Biology subjects

Xu, M.

Publications and source records attributed to Xu, M..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Characterizing the Microbiome of 'Sterile' Organs in Experimental Mice

Recent studies have shown that microorganisms can be present in organs or blood traditionally considered sterile, both in healthy and diseased individuals. In this study, we investigated the presence of microorganisms in the "sterile" organs (brain, heart, kidney, liver, lung, and spleen) of commercially available experimental mice using culturomics and metagenomics. To avoid potential environmental contamination, strict disinfection assays were performed. Among 104 mice of the C57BL/6J, BALB/c, and ICR strains purchased from three major experimental animal suppliers in China, 23 mice (22.1%) exhibited a high microbial burden (>1 x 104 CFU/g tissue) in at least one organ, and 42 mice (40.4%) exhibited >1 x 103 CFU/g tissue in at least one organ. In total, 216 microbial species were identified through culturomics. Of them, 56 microbial species were found in the organs of at least three mice of the 42 mice (>1 x 103 CFU/g tissue in at least one organ). Metagenomics analysis of 10 high-burden mice verified the existence of microbes in the mouse organs and identified 262 species. Several species, including Acinetobacter sp., Alcaligenes faecalis, and Ligilactobacillus murinus, were identified as the most abundant microbes across both culturomics and metagenomics assays. 16S FISH staining assays verify the presence of microbes in the mouse organs. Feces Metagenomics analysis and detection of the wide distribution of L. murinus in the mouse mesenteric lymph nodes (MLNs) imply that microbial cells could be translocated from the gut to the MLNs and then to the remote tissues. Together, these findings reveal the presence of non-pathogenic microorganisms in the "sterile" tissues of experimental mice, raising concerns about potential variability in experimental outcomes when using such animals in research.

microbiology↗

bioRxiv2025

De novo design of inducibly assembling multi-component filaments

The design of multi-component nanomaterials is an outstanding challenge. Here, we describe the computational design of protein filaments with two or three distinct structural components that assemble into micron-scale, well-ordered fibers when mixed. CryoEM structure determination of four fiber designs was close to the computational design models. Filament assembly can be initiated by mixing the components, and modulated by addition and/or phosphorylation of designed regulatory subunits. This work demonstrates that regulatable multi-component protein filament systems can now be designed, opening the door to a wide range of engineered materials.

bioengineering↗

bioRxiv2025

Harnessing Uniform Design to Enhance AI-Driven Predictions of Physicochemical Properties of Short Peptides

Short peptides hold significant promise in drug discovery and materials science due to their biocompatibility, multifunctionality, and ease of synthesis. However, accurately predicting their physicochemical properties, a prerequisite for application development, remains a challenge. This study presents an innovative approach integrating uniform design (UD) with artificial intelligence (AI) to enhance prediction of key physicochemical properties, including aggregation propensity (AP), hydrophilicity (logP), and isoelectric point (pI). Using UD, we generate 31 distinct peptide datasets, with a consistent amino acid occupation fraction of 5% at each position, thereby creating unbiased training data for AI models. The performance of each AI model is rigorously evaluated using various testing schemes, and optimal sample sizes are determined for accurate prediction of each property. Additionally, Shapley Additive Explanations (SHAP) analysis identifies aromaticity, logP, net charge, and pI as the primary factors affecting peptide aggregation. This work provides comprehensive datasets on the physicochemical properties of all tetrapeptides, develops robust AI-based predictive models, and elucidates the relationships between key physicochemical characteristics and self-assembly behavior. By integrating experimental design, AI modeling, and peptide domain knowledge, our approach facilitates the discovery and optimization of functional peptides, offering new opportunities for peptide-based therapeutic applications.

bioinformatics↗

bioRxiv2025

Identification of a neural basis for energy expenditure in the arcuate hypothalamus

Given the evolutionary instinct for caloric intake and the tendency for weight rebound after discontinuing dietary interventions or medications, increasing energy expenditure emerges as an alternative obesity treatment. However, neural regulation of energy expenditure remains poorly understood. Here, we report that a hypothalamic neuronal subtype, characterized by Crabp1 expression, establishes connections with multiple hypothalamic nuclei to regulate energy expenditure in mice. Inactivation of Crabp1 neurons reduces physical activity, body temperature, and adaptive thermogenesis, leading to an obese phenotype. Conversely, activation of these neurons increases energy expenditure and mitigates diet-induced obesity. Structural and functional analyses reveal that Crabp1 neurons promote energy metabolism through a "one-to-many" projection pattern. While Crabp1 neurons are rapidly activated by cold exposure and physical activity, prolonged light exposure abrogates their firing and may mediate light-induced metabolic disorder. Together, we reveal a neural basis that integrate various physiological and environmental stimuli to control energy expenditure and body weight.

neuroscience↗

bioRxiv2025

Isl1 Controls Axon Pathfinding of Retinal Ganglion Cells in the Binocular Visual Pathway

Axons of retinal ganglion cells (RGCs) face a choice to project ipsilaterally or contralaterally at the optic chiasm. This decision is crucial for the establishment of binocular vision in mammals. The transcription factor ZIC2 is well known as a key determinant of ipsilateral RGC identity, however the transcriptional programs controlling contralateral RGC identity have only begun to be elucidated more recently. Here we show that inactivation of the LIM-HD transcription factor ISL1 results in an expansion of the ZIC2+ ventrotemporal (VT) domain of the retina and an increase in ipsilateral projections from outside the VT retina. RNA-Seq, gene expression and CUT&Tag analyses show that ISL1 regulates RGC laterality through a set of unique downstream effectors as well as a few common ones, as other transcription factors. Our data also show that RGC axons misrouted at the midline in Isl1-null mutants could innervate the appropriate eye-specific regions of the dorsal lateral geniculate nucleus (dLGN) and superior colliculus (SC), in agreement with earlier studies that have shown that eye specific targeting of visual nuclei in the brain is independent of laterality decisions at the optic chiasm.

neuroscience↗

bioRxiv2025

Macroscopic cerebral energy efficiency corresponds to neuron reorganization in awake and anesthetized mice

Non-invasive imaging of brain function and energy supply is crucial for diagnosing and treating brain disorders. Conventional imaging struggles to capture altered relationships between energy supply and utilization caused by brain diseases. A novel method, which can be translated to human patients, is to calculate relative power (rPWR) and relative cost (rCST) to assess cerebral energy efficiency. However, whether rPWR/rCST can track individual changes and neural activity remains unproven. Our study compared these non-invasive measures with invasive two-photon microscopy in awake and anesthetized mice. We found that rPWR/rCST distributions were similar between awake mice and humans, but changed in anesthetized mice, indicating a shift in the brains economic balance. Furthermore, changes in rPWR/rCST were linked to the reorganization of microscopic neural networks, observed with two-photon microscopy. Our work highlights the potential of rPWR/rCST for medical applications, and that neural network reorganization is linked to the brains economic balance.

neuroscience↗

bioRxiv2025

Mechanistic Insights into the Substrate Egress Pathways of Human Glucose Transporters GLUT1 and GLUT9

Glucose transporters (GLUTs) play critical roles in cellular energy homeostasis and substrate-specific transport. Dysfunctional mutations can cause GLUT1 deficiency syndrome and excessive expression of GLUT1 is linked to cancer progression; while abnormal regulation of urate transport by GLUT9 is associated with hyperuricemia and gout. In this study, machine-learning driven molecular dynamics simulations have been employed to investigate the mechanistic insights into the substrate egress pathways of GLUT1 and GLUT9, including the inhibition mechanism of GLUT9 by apigenin. Our findings reveal that intracellular helices play a crucial role in facilitating the transition from inward-closed to inward-open conformations in both transporters. Additionally, aromatic residues, F291 and W388 in GLUT1, and W336 and F435 in GLUT9, are identified as key mediators of conformational changes. Analysis of substrate exit pathways provides mechanistic insights into transport profiles and aligns with clinically observed mutations. Furthermore, the inhibitory effect of apigenin on GLUT9 is shown to arise from steric hindrance due to increased substrate size, rather than stable interactions. These findings enhance our understanding of GLUT transporter dynamics and highlight the potential of targeting substrate pathways for therapeutic intervention.

biophysics↗

bioRxiv2025

A single amino acid variant in the variable region I of AAV capsid confers liver detargeting

AAV capsid serotypes isolated from nature have been widely used in gene delivery and gene therapy. Recently, more than 1,000 distinct AAV capsids were identified from human clinical samples by high-throughput, long-read DNA sequencing. In this study, we tap into this broad natural biodiversity of AAV capsids to develop liver-tropic AAV capsids. We initially screened a subset of variants derived from AAV8 (n=159) for packaging efficiency. The high-yielding variants were subjected to a barcoded vector library screen in mice and ferrets for their ability to mediate liver gene transfer. Although no variant surpassed AAV8 for liver targeting, several exhibited a liver detargeting phenotype. Among these, we focused on the N271D variant (AAV8 VP1 numbering), located in the variable region I (VR-1), which has been previously implicated in influencing liver tropism. The liver detargeting phenotype of AAV8.N271D was confirmed by single vector administration in mice. Additionally, we grafted the N271D variant onto AAV9 and MyoAAV capsids (N270D by AAV9 VP1 numbering). The AAV9.N270D and MyoAAV.N270D vectors showed a similar liver-detargeting phenotype, although muscle targeting was moderately reduced. Although we did not identify any capsid variants that outperform AAV8 in liver transduction, this study reinforces the important role of VR-1 in modulating liver tropism and highlights the potential of engineering VR-1 residues to reduce liver gene transfer and associated toxicity observed in several gene therapy studies.

molecular biology↗

bioRxiv2025

Revealing Functional Hotspots: Temperature-Dependent Crystallography of K-RAS Highlights Allosteric and Druggable Sites

K-RAS mutations drive oncogenesis in multiple cancers, yet the lack of druggable sites has long hindered therapeutic development. Here, we use multi-temperature X-ray crystallography (MT-XRC) to capture functionally relevant K-RAS conformations across a temperature gradient, spanning cryogenic to physiological and even "fever" conditions, and show how cryogenic conditions may obscure key dynamic states as targets for new drug development. This approach revealed a temperature-dependent conformational landscape of K-RAS, shedding light on the dynamic nature of key regions. We identified significant conformational changes occurring at critical sites, including known allosteric and drug-binding pockets, which were hidden under cryogenic conditions but later discovered to be critically important for drug-protein interactions and inhibitor design. These structural changes align with regions previously highlighted by large-scale mutational studies as functionally significant. However, our MT-XRC analysis provides precise structural snapshots, capturing the exact conformations of these potentially important allosteric sites in unprecedented detail. Our findings underscore the necessity of advancing tools like MT-XRC to visualize conformational transitions that may be important in signal propagation which are missed by standard cryogenic XRC and to address hard-to-drug targets through rational drug design. This approach not only provides unique structural insights into K-RAS signaling events and identifies new potential sites to target with drug candidates but also establishes a powerful framework for discovering therapeutic opportunities against other challenging drug targets.

biochemistry↗

bioRxiv2025

Viral Infection Detector: Ensemble Learning for Predicting Viral Infection in Single-cell Transcriptomics of Virus-Induced Cancers

Oncoviruses cause around 15-20% of all human cancers. As 3 end-based single-cell RNA-sequencing (scRNA-seq) methods become more popular, the relationship between viral infection and tumor progression at the transcriptomic level has been increasingly studied at single-cell resolution. However, the identification of infected cells is challenging as viral reads from infected cells may not be captured, leading to high false negative rates. To recover these infected cells that have been missed, we developed VID, a stacked ensemble machine-learning model that predicts virus-infected cells in scRNA-seq datasets. Using VID, we uncovered biologically meaningful differences between infected and uninfected cells across different oncovirus-mediated cancers and different cell types. Our VID tool provides a user-friendly way to study changes induced by viral infections in scRNA-seq datasets.

bioinformatics↗

bioRxiv2025

panHiTE: a comprehensive and accurate pipeline for TE detection in large-scale population genomes

Transposable elements (TEs) are key drivers of genomic variation and species evolution. Advances in high-throughput sequencing have enabled whole-genome sequencing of individuals or subspecies, facilitating the identification of population-specific variations. Detecting population-specific TE insertions at scale is crucial for understanding species-specific phenotypic traits. However, tools for constructing comprehensive pan-TE databases remain limited. To address this gap, we develop panHiTE, a population-scale TE detection and annotation tool with several core innovations. panHiTE features a deep learning-based long terminal repeat retrotransposon (LTR-RT) detection algorithm, outperforming existing tools in both sensitivity and precision. It also introduces a novel de-redundancy algorithm, which eliminates highly divergent redundant TE instances, significantly reducing the size of the TE library. Additionally, panHiTE can detect low-copy TEs, which are overlooked in individual genome analyses and absent from existing databases due to their rarity. Furthermore, panHiTE allows for TE-gene association analysis, enabling comprehensive insights into TE-driven phenotypic variation. panHiTE, powered by a Nextflow pipeline, enables efficient and scalable TE detection in large plant genomes and has successfully been applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.

genomics↗

bioRxiv2025

Brucella proline racemase protein A targets Tpl2 to promote IL-10 secretion for establishment of chronic infection

IL-10, an anti-inflammatory cytokine, plays a crucial role in limiting immune responses to pathogens, preventing host damage. However, the mechanisms underlying Brucella-mediated IL- 10 production remain incompletely understood. In this study, we demonstrate that the proline racemase protein A (PrpA) of Brucella melitensis M5-90 induces macrophages to secrete IL-10 by activating the Tpl2-ERK signaling pathway, thereby promoting chronic infection. Moreover, Tpl2 deletion impairs macrophage bactericidal ability, accompanied by reduced TNF- and IL-1{beta} but unaffected IL-10 levels. Additionally, Trp309, Glu103, and Glu129 of PrpA participate in interaction with Tpl2, but these residues do not influence PrpA-mediated IL-10 production in macrophages. PrpA deletion enhances IFN-{gamma} levels, specific anti-Brucella IgG, and CD4+ and CD8+ T cell numbers in mice. Furthermore, the Brucella melitensis M5-90 prpA mutant provides higher protection than the parental strain against virulent Brucella melitensis M28 infection in mice. Our findings suggest that Brucella PrpA promotes IL-10 secretion by macrophages through Tpl2 activation for bacterial survival and persistent infection, making the Brucella melitensis M5-90 prpA mutant a promising vaccine for enhanced protection. Author SummaryIL-10, an anti-inflammatory cytokine, is exploited by Brucella for survival. We identified Brucella PrpA as a potent IL-10 inducer, activating the Tpl2-ERK signaling pathway. Tpl2 deletion increased Brucella survival in macrophages, accompanied by reduced TNF- and IL-1{beta} but unaffected IL-10 secretion. Residues (Trp309, Glu103, and Glu129) of PrpA were crucial for interaction with Tpl2, yet did not impact PrpA-mediated IL-10 production. The B. melitensis M5-90 prpA mutant induced higher anti-Brucella IgG, IFN-{gamma}, and CD4+ and CD8+ T cell numbers in mice, providing better protection than B. melitensis M5-90. These findings unveil PrpAs role in IL-10 production and highlight the potential of the B. melitensis M5-90 prpA mutant as a promising vaccine for further evaluation.

microbiology↗

bioRxiv2024

Elucidation of gene clusters underlying withanolide biosynthesis in ashwagandha through yeast metabolic engineering

Withanolides are medicinally relevant steroidal lactones produced by Withania somnifera (ashwagandha) amongst other Solanaceae family plants. However, the biosynthetic pathway to withanolides is largely unknown, preventing scale-up and hindering pharmaceutical applications. We sequenced the genome of W. somnifera and identified two biosynthetic gene clusters exhibiting a segmented tissue-specific expression pattern. We characterized the cluster enzymes through stepwise pathway reconstitution in yeast and transient expression in Nicotiana benthamiana, leading to the identification of three cytochrome P450s (CYP87G1, CYP88C7, and CYP749B2) and a short-chain dehydrogenase that produce a lactone ring- containing intermediate when co-expressed. A fourth cytochrome P450 (CYP88C10) and a sulfotransferase convert this into an intermediate with the characteristic withanolide A-ring structure, featuring a C1 ketone and C2-C3 unsaturation. The discovery of the sulfotransferase as a core pathway enzyme challenges the conventional paradigm of sulfotransferases as tailoring enzymes. These insights pave the way for an efficient biomanufacturing process for withanolides and future development of withanolide-derived drugs.

biochemistry↗

bioRxiv2024

Potential mechanisms and effects of melatonin-regulated Nrf2/HO-1 pathway on acute lung injury due to formaldehyde exposure

Acute lung injury is a topic of great interest in critical care medicine due to its high mortality rates. The lungs are the immediate target organ for formaldehyde inhalation damage. Lung damage and fibrosis are the most important outcomes of severe and acute lung disease and pose a serious threat to human health. Melatonin (MT), a natural bioactive compound with anti-inflammatory and antioxidant properties, However, it is not clear whether MT can prevent FA-induced acute lung injury (ALI). Therefore, in this study, we aimed to evaluate the protective effects of MT and the potential mechanisms against FA-induced ALI. An environmental exposure bin was used to inhale 3 mg{middle dot}m3 FA-induced ALI, which was given intraperitoneally with different doses of MT (5/10/20 mg/kg) after successful modeling. In addition, rats were treated with Nrf2 inhibitor (ML385) to validate the signaling pathway. Lung function was measured, histopathological/morphological changes in lung tissue were assessed, and inflammatory expression and oxidation levels in lung tissue were detected. We observed that MT greatly alleviated the lung dysfunction, pathological lung injury, pulmonary edema and inflammatory response after successful modeling of FA. In additional, MT played a role in modulating the Nrf2/HO-1 signaling pathway, which effectively inhibit oxidative stress caused by FA-induced lung tissue injure. Moreover, we found that activation of the NF-{kappa}B pathway is associated with inflammation caused by this injury. Overall, our data suggest that MT inhibits the expression of oxidative stress and inflammation in lung tissue through the institutional or Nrf2/HO-1 pathway, alleviating FA-induced ALI.

developmental biology↗

bioRxiv2024

E-box independent chromatin recruitment turns MYOD into a transcriptional repressor

MYOD is an E-box sequence-specific basic Helix-Loop-Helix (bHLH) transcriptional activator that, when expressed in non-muscle cells, induces nuclear reprogramming toward skeletal myogenesis by promoting chromatin accessibility at previously silent loci. Here, we report on the identification of a previously unrecognized property of MYOD as repressor of gene expression, via E-box-independent chromatin binding within accessible genomic elements, which invariably leads to reduced chromatin accessibility. MYOD-mediated repression requires the integrity of functional domains previously implicated in MYOD-mediated activation of gene expression. Repression of mitogen-and growth factor-responsive genes occurs through promoter binding and requires a highly conserved domain within the first helix. Repression of cell-of-origin/alternative lineage genes occurs via binding and decommissioning of distal regulatory elements, such as super-enhancers (SE), which requires the N-terminal activation domain as well as two chromatin-remodeling domains and leads to reduced strength of CTCF-mediated chromatin interactions. Surprisingly, MYOD-mediated chromatin compaction and repression of transcription do not associate with reduction of H3K27ac, the conventional histone mark of enhancer or promoter activation, but with reduced levels of the recently discovered histone H4 acetyl-methyl lysine modification (Kacme). These results extend MYOD biological properties beyond the current dogma that restricts MYOD function to a monotone transcriptional activator and reveal a previously unrecognized functional versatility arising from an alternative chromatin recruitment through E-box or non-E-box sequences. The E-box independent repression of gene expression by MYOD might provide a promiscuous mechanism to reduce chromatin accessibility and repress cell-of-origin/alternative lineage and growth factor/mitogen-responsive genes to safeguard the integrity of cell identity during muscle progenitor commitment toward the myogenic lineage.

molecular biology↗

bioRxiv2024

TomoPicker: Annotation-Efficient Particle Picking in cryo-electron Tomograms

MotivationLocalizing macromolecules in crowded cellular cryo-electron tomograms (cryo-ET) is crucial for determining their in situ structures. Traditional template matching-based approaches for this task suffer from template-specific biases and have low throughput. Given these problems, learning-based solutions are necessary. However, the paucity of annotated data for training poses substantial challenges for such learning-based methods. Moreover, preparing extensively annotated cellular cryo-ET tomograms for training macromolecule localization methods is extremely time-consuming and burdensome due to the large volume and low signal-to-noise ratio of the tomograms. ResultsIn this work, we developed TomoPicker, an annotation-efficient macromolecule localization method for cryo-ET tomograms. To achieve such annotation-efficiency, TomoPicker regards macromolecule localization as a voxel classification problem and solves it with two different positive-unlabeled learning approaches. We evaluated TomoPicker on two experimental cryo-electron tomography (cryo-ET) datasets of crowded eukaryotic cells and one experimental dataset of relatively less crowded prokaryotic cell. We observed that, with only 10 annotated macromolecule locations, TomoPicker with positive unlabeled learning achieved a performance comparable to that of state-of-the-art supervised methods trained with several hundred annotations. In other words, TomoPicker achieved plausible segmentation with up to 98% less data compared to supervised learning-based methods. Furthermore, it demonstrated substantial improvements over existing learning-based macromolecule localization methods under sparse annotation scenarios. CodeThe code to train and use TomoPicker is available on https://github.com/DuranRafid/TomoPicker.

bioinformatics↗

bioRxiv2024

Discovery of A Chimeric Polyketide Family as Cancer Immunogenic Chemotherapeutic Leads

Discovery of cancer immunogenic chemotherapeutics represents an emerging, highly promising direction for cancer treatment that uses a chemical drug to achieve the efficacy of both chemotherapy and immunotherapy. Herein we report a high-throughput screening platform and the subsequent discovery of a new class of cancer immunogenic chemotherapeutic leads. Our platform integrates informatics-based activity metabolomics for rapid identification of microbial natural products with both novel structures and potent activities. Additionally, we demonstrate the use of microcrystal electron diffraction (MicroED) for direct structure elucidation of the lead compounds from partially purified mixtures. Using this strategy to screen geographically and phylogenetically diverse microbial metabolites against pseudomyxoma peritonei, a rare and severe cancer, we discovered a new class of leads, aspercyclicins. The aspercyclicins feature an unprecedented tightly packed polycyclic polyketide scaffold that comprises continuous fused, bridged, and spiro rings. The biogenesis of aspercyclicins involves two distinct biosynthetic pathways, leading to formation of chimeric compounds that cannot be predicted by bottom-up approaches mining natural products biosynthetic genes. With comparable potency to some clinically used anticancer drugs, aspercyclicins are active against multiple cancer cell types by inducing immunogenic cell death (ICD), including the release of damage-associated molecular patterns and subsequent phagocytosis of cancer cells. The broad-spectrum ICD-inducing activity of aspercyclicins, combined with their low toxicity to normal cells, represents a new class of potential cancer immunogenic chemotherapeutics and particularly the first drug lead for pseudomyxoma peritonei treatment.

biochemistry↗

bioRxiv2024

Functionally Important Residues from Graph Analysis of Coevolved Dynamic couplings

The relationship between protein dynamics and function is essential for understanding biological processes and developing effective therapeutics. Functional sites within proteins are critical for activities such as substrate binding, catalysis, and structural changes. Existing computational methods for the predictions of functional residues are trained on sequence, structural and experimental data, but they do not explicitly model the influence of evolution on protein dynamics. This overlooked contribution is essential as it is known that evolution can fine tune protein dynamics through compensatory mutations, either to improve the proteins performance or diversify its function while maintaining the same structural scaffold. To model this critical contribution, we introduce DyNoPy, a computational method that combines residue coevolution analysis with molecular dynamics (MD) simulations, revealing hidden correlations between functional sites. DyNoPy constructs a graph model of residue-residue interactions, identifies communities of key residue groups and annotates critical sites based on their roles. By leveraging the concept of coevolved dynamical couplings--residue pairs with critical dynamical interactions that have been preserved during evolution--DyNoPy offers a powerful method for predicting and analysing protein evolution and dynamics. We demonstrate the effectiveness of DyNoPy on SHV-1 and PDC-3, chromosomally encoded {beta}-lactamases linked to antibiotic resistance, highlighting its potential to inform drug design and address pressing healthcare challenges.

evolutionary biology↗