Biology subjects

Xu, H.

Publications and source records attributed to Xu, H..

At least 181 records · Page 10Linked to original sources

bioRxiv2024

The comprehensive detection of hemoglobinopathy variants via long-read sequencing

BACKGROUNDThe genetic complexity of hemoglobin genes, characterized by high GC content and homologous sequences, poses significant challenges for detecting hemoglobin variants in clinical settings. METHODSA long-read indexed PCR method utilizing the novel CycloneSEQ nanopore sequencing platform was developed to detect all variant types, including single nucleotide variants (SNVs), deletions, structural variants (SVs) in HBA, HBB, HBD, and HBG genes. The method was validated using 507 clinical samples to assess its performance. RESULTSThe long-read indexed PCR system employed 13 primers targeting the hemoglobin gene clusters. This design enabled the detection of 37 types of HBA deletions, 5 SV (3 multicopies (, anti3.7, anti4.2) and 2 fusion allele (HK and anti-HK)), 37 HBB deletions, and all SNVs in the targeted regions. Validation across 507 samples (84 with HBA variants, 60 with HBB variants, 256 with both HBA and HBB variants, and 107 with no known variants) demonstrated 100.0% sensitivity and specificity. Additionally, the long-read sequencing enabled phasing of variants within hemoglobin genes, providing insights critical for clinical interpretation. CONCLUSIONSThe long-read indexed PCR method, combined with the CycloneSEQ nanopore sequencing platform, proved to be a robust and efficient solution for detecting hemoglobinopathy variants. The integration of indexed primers and barcoding enhances scalability, making this method ideal for large-scale population screening programs in the future.

genomics↗

bioRxiv2024

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

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

neuroscience↗

bioRxiv2024

A regulator controls both DNA damage response and anti-phage defense networks in Moraxellaceae

DNA damage chemicals, including many antibiotics, often induce prophage induction and phage outbreaks in microbial communities, a major threat to bacterial survival. Moraxellaceae contains clinically highly relevant strains with outstanding antibiotic and radio resistance, yet their cellular-level regulation in DNA damage response and anti-phage defense is largely unknown. Here, we identified a WYL family protein that had replaced the ubiquitous SOS system in evolution and directly regulated a transcriptional network of both DNA repair genes and anti-phage defense genes under DNA damage stress. This study depicts a mechanism that how bacteria maintain immunity to phages without compromising on antibiotic resistance, and sheds light on controlling the resistance of Moraxellaceae strains in clinical practice.

microbiology↗

bioRxiv2024

Simulated climate warming scenarios lead to earlier emergence and increased weight loss but have no effect on overwintering survival in solitary bees

Insect pollination is critical for both wildflower stability and agricultural yields, with solitary bees being a group of pollinators of fundamental importance. However, documented declines in populations, exacerbated by environmental pressures, including climate change, pose significant threats to the provision of ecosystem services. Exposure to elevated temperatures during periods of dormancy, such as overwintering, is predicted to lead to phenological shifts, changes in condition, and impacts on survival. However, we currently lack studies that inform how such aspects are affected in future climate change scenarios. Using simulated temperature regimes informed by predictions of the Intergovernmental Panel on Climate Change, we exposed overwintering mason bees (Osmia species) to three field-relevant temperature profiles based on either present-day overwintering temperatures or future temperatures predicted under two major climate warming scenarios (SSP2-4.5 and SSP5-8.5) and measured how temperature exposure affected emergence timing, weight loss and survival. We found that exposure to temperatures under intermediate and worst-case climate warming scenarios led to earlier emergence by approximately three and six weeks, respectively, with increasing divergences in timing of emergence between the sexes of Osmia bicornis, which may lead to intraspecific phenological mismatches. While we found no effect of temperature on overwintering survival rates, we observed increased weight loss prior to emergence but found that in contrast to other studies, it only mildly mediated shifts in emergence timing brought about by temperature exposure, suggesting that weight loss is unlikely to play a major role as a trigger of emergence timing in mason bees. Our study contributes to the growing literature highlighting the impact that temperatures under climate change models will have on the timing of key life events for essential pollinators, which may have consequences at the population and community levels.

ecology↗

bioRxiv2024

A Multi-Modal Genomic Knowledge Distillation Framework for Drug Response Prediction

Precision oncology utilizes genomic data to tailor treatment to individuals. Cancer drug sensitivity studies can predict the response levels of different drugs for the same cultured cancer cell line, which is beneficial for personalized medicine. Recent studies have demonstrated that integrating multi-modal genomic data, e.g., gene expression, mutation, copy number alteration, methylation, can provide comprehensive knowledge and improve drug response prediction. Although multimodal genomic profiles are generally available from public datasets, only gene expression data is commonly used in clinical settings. In this study, we propose a framework for privileged information knowledge distillation to transfer knowledge from a multi-modal genomic teacher network, using only gene expression for inference. Specifically, we train a teacher network by feature re-weighting based on inter-modality dependencies and align the inter-sample correlations through our proposed relation-aware differentiation distillation. Experiments on the Genomics of Drug Sensitivity in Cancer (GDSC) dataset demonstrate that our framework improves drug response prediction by about 6% compared to the baseline and outperforms state-of-the-art methods. Transferable studies performed on missing GDSC data and clinical datasets further confirm the feasibility of our model for predicting drug responses using only gene expression data.

bioinformatics↗

bioRxiv2024

A browser-based platform for storage, visualization, and analysis of large-scale 3D images in HPC environments

High-throughput microscopy necessitates 3D image storage, visualization, and analysis in terabyte to petabyte scales. Centralized high-performance computing (HPC) infrastructure provides the resources, but interfacing software is limited. We developed an extensible platform with a scalable image storage format (SISF) and content delivery network (CDN) to enable fast, random access to compressed data. Additionally, we built a cloud-based nTracer2 software to annotate neuron morphology from SISF images in a web browser.

bioinformatics↗

bioRxiv2024

Novel and optimized mouse behavior enabled by fully autonomous HABITS: Home-cage Assisted Behavioral Innovation and Testing System

Mice are among the most prevalent animal models used in neuroscience, benefiting from the extensive physiological, imaging and genetic tools available to study their brain. However, the development of novel and optimized behavioral paradigms for mice has been laborious and inconsistent, impeding the investigation of complex cognitions. Here, we present a home-cage assisted mouse behavioral innovation and testing system (HABITS), enabling free-moving mice to learn challenging cognitive behaviors in their home-cage without any human involvement. Supported by the general programming framework, we have not only replicated established paradigms in current neuroscience research but also developed novel paradigms previously unexplored in mice, resulting in more than 300 mice demonstrated in various cognition functions. Most significantly, HABITS incorporates a machine-teaching algorithm, which comprehensively optimized the presentation of stimuli and modalities for trials, leading to more efficient training and higher-quality behavioral outcomes. To our knowledge, this is the first instance where mouse behavior has been systematically optimized by an algorithmic approach. Altogether, our results open a new avenue for mouse behavioral innovation and optimization, which directly facilitates investigation of neural circuits for novel cognitions with mice.

animal behavior and cognition↗

bioRxiv2024

An Atlas of Linkage Disequilibrium Across Species

Linkage disequilibrium (LD) is a key metric that characterizes populations in flux. To reach a genomic scale LD illustration, which has a substantial computational cost of[O] (nm2), we introduce a framework with two novel algorithms for LD estimation: X-LD, with a time complexity of[O] (n2m) suitable for small sample sizes (n < 104); X-LDR, a stochastic algorithm with a time complexity of[O] (nmB) for biobank-scale data (B iterations); n the sample size, and m the number of SNPs. These methods can refine the entire genome into high-resolution LD grids, such as more than 9 million grids for UK Biobank samples ([~]4.2 million SNPs). The efficient resolution for genome-wide LD leads to intriguing biological discoveries. I) High-resolution LD illustrations revealed how the pericentromeric regions and the HLA region lead to intense and extended LD patterns. II) Two universal LD patterns, identified as Norm I and Norm II patterns, provide insights on the evolutionary history of populations and can also highlight genomic regions of deviation, such as chromosomes 6 and 11 or ncRNA regions. III) The results of our innovative LD decay method aligned with the LD decay scores of 59.5 for Europeans, 60.2 for East Asians, and 33.2 for Africans; correspondingly, the length of the LD was approximately 2.85 Mb, 2.18 Mb, and 1.58 Mb for these three ethnicities. Rare or imputed variants universally increased LD. IV) An unprecedented LD atlas for 25 reference populations contoured interspecies diversity in terms of their Norm I and Norm II LD patterns, highlighting the impact of refined population structure, quality of reference genomes, and uncovered a profound status quo of these populations. The algorithms have been implemented in C++ and are freely available (https://github.com/gc5k/gear2).

genetics↗

bioRxiv2024

Identification of Intrinsic Features for Cortical Separability of Human and Mouse Neurons

This work introduces a novel framework for holistic comparative analysis of cortical regions in mouse and human brains at single-neuron resolution, with a primary focus on the morphological and molecular characteristics of neurons. To do so, we generated one of the largest dendritic reconstruction datasets of cortical neurons to date, comprising 2,363 human neurons and 16,011 mouse neurons from the frontal, parietal, and temporal lobes, followed by establishing a rigorous procedure to identify anatomically and functionally corresponding brain regions with minimal variability in brain mapping. Additionally, we leveraged single nucleus/cell transcriptomic data from independent groups to validate the molecular correspondence of the brain regions identified in this study. The significance of these anatomically, functionally, and molecularly corresponding mouse-human region pairs is highlighted by examining the intrinsic features of their respective cortical regions. Our findings reveal that human neuron branching patterns differ dramatically from those in mouse brains, particularly in terms of dendritic branching frequency and normalized dendritic branching intervals. This difference is pronounced in the frontal and temporal lobes, underscoring the distinct neuronal architectures between the two species. At the single-neuron level, we found that neurons from the human frontal and parietal lobes are six times more separable than those from the same regions in mouse brains. This heightened separability is also observed between the frontal and temporal lobes, as well as between the parietal and temporal lobes in humans. We thoroughly explored the entire morphological feature space, along with its characteristic subspaces, and consistently found this distinct separability. Remarkably, this neuronal separability can be partially recapitulated when examining the global functional states of these brain lobes--using newly acquired Electroencephalography (EEG) and Magnetoencephalography (MEG) signals as physiological measures--as well as their global metabolic states, molecular profiles, and cortical geometry. These findings suggest that our comparative analysis of single-neuron intrinsic features could serve as a valuable foundation for future comprehensive studies of cross-species brain structures and functions.

neuroscience↗

bioRxiv2024

Lysosomal LRRC8 complex regulates lysosomal pH, morphology and systemic glucose metabolism

The lysosome integrates anabolic signalling and nutrient-sensing to regulate intracellular growth pathways. The leucine-rich repeat containing 8 (LRRC8) channel complex forms a lysosomal anion channel and regulates PI3K-AKT-mTOR signalling, skeletal muscle differentiation, growth, and systemic glucose metabolism. Here, we define the endogenous LRRC8 subunits localized to a subset of lysosomes in differentiated myotubes. We show LRRC8A regulates leucine-stimulated mTOR, lysosome size, number, pH, and expression of lysosomal proteins LAMP2, P62, LC3B, suggesting impaired autophagic flux. Mutating a LRRC8A lysosomal targeting dileucine motif sequence (LRRC8A-L706A;L707A) in myotubes recapitulates the abnormal AKT signalling and altered lysosomal morphology and pH observed in LRRC8A KO cells. In vivo, LRRC8A-L706A;L707A KI mice exhibit increased adiposity, impaired glucose tolerance and insulin resistance characterized by reduced skeletal muscle glucose-uptake, and impaired incorporation of glucose into glycogen. These data reveal a lysosomal LRRC8 mediated metabolic signalling function that regulates lysosomal activity, systemic glucose homeostasis and insulin-sensitivity.

cell biology↗

bioRxiv2024

A STAG2-PAXIP1/PAGR1 axis suppresses lung tumorigenesis

The cohesin complex is a critical regulator of gene expression. STAG2 is the most frequently mutated cohesin subunit across several cancer types and is a key tumor suppressor in lung cancer. Here, we coupled somatic CRISPR-Cas9 genome editing and tumor barcoding with an autochthonous oncogenic KRAS-driven lung cancer model and show that STAG2 is uniquely tumor suppressive among all core and auxiliary cohesin components. The heterodimeric complex components PAXIP1 and PAGR1 have highly correlated effects with STAG2 in human lung cancer cell lines, are tumor suppressors in vivo, and are epistatic to STAG2 in oncogenic KRAS-driven lung tumorigenesis in vivo. STAG2 inactivation elicits changes in gene expression, chromatin accessibility and 3D genome conformation that impact cancer cell state. Gene expression and chromatin accessibility similarities between STAG2- and PAXIP1-deficient neoplastic cells further relates STAG2-cohesin to PAXIP1/PAGR1. These findings reveal a STAG2-PAXIP1/PAGR1 tumor-suppressive axis and uncover novel PAXIP1-dependent and PAXIP1-independent STAG2-cohesin mediated mechanisms of lung tumor suppression. SUMMARYSTAG2 is a frequently mutated cohesin subunit across several cancers and one of the most important functional suppressors of lung adenocarcinoma. Our findings underscore important roles of STAG2 in suppressing lung tumorigenesis and highlight a STAG2-PAXIP1/PAGR1 tumor-suppressive program that may transcend cancer type.

cancer biology↗

bioRxiv2024

Integrative multiomic approaches reveal ZMAT3 and p21 as conserved hubs in the p53 tumor suppression network

TP53, the most frequently mutated gene in human cancer, encodes a transcriptional activator that induces myriad downstream target genes. Despite the importance of p53 in tumor suppression, the specific p53 target genes important for tumor suppression remain unclear. Recent studies have identified the p53-inducible gene Zmat3 as a critical effector of tumor suppression, but many questions remain regarding its p53-dependence, activity across contexts, and mechanism of tumor suppression alone and in cooperation with other p53-inducible genes. To address these questions, we used Tuba-seqUltra somatic genome editing and tumor barcoding in a mouse lung adenocarcinoma model, combinatorial in vivo CRISPR/Cas9 screens, meta-analyses of gene expression and Cancer Dependency Map data, and integrative RNA-sequencing and shotgun proteomic analyses. We established Zmat3 as a core component of p53-mediated tumor suppression and identified Cdkn1a as the most potent cooperating p53-induced gene in tumor suppression. We discovered that ZMAT3/CDKN1A serve as near-universal effectors of p53-mediated tumor suppression that regulate cell division, migration, and extracellular matrix organization. Accordingly, combined Zmat3-Cdkn1a inactivation dramatically enhanced cell proliferation and migration compared to controls, akin to p53 inactivation. Together, our findings place ZMAT3 and CDKN1A as hubs of a p53-induced gene program that opposes tumorigenesis across various cellular and genetic contexts.

cancer biology↗

bioRxiv2024

Recombination shapes the diversification of the wtf meiotic drivers

Meiotic drivers are selfish genetic elements that distort fair segregation. The wtf genes are poison-antidote meiotic drivers that are experiencing rapid diversification in fission yeasts. However, gene duplication alone is insufficient to drive the diversification of wtf genes, given the poison encoded by a newly duplicated wtf gene can be detoxified by the antidote encoded by the original wtf gene. Here, we analyze the evolution of wtf genes across 21 strains of Schizosaccharomyces pombe. Knocking out each of 25 wtf genes in S. pombe strain 972h-separately does not attenuate the yeast growth, indicating that the wtf genes might be largely neutral to their carriers in asexual life cycle. Interestingly, wtf genes underwent recurrent and intricate recombination. As proof-of-principle, we generate a novel meiotic driver through artificial recombination between wtf drivers, and its encoded poison cannot be detoxified by the antidotes encoded by their parental wtf genes but can be detoxified by its own antidote. Therefore, we propose that recombination can generate new meiotic drivers and thus shape the diversification of the wtf drivers.

evolutionary biology↗

bioRxiv2024

High-throughput unsupervised quantification of patterns in the natural behavior of marmosets

Recent advances in genetic engineering have accelerated the production of nonhuman primate models for neuropsychiatric disorders. To use these models for preclinical drug testing, behavioral screening methods will be necessary to determine how the model animals deviate from controls, and whether treatments can restore typical patterns of behavior. In this study, we collected a multimodal dataset from a large cohort of marmoset monkeys and described typical patterns in their natural behavior. We found that these behavioral measurements varied substantially across days, and that behavioral state usage was highly correlated to the behavior of cagemates and to the vocalization rate of other animals in the colony. To elicit acute behavioral responses, we presented animals with a panel of stimuli including novel, appetitive, neutral, aversive, and social stimuli. By comparing these behavioral conditions, we demonstrate that outlier detection can be used to identify atypical responses to a range of stimuli. This data will help guide the study of marmosets as models for neuropsychiatric disorders.

animal behavior and cognition↗

bioRxiv2024

Poly-alanine-tailing is a modifier of neurodegeneration caused by Listerin mutation

The surveillance of translation is critical for the fitness of organisms from bacteria to humans. Ribosome-associated Quality Control (RQC) is a surveillance mechanism that promotes the elimination of truncated polypeptides, byproducts of ribosome stalling during translation. In canonical mammalian RQC, NEMF binds to the large ribosomal subunit and recruits the E3 ubiquitin ligase Listerin, which marks the nascent-chains for proteasomal degradation. NEMF additionally extends the nascent-chains C-terminus with poly-alanine ( Ala-tail), exposing lysines in the ribosomal exit tunnel for ubiquitination. In an alternative, Listerin-independent RQC pathway, released nascent-chains are targeted by Ala-tail-binding E3 ligases. While mutations in Listerin or in NEMF selectively elicit neurodegeneration in mice and humans, the physiological significance of Ala-tailing and its role in disease have remained unknown. Here, we report the analysis of mice in which NEMFs Ala-tailing activity was selectively impaired. Whereas the Nemf homozygous mutation did not affect lifespan and only led to mild motor defects, genetic interaction analyses uncovered its synthetic lethal phenotype when combined with the lister neurodegeneration-causing mutation. Conversely, the lister phenotype was markedly improved when Ala-tailing capacity was partially reduced by a heterozygous Nemf mutation. Providing a plausible mechanism for this striking switch from early neuroprotection to subsequent neurotoxicity, we found that RQC substrates that evade degradation form amyloid-like aggregates in an Ala-tail dependent fashion. These findings uncover a critical role for Ala-tailing in mammalian proteostasis, and deepen our molecular understanding of pathophysiological roles of RQC in neurodegeneration.

biochemistry↗

bioRxiv2024

Functional mapping of epigenetic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes

Epigenetic dysregulation is widespread in cancer. However, the specific epigenetic regulators and the processes they control to drive cancer phenotypes are poorly understood. Here, we employed a novel, scalable and high-throughput in vivo method to perform iterative functional screens of over 250 epigenetic regulatory genes within autochthonous oncogenic KRAS-driven lung tumors. We identified multiple novel epigenetic tumor suppressor and tumor dependency genes. We show that a specific HBO1 complex and the MLL1 complex are among the most impactful tumor suppressive epigenetic regulators in lung. The histone modifications generated by the HBO1 complex are frequently absent or reduced in human lung adenocarcinomas. The HBO1 and MLL1 complexes regulate chromatin accessibility of shared genomic regions, lineage fidelity and the expression of canonical tumor suppressor genes. The HBO1 and MLL1 complexes are epistatic during lung tumorigenesis, and their functional correlation is conserved in human cancer cell lines. Together, these results demonstrate the value of quantitative methods to generate a phenotypic roadmap of epigenetic regulatory genes in tumorigenesis in vivo.

cancer biology↗

bioRxiv2024

3D Reconstruction of Neuronal Allometry and Neuromuscular Projections in Asexual Planarians Using Expansion Tiling Light Sheet Microscopy

The intricate coordination of the neural network in planarian growth and regeneration has remained largely unrevealed, partly due to the challenges of imaging the central nervous system (CNS) in three dimensions (3D) with high resolution and within a reasonable timeframe. To address this gap in systematic imaging of the CNS in planarians, we adopted high-resolution, nanoscale imaging by combining tissue expansion and tiling light-sheet microscopy, achieving up to 4-fold linear expansion. Using an automatic 3D cell segmentation pipeline, we quantitatively profiled neurons and muscle fibers at the single-cell level in over 400 wild-type planarians during homeostasis and regeneration. We validated previous observations of neuronal cell number changes and muscle fiber distribution. We found that the increase in neuron cell number tends to lag behind the rapid expansion of somatic cells during the later phase of homeostasis. By imaging the planarian with up to 120 nm resolution, we also observed distinct muscle distribution patterns at the anterior and posterior poles. Furthermore, we investigated the effects of {beta}-catenin RNAi on muscle fiber distribution at the posterior pole, consistent with changes in anterior-posterior polarity. The glial cells were observed to be close in contact with dorsal-ventral muscle fibers. Finally, we observed disruptions in neural-muscular networks in inr-1 RNAi planarians. These findings provide insights into the detailed structure and potential functions of the neural-muscular system in planarians and highlight the accessibility of our imaging tool in unraveling the biological functions underlying their diverse phenotypes and behaviors.

developmental biology↗

bioRxiv2024

Multi-Modal CLIP-Informed Protein Editing

AO_SCPLOWBSTRACTC_SCPLOWProteins govern most biological functions essential for life, but achieving controllable protein discovery and optimization remains challenging. Recently, machine learning-assisted protein editing (MLPE) has shown promise in accelerating optimization cycles and reducing experimental workloads. However, current methods struggle with the vast combinatorial space of potential protein edits and cannot explicitly conduct protein editing using biotext instructions, limiting their interactivity with human feedback. To fill these gaps, we propose a novel method called ProtET for efficient CLIP-informed protein editing through multi-modality learning. Our approach comprises two stages: in the pretraining stage, contrastive learning aligns protein-biotext representations encoded by two large language models (LLMs), respectively. Subsequently, during the protein editing stage, the fused features from editing instruction texts and original protein sequences serve as the final editing condition for generating target protein sequences. Comprehensive experiments demonstrated the superiority of ProtET in editing proteins to enhance human-expected functionality across multiple attribute domains, including enzyme catalytic activity, protein stability and antibody specific binding ability. And ProtET improves the state-of-the-art results by a large margin, leading to significant stability improvements of 16.67% and 16.90%. This capability positions ProtET to advance real-world artificial protein editing, potentially addressing unmet academic, industrial, and clinical needs.

bioinformatics↗