Biology subjects

Zhang, F.

Publications and source records attributed to Zhang, F..

At least 199 records · Page 11Linked to original sources

bioRxiv2024

Alcohol Sipping Patterns, Personality, and Psychopathology in Children: Moderating Effects of Dorsal Anterior Cingulate Cortex (dACC)

Alcohol, the most consumed drug in the United States, is associated with various psychological disorders and abnormal personality traits. Despite extensive research on adolescent alcohol consumption, the impact of early alcohol sipping patterns on changes in personality and mental health over time remains unclear. There is also limited information on the latent trajectory of early alcohol sipping, beginning as young as 9-10 years old. The dorsal anterior cingulate cortex (dACC) is crucial for cognitive control and response inhibition. However, the role of dACC remains unclear in the relationship between early alcohol sipping and mental health outcomes and personality traits over time. Utilizing the large data from the Adolescent Brain and Cognitive Development study, we aim to comprehensively examine the longitudinal impact of early alcohol sipping patterns on psychopathological measures and personality traits in adolescents, filling crucial gaps in the literature. We identified three latent alcohol-sipping groups, which demonstrate distinct personality traits and depression score trajectories. Bilateral dACC activation during the stop-signal task moderated the effect of early alcohol sipping on personality and depression over time. Additionally, bidirectional effects were observed between alcohol sipping and personality traits. This study provides insights into the impact of early alcohol consumption on adolescent development.

neuroscience↗

bioRxiv2024

Genome scale CRISPR screens identify actin capping proteins as key modulators of therapeutic responses to radiation and immunotherapy

Radiotherapy (RT), is a fundamental treatment for malignant tumors and is used in over half of cancer patients. As radiation can promote anti-tumor immune effects, a promising therapeutic strategy is to combine radiation with immune checkpoint inhibitors (ICIs). However, the genetic determinants that impact therapeutic response in the context of combination therapy with radiation and ICI have not been systematically investigated. To unbiasedly identify the tumor intrinsic genetic factors governing such responses, we performed a set of genome-scale CRISPR screens in melanoma cells for cancer survival in response to low-dose genotoxic radiation treatment, in the context of CD8 T cell co-culture and with anti-PD1 checkpoint blockade antibody. Two actin capping proteins, Capza3 and Capg, emerged as top hits that upon inactivation promote the survival of melanoma cells in such settings. Capza3 and Capg knockouts (KOs) in mouse and human cancer cells display persistent DNA damage due to impaired homology directed repair (HDR); along with increased radiation, chemotherapy, and DNA repair inhibitor sensitivity. However, when cancer cells with these genes inactivated were exposed to sublethal radiation, the persistence of DNA damage promoted activation of the STING pathway, induction of inhibitory CEACAM1 ligand expression and resistance to CD8 T cell killing. Patient cancer genomics analysis reveals an increased mutational burden in patients with inactivating mutations in CAPG and/or CAPZA3, at levels comparable to other HDR associated genes. There is also a positive correlation between CAPG expression, CD8 T cell tumor infiltration and response to immunotherapy among patient datasets. Our results unveil the critical roles of actin binding proteins for efficient HDR within cancer cells and demonstrate a previously unrecognized regulatory mechanism of therapeutic response to radiation and immunotherapy.

genetics↗

bioRxiv2024

Emotional prosody modulates visual mental imagery

Perceptual stimulis emotional properties are vital for human evolution and adaptation. While visual imagery is predominantly regarded as a weak form of perception, the influence of cross-modal emotional features on imagery is still unknown. The present study aims to investigate how emotional prosody modulates imagery quality (i.e., accuracy and clarity) and neural mechanisms using a combination of behavioral tasks and functional magnetic resonance imaging (fMRI). At the behavioral level, our results showed that frustrated conditions induced significant prosody effects on visual mental imagery quality measures, and the effects were particularly pronounced in individuals with lower imagery use tendency. At the neural level, compared with the neutral condition, the emotional prosody conditions (both happy and frustrated) showed stronger activation in various regions including the middle occipital gyrus, supporting the critical role of primary visual system in imagery. Moreover, compared to the frustrated prosody condition, the happy prosody showed stronger activation in the precuneus and anterior cingulate cortex, which are core components of the default mode network. A machine learning prediction analysis with a random forest model identified a significant brain-behavioral correlation between prosody-linked neural activity and individual imagery use tendency. A subsequent Shapley Additive exPlanations (SHAP) analysis further highlighted the primary visual and default mode regions as top contributors to this prediction. Taken together, these results provide new insights for the understanding of how emotional prosody modulates visual mental imagery, considering individual differences, and provide compelling evidence for incorporating emotion as important shaping factor in more general model for imagery.

neuroscience↗

bioRxiv2024

Chromosome-scale genome assembly of Camellia crapnelliana provides insights into the fatty acid biosynthesis

Camellia crapnelliana Tutch., belonging to the Theaceae family, is an excellent landscape tree species with high ornamental value. It is particularly an important woody oil-bearing plant with high ecological, economic, and medicinal values. Here, we first report the chromosome-scale reference genome of C. crapnelliana with integrated technologies of SMRT, Hi-C and Illumina sequencing platforms. The genome assembly had a total length of [~]2.94 Gb with contig N50 of [~]67.5 Mb, and [~]96.34% of contigs were assigned to 15 chromosomes. In total, we predicted 37,390 protein-coding genes, [~]99.00% of which were functionally annotated. Comparative genomic analysis showed that the C. crapnelliana genome underwent a whole-genome duplication event shared across the Camellia species and an {gamma} -WGT event that was shared by all core eudicot plants. Furthermore, we identified the major genes involved in the biosynthesis of oleic acids and terpenoids in C. crapnelliana. The chromosome-scale genome of C. crapnelliana will become valuable resources for understanding the genetic basis of the fatty acid biosynthesis, and greatly facilitate the exploration and conservation of C. crapnelliana.

genomics↗

bioRxiv2024

A new story of four Hexapoda classes: Protura as the sister to all other hexapods

Insects represent the most diverse animal group, yet previous phylogenetic analyses based on the morphological and molecular data have failed to agree on the evolutionary relationships of early insects and their six-legged relatives (together constituting the clade Hexapoda). In particular, the phylogenetic positions of the three early-diverging hexapod groups, the coneheads (Protura), springtails (Collembola), and two-pronged bristletails (Diplura), have been debated for over a century, with alternative topologies implying drastically different scenarios of the evolution of the insect body plan and hexapod terrestrialisation. We addressed this issue by sampling of all hexapod orders, and experimented with a broad range of across-site compositional heterogeneous models designed to tackle ancient divergences. Our analyses support Protura as the earliest-diverging hexapod lineage (Protura-sister) and Collembola as a sister group to the Diplura, a clade we refer to as Antennomusculata characterised by the shared possession of internal muscles in the antennal flagellum. The universally recognized Ellipura hypothesis is recovered under the site-homogenous LG model. Our cross-validation analysis shows that the CAT-GTR model that recovers Protura-sister fits significantly better than homogenous model. Furthermore, as a very unusual group, Protura as the first diverging lineage of hexapods is also supported by other lines of evidence, such as mitogenomics, comparative embryology, and sperm morphology. The backbone phylogeny of hexapods recovered in this study will facilitate the exploration of the underpinnings of hexapod terrestrialisation and mega-diversity.

evolutionary biology↗

bioRxiv2024

A Combinatorial Strategy for HRV 3C Protease Engineering to Achieve the N-terminal Free Cleavage

Human rhinovirus 3C protease (HRV 3C-P) has a high specificity against the substrate of LEVLFQ{downarrow}G at P1 site, which plays an important role in biotechnology and academia as a fusion tag removal tool. However, a non-ignorable limitation is that an extra residue of Gly would remain at the N terminus of the recombinant target protein after cleavage with HRV 3C-P, thus potentially causing protein mis-functionality or immunogenicity. Here, we developed a combinatorial strategy by integrating structure-guided library design and high-throughput screening of eYESS approach for HRV 3C-P engineering to expand its P1 specificity. Finally, a C3 variant was obtained, exhibiting a broad substrate P1 specificity to recognize 20 different amino acids with the highest activity against LEVLFQ{downarrow}M (kcat/KM= 3.72 {+/-} 0.04 mM-1{middle dot}s-1). Further biochemical and NGS-mediated substrate profiling analysis showed that C3 variant still kept its substrate stringency at P1 site and good residue tolerance at P2 site, but with an expanded P1 specificity. Structural simulation of C3 indicated a reconstructed S1 binding pocket as well as new interactions with the substrates. Overall, our studies here prompt not only the practical applications and understanding of substrate recognition mechanisms of HRV 3C-P, also provide new tools for other enzyme engineering. Abstract graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC="FIGDIR/small/574269v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@b891eborg.highwire.dtl.DTLVardef@174151dorg.highwire.dtl.DTLVardef@1656f4org.highwire.dtl.DTLVardef@a6c1bb_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Tractography-based automated identification of the retinogeniculate visual pathway with novel microstructure-informed supervised contrastive learning

The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and can inform the treatment of related brain diseases. Diffusion MRI (dMRI) tractography is an advanced imaging method that uniquely enables in vivo mapping of the 3D trajectory of the RGVP. Currently, identification of the RGVP from tractography data relies on expert (manual) selection of tractography streamlines, which is time-consuming, has high clinical and expert labor costs, and is affected by inter-observer variability. In this paper, we present a novel deep learning framework, DeepRGVP, to enable fast and accurate identification of the RGVP from dMRI tractography data. We design a novel microstructure-informed supervised contrastive learning method that leverages both streamline label and tissue microstructure information to determine positive and negative pairs. We propose a simple and successful streamline-level data augmentation method to address highly imbalanced training data, where the number of RGVP streamlines is much lower than that of non-RGVP streamlines. We perform comparisons with several state-of-the-art deep learning methods that were designed for tractography parcellation, and we show superior RGVP identification results using DeepRGVP. In addition, we demonstrate a good generalizability of DeepRGVP to dMRI tractography data from neurosurgical patients with pituitary tumors and we show DeepRGVP can successfully identify RGVPs despite the effect of lesions affecting the RGVPs. Overall, our study shows the high potential of using deep learning to automatically identify the RGVP.

neuroscience↗

bioRxiv2024

Predicting RNA Sequence-Structure Likelihood via Structure-Aware Deep Learning

MotivationThe active functionalities of RNA are recognized to heavily dependent on the structure and sequence. Therefore, A model that can accurately evaluate a design by giving RNA sequence-structure pairs would be a valuable tool for many researchers. Machine learning methods have been explored to develop such tools, showing promising results. However, two key issues remain. Firstly, the performance of machine learning models is affected by the features used to characterize RNA. Currently, there is no consensus on which features are the most effective for characterizing RNA sequence-structure pairs. Secondly, most existing machine learning methods extract features describing entire RNA molecule. We argue that it is essential to define additional features that characterize nucleotides and specific sections of RNA structure to enhance the overall efficacy of the RNA design process. ResultsWe develop two deep learning models for evaluating RNA sequence-structure pairs. The first model, NU-ResNet, uses a convolutional neural network architecture that solves the aforementioned problems by explicitly encoding RNA sequence-structure information into a 3D matrix. Building upon NU-ResNet, our second deep learning model, NUMO-ResNet, incorporates additional information derived from the characterizations of RNA, specifically the 2D folding motifs. In this work, we introduce an automated method to extract these motifs based on fundamental secondary structure descriptions. To assess the robustness of our models, we conduct 10-fold cross validation. Furthermore, we evaluate the performance of both models on two independent testing datasets. Our proposed models demonstrate excellent performance across both datasets and surpass the performance of the ENTRNA approach. Availability and ImplementationThe corresponding source code and data for this research is available at https://github.com/yzhou617/NU-ResNet_and_NUMO-ResNet. ContactGiulia.Pedrielli@asu.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

An Efficient and Safe Trans-complementation System of Mpox Virus Reproduces Authentic Viral Architecture and Infection

Since the Mpox virus (MPXV) outbreak in 2022, there have been 97,745 cases and 203 fatalities. This outbreak features increased transmission efficiency and a higher infection rate in the MSM population, with the underlying causes remaining unknown. The requirement of BSL-3 laboratories poses a barrier to MPXV research and antiviral development. Here, we report an efficient and safe trans-complementary system that produces a single-round infectious MPXV, preserving the viruss authentic architecture and enabling it to complete its life cycle in complementing cells. This deficient MPXV genome, lacking two essential genes crucial for late gene transcription and viral assembly, is restricted to a single-round infection in non-complementing cell lines. Notably, SCID mice inoculated with this deficient MPXV exhibited no detectable disease or viral load. This deficient MPXV platform has demonstrated its capacity to study innate immunity and cell death during infection in complementing cells. It can also be used for antibody neutralization assays and anti-MPXV drug evaluation. This trans-complementation platform, safe for use in low-biosafety laboratories, offers a valuable resource for MPXV research and countermeasure development.

microbiology↗

bioRxiv2023

Integrative genomics reveals the polygenic basis of seedlessness in grapevine

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, while the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated four haplotype-resolved telomere-to-telomere (T2T) genomes for two seedless grape cultivars, Thompson Seedless (TS, syn. Sultania) and Black Monukka (BM). Comparative genomics identified a [~]4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, tracing the origin of the seedlessness trait back to Sultania. Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including novel candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 groups related to seed development. Machine learning based genomic selection achieved a remarkable 99% precision in predicting grapevine seedlessness. Our findings highlight the polygenic nature of seedless and provide novel candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

genetics↗

bioRxiv2023

Senolytics enhance longevity in Caenorhabditis elegans by altering betaine metabolism

Aging triggers physiological changes in organisms, which are tightly interlinked to metabolic changes. Senolytics are being developed. However, metabolic responses to natural senescence and the molecular intricacies of how senolytics confer antiaging benefits remain enigmatic. We performed a metabolomics study on natural senescence based on the C.elegans model. The results suggest that age-dependent metabolic changes of natural aging occur in C. elegans. Betaine was identified as a crucial metabolite in the natural aging process. To explore the common pathway coregulated by different senolytics prolonging nematodes lifespan, we fed nematodes three antiaging drugs metformin, quercetin, and minocycline. Our data show that the coregulated metabolic pathways associated with aging include the forkhead box transcription factor (FoxO), p38-mitogen-activated protein kinase (MAPK) and the target of rapamycin (mTOR) signaling pathway, etc. Three antiaging drugs raised betaine levels, consistent with high betaine levels in the younger nematode. Supplement of betaine prolonged the lifespan of nematodes via stimulating autophagy and improving antioxidant capacity. Altogether, our data support proof-of-concept evidence that betaine at appropriate concentrations can extend the lifespan of nematodes.

biochemistry↗

bioRxiv2023

Rapid dexamethasone treatment inhibits LPS-induced cytokine storm in mice

Severe infection-induced cytokine storm is an urgent medical syndrome with high mortality. To date, no therapy is available. This study shows that high concentrations of lipopolysaccharide (LPS) induce cytokine storm within 48h and thus kill most experimental mice. Rapid, but not late dexamethasone administration remarkably inhibits cytokine storm and rescues LPS-treated mice. Monocytes and macrophages are the major source of cytokine storm. In these cells, pro-inflammatory genes (i.e., Tnf, Il6 and Il1{beta}) have preassembled RNA polymerase II (RNA Pol II), but stay at the pause stage of transcriptional elongation in the absence of stimulation. LPS rapidly activates transcription of these "pre-loaded" genes within 2h. Administration of dexamethasone within this time window inhibits RNA Pol II ser2 binding to the core promoters of pro-inflammatory genes and thus reduces LPS-induced cytokine transcription. Therefore, rapid utilization of dexamethasone might be efficacious to prevent severe bacterium-induced cytokine storm in clinical practice.

molecular biology↗

bioRxiv2023

Chronic metabolic stress drives developmental programs and loss of tissue functions in non-transformed liver that mirror tumor states and stratify survival

Under chronic stress, cells must balance competing demands between cellular survival and tissue function. In metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD/NASH), hepatocytes cooperate with structural and immune cells to perform crucial metabolic, synthetic, and detoxification functions despite nutrient imbalances. While prior work has emphasized stress-induced drivers of cell death, the dynamic adaptations of surviving cells and their functional repercussions remain unclear. Namely, we do not know which pathways and programs define cellular responses, what regulatory factors mediate (mal)adaptations, and how this aberrant activity connects to tissue-scale dysfunction and long-term disease outcomes. Here, by applying longitudinal single-cell multi-omics to a mouse model of chronic metabolic stress and extending to human cohorts, we show that stress drives survival-linked tradeoffs and metabolic rewiring, manifesting as shifts towards development-associated states in non-transformed hepatocytes with accompanying decreases in their professional functionality. Diet-induced adaptations occur significantly prior to tumorigenesis but parallel tumorigenesis-induced phenotypes and predict worsened human cancer survival. Through the development of a multi-omic computational gene regulatory inference framework and human in vitro and mouse in vivo genetic perturbations, we validate transcriptional (RELB, SOX4) and metabolic (HMGCS2) mediators that co-regulate and couple the balance between developmental state and hepatocyte functional identity programming. Our work defines cellular features of liver adaptation to chronic stress as well as their links to long-term disease outcomes and cancer hallmarks, unifying diverse axes of cellular dysfunction around core causal mechanisms.

systems biology↗

bioRxiv2023

Filter-aided expansion proteomics

Integration of hydrogel-based tissue expansion and mass spectrometry-based proteomics enables high spatial resolution analysis of global protein expression in tissues. Here, we introduce a filter-aided tissue expansion proteomics (FAXP) method with optimized hydrogel preparation and treatment steps for spatial proteomics analysis of formalin-fixed paraffin-embedded (FFPE) specimens. Compared with our original ProteomEx method, FAXP, partially automated with robotics, exhibited 14.5-fold higher volumetric resolution, increased peptide yield leading to 250% more protein identifications, and 50% time consumption for sample preparation. We demonstrated its application in clinical colorectal tissue samples. We further integrated it with laser capture microdissection for proteomic analysis of subcellular organelles.

biochemistry↗

bioRxiv2023

Uncover spatially informed shared variations for single-cell spatial transcriptomics with STew

MotivationThe recent spatial transcriptomics (ST) technologies have enabled characterization of gene expression patterns and spatial information, advancing our understanding of cell lineages within diseased tissues. Several analytical approaches have been proposed for ST data, but effectively utilizing spatial information to unveil the shared variation with gene expression remains a challenge. ResultsWe introduce STew, a Spatial Transcriptomic multi-viEW representative learning method, to jointly analyze spatial information and gene expression in a scalable manner, followed by a data-driven statistical framework to measure the goodness of model fit. Through benchmarking using Human DLPFC data with true manual annotations, STew achieved superior performance in both clustering accuracy and continuity of identified spatial domains compared with other methods. STew is also robust to generate consistent results insensitive to model parameters, including sparsity constraints. We next applied STew to various ST data acquired from 10x Visium and Slide-seqV2, encompassing samples from both mouse and human brain, which revealed spatially informed cell type clusters. We further identified a pro-inflammatory fibroblast spatial niche using ST data from psoriatic skins. Hence, STew is a generalized method to identify both spatially informed clusters and disease-relevant niches in complex tissues. AvailabilitySource code and the R software tool STew are available from github.com/fanzhanglab/STew. Contactfan.3.zhang@cuanschutz.edu Supplementary informationSupplementary data are provided.

bioinformatics↗

bioRxiv2023

Landscape of Large-Scale Somatic Genomic Insertions in Non-Small Cell Lung Carcinoma Revealed by Nanopore Sequencing

Previous NSCLC genomic studies were mostly based on the next-generation sequencing of short reads, which is an efficient approach for identifying single nucleotide variants and small indels but ineffective for identifying structural variants, especially large-scale insertions. Here, we studied 151 lung adenocarcinoma (LUAD) and 106 lung squamous cell carcinoma (LUSC) samples and paired blood samples using nanopore sequencing technology. We developed a rigorous computational pipeline and characterized the landscape of large-scale somatic insertions in NSCLC. Combining other omics data, we report three findings: 1. we identified an LUSC-enriched somatic simple repeat expansion shared by approximately 40% of LUSC patients that regulates PTPRZ1 gene expression through distal enhancers; 2. the somatic insertion of transposable elements (TEs) in NSCLC were mostly complex TEs consisting of multiple TE elements; and 3. the insertion of short interspersed nuclear elements, especially from the Alu family in young lineages, is a frequent somatic mutation type that shapes the transcriptome of NSCLC through the expression of these elements.

genomics↗

bioRxiv2023

Quantitative Profiling Method for Oxylipins in Neurodegenerative Diseases by Liquid Chromatography Coupled with Tandem Mass Spectrometry

Aging is one of the major risk factors for many chronic diseases, including diabetes, neuropathy, hypertension, cancer, and neurodegenerative diseases. However, the mechanism behind aging and how aging affects a variety of disease progression remains unknown. Recent research demonstrated the cytochrome P450 (CYP)-epoxide hydrolase (EH) metabolites of polyunsaturated fatty acids (PUFAs) play a critical role in the abovementioned age-associated diseases. Therefore, aging could affect the abovementioned chronic diseases by modulating CYP-EH PUFA metabolism. Unfortunately, investigating how aging affects CYP-EH metabolism in human and mammalian models poses significant challenges. In this regard, we will use C. elegans as a model organism to investigate the aging effects on CYP-EH metabolism of PUFA, owing to its long history of being used to study aging and its associated benefits of conducting aging research. This project will develop analytical tools to measure the endogenous levels of CYP-EH PUFA metabolites in C. elegans using state-of-the-art ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). These metabolites are very potent but present in low abundance. The dramatic increase in sensitivity in UPLC-MS/MS allows us to monitor these metabolites over the lifespan of C. elegans with minimum samples. Our results show that C. elegans produces similar CYP PUFA metabolites to mammals and humans using our SPE-UPLC-MS/MS method. We will also show that our method successfully determined the CYP-EH PUFA metabolites profile changes induced by the inhibition of C. elegans EH. The method developed from this project will significantly improve our understanding of the role of dietary PUFAs and associated metabolism on aging and neurodegeneration and will uncover new mechanisms of how aging affects neurodegeneration through the modulation of PUFA metabolic pathways. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC="FIGDIR/small/560544v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@415035org.highwire.dtl.DTLVardef@1f8d81eorg.highwire.dtl.DTLVardef@34a9f8org.highwire.dtl.DTLVardef@182de04_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2023

A genome-wide CRISPR/Cas9 screen identifies genes that regulate the cellular uptake of α-synuclein fibrils by modulating heparan sulfate proteoglycans

Synucleinopathies are characterized by the accumulation and propagation of -synuclein (-syn) aggregates throughout the brain, leading to neuronal dysfunction and death. Understanding how these aggregates propagate from cell to cell in a prion-like fashion thus holds great therapeutic promises. Here, we focused on understanding the cellular processes involved in the entry and accumulation of pathological -syn aggregates. We used an unbiased FACS-based genome-wide CRISPR/Cas9 knockout (KO) screening to identify genes that regulate the accumulation of -syn preformed fibrils (PFFs) in cells. We identified key genes and pathways specifically implicated in -syn PFFs intracellular accumulation, including heparan sulfate proteoglycans (HSPG) biosynthesis and Golgi trafficking. We show that all confirmed hits affect heparan sulfate (HS), a post-translational modification known to act as a receptor for proteinaceous aggregates including of -syn and tau. Intriguingly, KO of SLC39A9 and C3orf58 genes, encoding respectively a Golgi-localized exporter of Zn2+, and the Golgi-localized putative kinase DIPK2A, specifically impaired the uptake of -syn PFFs uptake but not of tau oligomers, by preventing the binding of PFFs to the cell surface. Mass spectrometry-based analysis of HS chains indicated major defects in HS maturation in SLC39A9 and C3orf58 KO cells, explaining the cell surface binding deficit. Our findings now clearly establish these two genes as HSPG-modulating factors. Interestingly, C3orf58 KO human iPSC-derived microglia exhibited a strong reduction in their ability to internalize -syn PFFs. Altogether, our data establish HSPGs as major receptors for -syn PFFs binding on the cell surface and identifies new players in -syn PFFs cell surface binding and uptake.

cell biology↗