Biology subjects

Zhu, Z.

Publications and source records attributed to Zhu, Z..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

Dynamic regulation of mRNA acetylation at synapses by learning and memory

Precise regulation of protein synthesis is critical for brain functions such as long-term memory, and its dysregulation is implicated in numerous memory disorders. While mRNA methylation such as N6-methyladenosine (m6A) that has been widely studied in memory, the role of mRNA acetylation remains largely unknown. N4-acetylcytidine (ac4C), the only known form of RNA acetylation in eukaryotes, promotes mRNA stability and translation. In this study, we identified the ac4C epitranscriptome in mouse hippocampal homogenates and synaptosomes through ac4C-RNA immunoprecipitation followed by next-generation sequencing (acRIP-seq). The Morris water maze (MWM) was employed to induce and evaluate memory acquisition and forgetting processes. We show that synaptic ac4C levels are dynamically regulated, increasing after memory formation and returning to baseline after natural forgetting. The dynamic changes of ac4C-mRNAs regulated by memory were validated by ac4C dot-blot, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and acRIP-qPCR analysis. We further demonstrate that NAT10, the ac4C writer, in mouse hippocampus is important for spatial memory via regulating memory-related mRNAs, proteins, and ultimately synaptic plasticity. Lastly, we generated a freely-accessible website (http://ac4catlas.com) that included the dataset of ac4C epitranscriptome in mouse hippocampus. Altogether these results demonstrate that dynamic and localized mRNA acetylation is important for synaptic plasticity and memory.

neuroscience↗

bioRxiv2024

Identification of the potential function-specific sites in subunits of vertebrate neuronal nicotinic acetylcholine receptors

The nicotinic acetylcholine receptors (nAChR) are complexes that are composed of subunits evolved from common ancestor. Although the subunits are similar in sequences and structures, their molecular function varies significantly. Therefore, detecting the molecular sites specific to each subunit is important to understand the property of the subunits and the receptors formed by them. As we know, the molecular sites critical to the structure and molecular function of a protein family usually are conserved in evolution, and those specific to each member of the family are often closely related to its structural and functional specificity. In this study, we analyzed the sequence specific sites in nAChR subunits by adopting the evolutionary trace method and the two-state model, and explored the relationship between structure and function in combination with the spatial location of the sites. The results showed that the detected sites in 7 subunit were closely related to ligand binding and conformational changes of the energetic coupling pathway. The conserved sites tended to be distributed in the interior of the spatial structure of protein molecules, and the sites potentially related to new functions were distributed on the surface of the spatial structure. In summary, our results could be helpful to understanding the molecular features related to the function specificity and diversity of the nAChR subunits.

bioinformatics↗

bioRxiv2024

Hypocotyl Development in Arabidopsis and other Brassicaceae Displays Evidence of Photoperiodic Memory

Sensing and responding to photoperiod changes is essential for plants to adapt to seasonal progression. Most of our understanding of how plants sense photoperiodic changes is through studies on flowering time. However, other aspects of plant development are regulated by the photoperiod, including hypocotyl elongation. Unlike flowering, hypocotyl elongation displays a greater plasticity to changes in the photoperiod with increases in daylength causing greater inhibition of growth until a threshold is met. Previous studies have only looked at hypocotyl development in the context of a stationary photoperiod. It is unknown if changes in the photoperiod during development influence hypocotyl elongation. Here, we developed a physiological assay to investigate this question. We have discovered that hypocotyl elongation is influenced by a memory of past photoperiod exposure in Arabidopsis and Brassicaceae cultivars used for microgreen agriculture. Photoperiodic memory persisted for multiple days, although it weakened over time, and the strength of the memory was dependent on the genetic background. We identified that phyB and ELF3, key regulators of hypocotyl development, were required for photoperiodic memory. Finally, we identified that the circadian clock is unlikely to function as a repository for photoperiodic memory as circadian rhythms quickly re-aligned with the new photoperiod. In summary, our work highlights for the first-time evidence of a photoperiodic memory that can control plant development.

plant biology↗

bioRxiv2024

Nicotine Ameliorates α-synuclein Pre-formed Fibril-Induced Behavioral Deficits and Pathological Features in Mice

BackgroundEpidemiologic study suggests nicotine reduces risk of PD, could be potential treatment for Parkinsons disease. ObjectiveTo study the effect of nicotine on behavioral phenotypes and pathological characteristics of mice induced by human alpha-synuclein preformed fibers (-syn-PFF). MethodsMice were injected with 5 g of human -syn-PFF in the hippocampus while administering nicotine-containing drinking water (200g/mL). After 1 month, the motor ability, mood, spatial learning, and memory ability of the Parkinsons disease(PD)phenotype-like model were detected using open field, rotarod, Y maze, and O maze tests. The expression of pathological -syn, apoptotic proteins and the numbers of glial cells and neural stem cells in the hippocampus of mice were detected using western blotting and immunofluorescence. ResultsNicotine significantly reduced pathological -syn accumulation, -syn serine 129 phosphorylation and cell death caused by PFF injection in the hippocampus of mice, inhibited the increase of glial, microglia and apoptotic cells, decreased the expression levels of PI3K and Akt. ConclusionsNicotine may have inhibitory effects on human -syn-PFF-induced neuroinflammation and apoptosis. Thus, it reduces human -syn-PFF-induced behavioral deficits and pathological changes in mice.

animal behavior and cognition↗

bioRxiv2024

Analyzing the Involvement of Cholinesterases in the Immune Landscape of Lung Adenocarcinoma and Their Prognostic Values

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer and its prognosis is poor. The cholinergic system is involved in the development of lung cancer but its role is still unclear. In this study, we collected 231 cholinergic-related genes, and examined their expression in LUAD samples and normal tissues, from which 37 differentially expressed genes were screened. Then, by survival analysis, we identified 7 genes related to the prognosis of LUAD, among which acetylcholinesterase (ACHE) and butyrylcholinesterase (BCHE) were included. The expression of AChE was upregulated in LUAD samples, and its expression had a significant positive correlation with the prognosis of male patients. But the expression of BChE was down-regulated in LUAD samples, and the elevated BChE expression was associated with a good prognosis in women and non-smoking patients. We also observed a close relationship between the two genes and immune landscape of LUAD. The AChE high expression patients had a higher ratio of tumor-infiltrating immune cells than the low expression patients, while the BChE high expression group had higher ratios of both tumor-infiltrating immune cells and stromal cells. We collected a total of 113 immunomodulatory genes associated with AChE and BChE to build an immunoregulatory network, which comprised several gene clusters. We also found that the expression of AChE and BChE was associated with immune escape in LUAD. Our results showed that AChE and BChE may play an important role in the development of LUAD, and could be promising biomarkers and targets for its diagnosis and treatment.

molecular biology↗

bioRxiv2024

LETSmix: a spatially informed and learning-based domain adaptation method for cell-type deconvolution in spatial transcriptomics

Spatial transcriptomics (ST) has revolutionized our understanding of gene expression patterns by incorporating spatial context. However, many ST technologies operate on heterogeneous cell mixtures due to limited spatial resolution. To resolve cell type composition at each sequencing spot, several deconvolution methods have been proposed. Yet, these approaches often underutilize spatial context inherent in ST data and paired histopathological images, meanwhile overlooking domain variances between ST and reference single-cell RNA sequencing (scRNA-seq) data. Here, we present LETSmix, a novel deconvolution method that enhances spatial correlations within ST data using a tailored LETS filter, and employs a mixup-augmented domain adaptation strategy to address domain shifts. The performance of LETSmix was validated across diverse ST platforms and tissue types, including 10x Visium human dorsolateral prefrontal cortex, ST human pancreatic ductal adenocarcinoma, 10x Visium mouse liver, and Stereo-seq mouse olfactory bulb datasets. Our findings demonstrate that the proposed method accurately estimates cell type proportions and effectively maps them to the expected regions, establishing a new record among current state-of-the-art models. LETSmix is expected to serve as a robust tool for advancing studies on cellular composition and spatial architecture in spatial transcriptomics. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/591425v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1b264cborg.highwire.dtl.DTLVardef@f77e8forg.highwire.dtl.DTLVardef@9609ddorg.highwire.dtl.DTLVardef@61af58_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Dissociable memory modulation mechanisms facilitate fear amnesia at different timescales

Memory reactivation renders consolidated memory fragile and thereby opens the window for memory updates, such as memory reconsolidation. However, whether memory retrieval facilitates update mechanisms other than memory reconsolidation remains unclear. We tested this hypothesis in three experiments with healthy human participants. First, we demonstrate that memory retrieval-extinction protocol prevents the return of fear expression shortly after extinction training and this short-term effect is memory reactivation dependent (Study 1, N = 57 adults). Furthermore, across different timescales, the memory retrieval-extinction paradigm triggers distinct types of fear amnesia in terms of cue-specificity and cognitive control dependence, suggesting that the short-term fear amnesia might be caused by different mechanisms from the cue-specific amnesia at a longer and separable timescale (Study 2, N = 79 adults). Finally, using continuous theta-burst stimulation (Study 3, N = 75 adults), we directly manipulated brain activity in the dorsolateral prefrontal cortex, and found that both memory reactivation and intact prefrontal cortex function were necessary for the short-term fear amnesia after the retrieval-extinction protocol. The differences in temporal scale, cue-specificity, and cognitive control ability dependence between the short- and long-term amnesia suggest that memory retrieval and extinction training trigger distinct underlying memory update mechanisms. These findings suggest the potential involvement of coordinated memory modulation processes upon memory retrieval and may inform clinical approaches for addressing persistent maladaptive memories.

neuroscience↗

bioRxiv2024

Problem-Solving as a Language: A Computational Lens into Human and Monkey Intelligence

1Human intelligence is characterized by our remarkable ability to solve complex problems. This involves planning a sequence of actions that leads us from an initial state to a desired goal state. Quantifying and comparing problem-solving capabilities across species and finding its evolutional roots is a fundamental challenge in cognitive science, and is critical for understanding how the brain carries out this intricate process. In this study, we introduce the Language of Problem-Solving (LoPS) model as a novel quantitative framework that investigates the structure of problem-solving behavior through a language model. We adapted the classic Pac-Man game as a cross-species behavioral paradigm to test both humans and macaque monkeys. Using the LoPS model, we extracted the latent structure -- or grammar -- embedded in the agents gameplay, revealing the non-Markovian temporal structure of their problem-solving behavior. The LoPS model captured fine-grained individual differences among the players and revealed the striking differences in the complexity and hierarchical organization of problem-solving behavior between humans and monkeys, reflecting the distinct cognitive capabilities of each species. Furthermore, both humans and monkeys evolved their LoPS grammars during learning, progressing from simpler to more complex ones, suggesting that the language of problem-solving is not fixed, but rather evolves to support more sophisticated and efficient problem-solving. Through the lens of a language model, our study provides insights into how humans and monkeys break down problem-solving into compositional units and navigate complex tasks. This framework deepens our understanding of human intelligence and its evolution, and establishes a foundation for future investigations of the neural mechanisms of problem-solving.

neuroscience↗

bioRxiv2024

Construction of Animal Models Based on Exploring Pathological Features and Mechanisms of Different Locations in the Progression of DVT-APTE-CTEPD/CTEPH

BackgroundChronic thromboembolic pulmonary disease (CTEPD) and chronic thromboembolic pulmonary hypertension (CTEPH) are sequelae of acute pulmonary embolism (APE) and severely affect patients health and quality of life. The treatment of these conditions is challenging, and their underlying mechanisms remain unclear. The main reason for this is the lack of an animal model that can fully simulate the entire chain of DVT-APTE-CTEPD/CTEPH progression. The objective of this study is to construct an ideal animal model that simulates the major pathological changes of DVT-APTE-CTEPD/CTEPH and can be used for mechanistic exploration. We aim to compare the advantages and disadvantages of different modeling approaches and provide an experimental basis for investigating the mechanisms of pulmonary embolism chronicization at different stages of evolution. Methods and MaterialsWe first evaluated the pathological changes in the pulmonary arterial intima stripping tissue of CTEPH patients. Animal models were established by multiple injections of thrombus columns through the internal jugular vein to simulate distal remodeling of the pulmonary artery. To simulate significant remodeling and fibrosis in the middle and distal segments of the pulmonary artery, thrombus columns were injected along with splenectomy. A CTEPD model with intimal fibrosis remodeling was successfully established by selectively injecting large thromboemboli into the pulmonary artery sites in large animals (dogs). A rat model with pathological manifestations of intimal fibrosis remodeling in the proximal end of the pulmonary artery was constructed using large thrombi combined with nitric oxide synthase inhibitors. An animal model of DVT was established using the inferior vena cava ligation method. ResultsAccording to the different pathological features and mechanisms observed in the progression of human DVT-APTE-CTEPD/CTEPH, we constructed animal models that conform to these pathological manifestations and mechanisms, each with its own advantages. Furthermore, the different methods used to construct animal models can be integrated and applied together. ConclusionAnimal models constructed using different modeling methods can effectively simulate the pathological and physiological manifestations of the corresponding stages of chronic pulmonary embolism. Researchers can select the aforementioned models according to their specific research purposes, directions, and requirements.

zoology↗

bioRxiv2024

Neuroprotective Effects of Bioactive Molecules Derived from Tobacco as Potential Therapeutic Candidates for Alzheimer Disease

Neurodegenerative diseases are significant global health challenges, particularly with an aging population. While tobacco is traditionally linked to health risks, recent studies suggest it may contain compounds beneficial for neurodegenerative conditions. Herein, we explore the potential of bioactive compounds in tobacco as neuroprotective agents for Alzheimers disease (AD). Using genetic engineering, we developed a novel approach with neural progenitor cells (NPCs) derived from embryonic stem cells, equipped with an NF-{kappa}B reporter system to screen tobacco extracts. Our screenings identified three compounds with significant inhibitory effects on NF-{kappa}B activation, a key mediator of neuroinflammation in AD. Among these, rutin exhibited profound neuroprotective effects in an NPC damage model induced by Amyloid-{beta}25-35, reducing apoptotic cell death, enhancing cellular proliferation, and activating critical survival signaling pathways. This modulation underlies rutins anti-inflammatory and neuroprotective activities. Together, our findings support the potential of tobacco-derived compounds in AD therapy and lay the foundation for further exploration of their pharmaceutical value.

pharmacology and toxicology↗

bioRxiv2024

Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction

Structure-based machine learning algorithms have been utilized to predict the properties of protein-protein interaction (PPI) complexes, such as binding affinity, which is critical for understanding biological mechanisms and disease treatments. While most existing algorithms represent PPI complex graph structures at the atom-scale or residue-scale, these representations can be computationally expensive or may not sufficiently integrate finer chemical-plausible interaction details for improving predictions. Here, we introduce MCGLPPI, a novel geometric representation learning framework that combines graph neural networks (GNNs) with the MARTINI molecular coarse-grained (CG) model to predict overall PPI properties accurately and efficiently. This framework maps proteins onto a concise CG-scale complex graph, where nodes represent CG beads and edges encode chemically plausible interactions. The GNN-based encoder is tailored to extract high-quality representations from this graph, efficiently capturing the overall properties of the protein complex structure. Extensive experiments on three different downstream PPI property prediction tasks demonstrate that MCGLPPI achieves competitive performance compared with the counterparts at the atom- and residue-scale, but with only a third of the computational resource consumption. Furthermore, the CG-scale pre-training on protein domain-domain interaction structures enhances its predictive capabilities for PPI tasks. MCGLPPI offers an effective and efficient solution for PPI overall property predictions, serving as a promising tool for the large-scale analysis of biomolecular interactions.

bioinformatics↗

bioRxiv2024

Engineered Migrasomes: A Robust, Thermally Stable Vaccination Platform

The increasing ability of pathogens and tumor cells to evade immune detection underscores the urgent need for novel vaccine platforms leveraging diverse biological mechanisms. Additionally, logistical challenges associated with cold-chain transportation significantly limit vaccine accessibility, especially in resource-limited regions. Recently, we identified migrasomes, specialized organelles generated during cell migration, which are inherently stable and enriched with immune-modulating molecules. To address the low yield of natural migrasomes, we engineered migrasome-like vesicles (eMigrasomes) using hypotonic shock combined with cytoskeletal disruption to enhance vesicle formation. The biogenesis of eMigrasomes relies on the core migrasome machinery, faithfully recapitulating the biophysical attributes of native migrasomes while significantly improving production efficiency. We demonstrate that eMigrasomes loaded with a model antigen elicit potent antibody responses and maintain structural integrity and immunogenic potential at room temperature. Furthermore, eMigrasomes displaying the SARS-CoV-2 Spike protein induce robust humoral immune responses, providing effective protection against viral infection. Our findings highlight the potential of utilizing migrasome biology and hypotonic shock-driven vesicle generation as an innovative, stable, and broadly accessible vaccine platform.

cell biology↗

bioRxiv2024

Epigenetic Reprogramming of Autophagy Drives Mutant IDH1 Glioma Progression and Response to Radiation

Mutant isocitrate dehydrogenase 1 (mIDH1) exhibits a gain of function mutation enabling 2-hydroxyglutarate (2HG) production and epigenetic reprogramming. This leads to enhanced DNA-damage response and radioresistance in mIDH1 gliomas. RNA-seq and ChIP-seq data revealed that human and mouse mIDH1 glioma neurospheres have downregulated gene ontologies (GOs) related to mitochondrial metabolism and upregulated GOs related to autophagy. Decreased mitochondrial metabolism was accompanied by decreased glycolysis, rendering autophagy a source of energy in mIDH1 gliomas. Human and mouse mutant IDH1 glioma cells exhibited increased expression of pULK1-S555 and enhanced LC3 I/II conversion, indicating augmented autophagy. Additionally, scRNA-seq data from human mIDH1 astrocytoma patients samples showed decreased mitochondrial metabolism and increased autophagy. We further demonstrate that inhibiting autophagy in vivo by systemic administration of synthetic protein nanoparticles encapsulating siRNA targeting Atg7 sensitized mIDH1 glioma cells to radiation-induced cell death, resulting in tumor regression, long-term survival, and immunological memory. In summary, our work uncovered that autophagy is a critical pathway for survival in mIDH1 gliomas and by blocking this pathway we can elicit radiosensitivity in vitro in human and mouse mIDH1 glioma cells, and in vivo in genetically engineered mouse models. Our data also highlights that blocking autophagy has significant potential for clinical translation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/584091v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@111f4a9org.highwire.dtl.DTLVardef@1d5bb30org.highwire.dtl.DTLVardef@f467ecorg.highwire.dtl.DTLVardef@1d2e9b5_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract:C_FLOATNO Our genetically engineered mIDH1 mouse glioma model harbors IDH1R132H in the context of ATRX and TP53 knockdown. The production of 2-HG elicited an epigenetic reprogramming associated with a disruption in mitochondrial activity and an enhancement of autophagy in mIDH1 glioma cells. Autophagy is a mechanism involved in cell homeostasis related with cell survival under energetic stress and DNA damage protection. Autophagy has been associated with radio resistance. The inhibition of autophagy thus radio sensitizes mIDH1 glioma cells and enhances survival of mIDH1 glioma-bearing mice, representing a novel therapeutic target for this glioma subtype with potential applicability in combined clinical strategies. C_FIG

cancer biology↗

bioRxiv2024

High Frequency Terahertz Stimulation Alleviates Neuropathic Pain by Inhibiting the Pyramidal Neuron Activity in the Anterior Cingulate Cortex of mice

Neuropathic pain (NP) is caused by a lesion or disease of the somatosensory system and is characterized by abnormal hypersensitivity to stimuli and nociceptive responses to non-noxious stimuli, affecting approximately 7-10% of the general population. However, current first-line drugs like non-steroidal anti-inflammatory agents and opioids have limitations, including dose-limiting side effects, dependence, and tolerability issues. Therefore, developing new interventions for the management of NP is urgent. In this study, we discovered that the high-frequency terahertz stimulation (HFTS) at approximate 36 THz effectively alleviates NP symptoms in mice with spared nerve injury. Computational simulation suggests that the frequency resonates with the carbonyl group in the filter region of Kv1.2 channels, facilitating the translocation of potassium ions. In vivo and in vitro results demonstrate that HFTS reduces the excitability of pyramidal neurons in the anterior cingulate cortex through enhancing the voltage-gated K+ and also the leak K+ conductance. This research presents a novel optical intervention strategy with terahertz waves for the treatment of NP and holds promising application in other nervous system diseases.

neuroscience↗

bioRxiv2024

DenoiseST: A dual-channel unsupervised deep learning-based denoising method to identify spatial domains and functionally variable genes in spatial transcriptomics

Spatial transcriptomics provides a unique opportunity for understanding cellular organization and function in a spatial context. However, spatial transcriptome exists the problem of dropout noise, exposing a major challenge for accurate downstream data analysis. Here, we proposed DenoiseST, a dual-channel unsupervised adaptive deep learning-based denoising method for data imputing, clustering, and identifying functionally variable genes in spatial transcriptomics. To leverage spatial information and gene expression profiles, we proposed a dual-channel joint learning strategy with graph convolutional networks to sufficiently explore both linear and nonlinear representation embeddings in an unsupervised manner, enhancing the discriminative information learning ability from the global perspectives of data distributions. In particular, DenoiseST enables the adaptively fitting of different gene distributions to the clustered domains and employs tissue-level spatial information to accurately identify functionally variable genes with different spatial resolutions, revealing their enrichment in corresponding gene pathways. Extensive validations on a total of 18 real spatial transcriptome datasets show that DenoiseST obtains excellent performance and results on brain tissue datasets indicate it outperforms the state-of-the-art methods when handling artificial dropout noise with a remarkable margin of [~]15%, demonstrating its effectiveness and robustness. Case study results demonstrate that when applied to identify biological structural regions on human breast cancer spatial transcriptomic datasets, DenoiseST successfully detected biologically significant immune-related structural regions, which are subsequently validated through Gene Ontology (GO), cell-cell communication, and survival analysis. In conclusion, we expect that DenoiseST is a novel and efficient method for spatial transcriptome analysis, offering unique insights into spatial organization and function.

bioinformatics↗

bioRxiv2024

Disentangling Mnemonic Metacognition from Confidence by Communication between the Precuneus and Hippocampus

Metacognition, the ability to introspectively monitor ones own performance, remains an area with poorly understood neural mechanisms, particularly regarding the intercommunication among various brain regions. Recent studies have identified the precuneus as a key region in mnemonic metacognitive tasks, while the hippocampus is recognized for its role in memory function. This study aimed to investigate the role of the precuneus and hippocampus in mnemonic metacognition by utilizing intracranial electrode recordings from patients with intractable epilepsy to analyze the correlational dynamics between these regions. Our findings revealed that high gamma activity serve as a key feature in both the precuneus and hippocampus for confidence judgment. Based on signal detection theory (SDT), we discovered that high gamma activity in the precuneus is significantly linked to type 2 sensitivity (meta-d), while hippocampal high gamma activity was primarily linked to type 1 sensitivity (d). Additionally, the correlation between high gamma activity in the hippocampus and precuneus was exclusively related to type 2 sensitivity (meta-d). Temporal analysis indicated that the hippocampus is initially engaged for the memory process, followed by its joint engagement together with the precuneus for confidence generation. These findings elucidate the distinct electrophysiological roles of the hippocampus and precuneus in mnemonic metacognition, providing deeper insights into the neural mechanisms underlying this cognitive process.

neuroscience↗

bioRxiv2024

LncRNA GAS6-AS1 contributes to 5-fluorouracil resistance in colorectal cancer

5-Fluorouracil (5-FU) resistance has always been a formidable obstacle in the adjuvant treatment of advanced colorectal cancer (CRC). In recent years, long non-coding RNAs have emerged as key regulators in various pathophysiological processes including 5-FU resistance. Here, RNA-seq combined with weighted gene correlation network analysis confirmed the close association of GAS6-AS1 with TRG grades. GAS6-AS1 expression was positively correlated with advanced clinicopathological features and poor prognosis in CRC. GAS6-AS1 increased the 50% inhibiting concentration of 5-FU, enhanced cell proliferation, and accelerated G1/S transition in CRC cells, both with and without 5-FU, both in vitro and in vivo. Mechanistically, GAS6-AS1 enhanced the stability of MCM3 mRNA by recruiting PCBP1, consequently increasing MCM3 expression. Furthermore, PCBP1 and MCM3 counteracted the effects of GAS6-AS1 on 5-FU resistance. Notably, the PDX model indicated that combining chemotherapeutic drugs with GAS6-AS1 knockdown yielded superior outcomes in vivo. Together, our findings elucidate that GAS6-AS1 directly binds to PCBP1, enhancing MCM3 expression and thereby promoting 5-FU resistance. GAS6-AS1 may serve as a robust biomarker and potential therapeutic target for combination therapy in CRC.

molecular biology↗

bioRxiv2024

A dual-gene reporter-amplifier architecture for enhancing the sensitivity of molecular MRI by water exchange

The development of genetic reporters for magnetic resonance imaging (MRI) is essential for investigating biological functions in intact animals. However, current MRI reporters have low sensitivity, making it challenging to create significant contrast against the tissue background, especially when only a small percentage of cells express the reporter. To overcome this limitation, we developed an approach that amplifies signals by co-expressing an MRI reporter gene, Oatp1b3, with a water channel, aquaporin-1 (Aqp1). We first show that the expression of Aqp1 amplifies the paramagnetic relaxation effect of Oatp1b3 by facilitating transmembrane water exchange. This mechanism provides Oatp1b3-expressing cells with access to a larger water pool compared with typical exchange-limited conditions. We further demonstrated that our methodology allows dual-labeled cells to be detected using approximately 10-fold lower concentrations of contrast agent than that in the Aqp1-free scenario. Finally, we show that our approach enables the imaging of mixed-cell populations containing a low fraction of Oatp1b3-labeled cells that are otherwise undetectable based on Oatp1b3 expression alone.

bioengineering↗