacteria constitutes a major medical challenge of our time. Previously, artesunate (AS) has been reported to exert antibacterial enhancement activity in combination with {beta}-lactam antibiotics, via inhibition of the efflux pump AcrB. However, combination of AS and colistin (COL) revealed weak synergistic effect against a limited number of strains, and few studies have further explored its possible mechanism of synergistic action. In this paper, we found that AS and EDTA could strikingly enhance the antibacterial effects of COL against mcr-1- and mcr-1+ Salmonella strains either in vitro or in vivo, when used in triple combination. The excellent bacteriostatic effect was primarily related to the increased cell membrane damage, accumulation of toxic compounds and inhibition of MCR-1. The potential binding sites of AS to MCR-1 (THR283, SER284, and TYR287) were critical for its inhibition of MCR-1 activity. Additionally, we also demonstrated that the CheA of chemosensory system and virulence-related protein SpvD were critical for the bacteriostatic synergistic effects of the triple combination. Selectively targeting CheA, SpvD or MCR using the natural compound AS could be further investigated as an attractive strategy for treatment of Salmonella infection. Collectively, our work opens new avenues towards the potentiation of COL and revealed an alternative drug combination strategy to overcome COL resistant bacterial infections.

microbiology↗

bioRxiv2024

VGLL2 and TEAD1 fusion proteins drive YAP/TAZ-independent transcription and tumorigenesis by engaging p300

Studies on Hippo pathway regulation of tumorigenesis largely center on YAP and TAZ, the transcriptional co-regulators of TEAD. Here, we present an oncogenic mechanism involving VGLL and TEAD fusions that is Hippo pathway-related but YAP/TAZ-independent. We characterize two recurrent fusions, VGLL2-NCOA2 and TEAD1-NCOA2, recently identified in spindle cell rhabdomyosarcoma. We demonstrate that in contrast to VGLL2 and TEAD1, the fusion proteins are strong activators of TEAD-dependent transcription, and their function does not require YAP/TAZ. Furthermore, we identify that VGLL2 and TEAD1 fusions engage specific epigenetic regulation by recruiting histone acetyltransferase p300 to control TEAD-mediated transcriptional and epigenetic landscapes. We showed that small molecule p300 inhibition can suppress fusion proteins-induced oncogenic transformation both in vitro and in vivo. Overall, our study reveals a molecular basis for VGLL involvement in cancer and provides a framework for targeting tumors carrying VGLL, TEAD, or NCOA translocations.

cancer biology↗