Biology subjects

Qin, Z.

Publications and source records attributed to Qin, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Rapid adaptive optics enabling near noninvasive high-resolution brain imaging in awake behaving mice

High-resolution imaging under physiological conditions is essential for studying biological mechanisms and disease processes. However, achieving this goal remains challenging due to optical aberrations and scattering from heterogeneous tissue structures, compounded by motion artifacts from awake animals. In this study, we developed a rapid and accurate adaptive optics system called multiplexing digital focus sensing and shaping (MD-FSS) for deep-tissue multiphoton microscopy. Under two-photon excitation, MD-FSS precisely measures the aberrated point spread function in approximately 0.1 s per measurement, effectively compensating for both aberrations and scattering to achieve subcellular resolution in deep tissue. Using MD-FSS integrated with two-photon microscopy, we achieved high-resolution brain imaging through thinned or optically cleared skull windows, two near noninvasive methods to access mouse brain, reaching depths up to 600 m below the pia in awake behaving mice. Our findings revealed significant differences in microglial functional states and microvascular circulation dynamics between awake and anesthetized conditions, highlighting the importance of studying brain function in awake mice through noninvasive methods. We captured functional imaging of fine neuronal structures at subcellular level in both somatosensory and visual cortices. Additionally, we demonstrated high-resolution imaging of microvascular structures and neurovascular coupling across multiple cortical regions and depths in the awake brain. Our work shows that MD-FSS robustly corrects tissue-induced aberrations and scattering through rapid PSF measurements, enabling near-noninvasive, high-resolution imaging in awake, behaving mice.

bioengineering↗

bioRxiv2025

DeepAden: an explainable machine learning for substrate specificity prediction in nonribosomal peptide synthetases

Microbial non-ribosomal peptides (NRPs) exhibit remarkable structural diversity and serve as valuable sources of lead compounds for clinical drug development. The biosynthesis of NRPs relies on non-ribosomal peptide synthetases (NRPSs), in which adenylation (A) domains play a pivotal role in defining the core structure by selectively recognizing and activating amino acid substrates. Accurately predicting the substrate specificities of A-domains is thus essential for understanding the core structural and biosynthetic logic of NRPs. Here, we present DeepAden, a two-stage deep learning framework. In the first stage, a graph attention network (GAT)-based model localizes 27-residue binding pockets within 6 [A] of bound substrates and convert these into pocket representations. In the second stage, pocket representations are then encoded alongside substrate information using pretrained language models, and aligned using contrastive learning. In addition, we introduce a SHapley Additive exPlanations (SHAP)-guided data augmentation strategy to mitigate class imbalance and improve robustness, particularly for nonproteinogenic substrates. DeepAden achieves competitive performance compared with state-of-the-art tools on a benchmark dataset, and enabled the identification of two Streptomyces NRPS gene clusters through accurate A-domain substrates specificity predictions. DeepAden offers a powerful tool for precise pocket localization and robust substrate prediction, accelerating the discovery and characterization of novel NRP natural products for future work. The DeepAden web server is available at https://deepnp.site/.

bioinformatics↗

bioRxiv2025

Structural insights into the remodeled RNA polymerase II complex on an RNA template

DNA-dependent RNA polymerases (DdRPs) recognize not only DNA but also RNA templates. This RNA-dependent RNA polymerase (RdRP) activity is exploited by viroids in plants and human hepatitis delta virus in animals. A major knowledge gap exists regarding the molecular basis conferring this RdRP activity. Here, we provide evidence supporting the reorganization of the 12-subunit Pol II to 7-subunit in vivo for PSTVd transcription. Rpb4, Rpb5, Rpb6, Rpb7, and Rpb9 are not involved in PSTVd transcription in planta. A splicing variant of transcription factor IIIA with seven zinc finger domains (TFIIIA-7ZF) aids the remodeled Pol II in transcribing PSTVd. Using AlphaFold3, the structure of the remodeled Pol II with PSTVd RNA and TFIIIA-7ZF was generated. The predicted structure and experimental data both show that the N-terminus of TFIIIA-7ZF binds to the left terminal domain of PSTVd, while the C-terminus interacts with Rpb2. Interestingly, AlphaFold3 also predicts the bending at PSTVd loop 8 in the TFIIIA-7ZF/PSTVd complex. Replacing this loop 8 with a rigid double-stranded conformation impairs the TFIIIA-7ZF/PSTVd interaction. Altogether, our demonstrate an active form of heterogenous organization of the essential Pol II enzyme in vivo and provide structural insights into the organization of Pol II transcription complex on RNA template.

molecular biology↗

bioRxiv2025

Concurrent PIK3CA mutant drives cachexia through inflammatory signaling in EGFR mutant lung cancer

PIK3CA mutation is frequently concurrent with known oncogenic drivers such as EGFR mutation in lung cancer, raising an interesting question about its real function. Cachexia is a systemic disease involving complex interaction between primary tumors and distant organs, significantly contributing to cancer-related mortality. Through integrative study of genetically engineered mouse models (GEMMs) and clinical data, we find concurrent PIK3CA mutant preferentially drives cachexia in EGFR-mutant lung cancer, promoting malignant progression instead of cancer initiation. PIK3CA mutant-mediated cachexia could be overcome by osimertinib (Osi) treatment in Osi-sensitive GEMM. In contrast, chemotherapy, routinely used in clinic for those relapsed from Osi therapy, fails to ameliorate cachexia in Osi-resistant GEMM despite notable tumor suppression. PIK3CA mutant-driven cachexia is mediated through NF-{kappa}B activation and could be dampened by combined aspirin treatment. This work uncovers the biological function of PIK3CA mutant and mechanism behinds its clinical impacts, and proposes a potentially effective strategy for clinical management.

cancer biology↗

bioRxiv2025

Langerhans Cells Drive Tfh and B Cell Responses Independent of Canonical Cytokine Signals

Dendritic cells (DCs) are key regulators of adaptive immunity, guiding T helper (Th) cell differentiation through antigen presentation, co-stimulation, and cytokine production. However, in steady-state conditions, certain DC subsets, such as Langerhans cells (LCs), induce T follicular helper (Tfh) cells and B cell responses without inflammatory stimuli. Using multiple mouse models and in vitro systems, we investigated the mechanisms underlying steady-state LC-induced adaptive immune responses. We found that LCs drive germinal center Tfh and B cell differentiation and antibody production independently of interleukin-6 (IL-6), type-I interferons, and ICOS ligand (ICOS-L) signaling, which are critical in inflammatory settings. Instead, these responses relied on CD80/CD86-mediated co-stimulation. Our findings challenge the conventional three-signal paradigm by demonstrating that cytokine signaling is dispensable for LC-mediated Tfh and B cell responses in steady-state. These insights provide a framework for understanding homeostatic immunity and the immune systems role in maintaining tolerance or developing autoimmunity under non-inflammatory conditions. SUMMARY STATEMENTLangerhans cells (LCs) drive germinal center Tfh and B cell responses in steady-state conditions independently of IL-6, type-I interferons, and ICOS ligand, challenging the established cytokine-centric model of T cell differentiation.

immunology↗

bioRxiv2024

MAAPE: A Modular Approach to Evolutionary Analysis of Protein Embeddings

We present MAPPE, a novel algorithm integrating a k-nearest neighbor (KNN) similarity network with co-occurrence matrix analysis to extract evolutionary insights from protein language model (PLM) embeddings. The KNN network captures diverse evolutionary relationships and events, while the co-occurrence matrix identifies directional evolutionary paths and potential signals of gene transfer. MAPPE overcomes the limitations of traditional sequence alignment methods in detecting structural homology and functional associations in low-similarity protein sequences. By employing sliding windows of varying sizes, it analyzes embeddings to uncover both local and global evolutionary signals encoded by PLMs. We have benchmarked MAAPE approach on two well-characterized protein family datasets: the Als regulatory system (AlsS/AlsR) and the Rad DNA repair protein families. In both cases, MAAPE successfully reconstructed evolutionary networks that align with established phylogenetic relationships. This approach offers a deeper understanding of evolutionary relationships and holds significant potential for applications in protein evolution research, functional prediction, and the rational design of novel proteins.

bioinformatics↗

bioRxiv2024

Cross-tissue Graph Attention Networks for Semi-supervised Gene Expression Prediction

High-throughput biotechnologies have significantly advanced precision medicine by enabling the exploitation of global gene expression patterns to enhance our understanding of disease etiology, progression, and treatment options. However, the tissue-specific nature of gene expression presents a challenge, particularly for less accessible tissues such as the brain, underscoring the need for computational methods to accurately impute gene expression in these critical but hard-to-reach tissues. While several attempts to impute gene expression in tissue-specific contexts have shown promising results, their reliance on regression analysis faces limitations due to the inability to capture complex, nonlinear relationships in gene expression patterns. In contrast, modern machine learning techniques, particularly graph neural networks, have demonstrated superior performance by efficiently modeling the intricate interactions among genes across different tissues. Therefore, we introduce gene expression imputation with Graph Attention Networks (gemGAT), a novel approach leveraging Graph Attention Networks (GATs) to enhance gene expression prediction across different tissues. gemGAT distinguishes itself by predicting the expression of all genes simultaneously, utilizing the full spectrum of genomic data to account for gene co-expressions and non-linear relationships. Validated through extensive experiments with Genotype-Tissue Expression (GTEx) data and a case study from the Alzheimers Disease Neuroimaging Initiative (ADNI), gemGAT demonstrates superior performance over existing methods by efficiently capturing non-linear gene co-expressions. This advancement underscores gemGATs potential to significantly contribute to precision medicine, showcasing its utility in advancing our understanding of gene expression in less accessible tissues.

bioinformatics↗

bioRxiv2024

DNA-SaM, a robust system for large-scale data storage

DNA data storage offers a viable strategy to address the impending data explosion. Early attempts to harness DNA as a storage medium have encountered scalability limitations, largely due to the complexity of codec algorithms, the generation of biochemically harmful sequences and lack of a robust architecture. We present "DNA-SaM", a novel system designed for DNA data storage, which achieves linear computational complexity and strict bio-constraint adherence, ensuring high coding efficiency and fidelity. It encoded data at speeds surpassing classic systems by over 2 orders of magnitude, with this superiority changes across various encoding algorithms. Importantly, DNA-SaM effectively eliminates any sequence that could be deleterious to in vitro and in vivo biochemical processes, including homopolymer runs, tandem repeat motifs, and potential promoter sequences, etc. It also involves an advanced DNA data storage architecture that incorporates a two-tiered indexing system and a novel "storage unit" distribution paradigm for large-scale data storage. It is further validated by practical data storage both in vitro and in vivo with a 100% success rate. Our system is capable of storing data over 1039 PB, which marks a critical advancement in the scalability of DNA-based data storage.

synthetic biology↗

bioRxiv2024

High-throughput, multiplexed quantification, and sorting of single EVs at single-molecule level

We have developed a platform for the high-throughput, multiplexed, and ultra-sensitive profiling of individual extracellular vesicles (EVs) directly in plasma, which we call BDEVS - Agarose Bead-based Digital Single Molecule-Single EV Sorting. Unlike conventional approaches, BDEVS achieves single molecule sensitivity and moderate multiplexing (demonstrated 3-plex) without sacrificing the throughput (processing ten thousand of EVs per minute) necessary to resolve EVs directly in human plasma. Our platform integrates rolling circle amplification (RCA) of EV surface proteins, which are cleaved from single EVs, and amplified within agarose droplets, followed by flow cytometry-based readout and sorting, overcoming steric hindrance, non-specific binding, and the lack of quantitation of multiple proteins on EVs that have plagued earlier approaches. We evaluated the analytical capabilities of BDEVS through head-to-head comparison with gold-standard technologies, and demonstrated a [~]100x improvement in the limit of detection of EV subpopulations. We demonstrate the high throughput ([~]100k beads / minute) profiling of individual EVs for key immune markers PD-L1, CD155, and the melanoma tumor marker TYRP-1, and showed that BDEVS can precisely quantify and sort EVs, offering unprecedented resolution for analyzing tumor-immune interactions and detecting rare EV subpopulations in complex clinical specimens. We demonstrate BDEVSs potential as a transformative tool for EV-based diagnostics and therapeutic monitoring in the context of cancer immunology by analyzing plasma samples from patients with melanoma, where EV heterogeneity plays a critical role in disease progression and response to therapy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/621423v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1a8a542org.highwire.dtl.DTLVardef@f9b9f0org.highwire.dtl.DTLVardef@11e4758org.highwire.dtl.DTLVardef@de1645_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

CIGB-300 reverses chemo-resistance in MDR1-transfected lung squamous cancer cells

BackgroundInhibition of ABC transporter protein activity is considered to be the most effective method to reverse multidrug resistance (MDR). In this study, we evaluated the MDR reversal potential of CIGB-300, a potent CK2 kinase inhibitor. MethodsABCB1 overexpressing lung adenocarcinoma NCI-H226 cells were constructed using lentivirus, and the expression of ABCB1 gene and protein was detected by real-time fluorescence quantitative PCR and Western blotting. MTT assay was used to assess the cytotoxicity and MDR reversal effect of CIGB-300.The effect of CIGB-300 on ABCB1 expression was determined by Western Blotting. Cell surface expression and subcellular localization of ABCB1 were examined by Flow Cytometry and Immunofluorescence Staining. Rh123 efflux and accumulation were measured by Fluorescent Enzyme Labeler and Flow Cytometry. ResultsCIGB-300 significantly increased the sensitivity of drug-resistant cells overexpressing the ABCB1 drug efflux pump (NCI-H226-ABCB1), while it had no effect on their parental cell lines. At the same time, its mechanism of action may be related to the inhibition of ABCB1 expression, which was dose-dependent, Moreover, in addition, we demonstrated that CIGB-300 reduced the expression of NFKB and CDC37 proteins. ConclusionsOur study elucidated that CIGB-300 reverses ABCB1-mediated MDR by inhibiting ABCB1 protein expression or intracellular signaling and provides a potential therapeutic strategy to improve tumor chemosensitivity.

cancer biology↗

bioRxiv2024

Longitudinal multi-omics reveals pathogenic TSC2 variants disrupt developmental trajectories of human cortical organoids derived from Tuberous Sclerosis Complex

Tuberous Sclerosis Complex (TSC), an autosomal dominant condition, is caused by heterozygous mutations in either the TSC1 or TSC2 genes, manifesting in systemic growth of benign tumors. In addition to brain lesions, neurologic sequelae represent the greatest morbidity in TSC patients. Investigations utilizing TSC1/2-knockout animal or human stem cell models suggest that TSC deficiency-causing hyper-activation of mTOR signaling might precipitate anomalous neurodevelopmental processes. However, how the pathogenic variants of TSC1/2 genes affect the longitudinal trajectory of human brain development remains largely unexplored. Here, we employed 3-dimensional cortical organoids derived from induced pluripotent stem cells (iPSCs) from TSC patients harboring TSC2 variants, alongside organoids from age- and sex-matched healthy individuals as controls. Through comprehensively longitudinal molecular and cellular analyses of TSC organoids, we found that TSC2 pathogenic variants dysregulate neurogenesis, synaptogenesis, and gliogenesis, particularly for reactive astrogliosis. The altered developmental trajectory of TSC organoids significantly resembles the molecular signatures of neuropsychiatric disorders, including autism spectrum disorders, epilepsy, and intellectual disability. Intriguingly, single cell transcriptomic analyses on TSC organoids revealed that TSC2 pathogenic variants disrupt the neuron/reactive astrocyte crosstalk within the NLGN-NRXN signaling network. Furthermore, cellular and electrophysiological assessments of TSC cortical organoids, along with proteomic analyses of synaptosomes, demonstrated that the TSC2 variants precipitate perturbations in synaptic transmission, neuronal network activity, mitochondrial translational integrity, and neurofilament formation. Notably, similar perturbations were observed in surgically resected cortical specimens from TSC patients. Collectively, our study illustrates that disease-associated TSC2 variants disrupt the neurodevelopmental trajectories through perturbations of gene regulatory networks during early cortical development, leading to mitochondrial dysfunction, aberrant neurofilament formation, impaired synaptic formation and neuronal network activity.

neuroscience↗

bioRxiv2024

The Unique Role of Intracellular Perinuclear β-Adrenergic Receptors in defining Signaling Compartmentation and Pathological Cardiac Remodeling

The {beta}-adrenergic receptor is a prototypical G-protein coupled receptor that initiates signaling from the plasma membrane. However, active receptors have been detected within intracellular compartments. The functional significance of these intracellular receptors remains unclear, including whether they regulate distinct cellular processes or function independently of plasma membrane receptors. We show using live cell imaging of primary cardiomyocytes that {beta}-adrenergic receptors localized to Golgi apparatus opposing the outer nuclear membrane are sufficient and necessary for the stimulation of cAMP and calcium signaling within a nanometer scale compartment independent of receptors at other sites. Using compartment-specific activators and inhibitors, we show Golgi {beta}-adrenergic receptors associated with the scaffold protein AKAP6{beta} and the outer nuclear membrane protein nesprin-1 are responsible for pathological gene transcription and the induction of cardiomyocyte hypertrophy. The functional significance of Golgi-localized receptors is demonstrated in mice models of cardiomyopathy, providing proof-of-concept for a compartment-specific therapeutic intervention in Dilated Cardiomyopathy.

cell biology↗

bioRxiv2024

Accessible chromatin regions and DNA methylation regulate gene expression leading to changes in agronomic traits in Brassica allotriploid hybrids

IntroductionInterspecific hybridization is a common method in plant breeding to combine traits from different species, resulting in allopolyploidization and significant genetic and epigenetic changes. However, our understanding of genome-wide chromatin and gene expression dynamics during allopolyploidization remains limited. ObjectivesWe aimed to explore the relationship and underlying mechanisms between accessible chromatin regions and DNA methylation and gene transcription in genome-wide reorganization after interspecific hybridization. MethodsThis study generated two Brassica allotriploid hybrids via interspecific hybridization, combining transcriptomics, whole-genome bisulfite sequencing (WGBS) and assay for transposase-accessible chromatin with high throughput sequencing (ATAC-seq), revealing that accessible chromatin regions (ACRs) and DNA methylation regulate gene expression after interspecific hybridization, ultimately influencing the agronomic traits of the hybrids. ResultsA total of 234,649 ACRs were identified in the parental lines and hybrids, the hybridization process induces changes in the distribution and abundance of there accessible chromatin regions, particularly in gene regions and their proximity. On average, genes associated with Proximal ACRs were more highly expressed than the genes associated with Distal and Genic ACRs. More than half of novel ACRs drove transgressive gene expression in the hybrids, and the transgressive up-regulated genes showed significant enrichment in metal ion binding, especially magnesium ion, calcium ion, and potassium ion binding. We also identified the Bna.bZIP11 in the single-parent activation ACR (SPA-ACR), which binds to BnaA06.UF3GT to promote anthocyanin accumulation in F1 hybrids. Additionally, in F1 hybrids, the level of DNA methylation in ACRs was higher compared to gene bodies, and the A-subgenome ACRs were associated with genome dosage rather than DNA methylation. ConclusionsThe interplay among DNA methylation, TEs, and sRNA contributes to the dynamic landscape of ACRs during interspecific hybridization, resulting in distinct gene expression patterns on the genome. HIGHLIGHTSO_LIThe study utilized the accessible chromatin regions (ACR) and DNA methylation to elucidate the mechanism behind gene expression changes following interspecific hybridization. C_LIO_LIWhole-genome recombination after interspecific hybridization leads to the rearrangement of ACR, and novel ACR and single-parent activation ACR regulate the expression of genes. C_LIO_LIDNA methylation plays a role in repressing gene expression within ACRs, and unmethylated ACRs have more transcriptionally active. C_LIO_LIA-subgenome ACRs were associated with genome dosage rather than DNA methylation. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/613586v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1504e51org.highwire.dtl.DTLVardef@145b0b8org.highwire.dtl.DTLVardef@551847org.highwire.dtl.DTLVardef@ace197_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Inhibitor of cardiolipin biosynthesis-related enzyme MoGep4 confers broad-spectrum anti-fungal activity

Plant pathogens cause devastating diseases, leading to serious losses to agriculture. Mechanistic understanding of pathogenesis of plant pathogens lays the foundation for the development of fungicides for disease control. Mitophagy, a specific form of autophagy, is important for fungal virulence. The role of cardiolipin, mitochondrial signature phospholipid, in mitophagy and pathogenesis is largely unknown in plant pathogenic fungi. The functions of enzymes involved in cardiolipin biosynthesis and relevant inhibitors were assessed using a set of assays, including genetic deletion, plant infection, lipidomics, chemical-protein interaction, chemical inhibition, and field trials. Our results showed that the cardiolipin biosynthesis-related gene MoGEP4 of the rice blast fungus Magnaporthe oryzae regulates growth, conidiation, cardiolipin biosynthesis, and virulence. Mechanistically, MoGep4 regulated mitophagy and Mps1-MAPK phosphorylation, which are required for virulence. Chemical alexidine dihydrochloride (AXD) inhibited the enzyme activity of MoGep4, cardiolipin biosynthesis and mitophagy. Importantly, AXD efficiently inhibited the growth of 10 plant pathogens and controlled rice blast and Fusarium head blight in the field. Our study demonstrated that MoGep4 regulates mitophagy, Mps1 phosphorylation and pathogenesis in M. oryzae. In addition, we found that the MoGep4 inhibitor, AXD, displays broad-spectrum antifungal activity and is a promising candidate for fungicide development.

microbiology↗

bioRxiv2024

A novel classification framework for genome-wide association study of whole brain MRI images using deep learning

Genome-wide association studies (GWASs) have been widely applied in the neuroimaging field to discover genetic variants associated with brain-related traits. So far, almost all GWASs conducted in neuroimaging genetics are performed on univariate quantitative features summarized from brain images. On the other hand, powerful deep learning technologies have dramatically improved our ability to classify images. In this study, we proposed and implemented a novel machine learning strategy for systematically identifying genetic variants that lead to detectable nuances on Magnetic Resonance Images (MRI). For a specific single nucleotide polymorphism (SNP), if MRI images labeled by genotypes of this SNP can be reliably distinguished using machine learning, we then hypothesized that this SNP is likely to be associated with brain anatomy or function which is manifested in MRI brain images. We applied this strategy to a catalog of MRI image and genotype data collected by the Alzheimers Disease Neuroimaging Initiative (ADNI) consortium. From the results, we identified novel variants that show strong association to brain phenotypes.

bioinformatics↗

bioRxiv2023

An automated archival single-nucleus total RNA sequencing platform mapping integrative and retrospective cell atlas of gliomas

Single-cell RNA sequencing (scRNA-seq) has dramatically transformed biomedical research within laboratory settings. It has been extensively employed to investigate the heterogeneity and plasticity of glioma, the most prevalent brain tumor. However, the clinical diagnosis and treatment of glioma remain complex and challenging, highlighting the need for comprehensive cancer research. Currently available scRNA-seq platforms are insufficient to fulfill the demands posed by large-scale clinical applications. Here, we present an automated high-throughput single-nucleus total RNA sequencing platform, known as AAsnRandom-seq. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, designed to accommodate a diverse range of sample types. The performance and versatility of AAsnRandom-seq are validated using over one hundred clinical FFPE and frozen samples. AAsnRandom-seq was applied to archival FFPE samples of various glioma subtypes, including rare clinical samples, and matched primary-recurrent glioblastomas (GBMs), delving into the comprehensive molecular characteristic of glioma at single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles within different glioma clusters are detected. Promising recurrence-related targets and pathways are identified from the matched primary-recurrent GBMs. AAsnRandom-seq holds significant application value on large-scale integrative and retrospective clinical research using archived specimens.

bioengineering↗

bioRxiv2023

Glioblastoma Margin as a Diffusion Barrier Revealed by Photoactivation of Plasmonic Nanovesicles

Glioblastoma (GBM) is the most complex and lethal adult primary brain cancer. Adequate drug diffusion and penetration are essential for treating GBM, but how the spatial heterogeneity in GBM impacts drug diffusion and transport is poorly understood. Herein, we report a new method, photoactivation of plasmonic nanovesicles (PANO), to measure molecular diffusion in the extracellular space of GBM. By examining three genetically engineered GBM mouse models that recapitulate key clinical features including angiogenic core and diffuse infiltration, we found that the tumor margin has the lowest diffusion coefficient (highest tortuosity) compared with the tumor core and surrounding brain tissue. Analysis of the cellular composition shows that the tortuosity in the GBM is strongly correlated with neuronal loss and astrocyte activation. Our all-optical measurement reveals the heterogeneous GBM microenvironment and highlights the tumor margin as a diffusion barrier for drug transport in the brain, with implications for therapeutic delivery.

bioengineering↗

bioRxiv2023

Elimination of subtelomeric repeat sequences exerts little effect on telomere functions in Saccharomyces cerevisiae

Telomeres, which are chromosomal end structures, play a crucial role in maintaining genome stability and integrity in eukaryotes. In the bakers yeast Saccharomyces cerevisiae, the X-and Y-elements are subtelomeric repetitive sequences found in all thirty-two and seventeen telomeres, respectively. While the Y-elements serve as a backup for telomere functions in cells lacking telomerase, the function of the X-elements remains unclear. This study utilized the S. cerevisiae strain SY12, which has three chromosomes and six telomeres, to investigate the role of X-elements (as well as Y-elements) in telomere maintenance. Deletion of Y-elements (SY12Y{Delta}), X-elements (SY12XY{Delta}+Y), or both X- and Y-elements (SY12XY{Delta}) did not impact the length of the terminal TG1-3 tracks or telomere silencing. However, inactivation of telomerase in SY12Y{Delta}, SY12XY{Delta}+Y, and SY12XY{Delta} cells resulted in cellular senescence and the generation of survivors. These survivors either maintained their telomeres through homologous recombination-dependent TG1-3 track elongation or underwent microhomology-mediated intra-chromosomal end-to-end joining. Our findings indicate the non-essential role of subtelomeric X-and Y-elements in telomere regulation in both telomerase-proficient and telomerase-null cells and suggest that these elements may represent remnants of S. cerevisiae genome evolution. Furthermore, strains with fewer or no subtelomeric elements exhibit more concise telomere structures and offer potential models for future studies in telomere biology.

genetics↗