Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 523 records · Page 29Linked to original sources

bioRxiv2024

Isolation and characterization of microbiota from human pancreatic tumors and small intestine

Pancreatic ductal adenocarcinoma has a unique tumor microbiome and the systemic depletion of bacteria or fungi using antibiotic/antifungal cocktails leads to a decrease in pancreatic tumor burden in mice. However, functional studies remain rare due to the limited availability of clinically relevant microbiota. Here, we describe in detail the isolation of bacteria and fungi from the small intestine and tumor of pancreatic cancer patients at the Rogel Cancer Center. We then further characterized the impact of a newly isolated Klebsiella oxytoca strain (UMKO1) on the pancreatic tumor microenvironment using bacterial genome sequencing, untargeted and targeted metabolomics, as well as an ex vivo tumor transplant system. We found that UMKO1 possesses a gene for the long form of cytidine deaminase, which can inactivate the standard PDAC chemotherapeutic agent gemcitabine. In addition, we found that UMKO1 can produce several indoles when grown in tumor-like conditions, metabolites that can lead to an immune suppressive environment and interfere with therapy outcome. To test this in detail, we assessed changes in immune populations in pancreatic tumor explants upon exposure to the supernatant of UMKO1 and other isolated bacteria grown in tumor Interstitial fluid media (TIFM). We found that while none of the bacterial supernatants changed the abundance of CD8 T cells, granzyme B positive CD8 T cells were the lowest in tumor explants exposed to UMKO1, and not other isolated Klebsiella species or the non-pathogenic laboratory strain E. coli K12. In summary, the isolated collection of bacteria and fungi from this study are a valuable toolbox to study the impact of microbiota on pancreatic cancer.

cancer biology↗

bioRxiv2024

Constructing a holistic map of cell fate decision by hyper solution landscape

The Waddington landscape metaphor has inspired extensive quantitative studies of cell fate decisions using dynamical systems. While these approaches provide valuable insights, the intrinsic nonlinear complexity and the parameter dependence limits systematic analysis of fate transitions. Here, we introduce the Hyper Solution Landscape (HSL), a minimally parameter-dependent methodology showing a comprehensive structure of all possible landscape configurations for gene regulatory networks. HSL connects different solution landscapes to reflect dynamic changes of the landscapes associated with bifurcations. Applied to the Cross-Inhibition with Self-activation motif, HSL analysis identifies key hyperparameters driving distinct directional changes in cell fate propensity. Different routes through the HSL between the same initial and final states can produce markedly different fate distributions. This enables rational design of transition strategies. We validate HSLs utility in the seesaw model of cellular reprogramming, establishing a powerful framework for understanding and engineering cell fate decisions. A record of this papers Transparent Peer Review process is included in the Supplemental Information.

systems biology↗

bioRxiv2024

A signal of temporal integration in the human auditory brain: psychological insights, EEG evidence, and clinical application

Temporal integration, the process by which the auditory system combines sound information over a curtain period to form a coherent auditory object, is essential for coherent auditory perception, yet its neural mechanisms remain underexplored. We use a "transitional click train" paradigm, which concatenates two click trains with slightly differing inter-click intervals (ICIs), to investigate temporal integration in the human cortex. Using a 64-channel electroencephalogram (EEG), we recorded responses from 42 healthy participants exposed to regular and irregular transitional click trains and conducted change detection tasks. Regular transitional click trains elicited significant change responses in the human cortex, indicative of temporal integration, whereas irregular trains did not. These neural responses were modulated by ICI length, ICI contrast, and regularity. Behavioral data mirrored EEG findings, showing enhanced detection for regular conditions compared to irregular conditions and pure tones. Furthermore, variations in change responses were associated with decision-making processes. Temporal continuity was critical, as introducing gaps between click trains diminished both behavioral and neural responses. In clinical assessments, 22 coma patients exhibited diminished or absent change responses, effectively distinguishing them from healthy individuals. Our findings identify distinct neural markers of temporal integration and highlight the potential of transitional click trains for clinical diagnostics.

neuroscience↗

bioRxiv2024

Enalapril mitigates aging by targeting antioxidative genes via phosphorylated Smad1/5/9

Aging increases the risk of a myriad of chronic diseases, which are expensive and difficult to treat owing to their various risk factors. Repurposing existing medications has accelerated the development of therapies aimed at slowing aging. In this study, we revealed that enalapril, a drug widely prescribed for hypertension, can improve both cellular senescence and individual health. Mechanistically, phosphorylated Smad1/5/9 act as pivotal mediators of the anti-senescence properties of enalapril. It stimulates downstream genes involved in cell cycle regulation and antioxidative defense, facilitating cell proliferation and diminishing the production of reactive oxygen species (ROS), thus increasing the antioxidative ability of enalapril. At the organismal level, enalapril has been shown to bolster the physiological performance of various organs; it notably enhances memory capacity and renal function and relieves lipid accumulation. Our work highlights the potential of enalapril to augment antioxidant defenses and combat the effects of aging, thereby indicating its promise as a treatment strategy for aging-associated diseases and its use for healthy aging.

cell biology↗

bioRxiv2024

Sirt5 preserves cardiac function in ischemia-reperfusion injury by inhibiting ANT2 lactylation

Myocardial ischemia-reperfusion (IR) injury is the most common type of heart disease. IR-disrupted mitochondrial homeostasis affects heart energy metabolism and function, but the mechanism remains poorly understood. Here we report a cardioprotective role of the mitochondrial protein Sirt5 in a mouse model of cardiac IR injury. The down-regulation of Sirt5 in IR-injured heart is associated with an increased protein lactylation and impaired mitochondrial function. Overexpression of Sirt5 alleviates, whereas conditional knockout of Sirt5 aggravates, mitochondrial damage and cardiac injury. Mechanistically, Sirt5 interacts with the inner mitochondrial membrane protein adenine nucleotide translocase 2 (ANT2), inhibiting its lysine lactylation to promote its association with the outer mitochondrial membrane protein voltage-dependent anion-selective channel 1 (VDAC1). Lactylation-resistant ANT2 efficiently complexes with VDAC1 and improves cardiac function after injury. Therefore, we uncover a Sirt5-regulated interaction of ANT2 and VDAC1 in maintaining mitochondrial homeostasis, highlighting the potential of targeting ANT2 lactylation as a therapeutic strategy in the treatment of cardiac injury. TeaserSirt5 promotes the interaction of mitochondrial proteins to protect mitochondrial homeostasis and improve heart function in ischemia-reperfusion injury.

pathology↗

bioRxiv2024

UniversalEPI: Harnessing Attention Mechanisms to Decode Chromatin Interactions in Rare and Unexplored Cell Types

Enhancer-promoter interactions (EPIs) play a central role in gene regulation, but experimental techniques such as Hi-C for mapping these interactions remain costly and labor-intensive. Computational methods have been developed to predict EPIs in silico from DNA sequence and chromatin information; however, there are major challenges with the generalizability and accuracy of predictions by existing methods across cell types and conditions unseen during model training. We developed and validated UniversalEPI, an attention-based deep ensemble model that predicts EPIs up to 2 Mb apart using only DNA sequence and chromatin accessibility (ATAC-seq) data. Unlike models that reconstruct full Hi-C contact maps, UniversalEPI focuses on biologically relevant, sparse chromatin interactions between accessible regulatory elements. It generalizes across both bulk and single-cell ATAC-seq-derived pseudo-bulk datasets, delivering state-of-the-art performance while using fewer input modalities than existing approaches. By modeling predictive uncertainty, UniversalEPI enables statistically robust differential analysis of chromatin interactions across conditions. We demonstrate its utility by tracking dynamic EPIs during human macrophage activation and identifying regulatory differences between cancer cell states in esophageal adenocarcinoma. By providing precalculated Hi-C predictions for 157 ENCODE datasets, UniversalEPI expands the scope and applicability of in silico 3D genome modeling for studying gene regulation in development and disease.

genomics↗

bioRxiv2024

Versatile Stain Transfer in Histopathology Using a Unified Diffusion Framework

Histological staining is vital in clinical pathology for visualizing tissue structures. However, these techniques are laborious and time-consuming. Digital virtual staining offers a promising solution, but existing methods typically rely on Generative Adversarial Networks (GANs), which may suffer from artifacts and mode collapse. Motivated by the success of diffusion models, we present DUST, a novel Diffusion-based Unified framework for versatile Stain Transfer in histopathology. To enhance domain awareness and task-specific performance, we propose a dual encoding strategy that integrates the stain types of both the source and target domains. Additionally, we introduce a dynamic dual-output head to address the unstable intensity issue encountered with conventional DDPM implementations. Validated on a curated fourstain kidney histopathological dataset (H&E, MT, PAS, and PASM), DUST demonstrates superior versatile stain transfer capabilities. Our research highlights the potential of diffusion models to advance virtual staining, paving the way for more efficient digital pathology analyses.

pathology↗

bioRxiv2024

Reciprocal links between methionine metabolism, DNA repair and therapy resistance in glioblastoma

Glioblastoma (GBM) is uniformly lethal due to profound treatment resistance. Altered cellular metabolism is a key mediator of GBM treatment resistance. Uptake of the essential sulfur-containing amino acid methionine is drastically elevated in GBMs compared to normal cells, however, it is not known how this methionine is utilized or whether it relates to GBM treatment resistance. Here, we find that radiation acutely increases the levels of methionine-related metabolites in a variety of treatment-resistant GBM models. Stable isotope tracing studies further revealed that radiation acutely activates methionine to S-adenosyl methionine (SAM) conversion through an active signaling event mediated by the kinases of the DNA damage response. In vivo tumor SAM synthesis increases after radiation, while normal brain SAM production remains unchanged, indicating a tumor- specific metabolic alteration to radiation. Pharmacological and dietary strategies to block methionine to SAM conversion slowed DNA damage response and increased cell death following radiation in vitro. Mechanistically, these effects are due to depletion of DNA repair proteins and are reversed by SAM supplementation. These effects are selective to GBMs lacking the methionine salvage enzyme methylthioadenosine phosphorylase. Pharmacological inhibition of SAM synthesis hindered tumor growth in flank and orthotopic in vivo GBM models when combined with radiation. By contrast, methionine depletion does not reduce tumor SAM levels and fails to radiosensitize intracranial models, indicating depleting SAM, as opposed to simply lowering methionine, is critical for hindering tumor growth in intracranial models of GBM. These results highlight a new signaling link between DNA damage and SAM synthesis and define the metabolic fates of methionine in GBM in vivo. Inhibiting radiation-induced SAM synthesis slows DNA repair and augments radiation efficacy in GBM. Using MAT2A inhibitors to deplete SAM may selectively overcome treatment resistance in GBMs with defective methionine salvage while sparing normal brain.

cancer biology↗

bioRxiv2024

GOBoost: Leveraging Long-Tail Gene Ontology Terms for Accurate Protein Function Prediction

MotivationWith the advancement of deep learning, researchers have increasingly proposed computational methods based on deep learning techniques to predict protein function. However, many of these methods treat protein function prediction as a multi-label classification problem, often overlooking the long-tail distribution of functional labels (i.e., Gene Ontology Terms) in datasets. To address this issue, we propose the GOBoost method, which incorporates the proposed long-tail optimization ensemble strategy. Besides, GOBoost introduces the proposed global-local label graph module and multi-granularity focal loss function to enhance long-tail functional information, mitigate the long-tail phenomenon, and improve overall prediction accuracy. ResultsWe evaluate GOBoost and other state-of-the-art (SOTA) protein function prediction methods on the PDB and AF2 datasets. The GOBoost outperformed SOTA methods across all evaluation metrics on both datasets. Notably, in the AUPR evaluation on the PDB test set, GOBoost improved by 10.71%, 35.91%, and 22.71% compared to the SOTA HEAL method in the MF, BP, and CC functions. The experimental results demonstrate the necessity and superiority of designing models from the label long-tail distribution perspective. Availabilityhttps://github.com/Cao-Labs/GOBoost Contactcaora@plu.edu

bioinformatics↗

bioRxiv2024

A whole-animal phenotypic drug screen identifies suppressors of atherogenic lipoproteins.

Lipoproteins are essential for lipid transport in all bilaterians. A single Apolipoprotein B (ApoB) molecule is the inseparable structural scaffold of each ApoB-containing lipoprotein (B-lps), which are responsible for transporting lipids to peripheral tissues. The cellular mechanisms that regulate ApoB and B-lp production, secretion, transport, and degradation remain to be fully defined. In humans, elevated levels of vascular B-lps play a causative role in cardiovascular disease. Previously, we have detailed that human B-lp biology is remarkably conserved in the zebrafish using an in vivo chemiluminescent reporter of ApoB (LipoGlo) that does not disrupt ApoB function. Thus, the LipoGlo model is an ideal system for identifying novel mechanisms of ApoB modulation and, due to the ability of zebrafish to generate many progeny, is particularly amenable to large-scale phenotypic drug screening. Here, we report a screen of roughly 3000 compounds that identified 49 unique ApoB-lowering hits. Nineteen hits passed orthogonal screening criteria and seven were subjected to extensive phenotyping. A licorice root component, enoxolone, significantly lowered B-lps only in animals that express a functional allele of the nuclear hormone receptor Hepatocyte Nuclear Factor 4 (HNF4). Consistent with this result, inhibitors of HNF4 also reduce B-lp levels. These data demonstrate that mechanism(s) of action can be rapidly determined from a whole animal zebrafish phenotypic screen. Given the well documented role of HNF4 in human B-lp biology, these data validate the LipoGlo screening platform for identifying small molecule modulators of B-lps that play a critical role in a leading cause of worldwide mortality.

physiology↗

bioRxiv2024

Distinct Binding Modes of Inter-Spike Cross-Linking Suggest a Supplementary Mechanism for SARS-CoV-2 Antibody Neutralization

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its Omicron subvariants drastically amplifies transmissibility, infectivity, and immune escape, mainly due to their resistance to most neutralizing antibodies. Thus, exploring the mechanisms underlying antibody evasion is crucial. Although the full-length native form of antibody, immunoglobulin G (IgG), offers valuable insights into the neutralization, structural investigations primarily focus on the fragment of antigen-binding (Fab). Here, we employ single-particle cryo-electron microscopy (cryo-EM) to characterize a W328-6H2 antibody, in its native IgG form complexed with severe acute respiratory syndrome (SARS), severe acute respiratory syndrome coronavirus 2 wild-type (WT) and Omicron variant BA.1 spike protein (S). Three high-resolution structures reveal that the full-length IgG forms a centered head-to-head dimer of trimer when bound fully stoichiometrically with both SARS and WT S, while adopting a distinct offset configuration with Omicron BA.1 S. Combined with functional assays, our results suggest that, beyond the binding affinity between the RBD epitope and Fab, the higher-order architectures of S trimer and full-length IgG play an additional role in neutralization, elucidate a potential molecular basis of Omicron immune escape, and expand our understanding on antibody evasion mechanisms.

immunology↗

bioRxiv2024

Generation of a novel constitutive smooth muscle cell-specific Myh11-driven Cre mouse model

Dysfunction in either embryonic or postnatal vascular smooth muscle cells (SMCs) significantly contributes to the progression of various cardiovascular diseases. Therefore, elucidating the molecular mechanisms governing VSMC development and homeostasis is crucial. MYH11 is the most reliable lineage gene for SMCs and has been utilized to develop tamoxifen-inducible Cre driver lines for achieving SMC-specific gene manipulation by crossing with mice carrying the loxP-flanked gene, particularly in adult mice. For studies involving SMCs during embryogenesis, the commonly used constitutive Cre driver is controlled by the Tagln (Sm22) promoter. However, this Cre driver exhibits activity in multiple non-SMC populations, including cardiomyocytes and skeletal muscle precursors, introducing confounding effects. Additionally, most existing SMC-specific Cre drivers are generated using a transgenic approach, raising concerns about random site integration and variable gene copy numbers. To address these limitations, we report a novel Cre mouse model generated by knock-in (KI) of a nuclear-localized Cre recombinase into the Myh11 gene locus using homologous recombination. We confirmed that the Cre activity precisely recapitulates endogenous Myh11 expression by crossing with Rosa26 mTmG or tdTomato reporter mice. Moreover, Myh11-driven Cre can efficiently delete the floxed allele of the transcription factor Tead1 specifically in SMCs. The Tead1 SMC-specific knockout mice did not exhibit an overt phenotype, thereby circumventing the embryonic lethal phenotype mediated by Tagln-driven Cre, as we previously reported. These findings establish this novel Cre driver line as a robust tool for tracing the Myh11-positive SMC lineage and manipulating gene function specifically in SMCs during embryonic development in mice.

genetics↗

bioRxiv2024

Better Prior Distribution for Antibody Complementarity-Determining Regions Design

Designing antibodies with desired binding specificity and affinity is essential for pharmaceutical research. While diffusion-based models have advanced the co-design of the Complementarity-Determining Regions (CDRs) sequences and structures, challenges remain, including non-informative prior distribution, incompatibility with discrete amino acid types, and impractical computational cost in large-scale sampling. To address these, we proposed FlowDesign, a sequence-structure co-design approach based on Flow Matching, offering: (1) Flexible selection of prior distributions; (2) Direct matching of discrete distributions; (3) Enhanced computational efficiency for large-scale sampling. By leveraging various priors, data-driven structural models proved the most informative. FlowDesign outperformed baselines in Amino Acid Recovery (AAR), RMSD, and Rosetta energy. We also applied FlowDesign to design antibodies targeting the HIV-1 receptor CD4. FlowDesign yielded antibodies with improved binding affinity and neutralizing potency compared to the antibody Ibalizumab across multiple HIV mutants, validated by Biolayer Interferometry (BLI) and pseudovirus neutralization. This highlights FlowDesigns potential in antibody and protein design. A record of this papers Transparent Peer Review process is included in the Supplemental Information.

bioinformatics↗

bioRxiv2024

YY1 Enhances the Stability of HIF-1α Protein by Interacting with NUSAP1 in Macrophages within the Prostate Cancer Microenvironment

Immune checkpoint therapy for prostate cancer (PCa) has failed in clinical trials; however, the precise underlying mechanisms involved remain elusive. PCa, a classic "immune-cold" tumor, is characterized by an immunosuppressive tumor microenvironment. Within this milieu, macrophages, the predominant immune cell population, have a propensity to infiltrate the hypoxic zones of tumors. In a previous study, we showed that Yin Yang 1 (YY1) is highly expressed in macrophages in PCa tissues. Here, through multiplexed imaging mass cytometry (IMC) of a PCa tissue microarray, we further demonstrate that YY1+ macrophages aggregate in hypoxic areas of tumors and that hypoxia promotes the phase separation of YY1 in the nucleus by increasing YY1 tyrosine phosphorylation in macrophages. Furthermore, YY1 binds to NUSAP1 and promotes the SUMOylation of HIF-1, which promotes phase separation and stabilization of the HIF-1 protein. We also demonstrated that either treatment with a small molecule inhibitor (tenapanor) to decrease the YY1-NUSAP1-HIF-1 interaction or myeloid-specific YY1 gene knockout impairs subcutaneous PCa tumor formation. Furthermore, we present a first-generation tetrahedral DNA nanostructure (TDN) based on the proteolysis targeting chimera (PROTAC) technique, named YY1-DcTAC, which targets and degrades YY1 in tumor-associated macrophages. In a PCa mouse model, YY1-DcTAC exhibited prolonged drug efficacy, robust macrophage-specific responsiveness, potent antitumor effects, and increased CD8+ T cell tumor infiltration. In summary, our findings underscore the pivotal role of YY1 within the hypoxia/HIF-1 pathway in tumor-associated macrophages and affirm the therapeutic potential of targeting YY1 for treating PCa.

cancer biology↗

bioRxiv2024

TIA1 Mediates Divergent Inflammatory Responses to Tauopathy in Microglia and Macrophages

The RNA binding protein TIA1 is known to regulate stress responses. Here we show that TIA1 plays a much broader role in inflammatory cells, being required for the microglial sensome. We crossed TIA1 cKO mice (using a CX3CR1 driven cre element) to PS19 MAPT P301S tauopathy mice. The peripheral macrophages of TIA1 cKO mice exhibited a hyper-inflammatory phenotype with increased cytokine signaling, as expected. Surprisingly, the brains of these mice showed striking reductions in inflammation, including decreases in microglial inflammatory cytokines (TNF and IL-1{beta}) and sensome markers (CLEC7A, TREM2, ITGAX); these reductions were accompanied by corresponding decreases in tau pathology. Analysis of the brain TIA1 protein interactome identified brain selective TIA1 protein mediated pathways, including strong interactions with the microglial protein C1q, which directs pruning of dystrophic neurons. These results uncover a previously unknown regulatory role for TIA1 in microglial activation in the context of neurodegenerative disease and highlights the divergent regulation of two mononuclear phagocytic lineages: microglia and macrophages.

neuroscience↗

bioRxiv2024

Dissecting the molecular basis of variability for flowering time in Camelina sativa

Camelina sativa is an important polyploid oilseed crop with multiple favorable agronomic traits. Capturing the leaf transcriptome of 48 accessions of C. sativa suggests allelic variation for gene expression levels and notably sub-genome dominance, both of which could provide opportunities for crop improvement. Flowering time (FT) is a crucial factor affecting the overall yield of crops. However, our understanding of the molecular mechanisms underlying FT regulation in C. sativa are still limited, partly due to its complex allohexaploid genome. In this study, weighted gene co-expression network analysis (WGCNA), expression quantitative trait loci (eQTL) analysis and transcriptome-wide association study (TWAS) were employed to explore the FT diversity among 48 C. sativa accessions and dissect the underlying molecular basis. Our results revealed a FT-related co-expressed gene module highly enriched with SOC1s and SOC1-like genes, and identified 10 significant FT-associated single nucleotide polymorphisms (SNPs) defining three haplotype groups; thus providing a molecular basis for future genetic improvements in C. sativa breeding.

plant biology↗

bioRxiv2024

CIWARS: a web server for waterborne antibiotic resistance surveillance using longitudinal metagenomic data

The rise of antibiotic resistance (AR) is a major global health crisis, exacerbated by the overuse and misuse of antibiotics, leading to the rapid spread of antibiotic resistance genes (ARGs) in bacterial pathogens. This phenomenon poses significant threats to human and animal health, food security, and economic stability. Water bodies, particularly wastewater treatment plants (WWTPs), serve as critical reservoirs for ARGs, creating environments that favor the proliferation of resistant bacteria. Wastewater-based surveillance (WBS) has emerged as a cost-effective strategy for monitoring AR at the population level, providing real-time data to guide public health and policy decisions. Despite advancements in WBS, there are no comprehensive online analytical platforms for continuous environmental AR surveillance. This paper introduces CIWARS, a web server designed for AR analyses of longitudinal metagenomic data. CIWARS offers comprehensive ARG profiling, taxonomic annotation, and anomalous AR risk points detection. We demonstrate its capabilities through an interactive temporal data visualization, showcasing its potential for enhancing AR risk monitoring and guiding effective mitigation strategies. CIWARS is broadly applicable to longitudinal metagenomic data generated from any environment and aims to support global efforts in addressing the AR crisis by providing cyberinfrastructure for continuous AR surveillance. The web server is freely available at https://ciwars.cs.vt.edu/.

bioinformatics↗

bioRxiv2024

Development of an ELISA assay for EV quantification to assist the large-scale EV manufacture

Accurate EV quantitation is essential for ensuring quality, consistency, and safety during large-scale extracellular vesicle (EV) manufacturing. In the upstream phase, EV quantitation allows for the monitoring of cell culture conditions that impact EV yield and quality, while in the downstream phase, it helps to control the efficiency and purity of EV purification. Nanoparticle Tracking Analysis is the most commonly used method for EV quantification, while it faces significant limitations due to interference from nanosize contaminants like protein aggregates, especially in crude samples (e.g. cell culture media). To address this issue, we developed a highly specific and accurate ELISA assay that quantifies EVs even in crude samples. With ultra-pure EV standard samples, this assay showed reliable quantitative result of EV detection to support method development as well as in-process control of large-scale EV manufacture. The detection range of this assay is from 4.1E7 to 3E10 EVs/mL, with an LOD of 1.04E7 EVs/mL and an LOQ of 3.21E7 EVs/mL. We therefore developed this assay into a testing kit and demonstrated that this EV quantification ELISA kit is capable of ensuring minimal interference from impurities and supporting the process development and in-process control in EV production.

biochemistry↗