Biology subjects

Liu, W.

Publications and source records attributed to Liu, W..

At least 181 records · Page 10Linked to original sources

bioRxiv2025

Lower spatial turnover of rare fungal taxa dominantly shaped by stochastic processes in grassland soils

The spatial pattern and community assembly of soil microbial taxa have notable meanings for biodiversity shaping and maintaining mechanisms. Rare fungal taxa may exhibit distinct patterns and assembly mechanisms compared to abundant taxa, but such information is limited, especially at large scales. Here, we investigated distance-decay patterns and underlying assembly mechanisms for abundant and rare fungal taxa in 129 soil samples collected across 4,000 km in Chinese Northern grasslands, based on high-throughput sequencing data. A total of 208 abundant OTUs (relative abundance > 0.1%, 2.73% of entire OTUs) and 5,779 rare OTUs (relative abundance < 0.01%, 75.85% of entire OTUs) were identified. Both abundant and rare fungal taxa showed significant distance-decay relationships (P < 0.001), but the turnover rate for rare taxa (0.0024 per 100 km) was nearly half that of abundant taxa (0.0054 per 100 km) based on the binary Bray-Curtis distance. The lower turnover of rare fungal taxa was likely due to their community assembly mechanism dominated by stochastic processes, which were less influenced by environmental gradients. In contrast, abundant taxa assembly was dominated by deterministic factors like soil variables and plant traits, which varied significantly along the geographic distance. Consistently, rare fungal taxa were also less sensitive to environmental changes, with a lower turnover rate by environmental distance (0.0027 vs. 0.0099) than abundant taxa. In summary, our findings revealed that rare fungal taxa, shaped mainly by stochastic processes, had lower spatial turnover compared to abundant taxa, dominated by deterministic processes, enhancing our understanding of rare microbial biogeography.

ecology↗

bioRxiv2025

Neuron type-specific mRNA translation programs provide a gateway for memory consolidation.

Long-term memory consolidation is a dynamic process that requires a heterogeneous ensemble of neurons, each with a highly specialized molecular signature. Considerable effort has been devoted to identifying molecular changes that accompany the process of consolidation, but mostly hours or days after training, when memory consolidation is already complete. Studies have shown that protein synthesis is elevated during the early stages of consolidation, but how this increase impacts neuronal function remains unclear. We hypothesize that mRNAs translated during the early stages of consolidation could provide information on how diverse neurons involved in memory formation restructure their molecular signatures to support memory. Here, we generate a landscape of the translatome of three neuron types in the dorsal hippocampus during the first hour of contextual memory consolidation. Our results reveal that translation programs associated with consolidation are different among neurons, fueling the reconfiguration of specific biological processes. We further demonstrate the patterned translation of mRNAs in different neuron types during consolidation is explained by features hard-coded in the mRNA sequence, suggesting ubiquitous mechanisms controlling activity-induced neuronal translation. Altogether, our work uncovers previously unknown mechanisms controlling activity-induced translation in neurons and provides a large, readily available resource for scientists interested in the role of memory formation in health and disease.

neuroscience↗

bioRxiv2025

Collagen Hydrogel Tube Microbioreactors for Cell and Tissue Manufacturing

The production of mammalian cells in large quantities is essential for various applications. However, scaling up cell culture using existing bioreactors poses significant technical challenges and high costs. To address this, we previously developed an innovative 3D culture system, known as the AlgTube cell culture system, for high-density cell cultivation. This system involves processing cells into microscale alginate hydrogel tubes, which are suspended in the culture medium within a vessel. These hydrogel tubes shield cells from hydrodynamic stress and maintain the cell mass below 400 {micro}m in diameter, facilitating efficient mass transport and creating a favorable microenvironment for cell growth. Under optimized conditions, AlgTubes supported long-term culture with high cell viability, rapid expansion (1000-fold increase over 9 days per passage), and high yield (5x10 cells/mL), offering significant advantages over conventional methods. Despite these benefits, AlgTubes have critical drawbacks. They are mechanically fragile, with frequent breakage during culture leading to cell leakage and production failures. Additionally, many cell types exhibit poor growth due to the inability to adhere to the alginate surface, making alginate hydrogel microtubes unsuitable for industrial-scale cell production. To overcome these challenges, we developed a novel collagen hydrogel tube-based microbioreactor system in this work. This system provides enhanced robustness and adhesion, enabling scalable, cost-effective, and efficient cell production for a wide range of applications.

bioengineering↗

bioRxiv2025

Using green space virtual reality to prevent stress-induced working memory impairment

Exposure to green space is associated with both physical and mental health benefits, including the potential to buffer acute stress responses, positioning it as a promising non-pharmacological approach to protect cognitive functions against stress. However, urban residents often face significant barriers in accessing green spaces, which are not equitably distributed. Virtual Reality (VR) technology offers a potential solution by simulating green space that could be made accessible to a broader demographic. Here, we explored whether VR-stimulated green space could dampen biological stress responses (i.e., heart rate and cortical response) and prevent stress-induced working memory (WM) impairment. Healthy young participants underwent acute stress induction followed by 15 minutes of VR-based green space (N=36) or control empty space (N=30) intervention. Although we observed the expected stress-induced increase in heart rates and elevated cortisol levels under stress, VR green space exposure failed to temper cortisol responses compared to the control VR space. Further, VR green space exposure did not bring benefits to protect working memory performance under stress across three WM tasks. Applying a Bayesian analysis approach throughout enabled us to find substantial evidence for the absence of an effect of VR-based green space exposure on biological markers of acute stress responses and working memory performance. Our findings suggest that VR-generated green space may not effectively replicate the stress-buffering effects of actual green space exposure. We discussed the implications of our findings regarding the potential and limitations of using VR or green space exposure to buffer stress responses.

neuroscience↗

bioRxiv2025

Transcription Machinery Anchors ecDNAs to Mitotic Chromosomes for Segregation

Extrachromosomal DNAs (ecDNAs) attach to chromosomes during mitosis for random segregation and promote cancer heterogeneity. However, the mechanism governing ecDNA-chromosome mitotic interactions remains poorly understood. This study shows that ecDNAs tether to histone H3 lysine 27 acetylation (H3K27ac)-marked chromatin during mitosis. Depleting H3K27ac disrupts this interaction. Diverse bromodomain proteins, as H3K27ac readers, stabilise ecDNA-chromosome binding in a context-dependent and complementary manner. Although disrupting the Mediator complex in asynchronous cells detaches ecDNAs from mitotic chromosomes, Mediator and active Pol II are absent from ecDNAs during mitosis, suggesting that ecDNAs are transcriptionally silent during mitosis. Instead, inactive Pol II mediates ecDNA attachment. Furthermore, CRISPR interference targeting transcriptional regulatory elements on ecDNA impairs ecDNA segregation. Mis-segregated ecDNAs were expelled into the cytosol, leading to diminished oncogene expression and a reversal of therapy resistance. Our research provides universal cis and trans regulatory mechanisms of ecDNA segregation, offering deeper insight into ecDNA-driven oncogenesis.

cancer biology↗

bioRxiv2024

Transient glycan-shield reduction induces CD4-binding site broadly neutralizing antibodies in SHIV-infected macaques

Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 CD4-binding site (CD4bs) occur infrequently in macaques and humans and have not been reproducibly elicited in any outbred animal model. To address this challenge, we first isolated RHA10, an infection-induced rhesus bNAb with 51% breadth. The cryo-EM structure of RHA10 with HIV-1 envelope (Env) resembled prototypic human CD4bs bNAbs with CDR-H3-dominated binding. Env-antibody co-evolution revealed transient elimination of two Env CD4bs-proximal glycans near the time of RHA10-lineage initiation, and these glycan-deficient Envs bound preferentially to early RHA10 intermediates, suggesting glycan deletions in infecting SHIVs could consistently induce CD4bs bNAbs. To test this, we constructed SHIV.CH505.D3 with CD4bs-proximal glycan deletions. Infection of 10 macaques resulted in accelerated CD4bs bNAb responses in 8, compared with 1 of 115 control macaques. Glycan hole-based immunofocusing coupled to Env-Ab co-evolution can consistently induce broad CD4bs responses in macaques and thus serve as a model for HIV vaccine design. HighlightsO_LIOut of 115 wildtype HIV-1 Env bearing SHIV infected macaques, only one macaque (T681) developed CD4bs bNAbs C_LIO_LICD4bs bNAbs in macaque T681 recognized Env similarly to previously described CDR-H3 dominated human CD4bs bNAbs and exhibited comparable breadth and potency C_LIO_LITransient CD4bs-proximal glycan deletions in macaque T681 preceded bNAb induction C_LIO_LIA novel SHIV with CD4bs-proximal glycan holes and enhanced CD4bs antigenicity immunofocused B cell responses to the CD4bs and elicited cross-clade neutralizing responses in 80% of macaques C_LI

microbiology↗

bioRxiv2024

A three-dimensional ex vivo model recapitulates in vivo features and unravels increased drug resistance in childhood acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) preferentially localizes in the bone marrow (BM) and displays recurrent patterns of medullary and extra-medullary involvement. Leukemic cells exploit their niche for propagation and survive selective pressure by chemotherapy in the BM microenvironment, suggesting the existence of protective mechanisms. Here, we established a three-dimensional (3D) BM mimic with human mesenchymal stromal cells and endothelial cells that resemble vasculature-like structures to explore the interdependence of leukemic cells with their microenvironment. This model recapitulates recurrent topologic differences between B-cell and T-cell precursor ALL, whereby B-ALL interacts more closely with the mesenchymal compartment. Migration versatility was found to be associated with subtype, consistent with increased motility observed in T-ALL in vivo. Single-cell RNA signatures revealed similarities to profiles from in vivo patient derived xenografts, suggesting relevant states ex vivo. Furthermore, enhanced migration, adherence and cell cycle heterogeneity was visualized in our co-culture model. Finally, drug response profiling experiments in this 3D system reproduced established response patterns and indicated that drug resistant leukemic subpopulations may be detected more faithfully compared to information from two-dimensional models.

cancer biology↗

bioRxiv2024

Benchmarking deep learning methods for biologically conserved single-cell integration

Advancements in single-cell RNA sequencing (scRNA-seq) have enabled the analysis of millions of cells, but integrating such data across samples and methods while mitigating batch effects remains challenging. Deep learning approaches address this by learning biologically conserved gene expression representations, yet systematic benchmarking of loss functions and integration performance is lacking. This study evaluated 16 integration methods using a unified variational autoencoder framework, incorporating batch and cell-type information. Results revealed limitations in the single-cell integration benchmarking index (scIB) for preserving intra-cell-type information. To address this, we introduced a correlation-based loss function and enhanced benchmarking metrics to better capture biological conservation. Using annotations from the Human Lung Cell Atlas and Human Fetal Lung Cell Atlas, our approach improved biological signal preservation. This work highlights the need for biologically informed metrics in scRNA-seq integration and offers guidance for future deep learning developments.

bioinformatics↗

bioRxiv2024

Oligomerization of PRMT1 Regulated RNA-Binding Protein Cascade Promotes Pancreatic Ductal Adenocarcinoma

PRMT1 is the predominant type I protein arginine methyltransferase responsible for generating monomethylarginine and asymmetric dimethylarginine (MMA and ADMA) in various protein substrates. It regulates numerous biological processes, including RNA metabolism, mRNA splicing, DNA damage repair, and chromatin dynamics. The crystal structure of rat PRMT1 has been previously reported as a homodimer; however, higher-order oligomeric species of human PRMT1 have been observed in vivo, and their structural basis remains elusive. In this study, we present the cryo-EM structure of human PRMT1 in its oligomeric form, revealing novel interfaces crucial for PRMT1 self-assembly and normal function. PRMT1 shows a strong preference for intrinsically disordered RGG/RG motifs, which are commonly found in RNA-binding proteins (RBPs), highlighting its critical role in regulating RNA metabolism. In vitro studies indicate that disrupting PRMT1 oligomerization impairs its binding affinity for RGG motif substrates, thereby reducing arginine methylation levels on these substrates. This finding emphasizes the essential role of the oligomeric state of PRMT1 in its function with RGG motif-containing RBPs. In vivo, the loss of PRMT1 oligomerization leads to decreased global ADMA levels in pancreatic ductal adenocarcinoma (PDAC) cells and inhibits PDAC tumor growth. Collectively, we propose that PRMT1 oligomerization, rather than mere dimerization, is sufficient for PRMT1-driven PDAC tumor growth, offering novel insights into the potential therapeutic targeting of PRMT1 oligomeric forms in PDAC. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC="FIGDIR/small/627716v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1ed6232org.highwire.dtl.DTLVardef@1c9e688org.highwire.dtl.DTLVardef@3e2c43org.highwire.dtl.DTLVardef@1cbf33e_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Downstream branches of receptor tyrosine kinase signaling act interdependently to shape the face

BackgroundPreviously we found that increasing fibroblast growth factor (FGF) signaling in the neural crest cells within the frontonasal process (FNP) of the chicken embryo caused dysmorphology that was correlated with reduced proliferation, disrupted cellular orientation, and lower MAPK activation but no change in PLCy and PI3K activation. This suggests RTK signaling may drive craniofacial morphogenesis through specific downstream effectors that affect cellular activities. In this study we inhibited three downstream branches of RTK signaling to determine their role in regulating cellular activities and how these changes affect morphogenesis of the FNP. ResultsSmall molecule inhibitors of MEK1/2, PI3K, and PLCy were delivered individually and in tandem to the right FNP of chicken embryos. All treatments caused asymmetric proximodistal truncation on the treated side and a mild expansion on the untreated side compared to DMSO control treated FNPs. Inhibiting each pathway caused similar decreased proliferation and disrupted cellular orientation, but did not affect apoptosis. ConclusionsSince RTK signaling is a ubiquitous and tightly regulated biochemical system we conclude that the downstream pathways are robust to developmental perturbation through redundant signaling systems. Bullet pointsInhibiting three downstream effectors of receptor tyrosine kinase (RTK) signaling (MEK1/2, PLCy, and PI3K) in the frontonasal process of chicken embryos caused similar mild truncation of growth. Combining all three inhibitors had a slightly stronger effect on truncation. Individual inhibitors did not have specific effects on cellular proliferation, apoptosis, or cellular orientation. The downstream branches of RTK signaling likely have shared interdependent effects on cellular activities that contribute to morphogenesis.

developmental biology↗

bioRxiv2024

Direct Feature Identification from Raman Spectra and Precise Data-driven Classification of Phytopathogens at Single Conidium-Species Level

Conidia can cause outbreaks of fungal plant diseases, resulting in significant losses in crop yield and economy. Traditional diagnosis of phytopathogenic conidia based on morphology and molecular biology is time-consuming, labor-intensive, and often fails to differentiate fungal conidia. To overcome these challenges, a new classification approach was developed in this study by integrating Raman spectroscopy with data-driven modeling. Eight fungal species were selected and characterized using Raman spectra. Three characteristic Raman wavenumbers at 1003 to 1005 cm-1, 1153 to 1157 cm-1, and 1515 to 1522 cm-1 shared a consistent pattern across species and could be attributed to carotenoids. Clustering of the Raman spectra using principal component analysis (PCA) showed substantial overlap, indicating inaccurate classification of conidia. Three data-driven models, support vector machines (SVMs), decision trees (DTs), and eXtreme Gradient Boosting Forest (XGBoost) were trained with three categories of features (number of peaks, maximum peak, and curve roughness) identified within eight characteristic wavenumber ranges, The optimal SVM, DT, and XGBoost determined by hyperparameter tuning achieved prediction precision of 0.88, 0.88, and 0.96, respectively. PCA-XGBoost trained by feeding principal components of PCA to XGBoost achieved prediction precision of 0.94, suggesting that features extracted from the raw datasets outperformed those extracted with PCA in terms of data-driven classification. This study has demonstrated the great potential of Raman spectroscopy combined with data-driven modeling for classification of phytopathogenic conidia.

microbiology↗

bioRxiv2024

AACDB: Antigen-Antibody Complex Database -- a Comprehensive Database Unlocking Insights into Interaction Interface

Antibodies are critical components of the vertebrate immune system and possess a wide array of biomedical applications. Elucidating the complex interactions between antibodies and antigens is an important step in drug development. However, the complex and vast nature of the data presents significant challenges in accurately identifying and comprehending these interactions. To overcome these challenges and deepen our understanding of the antibody-antigen interface, we developed the Antigen-Antibody Complex Database (AACDB). The current version provides a comprehensive collection of 7,498 manually processed antigen-antibody complexes, ensuring accuracy and detail. This database provides extensive metadata and rectifies annotation errors found in the PDB database. Furthermore, it integrates data on antibody developability and antigen-drug target relationships, making it valuable for assisting new antibody therapies development. Notably, the database includes comprehensive paratope and epitope annotation information, thereby serving as a valuable benchmark for immunoinformatics research. The AACDB interface is designed to be user-friendly, providing researchers with powerful search and visualization tools that enable effortless querying, manipulation, and visualization of complex data. Researchers can access AACDB completely online at http://i.uestc.edu.cn/AACDB. Regular updates are promised to ensure the timely provision of scientific and valuable information.

bioinformatics↗

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

Delineation of Single-cell Altas Provides New Insights for Development of Coronary Artery Lesions in Kawasaki Disease: Bad and Good Signaling Molecules

BackgroundKawasaki Disease (KD) is a vasculitis syndrome featured with a high and persistent fever and mainly affects children under 5 years of age. It is the leading cause of acquired heart disease in the form of coronary artery lesions (CALs) for children in developed countries. Most KD can be relieved with the high-dosage Intravenous immunoglobulin (IVIG) therapy, but a small proportion develop CALs after IVIG treatment. MethodsWe performed the single-cell RNA sequencing for the peripheral blood mononuclear cells (PBMCs) from three KD non-CAL patients whose samples were acquired before and after IVIG treatment and three KD CAL patients whose samples were acquired only after IVIG treatment. Cell-to-cell communication patterns were also analyzed in KD CAL and non-CAL patients ResultsOverall cell expression feature analyses show immunoglobulin and adaptive immunity related genes are upregulated in KD CAL patients while B cell activation related genes are downregulated in them. Pseudo-time analyses demonstrate that both KD non-CAL patients before treatment and KD CAL patients after treatment have a dysregulated B cell developmental trajectory while the former has a mixed T and B lineage and the latter has a mixed monocyte and B lineage. The early elevated expression of SPI1 could partly explain the dysregulated B cell development in KD CAL patients. Cell communication analyses propose a disorder cell communication pattern in KD non-CAL patients before treatment and some persistent bad cell-to-cell signals in KD CAL patients after treatment. There are four signaling molecules, APP, CCL, and MCH-II, whose expression is significantly increased in the CD14 and CD16 monocytes of KD CAL patients, where the expression of RESISTIN is significantly increased in those KD non-CAL patients. ConclusionsOur results suggest that APP, CCL, and MCH-II might be the bad signals for indicating the possible development of CAL while RESISTIN is a good one for protecting from CAL.

immunology↗

bioRxiv2024

Aberrant expression of collagen type X in solid tumor stroma is associated with EMT, immunosuppressive and pro-metastatic pathways, bone marrow stromal cell signatures, and poor survival prognosis

BackgroundCollagen type X (ColX1, encoded by COL10A1) is expressed specifically in the cartilage-to-bone transition, in bone marrow cells, and in osteoarthritic (OA) cartilage. We have previously shown that ColX1 is expressed in breast tumor stroma, correlates with tumor-infiltrating lymphocytes, and predicts poor adjuvant therapy outcomes in ER+/HER2+ breast cancer. However, the underlying molecular mechanisms for these effects are unknown. In this study, we performed bioinformatic analysis of COL10A1-associated gene modules in breast and pancreatic cancer as well as in cells from bone marrow and OA cartilage. These findings provide important insights into the mechanisms of transcriptional and extracellular matrix changes which impact the local stromal microenvironment and tumor progression. MethodsImmunohistochemistry was performed to examine collagen type X expression in solid tumors. WGCNA was used to generate COL10A1-associated gene networks in breast and pancreatic tumor cohorts using RNA-Seq data from The Cancer Genome Atlas. Computational analysis was employed to assess the impact of these gene networks on development and progression of cancer and OA. Data processing and statistical analysis was performed using R and various publicly-available computational tools. ResultsExpression of COL10A1 and its associated gene networks highlights inflammatory and immunosuppressive microenvironments, which identify aggressive breast and pancreatic tumors and contribute to metastatic potential in a sex-dependent manner. Both cancer types are enriched in stroma, and COL10A1 implicates bone marrow-derived fibroblasts as drivers of the epithelial-to-mesenchymal transition (EMT) in these tumors. Heightened expression of COL10A1 and its associated gene networks is correlated with poorer patient outcomes in both breast and pancreatic cancer. Common transcriptional changes and chondrogenic activity are shared between cancer and OA cartilage, suggesting that similar microenvironmental alterations may underlie both diseases. ConclusionsCOL10A1-associated gene networks may hold substantial value as regulators and biomarkers of aggressive tumor phenotypes with implications for therapy development and clinical outcomes. Identification of tumors which exhibit high expression of COL10A1 and its associated genes may reveal the presence of bone marrow-derived stromal microenvironments with heightened EMT capacity and metastatic potential. Our analysis may enable more effective risk assessment and more precise treatment of patients with breast and pancreatic cancer. Research HighlightsO_LIColX highlights features of EMT in breast and pancreatic cancer C_LIO_LIColX gene modules are immunosuppressive and pro-metastatic C_LIO_LIColX-associated gene networks contribute to sex differences in pancreatic cancer C_LIO_LIColX-positive fibroblasts define more aggressive tumors with poorer survival C_LIO_LIColX is emerging as a biomarker for bone marrow-derived cells in cancer C_LI

cancer biology↗

bioRxiv2024

Evaluation of T Cell Receptor Construction Methods from scRNA-Seq Data

T cell receptors (TCRs) serve pivotal roles in the adaptive immune system by enabling recognition and response to pathogens and irregular cells. Various methods exist for TCR construction from single-cell RNA sequencing (scRNA-seq) datasets, each with its unique characteristics regarding accuracy, sensitivity, adaptability, usability, time, and memory consumption. Yet, a comprehensive understanding of their relative strengths and weaknesses for different applications remains elusive. In our research, we implemented a benchmark analysis utilizing experimental single-cell immune profiling datasets encompassing paired scRNA-seq as input and scTCR-seq datasets as ground truth reference from human and mouse. Additionally, we introduced a novel simulator, YASIM-scTCR (Yet Another Simulator for single-cell TCR), capable of generating scTCR-seq reads containing a diverse array of TCR- derived sequences under different sequencing depths and read lengths. Our results consistently showed that TRUST4 outperformed others across multiple datasets, while MiXCR and DeRR also demonstrated considerable accuracy. We also discovered that the sequencing depth inherently imposes a critical constraint on successful TCR construction from scRNA-seq data. In summary, we present a benchmark study to aid researchers in choosing the most appropriate methods for reconstructing TCR from scRNA-seq data.

bioinformatics↗

bioRxiv2024

The persistent effects of predator odor stressor enhance interoceptive sensitivity to alcohol through GABA-A receptor adaptations in the prelimbic cortex in male, but not female rats

BackgroundTraumatic stress is associated with high rates of problematic alcohol use, but how the persistent effects of trauma impact sensitivity to alcohol remain unknown. This study examined the persistent effects of traumatic stress exposure on sensitivity to alcohol and underlying neurobiological mechanisms in rats. MethodsMale (N=98) and female (N=98) Long-Evans rats were exposed to the predator odor TMT, and two weeks later, molecular, neuronal, and behavioral sensitivity to alcohol were assessed. Next, rats were trained to discriminate alcohol from water (male N=70; female N=56), and the impact of TMT on interoceptive sensitivity to alcohol and the alcohol-like effects of systemic GABAA receptor activation were evaluated. Lastly, functional involvement of GABAA and NMDA receptors in the prelimbic cortex (PrL) and the anterior insular cortex (aIC) was investigated. ResultsTMT exposure sex-dependently altered PrL Gabra1, and elevated aIC Grin2b and Grin2c in males. TMT increased PrL c-Fos in males, which was attenuated by alcohol administration. Alcohol-induced locomotor and startle response effects were attenuated in the TMT group in both sexes. TMT exposure potentiated interoceptive sensitivity to alcohol in males but not in females, and this effect was driven by GABAA receptors in the PrL. Greater stress reactivity during TMT exposure was associated with higher interoceptive sensitivity to alcohol, and alcohol exposure history was linked to a heightened stress response to TMT in males. ConclusionsTraumatic stress increased interoceptive sensitivity to alcohol in males, but not females, through PrL GABAA receptor adaptations, potentially enhancing the stimulatory, and by extension the rewarding, effects of alcohol.

neuroscience↗

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↗