Biology subjects

Ali, H.

Publications and source records attributed to Ali, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Population-Scale Landscape of Mobile Element Insertions Across 82 Diverse Indian Populations

Mobile element insertions (MEIs) are a major source of structural variation in human DNA that can affect gene regulation and disrupt coding sequences. Population-scale MEI catalogs remain disproportionately skewed toward European-ancestry cohorts, with limited representation from India despite comprising nearly one-sixth of the global population and encompassing thousands of genetically distinct, largely endogamous communities. We characterized non-reference Alu and LINE1 insertions in 7,478 whole genomes from the GenomeIndia project, representing 82 populations selected to capture Indias geographic, linguistic, and social diversity. We cataloged 26,977 Alu and 7,075 LINE1 insertions, identifying 18,982 previously unreported insertions absent from existing publicly available MEI databases. Insertions bore signatures of purifying selection, depleted in exons and active chromatin and enriched in quiescent regions. MEI variants recapitulated the population structure seen in SNP data. Regulatory variation associated with MEIs was strongly population-structured, with a substantial fraction of European-defined MEI-eQTLs absent in the GenomeIndia cohort or carried at sharply different frequencies across communities, and MEIs in high linkage disequilibrium with GWAS variants. Sixty-nine insertions fell within exons, including a truncating LINE1 in CYP2J2 carried across five populations and a community-specific Alu in CABYR with a founder-effect signature. Collectively, these results reveal a layer of population-specific mobile element variation in Indian populations that is not captured by existing European-anchored reference resources. These variants represent potentially novel sources of genetic variation contributing to lack of transferability of disease associations across populations.

genomics↗

bioRxiv2026

Generalisable signatures of anaesthesia in the large-scale functional organisation of the marmoset brain

How the activity and connectivity of the brain support consciousness remains a central question in neuroscience. Recent progress driven by the use of functional MRI has seen growing recognition that large-scale distributed functional organisation of the human and non-human primate brain are systematically and consistently reshaped by anaesthetic-induced unconsciousness, across anaesthetics and across human and macaque. Here, we generalise these results to a different primate species that is gaining traction as model organism in neuroscience, the marmoset (Callithrix jacchus). We also generalise results to an additional anaesthetic, isoflurane, which we compare with propofol and sevoflurane. We report that under anaesthesia with propofol, sevoflurane, or isoflurane, distributed brain activity from functional MRI is increasingly constrained by the underlying structural connectivity across scales. Anaesthesia also induces a collapse of the principal gradient and intrinsic functional geometry of the marmoset brain, coinciding with a breakdown of hierarchical integration. Altogether, the present results indicate generalisable signatures of anaesthesia in the large-scale organisation of the primate brain.

neuroscience↗

bioRxiv2026

Cervicovaginal Dysbiosis in HPV-Negative Women: Metagenomic Evidence Implicates Achromobacter in Female Infertility

The cervicovaginal microbiome is pivotal to reproductive health, yet its dynamics in HPV-negative women with gynaecological disorders remain underexplored. We investigated microbial diversity and taxonomic shifts in HPV-negative women from Bangladesh using 16S rRNA gene sequencing and shotgun metagenomics. Of 224 women screened, 136 were HPV-negative; 29 underwent 16S profiling, and three infertility-associated cases were further analyzed by shotgun metagenomics. Healthy controls exhibited low alpha diversity and a Lactobacillus-dominated profile (98.2%), reflecting ecological stability. In contrast, pathological cases displayed significantly elevated richness and evenness, reduced Lactobacillus (28.0%), and enrichment of anaerobic and opportunistic taxa, including Bifidobacterium (23.4%), Achromobacter (12.9%) and Sneathia (7.5%). Distinct microbial signatures emerged across clinical subgroups: pelvic inflammatory disease was enriched in Bifidobacterium, intra-menstrual bleeding retained moderate Lactobacillus, while infertility exhibited prominent dominance of Achromobacter (45.5%). Shotgun metagenomics confirmed Achromobacter spp. (A. ruhlandii, A. dolens, A. xylosoxidans) as the predominant taxa (84.9%) in infertility cases, accompanied by depletion of protective Lactobacillus. Functional inference revealed conserved metabolic backbones but disease-specific enrichment of stress-response and biosynthetic pathways, particularly in infertility and PID. Co-occurrence network analysis identified condition-specific microbial consortia, with Achromobacter forming infertility-associated clusters. This study represents the first integrated application of amplicon and shotgun metagenomic approaches to profile the cervicovaginal microbiota in HPV-negative women. It identifies Achromobacter as a potential microbial biomarker of infertility and highlights the urgent need for microbiome-informed diagnostics and targeted interventions to restore cervicovaginal homeostasis.

microbiology↗

bioRxiv2026

Hybrid TF-IDF and SBERT Feature Engineering with SMOTE-Tomek Resampling for Enhanced Software Requirements Classification

Software requirements classification remains one of the important challenges in requirements engineering. Engineering that affects the smoothness of project success about software development life cycles. in this paper, a novel hybrid solution is being presented that beats the benchmarks set by previous approaches using TF-IDF. The vectorization, coupled with SBERT embeddings, has been further reinforced by application of SMOTE-Tomek resampling. The solution addresses typical limitations detected in Ors baseline solution, which achieved 76.16% {+/-} 2.58% accuracy of the model using the conventional SMOTE-Tomek pre-processing with logistic regression. Via comprehensive experimentation on the PROMISE dataset containing 969 categorized requirements accross 12 classes, our hybrid feature engineering approach has shown significant improvements: Random Forest achieves. Thus, the character CNN records an accuracy of 74.40% {+/-} 3.00% versus the baseline 60.37% {+/-} 2.76%, while critically, Naive Bayes shows remarkable improvement from complete failure 0.00% to 53.97% {+/-} 5.08% accuracy. The integration of semantic contextual understanding through SBBERT, with statistical term importances via TF-IDF, forms a robust representation space that captures the synthetic pattern along with semantic relations in the texts of requirements. Our methodology uses stratified 10-fold cross-validation with Matthews Correlation Coefficient (MCC). Evaluation, Ensuring reliable performance assessment across imbalanced classes. The results demonstrate that hybrid feature engineering, when combined with appropriate resampling techniques, provides a more effective solution for automated software requirement classification than traditional pre-processing methods alone.

bioinformatics↗

bioRxiv2026

In-Depth Characterization of Stem Cell Potency and Genotoxicity for Clinical-Scale Ex Vivo CRISPR/Cas9 Gene Editing

Translating CRISPR/Cas9-based homology-directed repair (HDR) strategies into clinical application remains a major challenge due to limited standardization, concerns over safety, and efficacy issues. Here, we present a comprehensive and clinically compliant preclinical framework for the ex vivo correction of Wiskott-Aldrich Syndrome (WAS) using a CRISPR/Cas9-AAV6 platform targeting hematopoietic stem and progenitor cells (HSPCs). In this study, we established a clinical-compatible platform enabling large-scale manufacturing while preserving HSPC viability, stemness, and multilineage functionality. To overcome low HSPC long-term engraftment, we fine-tuned AAV dosing and transiently modulated p53 signalling, achieving significantly improved in vivo correction and repopulation. Importantly, we implemented a multi-tiered genotoxicity assessment strategy, integrating in silico, genome-wide, and orthogonal assays, revealing a largely favorable safety profile with minimal off-target risks and no signs of clonal dominance or transformation. Longitudinal in vivo safety monitoring revealed donor specific rare off-target events and structural variants. This highlights the crucial importance of patient monitoring after transplantation, further emphasized by the identification of a de novo chromosomal rearrangements that could be detected exclusively following cell engraftment in mice. This work offers a robust and adaptable roadmap for future HDR-based gene editing platforms, establishing critical benchmarks for efficacy, safety, and regulatory readiness in the development of advanced therapeutic medicinal products.

molecular biology↗

bioRxiv2025

Cognitive cartography of mammalian brains using meta-analysis of AI experts

The complexity of the brain is increasingly mirrored by the complexity of the neuroscientific literature, yet no individual mind can fully grasp the diversity of scales, methodologies and model organisms. Where human experts flag, the latest AI models excel: large language models can seamlessly integrate knowledge across scientific domains. Here we show how large language models can systematically and quantitatively synthesise literature-wide neuroscientific knowledge about the cognitive operations and dysfunctions associated with each brain region. Meta-analysis of AI experts reveals structure-function mappings to which existing meta-analytic frameworks are blind, demonstrated by lesions and direct intracranial stimulation. It also unlocks the possibility of extending quantitative literature meta-analysis and decoding of brain maps to other model organisms beyond human. As proof of concept, we integrate LLM meta-analysis with species-specific transcriptomics in human, macaque, and mouse, to discover an evolutionarily conserved molecular circuit for cognition. Altogether, meta-analysis of AI experts can fundamentally catalyze neuroscientific discovery by overcoming the barrier of data aggregation from heterogeneous studies, finally bringing together a scattered literature to identify emergent patterns and latent insights across disparate subfields, modalities, and species.

neuroscience↗

bioRxiv2025

A modified cyclosporine enhances lentivector transduction ex vivo and in vivo by degrading IFITM3

Intrinsic innate immune barriers have evolved to suppress viral infection and can reduce effective gene delivery in gene therapy. We have developed BG147, a novel cyclosporine A analogue, optimised via structure-guided design to prevent inhibition of HIV cofactor Cyclophilin A and to specifically inhibit interferon-induced transmembrane proteins (IFITM1-3). BG147 enhances VSV-G pseudotyped lentiviral vector transduction ex vivo in hematopoietic stem and progenitor cells (HSPCs) and in in vivo ocular gene therapy of photoreceptor cells in mice. Upon BG147 treatment, IFITM proteins are mislocalised and degraded through lysosomal acidification-dependent pathways. IFITM3 levels functionally return in cells 96 h after BG147 washout. BG147 promises to transform ex vivo and in vivo eye gene therapies by transiently inhibiting intrinsic immune barriers mediated by IFITM proteins to enhance a wide range of protocols. One Sentence SummaryModified cyclosporine, BG147, enhances lentivector gene therapy transduction, ex vivo in HSPC and in vivo in mouse photoreceptors, by degrading IFITM3.

cell biology↗

bioRxiv2025

Molecular mimicry of plant cell-surface immune receptors by fungal secreted leucine-rich repeat proteins

O_LILeucine-rich repeat (LRR) receptor-like kinases (LRR-RLKs) are important plant immunity proteins. The wheat pathogen Zymoseptoria tritici produces many virulence effectors during infection; however, most remain uncharacterised. We identified a secreted protein from Z. tritici (ZtLRR) that consists of a single LRR domain and hypothesised that it mimics host LRR-RLKs to suppress plant immunity. C_LIO_LIWe used transient expression to probe ZtLRR function related to production of reactive oxygen species (ROS) and cell death, two important immune processes. We used AlphaFold structural predictions with targeted yeast two-hybrid to demonstrate protein-protein interactions. Transgenic wheat allowed assessment of effector function in the natural host. C_LIO_LIZtLRR suppressed ROS production and cell death in N. benthamiana with high potency. Structural predictions suggested high similarity to several plant LRR-RLKs and interaction with TaBAK1 was confirmed by targeted yeast two-hybrid. Transgenic wheat expressing ZtLRR was impaired in PAMP-triggered immunity (PTI) and had increased susceptibility to infection with compatible Z. tritici. We identified structural orthologs of ZtLRR in diverse fungal lineages and demonstrated that several of these proteins have similar immune-suppressing properties as ZtLRR. C_LIO_LIOur work demonstrates that molecular mimicry of host LRR-RLKs by phytopathogen sLRR effectors is effective at disrupting host immune pathways. C_LI

molecular biology↗

bioRxiv2025

An engine for systematic discovery of cause-effect relationships between brain structure and function

Characterising how perturbations of brain architecture influence brain function is essential to understand the origins of brain dysfunction, and devise potential avenues of treatment. Here we introduce a computational engine for systematic causal discovery of the functional consequences of altering network architecture and local biophysics in the brain. We integrate multimodal anatomical and functional neuroimaging to implement over 2, 000 in-silico brains, and provide mechanistic insight into the functional consequences of local lesions, global wiring, and empirically-derived maps of regional cytoarchitecture and chemoarchitecture. We comprehensively assess how each manipulation of brain macrostructure reshapes spatial and temporal signal coordination, information dynamics, and functional hierarchy--as well as spontaneous co-activation of meta-analytic cognitive circuits, and > 6, 000 dimensions of local neural dynamics. Our computational model systematically identifies which features of brain architecture have overlapping or antagonistic causal influence over each dimension of brain function, and how functional properties are traded off against each other across disorders and neuromodulation. We find that regions functional vulnerability to lesions in silico recapitulates their vulnerability to neurodevelopmental and psychiatric in vivo, along a core-periphery organisation. We provide convergent evidence that the brains wiring diagram is finely tuned to favour the hierarchical integration of information. Notably, our model successfully recapitulates known empirical results that have not been modelled before, including desynchronisation and flattening of the brains functional hierarchy induced by psychedelic 5HT2A agonists. To catalyse future discoveries, we make this resource freely available to the neuroscience community through an interactive website (https://systematic-causal-mapping.up.railway.app/), where users can interrogate our systematic database of simulated cause-effect relationships. Altogether, we provide a powerful computational engine to predict the functional consequences of experimental or clinical interventions, and drive neuroscientific hypothesis-generation.

neuroscience↗

bioRxiv2025

From Shadows to Data: A Robust Population Assessment of Snow Leopards in the Highland Crossroads

The snow leopard (Panthera uncia) is a flagship species of the greater Himalayan region - referred to as the Third Pole - and symbolizes integrity of this ecological system. Within the greater Himalayas, Pakistan holds special significance as the north of the country represents a confluence of four major mountain ranges (Hindu Kush, Pamir, Karakoram, and Himalaya). However, robustly surveying and monitoring elusive, low-density species such as snow leopards has historically been difficult in the region. As a result, our understanding of the spatial patterns in density and overall population size of snow leopards has remained conjectural in the highland crossroads of northern Pakistan. This lack of objective information is an obstacle to realizing effective conservation planning for the species in Pakistan, as well as the broader ecosystem within which it plays a key role. This study aimed to empirically derive population estimates for snow leopards in Pakistan, based on robust camera trapping. Extensive camera trapping was conducted covering about 39% of the snow leopard range in Pakistan from 2010 to 2019, spread across the four major mountain ranges in the north of the country. A total of 828 cameras were placed over 26,540 trap days, resulting in 4,712 photos of snow leopards obtained from 65 different locations. Among the 53 unique individuals identified, the majority (53%) were detected only once, with an overall recapture frequency of 2.28 times per individual. Spatial capture-recapture (SCR) was employed for population and density estimation. Model selection strongly favored a model in which density was positively associated with elevation, and camera type influenced baseline encounter rates. The estimated population size for snow leopards in this highland crossroads was 127 (95% CI 88-182) adult animals, with a mean density of 0.13 (95% CI 0.09-0.19) animals per 100 km{superscript 2}. Examination of the density predictions revealed that higher density areas were associated with protected areas and greater prey biomass, highlighting the importance of these two key factors. This research provides the first robust population estimate for snow leopards in this region, establishing a foundation for long-term population monitoring and assessing the effectiveness of conservation measures. We recommend the integration of complementary approaches, such as non-invasive genetic methods, to validate and refine population estimates.

ecology↗

bioRxiv2025

Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

Although GBMs immunosuppressive environment is well known, the tumors resistance to CD8+ T cell killing is not fully understood. Our previous study identified Checkpoint Kinase 2 (Chek2) as the key driver of CD8+ T cell resistance in mouse glioma through an in vivo CRISPR screen and demonstrated that Chk2 inhibition, combined with PD-1/PD-L1 blockade, significantly enhanced CD8+ T cell-mediated tumor killing and improved survival in preclinical model. Here, we aimed to elucidate the immunosuppressive function of Chek2. Immunoprecipitation (IP) followed by mass spectrometry (MS) and phosphoproteomics identified an association between Chek2 with the DNA/RNA-binding proteins YBX1 and YBX3 that are implicated in transcriptional repression of pro-inflammatory genes. Single-gene knock-out and overexpression studies of CHEK2, YBX1, and YBX3 in multiple glioma cell lines revealed that these proteins positively regulate each others expression. RNA sequencing coupled with chromatin immunoprecipitation-sequencing (ChIP-seq) analysis demonstrated common inflammatory genes repressed by CHK2-YBX1&YBX3 hub. Targeting one of the hub proteins, YBX1, with the YBX1 inhibitor SU056 led to degradation of CHK2-YBX1&YBX3 hub. Targeting of this hub by SU056 led to enhanced antigen presentation and antigen specific CD8+ T cell proliferation. Further, combination of SU056 with ICB significantly improved survival in multiple glioma models. Collectively, these findings reveal an immunosuppressive mechanism mediated by the CHK2-YBX1&YBX3 hub proteins. Therefore, CHK2-YBX1&YBX3 hub targeting in combination with immune checkpoint blockade therapies in gliomas is warranted.

cancer biology↗

bioRxiv2024

The propensity of fructose to induce metabolic dysfunction is dependent on the baseline diet, length of the dietary exposure, and sex of the mice.

Background/ObjectivesNumerous studies have implicated high intake of sugar, particularly fructose, with the development of obesity and metabolic complications. On the other hand, fructose from fruits and vegetables has undisputed benefits for metabolic health. This paradox questions how the same fructose molecule can be associated with detrimental health effects in some studies and beneficial in others. MethodsTo answer this question, male and female mice were fed different normal chow diets and provided 30% fructose solution in water. ResultsFructose-supplemented male mice on the Boston Chow Diet (BCD=23% protein, 22% fat, 55% carbs) gained weight, developed glucose intolerance and hepatic steatosis. In contrast, male mice on the Lexington Chow Diet (LXD=24% protein, 18% fat, 58% carbs) did not gain weight, remained glucose tolerant, and had normal hepatic lipid content when supplemented with fructose. Furthermore, fructose-fed male mice on a Low-Fat Diet (LFD=20% protein, 10% fat, 70% carbs) didnt gain weight, but once switched to the BCD, they gained weight, exhibited worsening liver steatosis, and more advanced hepatic insulin resistance. The effects of fructose are sex-dependent, as female mice didnt gain weight and remained insulin-sensitive when given fructose on BCD, despite developing hepatic steatosis. ConclusionsThe differences in metabolic outcomes correlate with the propensity of the baseline diet to suppress hepatic ketohexokinase expression and the de novo lipogenesis pathway. This is likely driven by the dietary fat-to-carbohydrate ratio. Thus, metabolic dysfunction attributed to fructose intake is not a universal outcome; rather, it depends on the baseline diet, sex, and exposure length.

molecular biology↗

bioRxiv2024

Next-generation snow leopard population assessment tool: multiplex-PCR SNP panel for individual identification from feces

Snow leopards, Panthera uncia, are under threat from numerous pressures and are the focus of a great deal of conservation efforts. However, their elusive nature makes it difficult to estimate population sizes. Current methods used to monitor local population sizes include visually identifying individuals from camera trap photos and genetically identifying individuals from fecal samples using microsatellite loci. Here, we present a new method for identifying snow leopard individuals from fecal samples using a multiplex PCR single nucleotide polymorphism (SNP) panel method. The SNP panel we present consists of 144 SNPs and utilizes next-generation sequencing technology, making it cheaper and easier than current microsatellite methods. We validate our SNP panel with paired tissue and fecal samples from zoo individuals, showing a minimum of 96.7% accuracy in allele calls per run. We then generate SNP data from 235 field-collected fecal samples from across Pakistan to show that the panel can reliably identify individuals from low-quality fecal samples of unknown age and is robust to contamination. We also show that our SNP panel has the capability to identify first-order relatives and provides insights into the geographic origin of samples. This SNP panel will empower the snow leopard research community in their efforts to assess local and global snow leopard population sizes. More broadly, we present a method for developing a SNP panel that utilizes open source software for SNP selection and primer design, Illumina sequencing technology, and a streamlined lab and bioinformatics protocol which can be used to create similar SNP panels for any species of interest for which adequate genomic reference data is available.

genetics↗

bioRxiv2024

Phytochemical Analysis and Cytotoxic Effects of Phyllanthus polygonoides Leaf Extracts on Hepatocellular Carcinoma: A Combined In-Vitro and In-Silico Approach

The authors have withdrawn their manuscript owing to the Paper was mistakenly uploaded by the students and the paper was having a lots of mistake and fake data. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

bioinformatics↗

bioRxiv2024

Exploration of Flavonoids to identify Potential Therapeutic Compounds by Targeting the Non-Structural V protein of Nipah Virus

Researchers are interested in a number of interdisciplinary approaches that might speed up and reduce the cost of creating new medications. This work aims to determine target proteins and choose a lead medication to combat the Nipah Virus. Following a study of the literature, we discover the non-structural V protein (UniProt ID: Q997F2). I-TASSER was used to estimate the 3D structure. We examined the flavonoid dataset in search of a strong inhibitor. Pyrx is used to use AutoDock Vina for docking. The interactions between the drug and the target protein binding were examined using BIOVIA Discovery Studio. Desmonds Molecular Dynamics Simulation (MD simulation) was used to study the stability of protein and inhibitor complexes in a physiological environment. Based on our research, we have designed two lead compounds that lessen the viruss effect. This discovery will benefit science as it may lead to the development of novel medications. The newly discovered natural compounds showed promise as inhibitors, showing less adverse effects and more efficiency.

biochemistry↗

bioRxiv2024

An array of Zymoseptoria tritici effectors suppress plant immune responses

Zymoseptoria tritici is the most economically significant fungal pathogen of wheat in Europe. However, despite the importance of this pathogen, the molecular interactions between pathogen and host during infection are not well understood. Herein, we describe the use of two libraries of cloned Z. tritici effectors that were screened to identify effector candidates with putative pathogen associated molecular pattern (PAMP) triggered immunity (PTI)-suppressing activity. The effectors from each library were transiently expressed in Nicotiana benthamiana, and expressing leaves were treated with bacterial or fungal PAMPs to assess the effectors ability to suppress reactive oxygen species (ROS) production. From these screens, numerous effectors were identified with PTI-suppressing activity. In addition, some effectors were able to suppress cell death responses induced by other Z. tritici secreted proteins. We used structural prediction tools to predict the putative structures of all of the Z. tritici effectors, and used these predictions to examine whether there was enrichment of specific structural signatures among the PTI-suppressing effectors. From among the libraries, multiple members of the killer protein-like 4 (KP4) and killer protein-like 6 (KP6) effector families were identified as PTI-suppressors. This observation is intriguing, as these protein families were previously associated with antimicrobial activity rather than virulence or host manipulation. This data provides mechanistic insight into immune suppression by Z. tritici during infection, and suggests that similar to biotrophic pathogens, this fungus relies on a battery of secreted effectors to suppress host immunity during early phases of colonisation.

plant biology↗

bioRxiv2024

Distinguishable topological properties of functional genome networks in HIV-1 reservoirs

HIV-1 reservoirs display heterogeneous nature, lodging both intact and defective proviruses. Recent evidence has shed light on their difference, particularly in the context of immune-mediated selection. To deepen our understanding of such heterogeneous HIV-1 reservoirs and their functional implications, we pioneered the integration of basic concepts of graph theory to characterize the composition of HIV-1 reservoirs. Our analysis revealed noticeable topological properties in networks, featuring immunologic signatures enriched by genes harboring intact and defective proviruses, when comparing antiretroviral therapy (ART)-treated HIV-1-infected individuals and elite controllers. The key variable, the rich factor, played a pivotal role in classifying distinct topological properties in networks. The host gene expression strengthened the accuracy of classification between elite controllers and ART-treated patients. Overall, our work provides a prime example of leveraging genomic approaches alongside mathematical tools to unravel the complexities of HIV-1 reservoirs.

genomics↗

bioRxiv2024

The astrovirus N-terminal nonstructural protein anchors replication complexes to the perinuclear ER membranes

An essential aspect of viral replication is the anchoring of the replication complex (RC) to cellular membranes. Positive-sense RNA viruses employ diverse strategies, including co-translational membrane targeting through signal peptides and co-opting cellular membrane trafficking components. Often, N-terminal nonstructural proteins play a crucial role in linking the RC to membranes, facilitating the early association of the replication machinery. Astroviruses utilize a polyprotein strategy to synthesize nonstructural proteins, relying on subsequent processing to form replication-competent complexes. In this study, we provide evidence for the perinuclear ER membrane association of RCs in five distinct human astrovirus strains. Using tagged recombinant classical human astrovirus 1 and neurotropic MLB2 strains, we establish that the N-terminal domain guides the ER membrane association. Through mutational analysis of the N-terminal domain in replicon and reverse genetics systems, we identified di-arginine motifs responsible for the perinuclear ER retention and formation of functional RCs. Our findings highlight the intricate virus-ER interaction mechanism employed by astroviruses, potentially leading to the development of novel antiviral intervention strategies. Author SummaryHuman astroviruses are a significant cause of acute gastroenteritis, accounting for up to 9% of cases in young children. Immunocompromised individuals and infants experience more critical symptoms, such as severe and persistent diarrhea, as well as sporadic systemic and even fatal diseases. To date, no drugs have been developed to protect against astrovirus infection. Our study provides the first evidence that the integrity of the N-terminal domain of nsP1a is essential for establishing early replication. Central to this process, the di-arginine motifs in the N-terminal domain are responsible for ER retention, the formation of functional replication complexes, and viral replication. Therefore, selectively targeting N-terminal domain-mediated ER retention could be a promising therapeutic strategy to effectively control astrovirus infection.

microbiology↗