Biology subjects

Xu, X.

Publications and source records attributed to Xu, X..

At least 235 records · Page 13Linked to original sources

bioRxiv2025

The ift140-Deficient Zebrafish: A Model for Renal Cystogenesis and an F0-Based Screen to Identify Genetic Modifiers of Kidney Cysts

Genetic modifiers are believed to play an important role in the onset and severity of polycystic kidney disease (PKD), but identifying these modifiers has been challenging due to the lack of effective methodologies. In this study, we investigated zebrafish mutants of IFT140, a newly identified ADPKD gene, and observed phenotypes similar to those seen in mammalian models, including kidney cysts and bone defects. Using efficient microhomology-mediated end joining (MMEJ)-based genome editing technology, we demonstrated that ift140 CRISPRants recapitulate mutant phenotypes while bypassing the early lethality of the mutants to allow for renal cyst analysis in adult fish. In addition to cilia defects, non-cilia phenotypes, such as disrupted cell polarity and aberrant microtubule stabilization in kidney epithelial cells, may also contribute to ift140-associated cystogenesis. Importantly, the ability to detect ift140-associated renal cysts with ease allowed us to develop an F0-based genetic screen to identify potential protective modifiers. A pilot screen of sixteen genes previously linked to dysregulated signaling pathways in ADPKD revealed both known and novel modifiers, including mtor and ulk1a. Inhibition of mtor and ulk1a reversed both cilia-related and non-cilia-related abnormalities. In summary, our study underscores the potential of using zebrafish as a model for the efficient discovery of genetic modifiers of kidney cysts.

genetics↗

bioRxiv2024

CDH3-AS1 antisense RNA enhances P-cadherin translation and acts as a tumor suppressor in melanoma

Thousands of regulatory noncoding RNAs (ncRNAs) have been annotated; however, their functions in gene regulation and contributions to cancer formation remain poorly understood. To gain a better understanding of the influence of ncRNAs on gene regulation during melanoma progression, we mapped the landscape of ncRNAs in melanocytes and melanoma cells. Nearly half of deregulated genes in melanoma are ncRNAs, with antisense RNAs (asRNAs) comprising a large portion of deregulated ncRNAs. CDH3-AS1, the most significantly downregulated asRNA, overlaps the CDH3 gene, which encodes P-cadherin, a transmembrane glycoprotein involved in cell adhesion that was also reduced in melanoma. Overexpression of CDH3-AS1 increased cell aggregation and reduced xenograft tumor growth, mimicking the tumor-suppressive effects of CDH3. CDH3-AS1 interacted with CDH3 mRNA and enhanced P-cadherin protein levels. Interestingly, secondary structures at the CDH3 5 end regulated P-cadherin translation, and ribosome profiling revealed that CDH3-AS1 promotes ribosome occupancy at the CDH3 mRNA. Notably, ribosome occupancy was generally increased in mRNAs having cognate asRNA that are complementary to the 5UTR. Taken together, this study revealed the CDH3-AS1-mediated enhancement of P-cadherin translation, underscoring the broader potential of asRNAs as regulators of protein-coding genes and their role in diseases like melanoma.

molecular biology↗

bioRxiv2024

Development of a novel peripherally acting alpha2A-adrenergic receptor antagonist for anti-diabetic

Yohimbine, a potent alpha2A-adrenergic receptor (2AAR) antagonist, was found therapeutic potential for type 2 diabetes through improving insulin release. However, the adverse side effects mediated by its actions in the brain hampered its use. Here, based on molecular docking analysis and structural modification, we have developed a novel peripherally acting yohimbine derivative (CDS479-2). CryoEM data found that yohimbine and CDS479-2 have similar interactions with the structure of 2AAR. Importantly, CDS479-2 shows similar 2AAR antagonist activity as yohimbine, but with very limited access to the brain, and thus avoiding the unwanted central effects such as hypertension and anxiety. Acute administration of CDS479-2 by injection or gavage lowered blood glucose levels and improved glucose tolerance in the high-fat diet-induced obesity (DIO) mice, an animal model for human type 2 diabetes. Remarkably, DIO mice received 2 weeks of daily administration of CDS479-2, but not yohimbine, exhibited sustained normoglycaemia, and increased density of the insulin-producing beta cells, in which important proliferation genes were found upregulated. Moreover, the overall protein expression levels of their pancreas were more similar to that of the healthy chow-fed mice. Thus, CDS479-2 may indicate a new direction for type 2 diabetes treatment. Importantly, the strategy we employed in this study will inspire the optimization for drugs that with both peripheral and central targets. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/628818v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1d3d7corg.highwire.dtl.DTLVardef@1afbad3org.highwire.dtl.DTLVardef@12a1aborg.highwire.dtl.DTLVardef@1341a02_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2024

THE IMPACT OF EXPERIMENTAL DESIGNS & SYSTEM SLOPPINESS ON THE PERSONALISATION PROCESS: A CARDIOVASCULAR PERSPECTIVE

To employ a reduced-order cardiovascular model as a digital twin for personalised medicine, it is essential to understand how uncertainties in the models input parameters affect its outputs. The aim is to identify a set of input parameters that can serve as clinical biomarkers, providing insight into a patients physiological state. Given the challenge of finding useful clinical data, careful consideration must be given to the experimental design used to acquire patient-specific input parameters. In this paper, we conduct the first quantification of a cardiovascular systems sloppiness to elucidate the structure of the input parameter space. By utilising Sobol indices and examining various synthetic cardiovascular measures with increasing invasiveness, we uncover how the personalisation process and the cardiovascular systems sloppiness are contingent upon the chosen experimental design. Our findings reveal that continuous clinical measures induce system sloppiness and increase the number of personalisable biomarkers, whereas discrete clinical measurements produce a non-sloppy system with a reduced number of biomarkers. This study underscores the necessity for careful consideration of available clinical data as differing measurement sets can significantly impact model personalisation. Author SummaryIn personalised medicine, computational models that replicate physical systems -- are becoming vital tools for understanding and predicting individual health. Our study explores cardiovascular models, which simulate heart and circulatory functions from which clinical metrics may be derived. These models aim to provide personalised insights into heart health and treatment planning. A key challenge in building these models is addressing "sloppiness," a property which provides vital insight into the response surface structure for which one calibrates a model searching for a global minimum point, a position in parameter space which best represents a patients cardiovascular health. In order to personalise a model different types of clinical metrics must be available for a model response to be compared to. We examined how different types of clinical data -- ranging from simple discrete blood pressure readings to detailed invasive continuous waveform data -- impact model sloppiness and the number of personalisable biomarkers. Our results show that continuous measurements increase the number of personalisable biomarkers but make the personalisation process more complex through increased sloppiness. In contrast, simpler discrete measurements reduce model sloppiness simplifying the personalisation process but yield fewer personalisable biomarkers. By analysing the impact of experimental designs on the personalisation process, our work offers practical insights into improving the reliability of cardiovascular digital twins, supporting their adoption in personalised medicine.

systems biology↗

bioRxiv2024

Convincing Evidence of Carnivorous Diet in Alvarezsaurian Dinosaur

A dietary shift from carnivory to insectivore has been proposed to explain the dramatic morphological evolution of alvarezsaurians, particularly the adaptation related to the manual digital reduction and body size miniaturization. However, based solely on morphological shifts, this hypothesis lacked direct dietary evidence to support either carnivory or insectivore. Here, we present the first convincing dietary evidence for alvarezsaurians, derived from the intestinal contents of the Early Cretaceous Bannykus wulatensis. Our analysis revealed significantly higher levels of calcium and phosphorus in the intestinal contents compared to the surrounding sandstone. Scanning electron microscopy identified hard tissue debris and possible soft tissues surrounding by phosphatized bacteria and tightly packed hollow microspheres, suggesting that the intestinal contents were strongly pseudomorphed by phosphatized microbes during fossilization. Raman spectroscopy showed characteristic peaks indicative of bone-derived material, consistent with the hard tissue debris appeared in the intestinal contents. Our results suggest that Bannykus had a carnivorous diet with strong chemical digestion, which likely compensated for its delicate cranial structures and small teeth. These results imply that if a dietary shift to insectivore occurred, it likely took place later in alvarezsaurian evolution, probably coinciding with a reduction in body size.

paleontology↗

bioRxiv2024

ANKRD5: a key component of the axoneme required for spermmotility and male fertility

Sperm motility is essential for male fertility and depends on the structural integrity of the sperm axoneme, which features a canonical "9+2" microtubule arrangement. This structure comprises nine outer doublet microtubules (DMTs) that are associated with various macromolecular complexes. Among them, the nexin-dynein regulatory complex (N-DRC) forms crossbridges between adjacent DMTs, contributing to their stabilization and enabling flagellar bending. In this study, we investigated Ankyrin repeat domain 5 (ANKRD5, also known as ANK5 or ANKEF1), a protein highly expressed in the sperm axoneme. We found that ANKRD5 interacts with DRC5/TCTE1 and DRC4/GAS8, two key components of the N-DRC, and these interactions occur independently of calcium regulation. Male Ankrd5-/- mice exhibited impaired sperm motility and infertility. Cryo-electron tomography revealed a typical "9+2" axoneme structure with intact DMTs in Ankrd5 null sperm; however, the DMTs showed pronounced morphological variability and increased structural heterogeneity. Notably, ANKRD5 deficiency did not alter ATP levels, reactive oxygen species (ROS) levels, or mitochondrial membrane potential. These findings suggest that ANKRD5 may attenuate the N-DRCs mechanical buffering-akin to a "car bumper"-between adjacent DMTs, thereby compromising axonemal stability under high mechanical stress during vigorous flagellar beating. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/626701v3_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1ca36eforg.highwire.dtl.DTLVardef@dcafe3org.highwire.dtl.DTLVardef@9f6086org.highwire.dtl.DTLVardef@17a0a0b_HPS_FORMAT_FIGEXP M_FIG C_FIG Significance StatementMale infertility affects approximately 8%-12% of men globally, with defects in sperm motility accounting for over 80% of these cases. The axoneme, which functions as the motor apparatus of the sperm, adopts a canonical "9+2" microtubule arrangement, where the nexin-dynein regulatory complex (N-DRC) plays a critical role in providing structural support between adjacent outer microtubule doublets. Elucidating the interplay between the structural organization and protein composition of the N-DRC is essential for advancing the understanding of male reproductive biology. In this study, we identify ANKRD5 as a new component of N-DRC that is essential for maintaining normal sperm motility. These findings contribute to the molecular understanding of sperm motility and highlight ANKRD5 as a potential target for the development of novel male contraceptives.

developmental biology↗

bioRxiv2024

Assessing target genes for homing suppression gene drive

Gene drives are engineered alleles that bias their own inheritance in offspring, enabling the spread of specific traits throughout a population. Targeting female fertility genes in a gene drive can be an efficient strategy for population suppression. In this study, we investigated nine female fertility genes in Drosophila melanogaster using CRISPR-based homing gene drives. Employing a multiplexed gRNA approach to prevent the formation of functional resistance alleles, we aimed to maintain high drive conversion efficiency with low fitness costs in female drive carriers. Drive efficiency was assessed in individual crosses and had varied performance across different target genes. Notably, drives targeting the octopamine {beta}2 receptor (oct) and stall (stl) genes exhibited the highest drive conversion rates and were further tested in cages. A drive targeting stl successfully suppressed a cage population with a high release frequency, though suppression failed in another replicate cage with a lower initial release frequency. Fitness costs in female drive carriers were observed in test cages, impacting the overall efficiency of population suppression. Further tests on the fertility of these lines using individual crosses indicated that some fitness costs were due to maternal deposition of Cas9 combined with new gRNA expression, which would only occur in progeny of drive males when testing split drives with separate Cas9 (when mimicking cages with complete drives) but not for complete drive systems. This could enable success in complete drives with higher maternal Cas9 deposition, even if cage experiments in split drives fail. Our findings underscore the potential and challenges of assessing gene drives for population control, providing valuable insights for optimizing and testing suppression gene drive designs.

genetics↗

bioRxiv2024

Single-Cell full-length Isoform Sequencing Unveils Transcriptional Dysregulation in Autism Spectrum Disorder During Cerebral Cortex Development

Regulation of RNA splicing is pivotal in neural development, with established gene isoform expression patterns (1, 2). However, the specific roles of isoform diversity across cell types in both healthy and diseased brains warrant further investigation. Here, we employed a combination of metabolic RNA labeling using 4-thiouridine (4sU) and long-read sequencing based single-cell full-length transcriptome sequencing to capture newly synthesized transcripts within the developing mouse cortices. This approach allowed us to identify predetermined cell states supported by new RNAs and the driving isoforms of transcription factors that regulate the development of deep-and upper-layer neurons. Through detailed single-cell isoform expression analysis, we discovered novel cell type-specific isoforms and uncovered isoform switch events that modulate neuron differentiation. Additionally, we investigated isoform regulation associated with Autism Spectrum Disorder (ASD) during embryonic development of BTBR T+ Itpr3tf (BTBR) mice. Notably, our findings indicate a premature emergence of cortical projection neurons (CPNs) with an immature identity in ASD-affected cortices. These CPNs exhibit the highest degree of differential transcript usage (DTU), significantly overlapping with their cell type markers and being enriched in RNA splicing processes. Exon inclusion was significantly enriched in ASD and the related RNA binding proteins (RBPs) were extracted, nearly 60% of which have been reported as ASD risk genes. Lastly, we revealed a reduction in isoform diversity in ASD, potentially linked to H3K27ac dysregulation in the associated genes. Collectively, our study marks a substantial advancement in understanding the molecular basis of cortical development and function, paving the way for future studies on neurodevelopmental disorders.

developmental biology↗

bioRxiv2024

PlantRing: A high-throughput wearable sensor system for decoding plant growth, water relations and innovating irrigation

The combination of flexible electronics and plant science has generated various plant-wearable sensors, yet challenges persist in their applications in real-world agriculture, particularly in high-throughput settings. Overcoming the trade-off between sensing sensitivity and range, adapting them to a wide range of crop types, and bridging the gap between sensor measurements and biological understandings remain the primary obstacles. Here we introduce PlantRing, an innovative, nano-flexible sensing system designed to address the aforementioned challenges. PlantRing employs bio-sourced carbonized silk georgette as the strain sensing material, offering exceptional resolution (tensile deformation: < 100 m), stretchability (tensile strain up to 100 %), and remarkable durability (season long), exceeding existing plant strain sensors. PlantRing effectively monitors plant growth and water status, by measuring organ circumference dynamics, performing reliably under harsh conditions and being adaptable to a wide range of plants. Applying PlantRing to study fruit cracking in tomato and watermelon reveals novel hydraulic mechanism, characterized by genotype-specific excess sap flow within the plant to fruiting branches. Its high-throughput application enabled large-scale quantification of stomatal sensitivity to soil drought, a traditionally difficult-to-phenotype trait, facilitating drought tolerant germplasm selection. Combing PlantRing with soybean mutant led to the discovery of a potential novel function of the GmLNK2 circadian clock gene in stomatal regulation. More practically, integrating PlantRing into feedback irrigation achieves simultaneous water conservation and quality improvement, signifying a paradigm shift from experience- or environment-based to plant-based feedback control. Collectively, PlantRing represents a groundbreaking tool ready to revolutionize botanical studies, agriculture, and forestry.

plant 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

Fate (or state) of CA2 neurons in a mineralocorticoid receptor knockout.

Hippocampal area CA2 has emerged as a functionally and molecularly distinct part of the hippocampus and is necessary for several types of social behavior, including social aggression. As part of the unique molecular profile of both mouse and human CA2, the mineralocorticoid receptor (MR; Nr3c2) appears to play a critical role in controlling CA2 neuron cellular and synaptic properties. To better understand the fate (or state) of the neurons resulting from MR conditional knockout, we used a spatial transcriptomics approach. We found that without MRs, CA2 neurons acquire a CA1-like molecular phenotype. Additionally, we found that neurons in this area appear to have a cell size and density more like that in CA1. These finding support the idea that MRs control at least CA2s state during development, resulting in a CA1-like fate.

neuroscience↗

bioRxiv2024

Stage-Specific Transcriptome Landscape of Hepatocellular Carcinoma: Insights from Super and Poor Survivors with Prognostic Signature Identification

BackgroundThe prognosis for hepatocellular carcinoma (HCC) patients can vary significantly even within the same clinical stage. This study aims to characterize the stage-specific transcriptomic landscape of super survivors with HCC and identify a prognostic gene signature. MethodsWe analyzed data from The Cancer Genome Atlas (TCGA) for 76 matched super survivors (alive at 5 years) and poor survivors (deceased within 1 year) with HCC. Gene set enrichment analysis stratified by stage was conducted and a key prognostic gene signature was developed. The signature was then applied to the full TCGA cohort and independently validated in International Cancer Genome Consortium (ICGC) data. FindingsStage-specific transcriptomic profiling revealed distinct patterns in super survivors. Stage I and II showed positive enrichment in immune response pathways, while stage III exhibited enhanced catabolic activities and reduced glycolysis. Across all stages, cell cycle processes were less active in super survivors. A 19-gene signature, incorporating immune, metabolic, and cell cycle genes, accurately distinguished super from poor survivors with 91% accuracy (69/76). The signature reliably predicted overall survival in both the verification cohort (1-year, 3-year, and 5-year AUROCs of 0.82, 0.80, and 0.78) and the independent validation cohort (1-year and 3-year AUROCs of 0.80 and 0.83). Consistent AUROCs were observed across all tumor stages. InterpretationOur findings reveal a dynamic shift in HCC progression, with immune dominance in early stages and metabolic dominance in later stages, alongside reduced cell cycle activity across all stages. Integrating stage-specific transcriptomic profiles offers a promising approach to enhancing individualized management for HCC patients.

bioinformatics↗

bioRxiv2024

Microbial virulome and resistome in deep-sea cold seeps pose minimal public health risks

Deep-sea cold seeps host high microbial biomass and biodiversity that thrive on hydrocarbon and inorganic compound seepage, exhibiting diverse ecological functions and unique genetic resources. However, potential health risks from pathogenic or antibiotic-resistant microorganisms in these environments remain largely overlooked, especially during resource exploitation and laboratory research. Here, we analyzed 165 metagenomes and 33 metatranscriptomes from 16 global cold seep sites to investigate the diversity and distribution of virulence factors (VFs), antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs). A total of 2,353 VFs are retrieved in 689 MAGs, primarily associated with non-pathogenic functions like adherence. Additionally, cold seeps harbor nearly 100,000 ARGs, as important reservoirs, with high-risk ARGs presenting at low abundance. Compared to other environments, microorganisms in cold seeps exhibit substantial differences in VF and ARG counts, with potential horizontal gene transfer facilitating their spread. These virulome and resistome profiles provide valuable insights into the evolutionary and ecological implications of pathogenicity and antibiotic resistance in extreme deep-sea ecosystems. Collectively, these results indicate that cold seep sediments pose minimal public health risks, shedding lights on environmental safety in deep-sea resource exploitation and research. ImportanceUnderstanding pathogenicity and antibiotic resistance in environmental reservoirs like deep-sea cold seeps is critical for assessing public health risks, particularly with increasing human activities such as deep-sea mining. This study offers the first comprehensive analysis of virulome, resistome, and mobilome profiles in cold seep microbial communities. While cold seeps act as reservoirs for diverse ARGs, high-risk ARGs are rare, and most VFs contribute to non-pathogenic ecological functions. These results highlight the minimal threat to public health posed by cold seeps, providing a reference for monitoring the spread of pathogenicity and resistance in extreme ecosystems and informing environmental safety assessments during deep-sea resource exploitation.

microbiology↗

bioRxiv2024

Lewy-MSA hybrid fold drives distinct neuronal a-synuclein pathology

The ordered assembly of -synuclein protein into filaments encoded by SNCA characterizes neurodegenerative diseases called synucleinopathies. Lewy body disease (LBD) shows predominantly neuronal -synuclein pathology and multiple system atrophy (MSA) predominantly oligodendrocytic -synuclein pathology affecting subcortical brain structures. Based on cryo-electron microscopy, it was reported that structures of -synuclein filaments from LBD differ from MSA and juvenile onset synucleinopathy (JOS) caused by a 21-nucleotide duplication in the second exon of one allele of SNCA gene 1-3. Importantly, a rare subtype of MSA, called atypical MSA4 shows abundant neuronal argyrophilic -synuclein inclusions in the limbic system. Current concepts indicate that disease entities are characterized by unique protofilament folds. Here we demonstrate that in addition to the MSA fold, -synuclein can form a new Lewy-MSA hybrid fold in the same brain region, leading to the atypical histopathological form of MSA. Distinct biochemical characteristics of -synuclein, as demonstrated by protease-sensitivity digestion assay, seed amplification assays (SAAs) and conformational stability assay (CSA), are also linked to cytopathological differences (e.g. neuronal or oligodendroglial). We expand the current structure-based classification of -synucleinopathies and propose that cell-specific protein pathologies can be associated with distinct filament folds.

pathology↗

bioRxiv2024

Exploring the Neural Basis and Validity of Ordinal Emotion Representation through EEG

Accurately measuring emotion is a major challenge in advancing the understanding of human emotion and developing emotional artificial intelligence. In many existing studies, participants emotional ratings in interval scales are considered the true reflection of their emotional experiences. However, recent research suggests that ordinal annotations of emotions can more accurately capture the emotional expression process, providing a potential method for more precise emotion measurement. However, our understanding of the characteristics and validity of this new form of emotion representation is still relatively lacking. In particular, there is a lack of research using neural signals to explore the validity and neural basis of ordinal emotion representation. In this study, we used a video-elicited electroencephalogram (EEG) dataset (n = 123) to identify the neural basis of ordinal emotion representation and demonstrate its validity from a neural perspective. Furthermore, we explored various characteristics of ordinal emotion representation, showing how it is superior to the interval form. First, we conducted inter-situation representational similarity analysis (RSA) and inter-subject RSA to test the degree to which ordinal representation captures both group commonalities and individual differences of emotion. Next, we investigated the characteristics of ordinal representation under different combinations of emotion items, including uni-variate and multivariate emotions, positive and negative emotions. Our results show that both group commonalities and inter-subject variations in EEG features are better explained by ordinal emotion representations than by interval ones. Multivariate ordinal representations showed better inter-subject reliability and higher representational similarity with EEG features compared to uni-variate counterparts, highlighting the co-occurrence nature of human emotions. Compared to negative emotions, ordinal representation showed greater improvements for positive emotions, suggesting that the complexity of positive emotions is well captured by ordinal representations. Taken together, these findings demonstrate that multivariate ordinal emotion ratings provide a more accurate measure of real emotional experience, which is crucial for enabling machines to precisely understand and express human emotions.

neuroscience↗

bioRxiv2024

Elevated EGR1 Binding at Enhancers in Excitatory Neurons Correlates with Neuronal Subtype-Specific Epigenetic Regulation

Brain development and neuronal cell specification are accompanied with epigenetic changes to achieve diverse gene expression regulation. Interacting with cell-type specific epigenetic marks, transcription factors bind to different sets of cis-regulatory elements in different types of cells. Currently, it remains largely unclear how cell-type specific gene regulation is achieved for neurons. In this study, we generated epigenetic maps to perform comparative histone modification analysis between excitatory and inhibitory neurons. We found that neuronal cell-type specific histone modifications are enriched in super enhancer regions containing abundant EGR1 motifs. Further CUT&RUN data validated that more EGR1 binding sites can be detected in excitatory neurons and primarily located in enhancers. Integrative analysis revealed that EGR1 binding is strongly correlated with various epigenetic markers for open chromatin regions and associated with distinct gene pathways with neuronal subtype-specific functions. In inhibitory neurons, the majority of genomic regions hosting EGR1 binding sites become accessible at early embryonic stages. In contrast, the super enhancers in excitatory neurons hosting EGR1 binding sites gained their accessibility during postnatal stages. This study highlights the significance of transcription factor binding to enhancer regions, which may play a crucial role in establishing cell-type specific gene regulation in neurons.

neuroscience↗

bioRxiv2024

Targeting GOF p53 and c-MYC through LZK Inhibition or Degradation Suppresses Head and Neck Tumor Growth

The worldwide frequency of head and neck squamous cell carcinoma (HNSCC) is approximately 800,000 new cases, with 430,000 deaths annually. We determined that LZK (encoded by MAP3K13) is a therapeutic target in HNSCC and showed that inhibition with small molecule inhibitors decreases the viability of HNSCC cells with amplified MAP3K13. A drug-resistant mutant of LZK blocks decreases in cell viability due to LZK inhibition, indicating on-target activity by two separate small molecules. Inhibition of LZK catalytic activity suppressed tumor growth in HNSCC PDX models with amplified MAP3K13. We found that the kinase activity of LZK stabilized c-MYC and that LZK stabilized gain-of-function (GOF) p53 through a kinase-independent mechanism. Therefore, we designed proteolysis-targeting chimeras (PROTACs) and demonstrate that our lead PROTAC promotes LZK degradation and suppresses expression of GOF p53 and c-MYC leading to impaired viability of HNSCC cell lines. This research provides a strong basis for development of therapeutics targeting LZK in HNSCCs with amplification of the gene. One Sentence SummaryThis study establishes the kinase LZK as a therapeutic target for HNSCC through regulation of c-MYC expression.

cancer biology↗

bioRxiv2024

Detecting interspecific positive selection using convolutional neural networks

Traditional statistical methods using maximum likelihood and Bayesian inference can detect positive selection from an interspecific phylogeny and a codon sequence alignment based on model assumptions, but they are prone to false positives due to alignment errors and can lack power. These problems are particularly pronounced when faced with high levels of indels and divergence. Leveraging the feature-detection capabilities of convolutional neural networks (CNNs), we achieve higher accuracy in detecting selection across a specific range of phylogenetic scenarios and evolutionary modes. This advantage is particularly evident with noisy data prone to misalignments. Our method shows some ability to account for these errors, where most statistical frameworks fail to do so in a tractable manner. We explore generalisability and identify future avenues to achieve broader utility. Once trained, our CNN model is faster at test time, making it a scalable alternative to traditional statistical methods for large-scale, multi-gene analyses. In addition to binary classification (inference of the presence or absence of positive selection during the evolution of the sequences), we use saliency maps to understand what the model learns and observe how this could be leveraged for sitewise inference of positive selection.

evolutionary biology↗