Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 451 records · Page 25Linked to original sources

bioRxiv2024

Platelet Factor 4 (PF4) Regulates Hematopoietic Stem Cell Aging

Hematopoietic stem cells (HSCs) responsible for blood cell production and their bone marrow regulatory niches undergo age-related changes, impacting immune responses and predisposing individuals to hematologic malignancies. Here, we show that the age-related alterations of the megakaryocytic niche and associated downregulation of Platelet Factor 4 (PF4) are pivotal mechanisms driving HSC aging. PF4-deficient mice display several phenotypes reminiscent of accelerated HSC aging, including lymphopenia, increased myeloid output, and DNA damage, mimicking physiologically aged HSCs. Remarkably, recombinant PF4 administration restored old HSCs to youthful functional phenotypes characterized by improved cell polarity, reduced DNA damage, enhanced in vivo reconstitution capacity, and balanced lineage output. Mechanistically, we identified LDLR and CXCR3 as the HSC receptors transmitting the PF4 signal, with double knockout mice showing exacerbated HSC aging phenotypes similar to PF4-deficient mice. Furthermore, human HSCs across various age groups also respond to the youthful PF4 signaling, highlighting its potential for rejuvenating aged hematopoietic systems. These findings pave the way for targeted therapies aimed at reversing age-related HSC decline with potential implications in the prevention or improvement of the course of age-related hematopoietic diseases. Key PointsO_LIAge-related attrition of the megakaryocytic niche and associated PF4 downregulation is a central mechanism in HSC aging. C_LIO_LIPF4 supplementation, acting on LDLR and CXCR3 receptors, rejuvenates the function of aged HSCs. C_LI

cell biology↗

bioRxiv2024

Towards robust machine olfaction: debiasing GC-MS data enhances prostate cancer diagnosis from urine volatiles

Prostate cancer (PCa) is a major, and increasingly global, health concern with current screening and diagnostic tools severe limitations causing unnecessary, invasive biopsy procedures. While gas chromatography-mass spectrometry (GC-MS) has been used to detect urinary volatile organic compounds (VOCs) associated with PCa, efforts to identify consistent molecular biomarkers have failed to generalize across studies. Inspired by the olfactory diagnostic capabilities of medical detection dogs, we do not reduce chromatograms to a list of compounds and concentrations. Instead, we deploy a machine learning approach that bypasses molecular identification: PCa "scent character" signatures are extracted from raw time series data transformed into image representations for classification via convolutional neural networks. To address confounding factors such as sample-source bias, we implement a multi-step pre-processing and debiasing pipeline, including empirical Bayes correction, baseline drift removal, and domain adversarial learning. The resulting model achieves classification performance on par with similarly trained canines, achieving a recall of 88% and an F1-score of 0.78. These findings demonstrate that, at least in the context of PCa detection from urine, machine learning-based scent signature analysis can serve as a fully non-invasive diagnostic alternative, with these early results being also relevant to the wider emergent field of medical machine olfaction.

cancer biology↗

bioRxiv2024

CellPatch: a Highly Efficient Foundation Model for Single-Cell Transcriptomics with Heuristic Patching

The rapid advancement of foundation models has significantly enhanced the analysis of single-cell omics data, enabling researchers to gain deeper insights into the complex interactions between cells and genes across diverse tissues. However, existing foundation models often exhibit excessive complexity, hindering their practical utility for downstream tasks. Here, we present CellPatch, a lightweight foundation model that leverages the strengths of the cross-attention mechanism and patch tokenization to reduce model complexity while extracting efficient biological representations. Comprehensive evaluations conducted on single-cell RNA-sequencing datasets across multiple organs and tissue states demonstrate that CellPatch achieves state-of-the-art performance in downstream analytical tasks while maintaining ultra-low computational costs during both pretraining and finetuning phases. Moreover, the flexibility and scalability of CellPatch allow it to serve as a general framework that can be incorporated with other well established single-cell analysis software, thereby enhancing their performance through transfer learning on diverse downstream tasks.

bioinformatics↗

bioRxiv2024

Mapping Pesticide-Induced Metabolic Alterations in Human Gut Bacteria

Pesticides can modulate gut microbiota (GM) composition, but their specific effects on GM remain largely elusive. Our study demonstrated that pesticides inhibit or promote growth in various GM species, even at low concentrations, and can accumulate in GM to prolong their presence in the host. Meanwhile, the pesticide induced changes in GM composition are associated with significant alterations in gut bacterial metabolism that reflected by the changes of hundreds of metabolites. We generated a pesticide-GM-metabolites (PMM) network that not only reveals pesticide-sensitive gut bacteria species but also report specific metabolic changes in 306 pesticide-GM pairs (PGPs). Using an in vivo mice model, we further demonstrated a PGPs interactions and verified the inflammation-inducing effects of pesticides on the host through dysregulated lipid metabolism of microbes. Taken together, our findings generate a PMM interactions atlas, and shed light on the molecular level of how pesticides impact host health by modulating GM metabolism. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/623895v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@17ed5f5org.highwire.dtl.DTLVardef@10d3e0org.highwire.dtl.DTLVardef@c61b43org.highwire.dtl.DTLVardef@27d035_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

scCompass: An integrated cross-species scRNA-seq database for AI-ready

Emerging single-cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single-cell resolution. Advances in artificial intelligence enhance life sciences research by delivering critical insights and optimizing data analysis processes. However, inconsistent data processing quality and standards remain to be a major challenge. Here we propose scCompass, which provides a data quality solution to build a large-scale, cross-species and model-friendly single-cell data collection. By applying standardized data pre-processing, scCompass integrates and curates transcriptomic data from 13 species and nearly 105 million single cells. Using this extensive dataset, we are able to archieve stable expression genes (SEGs) and organ-specific expression genes (OSGs) in human and mouse. We provide different scalable datasets that can be easily adapted for AI model training and the pretrained checkpoints with state-of-the-art (SOTA) single-cell foundataion models. In summary, the AI-readiness of scCompass, which combined with user-friendly data sharing, visualization and online analysis, greatly simplifies data access and exploitation for researchers in single cell biology(http://www.bdbe.cn/kun).

bioinformatics↗

bioRxiv2024

Phosphorylation of MdWRKY70L by MdMPK6/02G mediates reactive oxygen synthesis to regulate apple fruit senescence

Apple (Malus domestica) is a globally significant crop and a vital dietary component worldwide. During ripening, apples exhibit a longitudinal gradient, ripening first at the stalk cavity and extending toward the calyx pit. Over-ripening in the stalk cavity leads to early senescence, characterized by peel browning, which diminishes fruit quality. This study examines the natural senescence process in 6-year-old Ruixue apples by screening transcriptome data to uncover senescence-related genes and validate their molecular functions. Our analysis of antioxidant capacity and reactive oxygen species in different peel regions revealed that malondialdehyde, hydrogen peroxide, and superoxide anion levels increased with senescence, especially in the stalk cavity. Transcriptome clustering and enrichment analyses across developmental stages revealed MdWRKY70L, MdSAG101, and MdZAT12 as key regulators of peel senescence. Further in vitro and in vivo studies demonstrated that MdWRKY70L is phosphorylated at Ser199 by MdMPK6/02G, enhancing its stability and promoting peel senescence. These findings offer insights for developing strategies to delay fruit senescence and improve postharvest quality control.

plant biology↗

bioRxiv2024

AlphaFold-Metainference: Prediction of Structural Ensembles of Disordered Proteins

Deep learning methods of predicting protein structures have reached an accuracy comparable to that of high-resolution experimental methods. It is thus possible to generate accurate models of the native states of hundreds of millions of proteins. An open question, however, concerns whether these advances can be translated to disordered proteins, which should be represented as structural ensembles because of their heterogeneous and dynamical nature. To address this problem, we introduce the AlphaFold-Metainference method to use AlphaFold-derived distances as structural restraints in molecular dynamics simulations to construct structural ensembles of ordered and disordered proteins. The results obtained using AlphaFold-Metainference illustrate the possibility of making predictions of the conformational properties of disordered proteins using deep learning methods trained on the large structural databases available for folded proteins.

biophysics↗

bioRxiv2024

Machine learning reveals novel targets for both glioblastoma and osteosarcoma

Glioblastoma and osteosarcoma originate from the same lineage, yet patients with these two tumour types show significant differences in survival outcomes. Transcriptomic analysis comparing these tumours reveals that over 65% genes show similar expression patterns. Principal component analysis further demonstrates substantial similarities between these two tumour types, albeit with discernible differences. Deep learning analysis employing an autoencoder unveils nuanced distinctions and similarities of these two tumours at a high resolution. A classification model, leveraging gradient boosting with eXtreme Gradient Boosting (XGBoost), achieves high accuracy in distinguishing between these two tumour types. Identification of key contributors to the models performance is facilitated by SHapley Additive exPlanations (SHAP), yielding two lists of top target genes with and without considering gender. Notably, these SHAP targets tend to cluster within one or two networks of signalling pathways. Remarkably, gene expression levels of many of these SHAP targets alone can recapitulate survival differences solely based on clinical data between glioblastoma and osteosarcoma patients. Of particular interest, C2ORF72 emerges as a common target from both lists, representing an uncharacterised protein with promising potential as a novel target for diagnostic, prognostic, and therapeutic target for both glioblastoma and osteosarcoma.

genomics↗

bioRxiv2024

In vivo engineered quadrivalent CAR-macrophages break tumor barrier,remodel TME and overcome tumor heterogeneity through antigen spreading

CAR-macrophages have shown promising prospect in treating solid tumors. Ex vivo engineered CAR-macrophages face the challenge of low transfection efficiency, long preparation cycle, and limited cell number. Here, we designed two novel CAR molecules, GPC3-CAR-Super IL-2 and FAP-CAR-{bigtriangleup}TGF{beta}RII from the perspective of targeting tumor cells and improving tumor microenvironment, and generated quadrivalent CAR-macrophages in vivo for treating solid tumors by the LNP-mRNA system. We found that in vivo engineered quadrivalent CAR-macrophages can strongly activate tumor immunity and achieve complete tumor regression without significant side effects. Mechanically, in vivo engineered quadrivalent CAR-macrophages broke down physical barriers around the tumor constructed by CAFs and significantly promoted infiltration and expansion of CD8+ T cells. Moreover, the transiently formed CAR-macrophages in vivo are sufficient to form long-lasting T cell memory which can effectively prevent tumor recurrence. Most importantly, in vivo engineered CAR-macrophages also stimulated T cell memory against antigen-negative tumor cells through antigen spreading, which might effectively prevent the immune escape of heterogeneous tumor cells. Overall, we developed a platform of in vivo CAR-macrophages with dual roles as a tumor-killing effector cell and a recurrence-preventing vaccine.

bioengineering↗

bioRxiv2024

ENaC contributes to macrophage dysfunction in cystic fibrosis

BackgroundCystic fibrosis (CF) is a chronic systemic disease caused by dysfunctional or absent cystic fibrosis transmembrane conductance regulator (CFTR). CFTR is expressed in human immune cells and plays a role in regulating innate immunity both directly and indirectly. Besides CFTR, research indicates that the epithelial sodium channel (ENaC) also contributes to dysfunction in CF airway epithelial cells. However, the impact of non-CFTR ion channel dysfunction on CF immune responses is not yet fully understood. A precise understanding of how CF immune function is regulated by ion channels may allow antibiotic-and mutation-agnostic treatment approaches to chronic bacterial infection and inflammation. Therefore, we hypothesized that ENaC is aberrantly expressed in CF macrophages and directly contributes to impaired phagocytic and inflammatory functions. MethodsENaC expression was characterized in human immune cells isolated from CF and non-CF blood donors. Monocyte-derived macrophage (MDM) function and bacterial killing was tested in the setting of ENaC modulation. ResultsBaseline expression of ENaC in human CF MDMs, lymphocytes, and granulocytes was increased at both the transcript and protein level relative to non-CF controls and persisted after exposure to bacteria. Inhibition of CFTR in non-CF MDMs resulted in ENaC overexpression. CFTR modulator treatment reduced but did not eliminate ENaC overexpression in CF MDMs. Interestingly, ENaC inhibition with Amiloride increased CFTR expression. Amiloride-treated CF MDMs also showed normalized ROS production, improved autophagy, and decreased pro-inflammatory cytokine production. Finally, results from an ion channel microarray indicated that sodium channel expression in CF MDMs normalized after Amiloride treatment with minimal effect on other ion channels. DiscussionENaC is overexpressed in CF immune cells and is associated with abnormal macrophage function. ENaC modulation in immune cells is a novel potential therapeutic target for infection control in CF, either in combination with CFTR modulators, or as a sole agent for patients not currently eligible for CFTR modulators.

immunology↗

bioRxiv2024

DeFrND: detergent-free reconstitution into native nanodiscs with designer membrane scaffold peptides

Membrane scaffold proteins-based nanodiscs (NDs) have facilitated unprecedented structural and biophysical analysis of membrane proteins in a near-native lipid environment. However, successful reconstitution of membrane proteins in NDs requires prior solubilization and purification in detergents, which may impact their physiological structure and function. Furthermore, the detergent-mediated reconstitution of NDs is unlikely to recapitulate the precise composition or asymmetry of native membranes. To circumvent this fundamental limitation of traditional ND technology, we herein describe the development of membrane-solubilizing peptides to directly extract membrane proteins from native cell membranes into nanoscale discoids. By systematically protein engineering and screening, we created a new class of chemically modified Apolipoprotein-A1 mimetic peptides to enable the formation of detergent-free NDs (DeFrNDs) with high efficiency. NDs generated with these engineered membrane scaffold peptides are suitable for obtaining high-resolution structures using single-particle cryo-EM with native lipids. To further highlight the versatility of DeFrNDs, we directly extract a sampling of membrane signaling proteins with their surrounding native membranes for biochemical and biophysical interrogations.

biophysics↗

bioRxiv2024

Salt-dependent non-catalytic allostery of human USP14-regulated 26S proteasome

USP14, a deubiquitylating enzyme, regulates 26S proteasome function both catalytically and non-catalytically through multiple checkpoints. How USP14 non-catalytically regulates the proteasome activity remains elusive. Here, we combined genetic engineering and cryo-EM to disentangle how USP14 non-catalytically regulates proteasome activity in a salt-dependent manner. By solving 16 high-resolution cryo-EM structures of substrate-engaged human 26S proteasome complexed with a catalytically deficient mutant USP14, we demonstrate that USP14s non-catalytic activity alone can induce parallel pathways of proteasome state transitions, leading to opposing substrate fates. The USP14 mutant allosterically reprograms the AAA-ATPase motor, inducing novel substrate-engaged conformations and filling major gaps in understanding asymmetric ATP-hydrolysis cycling around the ATPase ring. Time-resolved cryo-EM and functional analysis reveal that sodium or potassium promotes substrate-engaged pathways and suppresses USP14 activity for enhanced degradation, uncovering another layer of complexity in proteasome regulation.

biochemistry↗

bioRxiv2024

Embryonic Mast Cells Arise from Cpa3-expressing Precursors Independent of Granulocyte-Monocyte Progenitors

Most of the mast cells (MCs) in connective tissues, such as skin, are long-lived embryonic-derived immune cells that play important roles in host defense and various immunological diseases, including allergies. Their embryonic origin and ontogeny remain to be fully studied since several overlapping waves of embryonic hematopoiesis have been shown to give rise to these cells. Here, combining single-cell RNA sequencing and new genetic fate mapping models, we identified a Cpa3-expressing population sequentially appearing in the yolk sac, fetal liver, and peripheral tissues which gives rise to dermal MCs during embryonic days 11.5 to 14.5. Using in vitro differentiation and in vivo transplant methods, we identified a Ter119-F4/80- CD45+CD117+CD16/32+CD135-CD115-Ly6C-CD34lo population as potential fetal liver MC precursors. Fate mapping with Cpa3CreERT2and Zbtb16CreERT2 models, as well as the granulocyte-monocyte progenitor (GMP) models Ms4a3Cre and ElaneCre, demonstrated that MCs arise from Cpa3+ progenitors rather than Ms4a3+ or Elane+ GMPs. A corresponding population with a similar developmental trajectory was also identified in human early yolk sac and fetal liver, suggesting a conserved MC developmental program across species. These findings delineate the detailed developmental path of MCs in embryos, permitting future functional studies in immunity and development. HighlightsO_LICpa3-expressing cells in the yolk sac and fetal liver contain mast cell precursors C_LIO_LICpa3CreERT2 labels embryonic mast cells and their precursors C_LIO_LIEmbryonic mast cells arise through Cpa3+ mast cell precursors, but not Elane+/Ms4a3+ GMPs C_LIO_LIThe seeding of MCPs to embryonic skin slows down after E14.5 C_LI

immunology↗

bioRxiv2024

Mechanical stretch induced collective cell alignment

Cell alignment is a fundamental process in tissue morphogenesis. While density-dependent collective cell alignment has been widely observed, its underlying mechanisms remain poorly understood. Here, using C2C12 myoblasts, we demonstrate that static uniaxial mechanical stretch induces collective cell alignment in a density-dependent manner: densely populated cultures align robustly, whereas sparse populations do not. We reveal a biphasic alignment process, comprising an initial passive phase and a subsequent active phase. The passive phase, driven by substrate deformation, transiently biases cell orientation along the stretch axis regardless of density. In the active phase, initial alignment progressively dissipates in low-density cultures, but is sustained and reinforced in high-density cultures. Supported by coarse-grained agent-based simulations, we propose that self-generated cellular forces facilitate kinetic transitions between orientations, enabling cells to explore orientational states, whereas cell-cell interactions provide a thermodynamic bias that stabilizes the locally aligned state. In dense cultures, strong intercellular interactions promote this stabilization, enabling persistent alignment. In contrast, sparse cultures lack sufficient cell-cell interaction, leading to alignment dissipation. Within this C2C12 system, our findings highlight the cooperative roles of cellular forces and intercellular interactions in orchestrating multicellular ordering, offering new insights into mechanobiology of tissue morphogenesis.

bioengineering↗

bioRxiv2024

Cross-Species Analysis Reveals No Universal Programmed Aging Mechanism: Insights from Single-Cell Transcriptomics in Zebrafish, Fruit Fly, and Nematode

The question of whether aging follows a universal programmed process has been a topic of debate for a long time. Previous arguments, either supporting or refuting programmed aging, were mainly based on different evolutionary biology theories. In this study, we analysed single-cell RNA sequencing data from zebrafish, fruit fly, and nematode at various stages of development to explore gene co-expression modules across these species. We successfully identified a co-expression module related to ribosomal protein genes that is shared across the early development stages in multiple tissues of all three species. However, we did not find any cross-species shared gene co-expression modules related to aging. Further analysis of gene regulatory networks (GRNs) demonstrated that although certain aging-related genes are conserved, their regulatory mechanisms vary significantly between species. These findings suggest that aging is not governed by a conserved universal program but rather by species-specific adaptations to damage and environmental conditions.

evolutionary biology↗

bioRxiv2024

Computational Identification of Migrating T cells in Spatial Transcriptomics Data

T cells are the central players in antitumor immunity, and effective tumor killing depends on their ability to infiltrate into the tumor microenvironment (TME) while maintaining normal cytotoxicity. However, late-stage tumors develop immunosuppressive mechanisms that impede T cell movement and induce exhaustion. Investigating T cell migration in human tumors in vivo could provide novel insights into tumor immune escape, although it remains a challenging task. In this study, we developed ReMiTT, a computational method that leverages spatial transcriptomics data to track T cell migration patterns within tumor tissue. Applying ReMiTT to multiple tumor samples, we identified potential migration trails. On these trails, chemokines that promote T-cell trafficking display an increasing trend. Additionally, we identified key genes and pathways enriched on these migration trails, including those involved in cytoskeleton rearrangement, leukocyte chemotaxis, cell adhesion, leukocyte migration, and extracellular matrix (ECM) remodeling. Furthermore, we characterized the phenotypes of T cells along these trails, showing that the migrating T cells are highly proliferative. Our findings introduce a novel approach for studying T cell migration and interactions within the tumor microenvironment (TME), offering valuable insights into tumor-immune dynamics.

bioinformatics↗

bioRxiv2024

α-Synuclein Strain Dynamics Correlate with Cognitive Shifts in Parkinson's Disease

-Synuclein (-syn) strains can serve as discriminators between Parkinsons disease (PD) and related -synucleinopathies. The relationship between -syn strain dynamics and clinical performance as patients transition from normal cognition (NC) to cognitive impairment (CI) is not known. Here, we show that the biophysical properties and neurotoxicity of -syn strains change as PD cognitive status transitions from NC to mild cognitive impairment (PD-MCI) and dementia (PD-D). Both cross-sectional and longitudinal analyses reveal distinct -syn strains in PD patients correlating to their level of cognitive impairment. Machine learning (ML) was employed to achieve high classification accuracy. The combination of thioflavin T (ThT) maximal fluorescence intensity (mfi), max slope of rise curve (forming rate), lag time (tlag), 20% time (t20), and half-time (t50), dynamic light scattering (DLS) (peak number, [1/2] peak size, [1/2] peak intensity) and neurotoxicity together with demographic variables for model training yielded superior performance (89[~]99% accuracy in the 4- and 2- classification schema) compared to individual features alone in classifying cognitive status. For the longitudinal study, DLS peak number emerged as the strongest predictor of cognitive transition (HR = 0.12, P = 0.002), with the optimal predictive model combining DLS peak number, sex, education, DLS peak 1 size, and DLS peak 2 polydispersity achieving high accuracy (C-index of [~]93%). This study presents evidence that individuals with PD have different -syn strains correlating to their cognitive status and highlights the potential of -syn strain dynamics to guide future diagnosis, management, and stratification of PD patients. One Sentence SummaryDistinct features of -syn strains change with cognitive decline in Parkinsons disease and AI-based analysis incorporating these combined characteristics serves as a powerful tool for PD clinical stratification.

neuroscience↗

bioRxiv2024

Mutations of schizophrenia risk gene SETD1A dysregulate synaptic function in human neurons

Schizophrenia (SCZ) is a complex neuropsychiatric disorder associated with both common risk variants of small effect sizes and rare risk variants of high penetrance. Rare protein truncating variants (PTVs) in SETD1A (SET Domain Containing 1A) show a strong association with SCZ; however, it remains largely unclear how rare PTVs in SETD1A contribute to the pathophysiology of SCZ. To understand the impact of SETD1A rare PTVs in human neurons, we CRISPR/Cas9-engineered five isogenic pairs of human induced pluripotent stem cells (iPSCs), with a recurrent heterozygous patient-specific PTV mutation c.4582-2delAG in two donor lines and a heterozygous frameshift mutation c.4596_4597insG (p. Leu1533fs) in three donor lines. These two mutations are predicted to cause a premature stop codon in exon 16 of SETD1A, leading to the loss of the conserved SET domain that is critical for its histone methyltransferase activity. We found that these presumably loss-of-function (LoF) mutations caused the SETD1A mRNAs to be degraded by nonsense-mediated decay (NMD), accompanied by a reduction of full-length SETD1A protein level in iPSCs. We then characterized the morphological, electrophysiological, and transcriptomic impacts of the SETD1A+/- LoF mutations in iPSC-derived human excitatory neurons induced by NGN2. We found that the SETD1A+/- exon-16 LoF mutations altered dendrite complexity, dysregulated synaptic transmission, and synaptic plasticity, likely by dysregulating genes involved in synaptic function. These results provide mechanistic insights into how SETD1A+/-exon-16 patient-specific LoF mutations affect neuron phenotypes that may be relevant to the pathophysiology of SCZ.

neuroscience↗