Biology subjects

Su, J.

Publications and source records attributed to Su, J..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

Boosting variant-calling performance with multi-platform sequencing data using Clair3-MP

BackgroundWith the continuous advances in third-generation sequencing technology and the increasing affordability of next-generation sequencing technology, sequencing data from different sequencing technology platforms is becoming more common. While numerous benchmarking studies have been conducted to compare variant-calling performance across different platforms and approaches, little attention has been paid to the potential of leveraging the strengths of different platforms to optimize overall performance, especially integrating Oxford Nanopore and Illumina sequencing data. ResultsWe investigated the impact of multi-platform data on the performance of variant calling through carefully designed experiments with a deep learning-based variant caller named Clair3-MP (Multi-Platform). Through our research, we not only demonstrated the capability of ONT-Illumina data for improved variant calling, but also identified the optimal scenarios for utilizing ONT-Illumina data. In addition, we revealed that the improvement in variant calling using ONT-Illumina data comes from an improvement in difficult genomic regions, such as the large low-complexity regions and segmental and collapse duplication regions. Moreover, Clair3-MP can incorporate reference genome stratification information to achieve a small but measurable improvement in variant calling. Clair3-MP is accessible as an open-source project at: https://github.com/HKU-BAL/Clair3-MP. ConclusionsThese insights have important implications for researchers and practitioners alike, providing valuable guidance for improving the reliability and efficiency of genomic analysis in diverse applications.

bioinformatics↗

bioRxiv2023

The Secondary Somatosensory Cortex Gates Mechanical and Thermal Sensitivity

The cerebral cortex is vital for the perception and processing of sensory stimuli. In the somatosensory axis, information is received by two distinct regions, the primary (S1) and secondary (S2) somatosensory cortices. Top-down circuits stemming from S1 can modulate mechanical and cooling but not heat stimuli such that circuit inhibition causes blunted mechanical and cooling perception. Using optogenetics and chemogenetics, we find that in contrast to S1, an inhibition of S2 output increases mechanical and heat, but not cooling sensitivity. Combining 2-photon anatomical reconstruction with chemogenetic inhibition of specific S2 circuits, we discover that S2 projections to the secondary motor cortex (M2) govern mechanical and thermal sensitivity without affecting motor or cognitive function. This suggests that while S2, like S1, encodes specific sensory information, that S2 operates through quite distinct neural substrates to modulate responsiveness to particular somatosensory stimuli and that somatosensory cortical encoding occurs in a largely parallel fashion.

neuroscience↗

bioRxiv2023

SEQUENCE VS. STRUCTURE: DELVING DEEP INTO DATA DRIVEN PROTEIN FUNCTION PREDICTION

AO_SCPLOWBSTRACTC_SCPLOWPredicting protein function is a longstanding challenge that has significant scientific implications. The success of amino acid sequence-based learning methods depends on the relationship between sequence, structure, and function. However, recent advances in AlphaFold have led to highly accurate protein structure data becoming more readily available, prompting a fundamental question: given sufficient experimental and predicted structures, should we use structure-based learning methods instead of sequence-based learning methods for predicting protein function, given the intuition that a proteins structure has a closer relationship to its function than its amino acid sequence? To answer this question, we explore several key factors that affect function prediction accuracy. Firstly, we learn protein representations using state-of-the-art graph neural networks (GNNs) and compare graph construction(GC) methods at the residue and atomic levels. Secondly, we investigate whether protein structures generated by AlphaFold are as effective as experimental structures for function prediction when protein graphs are used as input. Finally, we compare the accuracy of sequence-only, structure-only, and sequence-structure fusion-based learning methods for predicting protein function. Additionally, we make several observations, provide useful tips, and share code and datasets to encourage further research and enhance reproducibility.

bioinformatics↗

bioRxiv2023

Comprehensive Multi-omics Analysis Reveals the Core Role of Glycerophospholipid Metabolism in Rheumatoid Arthritis Development

ObjectivesRheumatoid arthritis (RA) is a chronic autoimmune disease with complex causes and recurrent attacks that can easily develop into chronic arthritis. Our study aims to elucidate potential mechanism among control, new-onset RA (NORA) and chronic RA (CRA) with multi-omics analysis. MethodsA total of 162 subjects were included in our study, 121 subjects were used for 16S rRNA, ITS sequencing and metabolomics analysis and 41 subjects were used for transcriptomics analysis. Enrichment analysis was based on significant difference metabolites and genes. Protein-protein interaction network and correlation analyses were performed to interpret the interactions among intestinal flora, metabolites and genes. We applied three models to distinguish between NORA and CRA using computational OR values, LASSO and random forest, respectively. ResultsOur results demonstrated intestinal flora disturbance in RA development, with significantly increased abundance of Escherichia-Shigella and Proteobacteria in NORA. We also found that the diversity was significantly reduced in CRA compared to NORA through fungi analysis. Moreover, we identified 28 differential metabolites between NORA and CRA. Pathway enrichment analysis revealed significant dysregulation of glycerophospholipid metabolism and phenylalanine metabolism pathways in RA patients. Next, we identified 40 differentially expressed genes between NORA and CRA, which acetylcholinesterase (ACHE) was the core gene and significantly enriched in glycerophospholipid metabolism pathway. Correlation analysis showed a strong negatively correlation between glycerophosphocholine and inflammatory characteristics. ConclusionsThese findings revealed that glycerophospholipid metabolism plays a crucial role in the development and progression of RA, providing new ideas for early clinical diagnosis and optimizing treatment strategies.

immunology↗

bioRxiv2023

Network-based molecular subtyping of acral melanoma

Acral melanoma is more biologically aggressive with a worse prognosis compared with other melanoma subtypes. However, the molecular basis underlying the biological and clinical behavior of this cancer is still unclear. Here, using the combination of multi-omics data analysis and network-based disease gene prediction algorithm, we first demonstrate the existence of two acral melanoma subtypes which greatly differed in clinical performance, cellular and molecular mechanisms, and discovered a biomarker panel (EREG, VSIG4, FCGR3A, RAB20) that accurately distinguished these two subtypes with the AUC of 0.946, which has been verified by clinical samples. Subtype I has thinner Breslow with a better prognosis. On the contrary, subtype II is a high-risk subtype that is easier to invade the dermis. We further analyzes the intrinsic biological mechanism of the two subtypes from the cellular level, and reveals the important role of macrophages subgroups in the molecular typing of acral melanoma. Feature genes of subtype I are enriched in FCN1+ macrophages that promote inflammatory and immune responses. In contrast, feature genes of subtype II are enriched in SPP1+ macrophages which ha the greatest impact on tumor cells. The identification of the two subtypes opens up important biological and clinical perspectives for acral melanoma.

bioinformatics↗

bioRxiv2023

ciRS-7-miR7 regulate ischemia induced neuronal death via glutamatergic signaling

Brain functionality relies on finely tuned regulation of gene expression by networks of non-coding RNAs (ncRNAs) such as the one composed by the circular RNA ciRS-7 (also known as CDR1as), the microRNA miR-7 and the long non-coding RNA Cyrano. Here we describe ischemia induced alterations in the ncRNA network both in vitro and in vivo and in transgenic mice lacking ciRS-7 or miR-7. Our data show that cortical neurons downregulate ciRS-7 and Cyrano and upregulate miR-7 expression upon ischemic insults. Mice lacking ciRS-7 show reduced lesion size and motor impairment, whilst the absence of miR-7 alone leads to an increase in the ischemia induced neuronal death. Moreover, miR-7 levels in pyramidal excitatory neurons regulate dendrite morphology and glutamatergic signaling suggesting a potential molecular link to the in vivo phenotype. Our data reveal that ciRS-7 and miR-7 contribute to the outcome of ischemic stroke and shed new light into the pathophysiological roles of intracellular networks of non-coding RNAs in the brain.

molecular biology↗

bioRxiv2022

Evaluation of Mycobacterium Tuberculosis enrichment in metagenomic samples using ONT adaptive sequencing and amplicon sequencing for identification and variant calling

Sensitive detection of Mycobacterium Tuberculosis (TB) in small percentages in metagenomic samples is essential for microbial classification and drug resistance prediction, and assisting in diagnosis and treatment planning. However, traditional methods, such as bacterial culture and microscopy, are time-consuming and sometimes have limited TB detection sensitivity. Oxford Nanopore Technologies MinION sequencing allows rapid and simple sample preparation for whole genome and amplicon sequencing. Its recently developed adaptive sequencing selects reads from targets, while allowing real-time base-calling during sequencing to achieve sequence enrichment or depletion. Another common enrichment method is PCR amplification of the target TB genes. In this study, we compared both methods with MinION sequencing for TB detection and variant calling in metagenomic samples using both simulation runs and those with synthetic and patient samples. We found that both methods effectively enrich TB reads from a high percentage of human and other microbial DNA. We provide a simple automatic analysis framework, including quality filtering, taxonomic classification, variant calling, and antimicrobial resistance prediction, to support these detection workflows for clinical use, openly available at https://github.com/HKU-BAL/ONT-TB-NF. Depending on the patients medical condition and sample type (commonly including bronchoalveolar lavage fluid, blood samples, sputum, and tissues), we discuss the findings and recommend that users optimize their workflow to improve the detection limit.

bioinformatics↗

bioRxiv2022

ClpP/ClpX deficiency impairs mitochondrial functions and mTORC1 signaling during spermatogenesis and meiosis

Caseinolytic protease proteolytic subunit (ClpP) and caseinolytic protease X (ClpX) are mitochondrial matrix peptidases that activate mitochondrial unfolded protein response to maintain protein homeostasis in the mitochondria. However, the role of ClpP and ClpX in spermatogenesis remains largely unknown. In this study, we demonstrated the importance of ClpP/ClpX for meiosis and spermatogenesis with two conditional knockout (cKO) mouse models. We found that ClpP/ClpX deficiency reduced mitochondrial functions and quantity in spermatocytes, affected energy supply during meiosis and attenuated zygotene-pachytene transformation of the male germ cells. The dysregulated spermatocytes finally underwent apoptosis resulting in decreased testicular size and vacuolar structures within the seminiferous tubules. We found mTORC1 pathway was over-activated after deletion of ClpP/ClpX in spermatocytes. Long-term inhibition of the mTORC1 signaling via rapamycin treatment in vivo partially rescue spermatogenesis. The data reveal the novel roles of ClpP and ClpX in regulating meiosis and spermatogenesis. One-Sentence SummaryClpP/ClpX is required for maintaining mitochondrial functions in spermatocytes during meiosis and spermatogenesis.

developmental biology↗

bioRxiv2022

Disrupting peroxisomes alters lipid metabolism in melanoma and uncovers a novel therapeutic vulnerability in combination with MAPK-targeted therapies

Melanomas reprogram their metabolism to rapidly adapt to therapy-induced stress conditions, allowing them to persist and ultimately develop resistance. We report that a subpopulation of melanoma cells tolerate MAPK pathway inhibitors (MAPKi) through a concerted metabolic reprogramming mediated by peroxisomes and UDP-glucose ceramide glycosyltransferase (UGCG). Compromising peroxisome biogenesis, by repressing PEX3 expression, potentiates the pro-apoptotic effects of MAPKi via an induction of ceramides, an effect limited by UGCG-mediated ceramide metabolism. Co-targeting PEX3 and UGCG selectively eliminates a subset of metabolically active, drug-tolerant CD36+ melanoma persister cells, thereby sensitizing melanoma to MAPKi and delaying resistance. Increased levels of peroxisomal genes and UGCG are found in patient-derived MAPKi-relapsed melanomas, and simultaneously inhibiting PEX3 and UGCG restores MAPKi sensitivity in multiple models of therapy resistance. Finally, triple therapy comprised of a newly identified inhibitor of the PEX3-PEX19 interaction, a UGCG inhibitor and a MAPKi demonstrates potent anti-tumor activity in pre-clinical melanoma models, thus representing a promising approach for melanoma treatment. HighlightsO_LIInhibiting peroxisome biogenesis uncovers a metabolic vulnerability in melanoma C_LIO_LICD36+ persister melanoma cells tolerate MAPK-targeted therapy through peroxisome/UGCG mediated metabolic rewiring C_LIO_LIDual blockade of PEX3 and UGCG potentiates melanoma response to MAPK-targeted therapies and restores therapeutic sensitivity in MAPKi-resistant tumors C_LIO_LINNC 55-0396 is a PEX3-PEX19 binding inhibitor with potent anti-tumor activity in melanoma C_LI

cancer biology↗

bioRxiv2022

A Unified Modular Framework to Incorporate Structural Dependency in Spatial Omics Data

Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a unified framework that integrates positional information into non-spatial models via modular priors and losses. In simulated and real datasets, Smoother enables accurate data imputation, cell-type deconvolution, and dimensionality reduction with remarkable efficiency. In colorectal cancer, Smoother-guided deconvolution revealed plasma cell and fibroblast subtype localizations linked to tumor microenvironment restructuring. Additionally, joint modeling of spatial and single-cell human prostate data with Smoother allowed for spatial mapping of reference populations with significantly reduced ambiguity.

bioinformatics↗

bioRxiv2022

MUC13 negatively regulates tight junction proteins and intestinal epithelial barrier integrity via Protein Kinase C

Regulation and adaptation of intestinal epithelial barrier function is essential for human health. The transmembrane mucin MUC13 is an abundant intestinal glycoprotein with important functions for mucosal maintenance that are not yet completely understood. We demonstrate that in intestinal epithelial monolayers MUC13 localized to both the apical surface and the tight junction (TJ) region on the lateral membrane. MUC13 deletion resulted in increased transepithelial resistance (TEER) and reduced translocation of small solutes. TJ proteins including claudins and occludin were highly increased in membrane fractions of MUC13 knockout cells. Removal of the MUC13 cytoplasmic tail (CT) also altered TJ composition but did not result in increased TEER. The increased buildup of TJ complexes in {Delta}MUC13 and MUC13-{Delta}CT cells was dependent on PKC, which is in line with a predicted PKC motif in the MUC13 cytoplasmic tail. The responsible PKC member might be PKC{delta} based on elevated protein levels in the absence of MUC13. Our results identify MUC13 as a central player in TJ complex stability and intestinal barrier permeability.

cell biology↗

bioRxiv2022

Heterosynaptic Plasticity of the Visuo-auditory Projection Requires Cholecystokinin released from Entorhinal Cortex Afferents

The entorhinal cortex is involved in establishing enduring visuo-auditory associative memory in the neocortex. Here we explored the mechanisms underlying this synaptic plasticity related to projections from the visual and entorhinal cortices to the auditory cortex, using optogenetics of dual pathways. High-frequency laser stimulation (HFLS) of the visuo-auditory projection did not induce long-term potentiation (LTP). However, after pairing with sound stimulus, the visuo-auditory inputs were potentiated following either infusion of cholecystokinin (CCK) or HFLS of the entorhino-auditory CCK-expressing projection. Combining retrograde tracing and RNAscope in situ hybridization, we show that CCK expression is higher in entorhinal cortex neurons projecting to the auditory cortex than in those originating from the visual cortex. In the presence of CCK, potentiation in the neocortex occurred when the pre-synaptic input arrived 200 ms before post-synaptic firing, even after just five trials of pairing. Behaviorally, inhibition of CCK signaling blocked the generation of associative memory. Our results indicate that neocortical visuo-auditory association is formed through heterosynaptic plasticity, which depends on release of CCK in the neocortex mostly from entorhinal afferents.

neuroscience↗

bioRxiv2022

Protein Language Model Predicts Mutation Pathogenicity and Clinical Prognosis

Accurately predicting the effects of mutations in cancer has the potential to improve existing treatments and identify novel therapeutic targets. In this paper, we evidence for the first time that the large-scale pre-trained protein language models (PPLMs) are zero-shot predictors for two clinically relevant tasks: identifying diseasecausing mutations and predicting patient survival rate. Then we benchmark a series of state-of-the-art (SOTA) PPLMs on 2279 protein variants across 20 cancer-related genes. Our empirical results show that the PPLMs outperform the SOTA baseline, EVE [1], trained on multiple sequence alignment (MSA) data. We also demonstrate that the evolutionary index score, generated from the PPLMs softmax layer, is good indicator for both mutation pathogenicity and patient survival rate. Our paper has taken a key step toward the clinical utility of large-scale PPLMs.

bioinformatics↗

bioRxiv2022

Optimised whole-genome CRISPR interference screens identify ARID1A-dependent growth regulators in human induced pluripotent stem cells

Perturbation of gene function is a powerful way to understand the role of individual genes in cellular systems. Whole-genome CRISPR/Cas-based screens have parallelized this approach and identified genes that modulate growth in many contexts. However, the DNA break-induced stress upon Cas9 action limits the efficacy of these screens in important models, such as human induced pluripotent stem cells (iPSCs). Silencing with a catalytically inactive Cas9 is a less stressful alternative, but has been considered less effective so far. Here, we first tested the efficiency of several dCas9 fusion proteins for target repression in human iPSCs, and identified dCas9-KRAB-MeCP2 as the most potent. We then produced monoclonal and polyclonal cell lines carrying this construct from multiple iPSC donors, and optimized genome-wide screens with them. We found silencing in a 200bp window around the transcription start site to be as effective as using wild-type Cas9 for identifying essential genes in iPSCs, but with a reduced cost due to better cell survival. Monoclonal lines performed better, but data from polyclonal lines were of sufficient quality for screening for larger effects. Finally, we performed whole-genome screens to identify dosage sensitivities that depend on the functionality of ARID1A, a commonly mutated cancer and developmental disorder gene. We observed differential growth upon depletion of NF2, TAF6L, EZH2, and PSMB2 genes in ARID1A+/-lines compared to wild type, and an enrichment of proteasome genes. Further, we confirmed that the context-specific growth decrease was phenocopied by treating the cells with a proteasome inhibitor, suggesting a pharmacologically targetable synthetic lethal interaction between the proteasome and ARID1A. We propose that many more plausible targets in challenging cell models can be efficiently identified with our approach.

cell biology↗

bioRxiv2022

SiGra: Single-cell spatial elucidation through image-augmented graph transformer

The recent advances in high-throughput molecular imaging push the spatial transcriptomics technologies to the subcellular resolution, which breaks the limitations of both single-cell RNA-seq and array-based spatial profiling. The latest released single-cell spatial transcriptomics data from NanoString CosMx and MERSCOPE platforms contains multi-channel immunohistochemistry images with rich information of cell types, functions, and morphologies of cellular compartments. In this work, we developed a novel method, Single-cell spatial elucidation through image-augmented Graph transformer (SiGra), to reveal spatial domains and enhance the substantially sparse and noisy transcriptomics data. SiGra applies hybrid graph transformers over a spatial graph that comprises high-content images and gene expressions of individual cells. SiGra outperformed state-of-the-art methods on both single-cell spatial profiles and spot-level spatial transcriptomics data from complex tissues. The inclusion of immunohistochemistry images improved the model performance by 37% (95%CI: 27% - 50%). SiGra improves the characterization of intratumor heterogeneity and intercellular communications in human lung cancer samples, meanwhile recovers the known microscopic anatomy in both human brain and mouse liver tissues. Overall, SiGra effectively integrates different spatial modality data to gain deep insights into the spatial cellular ecosystems.

bioinformatics↗

bioRxiv2022

Complement-dependent loss of inhibitory synapses on pyramidal neurons following Toxoplasma gondii infection

The apicomplexan parasite Toxoplasma gondii has developed mechanisms to establish a central nervous system infection in virtually all warm-blooded animals. Acute T. gondii infection can cause neuroinflammation, encephalitis, and seizures. Meanwhile, studies in humans, non-human primates, and rodents have linked chronic T. gondii infection with altered behavior and increased risk for neuropsychiatric disorders, including schizophrenia. We previously demonstrated that T. gondii infection triggers the loss of perisomatic inhibitory synapses, an important source of inhibition on excitatory pyramidal cells, and a type of synapse that is disrupted in neurological and neuropsychiatric disorders. Similar to other instances of inflammation and neurodegeneration, we showed that phagocytic cells (including microglia and infiltrating monocytes) contribute to the loss of these inhibitory synapses. However, in the case of T. gondii-induced synapse loss, phagocytic cells target and ensheath the cell bodies of telencephalic neurons. Here, we show that these phagocytic cells specifically ensheath excitatory pyramidal neurons, leading to the preferential loss of perisomatic synapses on these neurons. In contrast, inhibitory cortical interneuron subtypes are not extensively ensheathed by phagocytic cells following infection. Moreover, we show that infection induces expression of complement C3 protein by these excitatory neurons and that C3 is required for the loss of perisomatic inhibitory synapses, albeit not through activation of the classical complement pathway. Together, these findings provide evidence that T. gondii infection induces changes in excitatory pyramidal neurons that trigger selective removal of inhibitory perisomatic synapses in the infected neocortex and provide a novel role for complement in remodeling of inhibitory circuits in the infected brain.

neuroscience↗

bioRxiv2022

In vivo base editing rescues photoreceptors in a mouse model of retinitis pigmentosa

Retinitis pigmentosa (RP) is a group of retinal diseases that cause the progressive death of retinal photoreceptor cells and eventually blindness. Mutations in the {beta}-domain of the phosphodiesterase 6 (Pde6b) gene are among the most identified causes of autosomal recessive RP. Here, we report a base editing approach in which adeno-associated virus (AAV)-mediated adenine base editor (ABE) delivery to postmitotic photoreceptors is used to correct the Pde6b mutation in a retinal degeneration 10 (rd10) mouse model of RP. Subretinal delivery of AAV8-ABE corrects Pde6b mutation with up to 37.41% efficiency at the DNA level and up to 91.95% efficiency at the cDNA level, restores PDE6B expression, preserves photoreceptors and rescues visual function. RNA-seq reveals upregulation of genes associated with phototransduction and photoreceptor survival. Our data demonstrate that base editing is a potential gene therapy that could provide durable protection against RP.

genetics↗

bioRxiv2022

The highly expressed ERV1 forms virus-like particles for regulating early embryonic development

In mammals, the transcription of transposable elements (TEs) is important for maintaining early embryonic development. Here, we systematically analyzed the expression characteristics of TE-derived transcripts in early embryos by constructing a database of TEs and transcriptome data from goats and using it to study the function of endogenous retroviruses (ERVs) in regulating early embryo development. We found that ERV1 made up the highest proportion of TE sequences and exhibited a stage-specific expression pattern during early embryonic development. Among ERV elements, ERV1 had the potential to encode the Gag protein domain to form virus-like particles (VLPs) in early goat embryos. Knockdown of ERV1_1_574 significantly reduced the embryo development rate and the number of trophoblast cells (P< 0.05). Transcriptome sequencing analysis of morula embryos showed that ERV1_1_574 mainly regulated the expression of genes related to embryo compaction and trophoblast cell differentiation, such as CX43 and CDX2. In summary, we found that ERV1 expression was essential for early embryonic development in goats through regulation of trophoblast cell differentiation.

developmental biology↗