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Biology subjects

Han, S.

Publications and source records attributed to Han, S..

At least 127 records · Page 7Linked to original sources

Human tau promotes Warburg effect-like glycolytic metabolism under acute hyperglycemia conditions through modulating the homeostasis of protein-membrane association

The neurofilaments formed by hyperphosphorylated tau is a hallmark of tau-related neurodegenerative disease, including Alzheimers disease, tau related FTDP-17, Picks disease, et al. However, the biological functions of tau and the physiological significance of its phosphorylation are still not fully understood. By using human tau (441 a.a.) transgenic (hTau) mice in which murine tau has been deleted simultaneously, murine tau knockout (Tau KO) mice and C57BL/6J (C57) mice, unexpectedly, we found that under acute hyperglycemia conditions, JNK but not previously reported GSK-3{beta} mediated tau phosphorylation. Moreover, Akt, the upstream GSK-3{beta} inhibitory kinase, was activated in a tau dependent manner. By comparing the membrane-associated proteome, we found that human tau influenced the homeostasis of protein-membrane association under acute hyperglycemia conditions. Of note, with respect to WT and Tau KO mice, the membrane-association of Krts, TFAM, TRAP1, mTOR et al, were strengthened by human tau. Whereas, the membrane-association of ribosomal proteins Rpls, proteasome proteins Psmds, and mitochondrial proteins, such as COXs, Ndufa1, Mtnt4, et al, were impeded by human tau. In vitro study showed that aerobic glycolysis was promoted in the presence of human tau, which maintained NAD+/NADH ratio. On the other hand, it restricted oxidative phosphorylation level, modulated the activity of SDH, and reduced ROS production upon challenging by high glucose. Furthermore, under acute high glucose conditions, the presence of human tau significantly augmented Akt activation, but inhibited 4EBP phosphorylation simultaneously, indicating that human tau is also involved in regulating the alternative activation of mTORC1/2. In summary, the current study revealed that human tau played an important role in regulating glycolytic metabolism under acute high hyperglycemia conditions, which is similar with the Warburg-effect, through influencing the homeostasis of protein-membrane association.

molecular biology↗

Structure-Based Design of a Highly Immunogenic, Conformationally Stabilized FimH Antigen for a Urinary Tract Infection Vaccine

Adhesion of E. coli to the urinary tract epithelium is a critical step in establishing urinary tract infections. FimH is an adhesin positioned on the fimbrial tip which binds to mannosylated proteins on the urinary tract epithelium via its lectin domain (FimHLD). FimH is of interest as a target of vaccines to prevent urinary tract infections (UTI). Previously, difficulties in obtaining purified recombinant FimH from E. coli along with the poor inherent immunogenicity of FimH have hindered the development of effective FimH vaccine candidates. To overcome these challenges, we have devised a novel production method using mammalian cells to produce high yields of homogeneous FimH protein with comparable biochemical and immunogenic properties to FimH produced in E. coli. Next, to optimize conformational stability and immunogenicity of FimH, we used a computational approach to design improved FimH mutants and evaluated their biophysical and biochemical properties, and murine immunogenicity. This approach identified a highly immunogenic FimH variant (FimH-DSG TM) that is produced at high yields in mammalian cells. By x-ray crystallography, we confirmed that the stabilized structure of the FimHLD in FimH-DSG TM is similar to native FimH on the fimbrial tip. Characterization of monoclonal antibodies elicited by FimH-DSG TM that can block bacterial binding to mannosylated surfaces identified 4 non-overlapping binding sites whose epitopes were mapped via a combinatorial cryogenic electron microscopy approach. Novel inhibitory epitopes in the lectin binding FimH were identified, revealing diverse functional mechanisms of FimH-directed antibodies with relevance to FimH-targeted UTI vaccines. Author summaryEscherichia coli is the primary cause of urinary tract infections. Adherence to uroepithelial surfaces is mediated by the pilus adhesin protein FimH, which is of interest as a vaccine candidate. We developed a method for producing recombinant FimH at bioprocess scale, previously a barrier to commercial development. Structure-based design and screening was used to identify a novel FimH vaccine candidate with improved stability and immunogenicity in mice. Structure of this full-length protein was determined by X-ray crystallography and shown to closely resemble the pilus adhesin present in its native form on the bacterial surface. Binding sites of biologically active FimH monoclonal antibodies were determined by X-ray crystallography or by cryo-electron microscopy, providing insights into mechanisms by which antibodies block binding of the bacteria to urinary tract receptors. One sentence summaryStructure-based design of a conformationally stabilized E. coli FimH vaccine candidate capable of eliciting antibodies to diverse epitopes with the ability to block bacterial binding to bladder epithelial cells.

microbiology↗

MEK1/2 and ERK1/2 mediated lung endothelial injury and altered hemostasis promote diffuse alveolar hemorrhage in murine lupus

ObjectiveAbout 3% of lupus patients develop severe diffuse alveolar hemorrhage (DAH) with pulmonary vasculitis. B6 mice with pristane-induced lupus also develop DAH, but BALB/c mice are resistant. DAH is independent of TLR signaling and other inflammatory pathways. This study examined the role of the mitogen-activated protein kinase pathway (MEK1/2-ERK1/2, JNK, p38). MethodsB6 and BALB/c mice were treated with pristane {+/-} inhibitors of MEK1/2 (trametinib/GSK1120212, "GSK"), ERK1/2 (SCH772984, "SCH"), JNK, or p38. Effects on lung hemorrhage and hemostasis were determined. ResultsGSK and SCH abolished DAH, whereas JNK and p38 inhibitors were ineffective. Apoptotic cells were present in lung from pristane-treated mice, but not mice receiving pristane+GSK and endothelial dysfunction was normalized. Expression of the ERK1/2-regulated transcription factor Egr1 increased in pristane-treated B6, but not BALB/c, mice and was normalized by GSK. Pristane also increased expression of the anticoagulant genes Tfpi (tissue factor pathway inhibitor) and Thbd (thrombomodulin) in B6 mice. The ratio of tissue factor (F3) to Tfpi increased in B6 (but not BALB/c) mice and was normalized by GSK. Circulating Thbd protein increased in B6 mice and returned to normal after GSK treatment. Consistent with augmented endothelial anticoagulant activity, pristane treatment increased tail bleeding in B6 mice. ConclusionPristane treatment promotes lung endothelial injury and DAH in B6 mice by activating the MEK1/2-ERK1/2 pathway and impairing hemostasis. The hereditary factors determining susceptibility to lung injury and bleeding in pristane-induced lupus are relevant to the pathophysiology of life-threatening DAH in SLE and may help to optimize therapy.

immunology↗

Structural basis of the bacterial flagellar motor rotational switching

The bacterial flagellar motor is a huge bidirectional rotary nanomachine that drives rotation of the flagellum for bacterial motility1-5. The cytoplasmic C ring of the flagellar motor functions as the switch complex for the rotational direction switching from counterclockwise to clockwise2,3,6-9. However, the structural basis of the rotational switching and how the C ring is assembled have long remained elusive. Here, we present two high-resolution cryo-electron microscopy structures of the C ring-containing flagellar motor-hook complex from Salmonella Typhimurium, which are in the default counterclockwise state and in a constitutively active CheY mutant-induced clockwise state, respectively. In both complexes, the C ring consists of four subrings, but is in two different conformations. The CheY proteins are bound into an open groove between two adjacent protomers on the surface of the middle subring of the C ring and interact with the FliG and FliM subunits. The binding of the CheY protein induces a significant upward shift of the C ring towards the MS ring and inward movements of its protomers towards the motor center, which eventually remodels the structures of the FliG subunits and reverses the orientations and surface electrostatic potential of the torque helices to trigger the counterclockwise-to-clockwise rotational switching. The conformational changes of the FliG subunits reveal that the stator units on the flagellar motors require a relocation process in the bacterial inner membrane during the rotational switching. This study provides unprecedented molecular insights into the rotational switching mechanism and a detailed overall structural view of the bacterial flagellar motors.

microbiology↗

Screening great ape museum specimens for DNA viruses

Natural history museum collections harbour a record of wild species from the past centuries, providing a unique opportunity to study animals as well as their infectious agents. Thousands of great ape specimens are kept in these collections, and could become an important resource for studying the evolution of DNA viruses. Their genetic material is likely to be preserved in dry museum specimens, as reported previously for monkeypox virus genomes from historical orangutan specimens. Here, we screened 209 great ape museum specimens for 99 different DNA viruses, using hybridization capture coupled with short-read high-throughput sequencing. We determined the presence of multiple viruses within this dataset from historical specimens and obtained several near-complete viral genomes. In particular, we report high-coverage (>18-fold) hepatitis B virus genomes from one gorilla and two chimpanzee individuals, which are phylogenetically placed within clades infecting the respective host species.

genomics↗

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structures specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

neuroscience↗

Enhancing Agrobacterium-Mediated Soybean Transformation Efficiency with an Auxiliary Solution

Soybean provides oil, protein, and biofuel. Efficient transformation systems are vital for advancing soybean research. Currently, Agrobacterium rhizogenes-mediated transformation is the predominant method for facilitating rapid transformation, producing transgenic hairy roots. However, the limitations of soybean transformation technology primarily originate from its low efficiency and genotype dependency, leaving significant room for improvement in the development more universally applicable and efficient methods. In this study, we explored the enhancement of soybean transformation efficiency through the generation and validation of three reporter vectors (ZsGreen, TdTomato, and Ruby) and the strategic use of Agrobacterium Auxiliary Solution (AAS) containing Silwet L-77 and hormone mixtures. Our findings demonstate that the incorporation of hormone mixtures and Silwet L-77 into AAS significantly improves hairy root transformation rates. Specifically, the combination of hormone mixtures with Silwet L-77 substantially increased both total root and cotyledon transformation efficiencies compared to the control. We also assessed the impact of vector size on transformation efficiency, observing a notable decrease in efficiency with larger vectors such as the Ruby cassette compared to smaller markers like GFP and RFP. Furthermore, our study examined the effects of AAS on the co-transformation rate of two separate vectors, revealing a slight but significant reduction in efficiency compared to single vector transformations. Additionally, we evaluated the role of AAS in enhancing soybean hypocotyl transformation rates in composite soybean plants across various varieties. The results consistently showed an increase in both positive roots and explant efficiencies with the addition of AAS, indicating its broad applicability and effectiveness in soybean transformation. However, significant varietal differences in transformation rates were observed, particularly between "Forrest" and other varieties such as "Williams 82" and "Dongnong 50". In summary, our research emphasizes the significant role of auxiliary agents and vector size in optimizing soybean transformation techniques, providing valuable insights for future advancements in soybean genetic modification and biotechnological research.

plant biology↗

SHP-1 interacts with NFκB1 to inhibit its phosphorylation and nuclear translocation to suppress excessive bacterial inflammation

The protein tyrosine phosphatase SHP-1 is a key negative regulator in cancer by dephosphorylating multiple target molecules. Specially in the NF{kappa}B signaling, where NF{kappa}B1/Rela dimer translocate to the nucleus and activate target gene transcription, SHP-1 inhibits the phosphorylation of Rela, while its regulation on NF{kappa}B1 has been unknown, especially in pathogen-induced inflammation. Chinese tongue sole, a representative flatfish, has been widely used as a genomics and disease model. Using the teleost and cellular model, we revealed for the first time that SHP-1 inhibits NF{kappa}B1 phosphorylation and nuclear translocation by interacting with NF{kappa}B1, thereby suppressing NF{kappa}B signaling to inhibit bacterial inflammation. In addition, we showed that SHP-1 decreased mortality and alleviated histopathological deterioration, manifested in the inhibition of immune-related pathways and secretion of pro- inflammatory cytokines. Using cellular model, SHP-1 overexpression reduced macrophages M1 polarization, phagocytosis, and oxidative stress, while silencing SHP- 1 exhibited opposite effects. Our findings systematically dissect the functions of SHP- 1 and provide mechanistic insights into the control of inflammation-related diseases. TeaserSHP-1 help maintain the cellular and individual homeostasis by inhibiting the excessive inflammation and immunity via regulating the NF{kappa}B signaling.

immunology↗

Structural basis for CCR6 modulation by allosteric antagonists

The CC chemokine receptor 6 (CCR6) is a potential target for chronic inflammatory diseases such as psoriasis and inflammatory bowel disease. Previously, we reported an active CCR6 structure in complex with its cognate chemokine CCL20, revealing the molecular basis of CCR6 activation mediated by CCL20. Here, we present two inactive CCR6 structures determined by cryo-EM in ternary complexes with different allosteric antagonists, CCR6/SQA1/OXM1 and CCR6/SQA1/OXM2. OXM1 and OXM2 are oxomorpholine (OXM) analogues which are highly selective for CCR6 and disrupt the molecular network critical for receptor activation by binding to an extracellular allosteric pocket within the transmembrane domain. A U-shaped conformation stabilized by intramolecular interactions was revealed by structural and NMR studies of active OXM analogues. SQA1 is a squaramide (SQA) derivative with close-in analogues that were previously reported to be antagonists of CCR6 and other chemokine receptors. Our structures reveal an intracellular pocket occupied by SQA1 that overlaps with the G protein binding site. In addition, SQA1 stabilizes a closed conformation of the intracellular pocket, a hallmark of the inactive state of GPCRs. Minimal communication was found between the two allosteric pockets. Overall, our work provides new evidence of the versatility of GPCR antagonism by small molecules, complementing previous knowledge on CCR6 activation, and sheds light on drug discovery approaches to target CCR6 for autoimmune disorders.

biochemistry↗

Human spermatogonial stem cells retain states with a foetal-like signature

Spermatogenesis involves a complex process of cellular differentiation maintained by spermatogonial stem cells (SSCs). Being critical to male reproduction, it is generally assumed that spermatogenesis starts and ends in equivalent transcriptional states in related species. Based on single-cell gene expression profiling it has been proposed that undifferentiated human spermatogonia can be sub-classified into four heterogenous subtypes, termed states 0, 0A, 0B, and 1. To increase the resolution of the undifferentiated compartment and trace the origin of the spermatogenic trajectory, we re-analysed the single-cell (sc)RNA-seq libraries of 34 post-pubescent human testes to generate an integrated atlas of germ cell differentiation. We then used this atlas to perform comparative analyses of the putative SSC transcriptome both across human development (using 28 foetal and pre-pubertal scRNA-seq libraries) and across species (including data from sheep, pig, buffalo, rhesus and cynomolgus macaque, rat and mouse). Alongside its detailed characterisation, we show that the transcriptional heterogeneity of the undifferentiated spermatogonial cell compartment varies not only between species but across development. Our findings associate state 0B with a suppressive transcriptomic program that, in adult humans, acts to functionally oppose proliferation and maintain cells in a ready-to-react state. Consistent with this conclusion, we show that human foetal germ cells - which are mitotically arrested - can be characterised solely as state 0B. While germ cells with a state 0B signature are also present in foetal mouse (and are likely conserved at this stage throughout mammals), they are not maintained into adulthood. We conjecture that in rodents, the foetal-like state 0B differentiates at birth into the renewing SSC population, whereas in humans it is maintained as a reserve population, supporting testicular homeostasis over a longer reproductive life while reducing mutagenic load. Together, these results suggest that SSCs adopt differing evolutionary strategies across species to ensure fertility and genome integrity over vastly differing life histories and reproductive timeframes.

cell biology↗

Integrative Co-Registration of Elemental Imag-ing and Histopathology for Enhanced Spatial Multimodal Analysis of Tissue Sections through TRACE

SummaryElemental imaging provides detailed profiling of metal bioaccumulation, offering more precision than bulk analysis by targeting specific tissue areas. However, accurately identifying comparable tissue regions from elemental maps is challenging, requiring the integration of hematoxylin and eosin (H&E) slides for effective comparison. Facilitating the streamlined co-registration of Whole Slide Images (WSI) and elemental maps, TRACE enhances the analysis of tissue regions and elemental abundance in various pathological conditions. Through an interactive containerized web application, TRACE features real-time annotation editing, advanced statistical tools, and data export, supporting comprehensive spatial analysis. Notably, it allows for comparison of elemental abundances across annotated tissue structures and enables integration with other spatial data types through WSI co-registration. Availability and ImplementationAvailable on the following platforms- GitHub: jlevy44/trace_app, PyPI: trace_app, Docker: joshualevy44/trace_app, Singularity: joshualevy44/trace_app. Contactjoshua.levy@cshs.org Supplementary informationSupplementary data are available.

bioinformatics↗

GP-HTNLoc: A Graph Prototype Head-Tail Network-based Model for Multi-label Subcellular Localization Prediction of ncRNAs

Numerous research findings demonstrated that understanding the subcellular localization of non-coding RNAs (ncRNAs) is pivotal in elucidating their roles and regulatory mechanisms in cells. Despite the existence of over ten computational models dedicated to predicting the subcellular localization of ncRNAs, a majority of these models are designed solely for single-label prediction. In reality, ncRNAs often exhibit localization across multiple subcellular compartments. Furthermore, the existing multi-label localization prediction models are insufficient in addressing the challenges posed by the scarcity of training samples and class imbalance in ncRNA dataset. This study addresses the limitations of existing models by introducing a novel multi-label localization prediction model for ncRNAs, termed GP-HTNLoc. To alleviate class imbalance, the model adopts a separate training approach for head and tail class labels. In GP-HTNLoc, a pioneering graph prototype module is introduced for capturing potential association of ncRNA samples with labels. This module efficiently learns the graph structure and aggregates sample features. Notably, only few samples are required to obtain label prototypes containing rich information. These prototypes are then utilized to train a transfer learner, facilitating the transfer of meta-knowledge from the head class to the tail class. Experimental results demonstrate that GP-HTNLoc surpasses current state-of-the-art models across all datasets. Ablation study underscore the vital role played by the graph prototype module in enhancing the performance of GP-HTNLoc. The user-friendly online GP-HTNLoc web server can be accessed at https://56s8y85390.goho.co.

bioinformatics↗

Learning the Relationship Between Variants, Metabolic Fluxes and Phenotypes

In the dynamic field of cancer research, the fusion of genetics and machine learning presents a groundbreaking opportunity to understand the intricate links between genomic variations and cancer phenotypes. Despite the wealth of genetic data, translating it into actionable insights remains a challenge, particularly in the context of complex cellular metabolism. VaMP (Variants, Metabolic Fluxes & Phenotypes), our novel approach, addresses this by integrating neural networks and metabolic models, offering a comprehensive framework for deciphering cancer biology. The developed method leverages a novel end-to-end neural network architecture, integrating genome-scale metabolic models (GSMs) to capture the intricate relationship between genetic variations and cellular phenotypes. VaMPs encoder maps genetic variants to metabolic fluxes through a series of carefully designed steps utilizing neural network and GSM, while the decoder predicts phenotype probabilities using the differences between input and reference fluxes. The training data comprise mutation information and phenotypes, eliminating the need for explicit metabolic flux data preparation. Validation experiments on five cancer types demonstrate VaMPs ability to identify significant genes and metabolic signatures. Further utilizing SCREENER and co-occurrence analyses, the assessment reveals VaMPs capacity to anticipate established gene-disease relationships. The identified metabolic signatures are robustly substantiated by diverse literature grounded in experimental studies. Furthermore, an in-depth exploration of the outcomes from five VaMP models involved the correlation analysis for variants and fluxes to establish connections between significant genes and cancer-causing variants. Overall, VaMP can be used as a promising tool for unraveling the complex interplay between genetic alterations and cancer phenotypes, with implications for understanding disease mechanisms and identifying novel therapeutic targets.

bioinformatics↗

Molecular and Cellular Mechanisms of Teneurin Signaling in Synaptic Partner Matching

In developing brains, axons exhibit remarkable precision in selecting synaptic partners among many non-partner cells. Evolutionally conserved teneurins were the first identified transmembrane proteins that instruct synaptic partner matching. However, how intracellular signaling pathways execute teneurins functions is unclear. Here, we use in situ proximity labeling to obtain the intracellular interactome of teneurin (Ten-m) in the Drosophila brain. Genetic interaction studies using quantitative partner matching assays in both olfactory receptor neurons (ORNs) and projection neurons (PNs) reveal a common pathway: Ten-m binds to and negatively regulates a RhoGAP, thus activating the Rac1 small GTPases to promote synaptic partner matching. Developmental analyses with single-axon resolution identify the cellular mechanism of synaptic partner matching: Ten-m signaling promotes local F-actin levels and stabilizes ORN axon branches that contact partner PN dendrites. Combining spatial proteomics and high-resolution phenotypic analyses, this study advanced our understanding of both cellular and molecular mechanisms of synaptic partner matching. HIGHLIGHTSO_LIIn situ spatial proteomics reveal the first intracellular interactome of teneurins C_LIO_LITen-m signals via a RhoGAP and Rac1 GTPase to regulate synaptic partner matching C_LIO_LISingle-axon analyses reveal a stabilization-upon-contact model for partner matching C_LIO_LITen-m signaling promotes F-actin in axon branches contacting partner dendrites C_LI

neuroscience↗

Mitochondrial bioenergetics stimulates autophagy for pathological tau clearance in tauopathy neurons

Hyperphosphorylation and aggregation of microtubule-associated tau is a pathogenic hallmark of tauopathies and a defining feature of Alzheimers disease (AD). Pathological tau is targeted by autophagy for clearance, but autophagy dysfunction is indicated in tauopathy. While mitochondrial bioenergetic failure has been shown to precede the development of tau pathology, it is unclear whether energy metabolism deficiency is involved in tauopathy-related autophagy defects. Here, we reveal that stimulation of anaplerotic metabolism restores defective oxidative phosphorylation (OXPHOS) in tauopathy which, strikingly, leads to enhanced autophagy and pronounced tau clearance. OXPHOS-induced autophagy is attributed to increased ATP-dependent phosphatidylethanolamine biosynthesis in mitochondria. Excitingly, early bioenergetic stimulation boosts autophagy activity and reduces tau pathology, thereby counteracting memory impairment in tauopathy mice. Taken together, our study sheds light on a pivotal role of bioenergetic dysfunction in tauopathy-linked autophagy defects and suggests a new therapeutic strategy to prevent toxic tau buildup in AD and other tauopathies.

neuroscience↗

Peptide-based capture-and-release purification of extracellular vesicles and statistical algorithm enabled quality assessment

Circulating extracellular vesicles (EVs) have gained significant attention for discovering tumor biomarkers. However, isolating EVs with well-defined homogeneous populations from complex biological samples is challenging. Different isolation methods have been found to derive different EV populations carrying different molecular contents, which confounds current investigations and hinders subsequent clinical translation. Therefore, standardizing and building a rigorous assessment of isolated EV quality associated with downstream molecular analysis is essential. To address this need, we introduce a statistical algorithm (ExoQuality Index, EQI) by integrating multiple EV characterizations (size, particle concentration, zeta potential, total protein, and RNA), enabling direct EV quality assessment and comparisons between different isolation methods. We also introduced a novel capture-release isolation approach using a pH-responsive peptide conjugated with NanoPom magnetic beads (ExCy) for simple, fast, and homogeneous EV isolation from various biological fluids. Bioinformatic analysis of next-generation sequencing (NGS) data of EV total RNAs from pancreatic cancer patient plasma samples using our novel EV isolation approach and quality index strategy illuminates how this approach improves the identification of tumor associated molecular markers. Results showed higher human mRNA coverage compared to existing isolation approaches in terms of both pancreatic cancer pathways and EV cellular component pathways using gProfiler pathway analysis. This study provides a valuable resource for researchers, establishing a workflow to prepare and analyze EV samples carefully and contributing to the advancement of reliable and rigorous EV quality assessment and clinical translation.

bioengineering↗

scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells. Through comprehensive evaluations, we demonstrate the superior performance of scMeFormer compared to alternative models across four single-nucleus DNAm datasets generated by distinct technologies. Remarkably, scMeFormer exhibits high-fidelity imputation, even when dealing with significantly reduced coverage, as low as 10% of the original CpG sites. Furthermore, we applied scMeFormer to a single-nucleus DNAm dataset generated from the prefrontal cortex of four schizophrenia patients and four neurotypical controls. This enabled the identification of thousands of differentially methylated regions associated with schizophrenia that would have remained undetectable without imputation and added granularity to our understanding of epigenetic alterations in schizophrenia within specific cell types. Our study highlights the power of deep learning in imputing DNAm states in single cells, and we expect scMeFormer to be a valuable tool for single-cell DNAm studies.

genomics↗

Deep learning predicts DNA methylation regulatory variants in specific brain cell types and enhances fine mapping for brain disorders

DNA methylation (DNAm) is essential for brain development and function and potentially mediates the effects of genetic risk variants underlying brain disorders. We present INTERACT, a transformer-based deep learning model to predict regulatory variants impacting DNAm levels in specific brain cell types, leveraging existing single-nucleus DNAm data from the human brain. We show that INTERACT accurately predicts cell type-specific DNAm profiles, achieving an average area under the Receiver Operating Characteristic curve of 0.98 across cell types. Furthermore, INTERACT predicts cell type-specific DNAm regulatory variants, which reflect cellular context and enrich the heritability of brain-related traits in relevant cell types. Importantly, we demonstrate that incorporating predicted variant effects and DNAm levels of CpG sites enhances the fine mapping for three brain disorders--schizophrenia, depression, and Alzheimers disease--and facilitates mapping causal genes to particular cell types. Our study highlights the power of deep learning in identifying cell type-specific regulatory variants, which will enhance our understanding of the genetics of complex traits. TeaserDeep learning reveals genetic variations impacting brain cell type-specific DNA methylation and illuminates genetic bases of brain disorders

genetics↗