Biology subjects

Han, C.

Publications and source records attributed to Han, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Bridging the Dimensional Gap from Planar Spatial Transcriptomics to 3D Cell Atlases

Spatial transcriptomics (ST) has revolutionized our understanding of tissue architecture, yet constructing comprehensive three-dimensional (3D) cell atlases remains challenging due to technical limitations and high cost. Current approaches typically capture only sparsely sampled two-dimensional sections, leaving substantial gaps that limit our understanding of continuous organ organization. Here, we present SpatialZ, a computational framework that bridges these gaps by generating virtual slices between experimentally measured sections, enabling the construction of dense 3D cell atlases from planar ST data. SpatialZ is designed to operate at single-cell resolution and function independently of gene coverage limitations inherent to specific spatial technologies. Comprehensive validation using real 3D ST and independent serial sectioning datasets demonstrates that SpatialZ accurately reconstructs virtual slices while preserving cell identities, gene expression patterns, and spatial relationships. Leveraging the BRAIN Initiative Cell Census Network data, we constructed a 3D hemisphere atlas comprising over 38 million cells, a scale not feasible experimentally. This dense atlas enables unprecedented capabilities, including in silico sectioning at arbitrary angles, explorations of gene expression across both 3D volumes and surfaces, and 3D mapping of query tissue sections. While currently validated for spatial transcriptomics, the underlying principles of SpatialZ could potentially be adapted for spatial proteomics, spatial metabolomics, and even spatial multi-omics. Validated through internal and external testing, our computationally generated atlas maintains biological accuracy, providing unprecedented resolution of spatial molecular landscapes and demonstrating the potential of computational approaches in advancing 3D ST.

bioinformatics↗

bioRxiv2024

NicheTrans: Spatial-aware Cross-omics Translation

Spatial omics technologies have revolutionized our studies on tissue architecture and cellular interactions at single-cell resolution. While spatial multi-omics approaches offer unprecedented insights into complex biological systems, their widespread adoption is hindered by technical challenges, specialized requirements, and limited accessibility. To address these limitations, we present NicheTrans, the first spatially-aware cross-omics translation method and a flexible Transformer-based multi-modal deep learning framework. Unlike existing single-cell (non-spatial) translation methods, NicheTrans uniquely incorporates both cellular microenvironment information and flexible integration of multi-modal data, such as morphology and prior knowledge. We validated NicheTrans across diverse biological cases: Parkinsons Disease (PD), Alzheimers Disease (AD), breast cancer, and lymph nodes. Our approach demonstrated superior performance compared to existing single-cell methods, highlighting the crucial role of spatial and multi-modal information in cross-omics translation. Through NicheTrans, we uncovered spatial multi-omics domains that were not detectable through single-omics analysis alone. Model interpretation revealed key molecular relationships, including gene programs associated with dopamine metabolism and amyloid {beta}-associated cell states. Additionally, using translated protein markers as spatial landmarks, we quantified the spatial organization of key glial cell subtypes in the AD brain. NicheTrans represents a powerful tool for generating comprehensive spatial multi-omics insights from more accessible single-omics measurements, making multi-omics analysis more feasible for the broader research community.

bioinformatics↗

bioRxiv2024

Decipher Fundamental Atomic Interactions to Unify Generative Molecular Docking and Design

Understanding molecular interactions is essential to structural biology and drug discovery. Despite the progress of AI models in revealing and exploiting the interaction mechanisms for various applications, they are predominantly tailored to specific tasks without fully exploiting the underlying transferability across molecular data and tasks. Here, we present PocketXMol, an atom-level generative foundation model to decipher fundamental atomic interactions for general protein-pocket-interacting molecular tasks. It adopts a novel unified generative framework with an innovative task prompt mechanism and an exclusive atom-level representation, making it applicable to diverse tasks covering structure prediction and design of small molecules and peptides, without requiring fine-tuning. PocketXMol was compared to 55 baseline models across 13 typical tasks, achieving state-of-the-art performance in 11 tasks and remaining competitive in the others. We successfully utilized PocketXMol to design novel small molecules that inhibit caspase-9 with efficacy comparable to that of commercial pan-caspase inhibitors. Furthermore, we employed PocketXMol to design PD-L1-binding peptides, demonstrating a success rate substantially higher than random library screening. Three representative peptides underwent further experiments, which validated the cellular specificity and confirmed their potential for molecular probing and therapeutics. PocketXMol presents a powerful and versatile tool with promising prospects for future applications and will have a profound impact on AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

Comparative Genome Study of Multidrug-resistant Serratia marcescens strain IU-BTGE-M-3 Isolated from a Diarrheal Patient Reveals Antibiotic Resistance Profile

Serratia marcescens is a notable pathogen known for its intrinsic and acquired antimicrobial resistance, posing challenges in healthcare. The study investigates the multidrug-resistant (MDR) Serratia marcescens strain BTGE-M-3, focusing on its genomic features and antibiotic resistance. The strain was identified using both morphological and molecular approaches, and its genome, which measured 4.97 Mbp and exhibited a GC content of 59.7%, was sequenced. The genome has 4,827 genes, including essential antibiotic resistance genes, such as tet (41) for tetracyclines, aac (6')-Ic for aminoglycosides, OqxB for fluoroquinolones, and blaSST-1 beta-lactam, alongside various virulence determinants. Comparative genomics revealed high similarity (98.06% ANI) to S. marcescens strain KS10, supporting its classification within the same species. Additionally, the genome analysis showed that S. marcescens strain IU-BTGE-M-3 comprises of 4390 gene clusters, 4564 genes, and 244 unique singleton genes. To summarize, the results showed that S. marcescens strain IU-BTGE-M-3 exhibited a high level of genomic diversity as well as diverse metabolic, cellular, and biological functions, and it is hypothesized that frequent strain exchanges resulted in the horizontal transfer of drug resistance genes. This study underscores the importance of genomic surveillance in understanding and combating antibiotic resistance in therapeutic settings.

genomics↗

bioRxiv2024

Neural Circuit Underlying Individual differences in Visual Escape Habituation

Emotions, like fear, are internal states enabling organisms to effectively confront environmental threats. When repeatedly exposed to predators, individuals show divergent adaptive responses. However, the neural circuit mechanisms underlying individual differences in to repeated threats remain largely unknown. Here, we identify two distinct types of visual escape--consistent escape (T1) and rapid habituation (T2) -- with unambiguous arousal states to repetitive threat stimuli. We systematically investigate distinct pathways originating from the superior colliculus (SC) and insula that project to the basolateral amygdala (BLA), with relay stations in the mediodorsal thalamus (MD) and ventral tegmental area (VTA), mediating T1 and T2 behavioral types. Additionally, we identify the MD as a critical hub integrating SC and insula inputs, projecting to the BLA and contributing to reduced arousal and attenuated defensive behaviors against looming stimuli. Our findings offer significant insights into the mechanisms of internal states, arousal modulation, and behavioral adaptability. O_FIG O_LINKSMALLFIG WIDTH=178 HEIGHT=200 SRC="FIGDIR/small/611366v1_ufig1.gif" ALT="Figure 1"> View larger version (77K): org.highwire.dtl.DTLVardef@164df34org.highwire.dtl.DTLVardef@17a01e6org.highwire.dtl.DTLVardef@112de44org.highwire.dtl.DTLVardef@1be6aea_HPS_FORMAT_FIGEXP M_FIG Graph Abstract C_FIG In briefWe identify two distinct visual escape behaviors--consistent escape (T1) and rapid habituation (T2)--linked to unique SC and insula pathways projecting to the BLA via MD and VTA. The MD acts as a hub integrating sensory inputs to modulate arousal and defensive responses. These findings advance our understanding of the neural mechanisms driving internal states, arousal modulation, and behavioral adaptability. Highlights[bullet] We identify two distinct visual escape behaviors with unambiguous arousal states--consistent escape (T1) and rapid habituation (T2) --to repeated looming stimuli. [bullet]The SC-VTA-BLA pathway mediated T1 behavioral type, while the SC-MD-BLA pathway mediated T2 type. [bullet]MD as a central hub integrating SC and insula inputs to modulate arousal and defensive behavioral adaptation.

neuroscience↗

bioRxiv2024

Toward De Novo Protein Design from Natural Language

Programming biological function-designing bespoke proteins to perform specified molecular tasks-is a foundational goal of molecular engineering. However, current design paradigms remain fundamentally limited: they typically require either natural proteins as starting points for optimization or manual reformulation of functional goals as geometric and sequence-level constraints to guide candidate generation. Here we introduce Pinal, a 16-billion-parameter foundation model that designs candidate proteins from natural-language descriptions of desired function. Trained on 1.7 billion synthetically annotated protein-text pairs, Pinal links functional intent to protein sequence and structure. In computational evaluations, generated candidates combined high predicted foldability with functional-description alignment and sequence diversity, providing a basis for prioritizing experimentally testable designs. We applied Pinal to four distinct design tasks-a fluorescent protein, a polyethylene terephthalate hydrolase, an alcohol dehydrogenase and a metabolic H-protein-and experimentally observed the intended function in each case, including catalytic activity for both designed enzymes. Crucially, without iterative experimental optimization, a Pinal-designed H-protein increased product titer by 1.7-fold relative to the corresponding native E. coli H-protein in a multi-enzyme CO2 fixation pathway. These findings support natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.

bioengineering↗

bioRxiv2024

Aging amplifies sex differences in low alpha and low beta EEG oscillations

Biological sex profoundly shapes brain function, yet its precise influence on neural oscillations was poorly understood. Despite decades of research, studies investigating sex-based variations in electroencephalographic (EEG) signals have yielded inconsistent findings that obstructs what may be a potentially crucial source of inter-individual variability in brain function. To address this, we analyzed five publicly available resting-state datasets, comprising EEG data (n=445) and iEEG data (n=103). Our results revealed striking age-dependent sex differences: older adults (30-80 years) exhibited robust sex differences, with males showing heightened low alpha (8-9 Hz) activity in temporal regions and attenuated low beta (16-20 Hz) oscillations in parietal-occipital areas compared to females. Intriguingly, these sex-specific patterns were absent in younger adults (20-30 years), suggesting a complex interplay between sex and aging in shaping brain dynamics. Furthermore, we identified consistent sex-related activity in the precentral gyrus with the results of scalp EEG, potentially driving the observed scalp EEG differences. This multi-level analysis allowed us to bridge the gap between cortical and scalp- level observations, providing a more comprehensive picture of sex-related neural dynamics. To further investigate the functional implications of these oscillatory differences, we conducted correlation analyses to uncover significant associations between sex-specific oscillatory patterns and several lifestyle factors (behavioral and anthropometric measures) in older adults. This comprehensive investigation demonstrates the complex interplay between sex, age, and neural oscillations, revealing the variability in brain dynamics. And our findings highlight the importance of careful demographic consideration in EEG research design to ensure fairness in capturing the full spectrum of neurophysiological diversity. Significance statementThe influence of biological sex and age on neural oscillations had been a long- standing, unresolved question in EEG research, largely unaddressed due to limited sample sizes and simplistic demographic matching. Our study leverages large-scale, open datasets to tackle this issue, analyzing hundreds of participants across five datasets. Our findings demonstrate substantial sex- based differences in even resting-state EEG baselines, particularly in low alpha and low beta bands, uncovering a significant source of variability in neural activity. By connecting these sex and age-related variations to potential neural circuit mechanisms and lifestyle factors, our findings highlight the importance of careful demographic consideration in EEG research design in EEG experimental design to accurately capture the rich spectrum of neurophysiological variability across the lifespan.

neuroscience↗

bioRxiv2024

Inclusive, Exclusive and Hierarchical Atlas of NFATc1+/PDGFR-alpha+ Cells in Dental and Periodontal Mesenchyme

Platelet-derived growth factor receptor alpha (PDGFR-) activity is crucial in the process of dental and periodontal mesenchyme regeneration facilitated by autologous platelet concentrates (APCs), such as platelet-rich fibrin (PRF), platelet-rich plasma (PRP) and concentrated growth factors (CGF), as well as by recombinant PDGF drugs. However, it is largely unclear about the physiological patterns and cellular fate determinations of PDGFR-+ cells in the homeostasis maintaining of adult dental and periodontal mesenchyme. We previously identified NFATc1 expressing PDGFR-+ cells as a subtype of skeletal stem cells (SSCs) in limb bone, but their roles in dental and periodontal remain unexplored. To this end, in the present study we investigated the spatiotemporal atlas of NFATc1+ and PDGFR-+ cells residing in dental and periodontal mesenchyme, their capacity for progeny cell generation, and their inclusive, exclusive and hierarchical relations in homeostasis. We utilized CRISPR/Cas9-mediated gene editing to generate two dual recombination systems, which were Cre/loxP-Dre/Rox combined intersectional and exclusive reporters respectively, to concurrently demonstrate the inclusive, exclusive, and hierarchical distributions of NFATc1+ and PDGFR-+ cells and their lineage commitment. By employing the state-of-the-art transgenic lineage tracing techniques in cooperating with tissue clearing-based advanced imaging and three-dimensional slices reconstruction, we systematically mapped the distribution atlas of NFATc1+ and PDGFR-+ cells in dental and periodontal mesenchyme and tracked their in vivo fate trajectories. Our findings extend current understanding of NFATc1+ and PDGFR-+ cells in dental and periodontal mesenchyme homeostasis, and furthermore enhance our comprehension of their sustained therapeutic impact for future clinical investigations.

developmental biology↗

bioRxiv2024

SaprotHub: Making Protein Modeling Accessible to All Biologists

Training and deploying large-scale protein language models typically requires deep machine learning expertise -- a barrier for researchers outside this field. SaprotHub overcomes this challenge by offering an intuitive platform that facilitates training and prediction as well as storage and sharing of models. We provide the ColabSaprot framework built on Google Colab which potentially powers hundreds of protein training and prediction applications, enabling researchers to collaboratively build and share customized models.

bioinformatics↗

bioRxiv2024

Clade-defining mutations in human H1N1 hemagglutinin protein from 2021-2023 have opposing effects on in vitro fitness and antigenic drift

Seasonal influenza viruses frequently acquire mutations that have the potential to alter both virus replication and antigenic profile. Recent seasonal H1N1 viruses have acquired mutations to their hemagglutinin (HA) protein receptor binding site (RBS) and antigenic sites, and have branched into the clades 5a.2a and 5a.2a.1. Both clades demonstrated improved in vitro fitness compared with the parental 5a.2 clade as measured through plaque formation, infectious virus production in human nasal epithelial cells, and receptor binding diversity. Both clades also showed reduced neutralization by serum from healthcare workers vaccinated in the 2022-23 Northern Hemisphere influenza season compared to the vaccine strain. To investigate the phenotypic impact of individual clade-defining mutations, recombinant viruses containing single HA mutations were generated on a 5a.2 genetic background. The 5a.2a mutation Q189E improved plaque formation and virus replication, but was more efficiently neutralized by serum from individuals vaccinated in 2022-23. In contrast, the 5a.2a mutation E224A and both 5a.2a.1 mutations P137S and K142R impaired aspects of in vitro fitness but contributed significantly to antigenic drift. Surprisingly, the E224A mutation and not Q189E caused broader receptor binding diversity seen in clinical isolates of 5a.2a and 5a.2a.1, suggesting that receptor binding diversity alone may not be responsible for the phenotypic effects of the Q189E mutation. These data document an evolutionary trade-off between mutations that improve viral fitness and those that allow for the evasion of existing host immunity. ImportanceSeasonal influenza is a significant contributor to global morbidity and mortality. To better understand how these viruses evolve, recent seasonal H1N1 viruses were characterized and the impact of individual mutational differences between the hemagglutinin proteins of these viruses was assessed. Mutations that contribute to escape from preexisting immunity were deleterious to virus replication in human nasal epithelial cell cultures, requiring the accumulation of additional mutations to compensate for this loss of fitness. This adds to our understanding of how influenza evolution balances replication fitness with antigenic drift.

microbiology↗

bioRxiv2024

Phagocytosis-driven neurodegeneration through opposing roles of an ABC transporter in neurons and phagocytes

Lipid homeostasis is critical to the survival of neurons. Lipid transporters from the ATP-binding cassette A (ABCA) subfamily are important regulators of lipid trafficking and are associated with multiple neurodegenerative diseases. How ABCA transporters regulate specific aspects of lipid homeostasis to impact neurodegeneration is an outstanding question. Here we report that the Drosophila ABCA protein Engulfment ABC Transporter in the ovary (Eato) contributes to phagocytosis-dependent neurodegeneration by playing two opposing roles in neurons and nearby phagocytes: In neurons, Eato prevents dendrites and axons from being attacked and engulfed by neighboring phagocytes; in phagocytes, however, Eato enhances the ability of these cells to detect neurons as engulfment targets. Thus, Eato deficiency in neurons alone results in severe phagocytosis-dependent dendrite and axon degeneration, whereas removing Eato from both neurons and phagocytes completely rescues the neurite degeneration. Surprisingly, Eato exerts its functions in both neurons and phagocytes by suppressing the effects of the eat-me signal phosphatidylserine (PS) exposed on the cell surface. Interestingly, multiple human and C. elegans ABCA homologs can compensate for the loss of Eato in phagocytes but not in neurons, suggesting both conserved and cell type-specific activities of these ABCA proteins. These results reveal how ABCA proteins participate in neurodegeneration by regulating PS homeostasis and imply possible mechanisms of neuron-phagocyte interactions in neurodegenerative diseases.

neuroscience↗

bioRxiv2024

Temporally controlled nervous system-to-gut signaling bidirectionally regulates longevity in Caenorhabditis elegans

The nervous system modulates aging by secreting signaling molecules to cell-nonautonomously regulate the physiological state of distal tissues such as the gut. However, the underlying mechanisms are not well understood. Here, using C. elegans as a model, we identified two distinct neuroendocrine signaling circuits through which motor neurons signal the gut in early life to shorten lifespan but in mid-late life to extend lifespan. Both circuits employ the same neurotransmitter acetylcholine (ACh), while recruiting two different gut ACh receptors ACR-6 and GAR-3 to regulate the transcription factor DAF-16 and HSF-1 in early and mid-late life, respectively. Strikingly, the gut expression of ACR-6 is restricted to early life, whereas that of GAR-3 is confined to mid-late life, providing a potential mechanism for the temporal control of the two circuits. These results identify a novel mechanism that empowers the nervous system to bidirectionally regulate longevity by differentially signaling the gut at different life stages.

cell biology↗

bioRxiv2024

Self-organization of embryonic stem cells into a reproducible embryo model through epigenome editing

Embryonic stem cells (ESCs) can self-organize in vitro into developmental patterns with spatial organization and molecular similarity to that of early embryonic stages. This self-organization of ESCs requires transmission of signaling cues, via addition of small molecule chemicals or recombinant proteins, to induce distinct embryonic cellular fates and subsequent assembly into structures that can mimic aspects of early embryonic development. During natural embryonic development, different embryonic cell types co-develop together, where each cell type expresses specific fate-inducing transcription factors through activation of non-coding regulatory elements and interactions with neighboring cells. However, previous studies have not fully explored the possibility of engineering endogenous regulatory elements to shape self-organization of ESCs into spatially-ordered embryo models. Here, we hypothesized that cell-intrinsic activation of a minimum number of such endogenous regulatory elements is sufficient to self-organize ESCs into early embryonic models. Our results show that CRISPR-based activation (CRISPRa) of only two endogenous regulatory elements in the genome of pluripotent stem cells is sufficient to generate embryonic patterns that show spatial and molecular resemblance to that of pre-gastrulation mouse embryonic development. Quantitative single-cell live fluorescent imaging showed that the emergence of spatially-ordered embryonic patterns happens through the intrinsic induction of cell fate that leads to an orchestrated collective cellular motion. Based on these results, we propose a straightforward approach to efficiently form 3D embryo models through intrinsic CRISPRa-based epigenome editing and independent of external signaling cues. CRISPRa-Programmed Embryo Models (CPEMs) show highly consistent composition of major embryonic cell types that are spatially-organized, with nearly 80% of the structures forming an embryonic cavity. Single cell transcriptomics confirmed the presence of main embryonic cell types in CPEMs with transcriptional similarity to pre-gastrulation mouse embryos and revealed novel signaling communication links between different embryonic cell types. Our findings offer a programmable embryo model and demonstrate that minimum intrinsic epigenome editing is sufficient to self-organize ESCs into highly consistent pre-gastrulation embryo models

developmental biology↗

bioRxiv2024

BMP9 and BMP10 coordinate liver cellular crosstalk to maintain liver health

The liver is the largest solid organ in the body and is primarily composed of HCs, ECs, KCs, and HSCs, which spatially interact and cooperate with each other to maintain liver homeostasis. However, the complexity and molecular mechanisms underlying the crosstalk between these different cell types remain to be revealed. Here, we generated mice with conditional deletion of Bmp9/10 in different liver cell types and demonstrated that HSCs were the major source of BMP9 and BMP10 in the liver. Using transgenic ALK1 (receptor for BMP9/10) reporter mice, we found that ALK1 is expressed on KCs and ECs other than HCs and HSCs, and BMP9/10 secreted by HSCs promotes the differentiation of KCs and ECs and maintain their identity. Pdgfb expression was significantly upregulated in KCs and ECs after BMP9 and BMP10 deletion, ultimately leading to HSCs activation and liver fibrosis. ECs express several angiocrine factors, such as BMP2, BMP6, Wnt2 and Rspo3, to regulate hepatocyte iron metabolism and metabolic zonation. We found that these angiocrine factors were significantly decreased in ECs from Bmp9/10HSC-KO mice, which further resulted in liver iron overload and disruption of HC zonation. In summary, we demonstrated that HSCs play a central role in mediating liver cell-cell crosstalk via the production of BMP9/10, highlighting the important role of intercellular interaction in organ development and homeostasis.

cell biology↗

bioRxiv2024

Brain-controlled augmented hearing for spatially moving conversations in multi-talker environments

Focusing on a specific conversation amidst multiple interfering talkers presents a significant challenge, especially for the hearing-impaired. Brain-controlled assistive hearing devices aim to alleviate this problem by separating complex auditory scenes into distinct speech streams and enhancing the attended speech based on the listeners neural signals using auditory attention decoding (AAD). Departing from conventional AAD studies that relied on oversimplified scenarios with stationary talkers, we present a realistic AAD task that mirrors the dynamic nature of acoustic settings. This task involves focusing on one of two concurrent conversations, with multiple talkers taking turns and moving continuously in space with background noise. Invasive electroencephalography (iEEG) data were collected from three neurosurgical patients as they focused on one of the two moving conversations. We propose an enhanced brain-controlled assistive hearing system that combines AAD and a binaural speaker-independent speech separation model. The separation model unmixes talkers while preserving their spatial location and provides talker trajectories to the neural decoder to improve auditory attention decoding accuracy. Our subjective and objective evaluations show that the proposed system enhances speech intelligibility and facilitates conversation tracking while maintaining spatial cues and voice quality in challenging acoustic environments. This research demonstrates the potential of our approach in real-world scenarios and marks a significant step towards developing assistive hearing technologies that adapt to the intricate dynamics of everyday auditory experiences. TAKEAWAYS- Brain-controlled hearing device for scenarios with moving conversations in multi-talker settings, closely mimicking real-world listening environments - Developed a binaural speech separation model that separates speech of moving talkers while retaining their spatial locations, enhancing auditory perception and auditory attention decoding - Proposed system enhances speech intelligibility and reduces listening effort in realistic acoustic scenes

neuroscience↗

bioRxiv2024

A systematic evaluation of computation methods for cell segmentation

Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation and instance segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including image channels, choice of training data, and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, substantially reducing the time and effort for training cell segmentation models.

bioinformatics↗

bioRxiv2023

Genome-wide exploration of metabolic-based pyrethroid resistance mechanism in Helicoverpa armigera

To elucidate the deltamethrin resistance mechanism in Helicoverpa armigera, we explored mutations at the deltamethrin target site, genomic level variations between insecticide-susceptible and -resistant strains, and differences in gene expression patterns between the strains. Known pyrethroid resistance-associated point mutations within the voltage-gated sodium channel were undetected in the cDNA and gDNA of resistant strains or field populations. The whole-genome de novo assembly of a Korean resistant strain was performed (GCA_026262555.1), and 13 genomes of susceptible and resistant individuals were re-sequenced using field populations. Approximately 3,369,837 variants (SNPs and indels) were compared with our reference H. armigera genome, and 1,032,689 variants were identified from open reading frames. A resistance-specific CYP3 subfamily gene with five variants (CYP321A1v1-v5) was identified in the resistant strains, indicating the potential role of these variants in resistance. RNA-seq analysis identified 36,720 transcripts from 45 Illumina RNA-seq datasets of the fat body, gut, and the rest of the body. Differential gene expression analysis revealed some differently overexpressed detoxification enzyme genes in the resistant strains, particularly cytochrome P450 genes. This finding was consistent with the results of bioassay tests using PBO-based synergists, further supporting the role of detoxification enzymes in resistance. Therefore, H. armigera may acquire deltamethrin resistance through a combination of actions, including the overexpression of various detoxification enzymes, such as CYP3 subfamilies (CYP321A5) and cuticular proteins. The five variants of CYP321A subfamily identified in this study may serve as a basis for understanding insecticide resistance at the molecular level and can be applied as diagnostic markers for resistance. Key MessagesO_LIKnown resistance-related mutations were undetected in all the resistant strains or field populations. C_LIO_LINo specific resistance-associated variations were identified at the genomic level. C_LIO_LIThe expression pattern of the CYP3 subfamily genes was strongly correlated with the level of resistance. C_LIO_LIGenes other than CYP337B3 are also involved in the development of high-level resistance. C_LIO_LIResistance developed as a result of changes in the expression of detoxification genes rather than target site modification through mutation. C_LI

ecology↗

bioRxiv2023

Regulation of blood pressure by METTL3 via RUNX1b-eNOS pathway in endothelial cells

BackgroundEndothelial cells regulate vascular tone to control the blood pressure (BP) by producing both relaxing and contracting factors. Previously, we identified methyltransferase-like 3 (METTL3), a primary N6-methyladenosine (m6A) methyltransferase, as a key player in alleviating endothelial atherogenic progression. However, its involvement in BP regulation remains unclear. MethodsTo evaluate the role of METTL3 in vivo, mice with EC specific METTL3 deficiency (EC-Mettl3KO) with or without Ang II infusion were used to create a hypertensive model. Functional and MeRIP sequencing analysis were performed to explore the mechanism of METTL3-mediated hypertension. ResultsWe observed a reduction in endothelial METTL3 activity by Ang II in vitro and in vivo. Endothelial METTL3-deficient mice exhibited higher BP than controls, both before and after Ang II infusion. Through m6A sequencing and functional analysis, we identified m6A modification of various RUNX1 monomers resulted in endothelial dysfunction. Mutations in the 3'UTR region of RUNX1b abolished its luciferase reporter activity, and enhanced eNOS promoter luciferase reporter activity with or without METTL3 overexpression. Overexpression of METTL3 by adeno-associated virus reduced Ang II-induced BP elevation. ConclusionThis study reveals that METTL3 alleviates hypertension through m6A-dependent stabilization of RUNX1b mRNA, leading to upregulation of eNOS, thus underscoring the pivotal role of RNA transcriptomics in the regulation of hypertension.

cell biology↗