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Huang, S.

Publications and source records attributed to Huang, S..

At least 217 records · Page 12Linked to original sources

GetPrimers: a generalized PCR-based genetic targeting primer designer enabling easy and standardized targeted gene modification across multiple systems

Genetic targeting (e.g., gene knockout and tagging) based on polymerase chain reaction (PCR) is a simple yet powerful approach for studying gene functions. Although originally developed in classic budding and fission yeast models, the same principle applies to other eukaryotic systems with efficient homologous recombination. One-step-PCR-based genetic targeting is conventionally used but the sizes of the homologous arms that it generates for recombination-mediated genetic targeting are usually limited. Alternatively, gene targeting can also be performed via fusion PCR, which can create homologous arms that are orders of magnitude larger, therefore substantially increases the efficiency of recombination-mediated genetic targeting. Here we present GetPrimers (https://www.evomicslab.org/app/getprimers/), a generalized computational framework and web tool to assist automatic targeting and verification primer design for both one-step-PCR-based and fusion-PCR-based genetic targeting experiments. Moreover, GetPrimers by design runs for any given genetic background of any species with full genome scalability. Therefore, GetPrimers is capable of empowering high-throughput functional genomics assays at multi-population and multi-species levels. Comprehensive experimental validations have been performed for targeting and verification primers designed by GetPrimers across multiple organism systems and experimental setups. We anticipate GetPrimers to become a highly useful and popular tool to facilitate easy and standardized gene modification across multiple systems. Take AwaysDeveloped GetPrimers for generalized primer design of PCR-based genetic targeting. GetPrimers shines with its high versatility and genome-wide scalability. GetPrimers was validated across multiple organisms and experimental setups.

genetics↗

The pore-forming apolipoprotein APOL7C drives phagosomal rupture and antigen cross-presentation by dendritic cells

Type I conventional dendritic cells (cDC1s) are essential for the generation of protective cytotoxic T lymphocyte (CTL) responses against many types of viruses and tumours. They do so by internalizing antigens from virally infected or tumour cells and presenting them to CD8+ T cells in a process known as cross-presentation (XP). Despite the obvious biological importance of XP, the molecular mechanism(s) driving this process remain unclear. Here, we show that a cDC-specific pore-forming protein called apolipoprotein 7C (APOL7C) is upregulated in response to innate immune stimuli and is recruited to phagosomes. Strikingly, the association of APOL7C with phagosomes leads to phagosomal rupture, which in turn allows for the escape of engulfed protein antigens to the cytosol where they can be processed via the endogenous major histocompatibility complex (MHC) class I antigen processing pathway. We show that APOL7C recruitment to phagosomes is voltage-dependent and occurs in response to NADPH oxidase-induced depolarization of the phagosomal membrane. Our data indicate the presence of dedicated pore-forming apolipoproteins that mediate the delivery of phagocytosed proteins to the cytosol of activated cDC1s to facilitate MHC class I presentation of exogenous antigen and to regulate adaptive immunity.

cell biology↗

Directly selecting differentially expressed genes for single-cell clustering analyses

In single-cell RNA sequencing (scRNA-seq) studies, cell-types and their associated marker genes are often identified by clustering and differential expression gene (DEG) analysis. scRNA-seq data contain many genes not relevant to cell-types and gene selection procedures are needed for more accurate clustering. An ideal gene selection procedure should select all DEGs between cell-types for best cell-type identification. However, because cell-types are unknown, gene selection and DEG analysis are performed separately using different methods. Genes are selected using surrogate criteria not directly related with clustering, which often miss important genes or select unimportant genes. Clustering accuracy could be seriously influenced because of the inferior gene selection. DEGs are often detected by comparing different clusters, leading to many false DEGs due to the selection bias problem. In this paper, we present Festem, a unified method for gene selection and DEG analysis in scRNA-seq studies. Festem investigates genes clustering information based on the observation that marginal distributions of DEGs are mixtures of their different cell-type-conditional distributions, and can directly select the clustering-informative DEGs and avoid the selection bias problem. Extensive simulation and real data analyses show that Festem achieves high precision and recall for DEG detection, and enables more accurate clustering and cell-type identification. Applications to several scRNA-seq datasets demonstrate that Festem can identify cell-types that are often missed by other methods. In a large intrahepatic cholangiocarcinoma dataset, we identify CD8+ T cell-types and find that their marker genes are novel prognostic biomarkers.

bioinformatics↗

Discovery of fibrotic intervertebral disc in mice

Intervertebral discs are crucial to spine flexibility and stability during locomotion, but the mechanism of their mechanoadaptation to stress remains inadequately elucidated. We discovered spontaneous collagenesis in discs at the tail base in mice occurring from 14 days post-natal development. These discs termed as type C, differ from typical discs by exhibiting intensive collagen II and reduced aggrecan deposition contributing to the stiffening of the extracellular matrix (ECM), without typical degenerative markers. The reinforced mechanical properties enable type C discs to withstand high mechanical stress during flexion. Further analysis revealed that type C discs experience a turnover in cell composition, with the emergence of Procr+ progenitor cells and depletion of notochord cells. We demonstrated the essential role of mechanical stress in type C disc formation, suggesting a mechanoadaptive process rather than a pathological condition. Mechanistically, we identified TRPV4, as pivotal factors in collagen II synthesis in type C discs, highlighting the role of mechanotransduction in this adaptation. Our findings introduce a novel mechanoadaptive process of intervertebral disc by orchestrating collagenesis, advancing understanding of diverse disc functions in spine development and homeostasis, thereby providing insights for leveraging this mechanism to address spinal disorders.

pathology↗

Modeling Human Spine-Spinal Cord Organogenesis by hPSC-Derived Neuromesodermal Progenitors

Human trunk development, including spine and spinal cord organogenesis, is a coordinated, orderly, and interdependent process with spatiotemporal tissue patterning. However, the underlying cellular and molecular mechanisms remain largely unclear due to the lack of an effective model that can simulate the early development of human body axis. Here, we reported the long-term patterning and dynamic morphogenesis of human trunk through the formation of spine-spinal cord organoids (SSCOs) self-organized from three-dimensional culture of human PSC-derived neuromesodermal progenitors (NMPs). The SSCOs resembled the morphogenetic features of spine and spinal cord along the anterior-posterior axis, and showed the chondro-osteogenic and neural trajectories consistent with developmental dynamics of spine and spinal cord in gestational embryo through single-cell RNA sequencing (scRNA-seq). In addition, we identified a new HMMR+ bipotent cell population with self-renewal ability and neural/mesodermal competence but distinct from NMPs, which may be involved in trunk development and represent an invaluable tool for disease modeling of spine- and spinal cord-related disorders. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/549829v1_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@14bfd30org.highwire.dtl.DTLVardef@1db7fe8org.highwire.dtl.DTLVardef@1aa66a1org.highwire.dtl.DTLVardef@380932_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

Using Saturation Mutagenesis-Reinforced Functional Assays (SMuRF) to improve the variant interpretation for alpha-dystroglycan glycosylation enzymes

Interpretation of disease-causing genetic variants remains a challenge in human genetics. Current costs and complexity of deep mutational scanning methods hamper crowd-sourcing approaches toward genome-wide resolution of variants in disease-related genes. Our framework, Saturation Mutagenesis-Reinforced Functional assays (SMuRF), addresses these issues by offering simple and cost-effective saturation mutagenesis, as well as streamlining functional assays to enhance the interpretation of unresolved variants. Applying SMuRF to neuromuscular disease genes FKRP and LARGE1, we generated functional scores for all possible coding single nucleotide variants, which aid in resolving clinically reported variants of uncertain significance. SMuRF also demonstrates utility in predicting disease severity, resolving critical structural regions, and providing training datasets for the development of computational predictors. Our approach opens new directions for enabling variant-to-function insights for disease genes in a manner that is broadly useful for crowd-sourcing implementation across standard research laboratories.

genetics↗

Unbiased phosphoproteomics analysis unveils modulation of insulin signaling by extramitotic CDK1 kinase activity in human myotubes

Sensitivity and plasticity of insulin signaling and glucose uptake in skeletal muscle depends on determinants such as genetic variation and obesity. We collected muscle biopsies and isolated myoblasts from a multi-ethnic cohort of lean South Asians (N=10), lean Chinese (N=10), and obese Chinese (N=10), and analysed the proteome and phosphoproteome dynamics in terminally differentiated myotubes after a low-dose insulin stimulation (10nM at 0, 5, 30 min). The myotubes initially responded with increased abundance and phosphorylation level changes along the PI3K/AKT/mTOR axis, decreased abundance of translation initiation factors, and increased phosphorylation levels on proteins involved in mRNA processing at 5 min. After the acute response, protein abundance returned to baseline at 30 min, while phosphorylation changes persisted in proteins including AKT, RPS6 and AS160 (TBC1D4). A joint kinase-substrate statistical analysis revealed that protein abundance changes of AKT, PAK1 and CDK1 showed concordant phosphorylation changes in their respective substrates upon insulin stimulation. We also observed increased phosphorylation of some substrates uniquely in each group, particularly the substrates of CDKs showing stronger changes in South Asians than in Chinese. Pharmacological inhibition and siRNA knockdown of CDK1, a non-myogenic kinase, in terminally differentiated myotubes reduced glucose uptake and desensitized several phosphorylation-mediated signaling on protein translation initiation factors, IRS1, and AS160. Our data suggest that basal extramitotic activity of CDK1 is required for PI3K/AKT/mTORC1 signaling cascade and glucose uptake in insulin-stimulated myotubes. The data also provide a rich resource for studying the role of other kinases in the mechanism of insulin resistance in human myotubes.

physiology↗

Evolution of chromosome arm aberrations in breast cancer through genetic network rewiring

The basal breast cancer subtype is enriched for triple-negative breast cancer (TNBC) and displays consistent large chromosomal deletions. Here, we characterize the evolution and maintenance of chromosome 4p (chr4p) loss in basal breast cancer. TCGA data analysis showed recurrent deletion of chr4p in basal breast cancer. Phylogenetic analysis of a unique panel of 23 primary tumor/patient-derived xenograft basal breast cancers revealed early evolution of chr4p deletion. Mechanistically we show that Chr4p loss is associated with enhanced proliferation. Gene function studies identified an unknown gene, C4orf19, within chr4p, which suppressed proliferation when overexpressed and is a novel member of a PDCD10-GCKIII kinase module, we name as PGCA1. Genome-wide pooled overexpression screens using a barcoded library of human open reading frames, identified chromosomal regions, including chr4p, that suppress proliferation when overexpressed in a context-dependent manner implicating network interactions. Together this sheds light on the early emergence of complex aneuploid karyotypes involving chr4p and adaptive landscapes shaping breast cancer genomes.

genomics↗

Concerted epithelial and stromal changes during progression of Barrett's Esophagus to invasive adenocarcinoma exposed by multi-scale, multi-omics analysis

Esophageal adenocarcinoma arises from Barretts esophagus, a precancerous metaplastic replacement of squamous by columnar epithelium in response to chronic inflammation. Multi-omics profiling, integrating single-cell transcriptomics, extracellular matrix proteomics, tissue-mechanics and spatial proteomics of 64 samples from 12 patients paths of progression from squamous epithelium through metaplasia, dysplasia to adenocarcinoma, revealed shared and patient-specific progression characteristics. The classic metaplastic replacement of epithelial cells was paralleled by metaplastic changes in stromal cells, ECM and tissue stiffness. Strikingly, this change in tissue state at metaplasia was already accompanied by appearance of fibroblasts with characteristics of carcinoma-associated fibroblasts and of an NK cell-associated immunosuppressive microenvironment. Thus, Barretts esophagus progresses as a coordinated multi-component system, supporting treatment paradigms that go beyond targeting cancerous cells to incorporating stromal reprogramming. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/544265v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@64c375org.highwire.dtl.DTLVardef@15c6ef2org.highwire.dtl.DTLVardef@177dee0org.highwire.dtl.DTLVardef@c945e7_HPS_FORMAT_FIGEXP M_FIG Graphical AbstractTo obtain a comprehensive picture of the coordinated changes in epithelial, stromal and immune compartments during development of Barretts-associated esophageal adenocarcinoma, patient-matched samples corresponding to various phases of disease progression were collected from 12 patients, each of which had at a given time point lesions at multiple stages progression (matched-normal, metaplasia, dysplasia, and carcinoma). Matched "normal" gastric tissues were also collected. These sample were analyzed by single cell RNA-sequencing (scRNAseq) for single-cell resolution transcriptomics and Copy Number Variant (CNV), by proteomics for extracellular matrix (ECM) proteins, by Atomic Force Microscopy (AFM for tissue stiffness and by CODEX spatial proteomics imaging The integrative multi-omics analysis exposed drastic alterations in cell type composition and shifts in cell states in all three compartments. A large subpopulation of fibroblasts absent in the normal esophagus and characteristic of dysplasia and adenocarcinoma sample, that based on markers would indeed be considered cancer associated fibroblasts (CAF), appeared already in the metaplastic phase. This fibroblast subpopulation had transcriptomes virtually indistinguishable with fibroblasts of the cancer free gastric epithelium in these patients C_FIG

cancer biology↗

Caspase-2 is essential for proliferation and self-renewal of nucleophosmin-mutated acute myeloid leukemia.

Mutation in nucleophosmin (NPM1) causes relocalization of this normally nucleolar protein to the cytoplasm (NPM1c+). Despite NPM1 mutation being the most common driver mutation in cytogenetically normal adult acute myeloid leukemia (AML), the mechanisms of NPM1c+-induced leukemogenesis remain unclear. Caspase-2 is a pro-apoptotic protein activated by NPM1 in the nucleolus. Here, we show that caspase-2 is also activated by NPM1c+ in the cytoplasm, and DNA damage-induced apoptosis is caspase-2-dependent in NPM1c+ AML but not in NPM1wt cells. Strikingly, in NPM1c+ cells, loss of caspase-2 results in profound cell cycle arrest, differentiation, and down-regulation of stem cell pathways that regulate pluripotency including impairment in the AKT/mTORC1 and Wnt signaling pathways. In contrast, there were minimal differences in proliferation, differentiation, or the transcriptional profile of NPM1wt cells with and without caspase-2. Together, these results show that caspase-2 is essential for proliferation and self-renewal of AML cells that have mutated NPM1. This study demonstrates that caspase-2 is a major effector of NPM1c+ function and may even be a druggable target to treat NPM1c+ AML and prevent relapse.

cancer biology↗

Chikungunya virus glycoproteins transform macrophages into productive viral dissemination vessels.

Despite their role as innate sentinels, macrophages are cellular reservoirs for chikungunya virus (CHIKV), a highly pathogenic arthropod-borne alphavirus that has caused unprecedented epidemics worldwide. Here, we took interdisciplinary approaches to elucidate the CHIKV determinants that subvert macrophages into virion dissemination vessels. Through comparative infection using chimeric alphaviruses and evolutionary selection analyses, we discovered for the first time that CHIKV glycoproteins E2 and E1 coordinate efficient virion production in macrophages with the domains involved under positive selection. We performed proteomics on CHIKV-infected macrophages to identify cellular proteins interacting with the precursor and/or mature forms of viral glycoproteins. We uncovered two E1-binding proteins, signal peptidase complex subunit 3 (SPCS3) and eukaryotic translation initiation factor 3 (eIF3k), with novel inhibitory activities against CHIKV production. These results highlight how CHIKV E2 and E1 have been evolutionarily selected for viral dissemination likely through counteracting host restriction factors, making them attractive targets for therapeutic intervention.

microbiology↗

Deep learning and host variable embedding augment microbiome-based simultaneous detection of multiple diseases

Microbiome has emerged as a promising indicator or predictor of human diseases. However, previous studies typically labeled each specimen as either healthy or with a specific disease, ignoring the prevalence of complications or comorbidities in actual cohorts, which may confound the microbial-disease associations. For instance, a patient may suffer from multiple diseases, making it challenging to detect their health status accurately. Furthermore, host phenotypes such as physiological characteristics and lifestyles can alter the microbiome structure, but this information has not yet been fully utilized in data models. To address these issues, we propose a highly explainable deep learning (DL) method called Meta-Spec. Using a deep neural network (DNN) based approach, it encodes and embeds the refined host variables with microbiome features, enabling the detection of multiple diseases and their correlations simultaneously. Our experiments showed that Meta-Spec outperforms regular machine learning (ML) strategies for multi-label disease screening in several cohorts. More importantly, Meta-Spec can successfully detect comorbidities that are often missed by regular ML approaches. In addition, due to its high interpretability, Meta-Spec captures key factors that shape disease patterns from host variables and microbial members. Hence, these efforts improve the feasibility and sensitivity of microbiome-based disease screening in practical scenarios, representing a significant step towards personalized medicine and better health outcomes.

bioinformatics↗

AnnoPRO: an innovative strategy for protein function annotation based on image-like protein representation and multimodal deep learning

Protein function annotation has been one of the longstanding issues, which is key for discovering drug targets and understanding physiological or pathological process. A variety of computational methods have therefore been constructed to facilitate the research developments in this particular direction. However, the annotation of protein function based on computational methods has been suffering from the serious "long-tail problem", and it remains extremely challenging for existing methods to improve the prediction accuracies for protein families in tail label levels. In this study, an innovative strategy, entitled AnnoPRO, for protein function annotation was thus constructed. First, a novel method enabling image-like protein representations was proposed. This method is unique in capturing the intrinsic correlations among protein features, which can greatly favor the application of the state-of-the-art deep learning methods popular in image classification. Second, a multimodal framework integrating multichannel convolutional neural network and long short-term memory neural network was constructed to realize a deep learning-based protein functional annotation. Since this framework was inspired by a reputable method used in image classification for dealing with its long-tail problem, our AnnoPRO was expected to significantly improve the annotation performance of the protein families in tail label level. Multiple case studies based on benchmark were also conducted, which confirmed the superior performance of AnnoPRO among the existing methods. All source codes and models of AnnoPRO were freely available to all users at https://github.com/idrblab/AnnoPRO, and would be essential complement to existing methods.

bioinformatics↗

Analysis of the heterogeneity and complexity of murine extraorbital lacrimal gland via single-cell RNA sequencing

PurposeThe lacrimal gland is essential for maintaining ocular surface health and avoiding external damage by secreting the aqueous layer of the tear film. However, a healthy lacrimal glands inventory of cell types and heterogeneity remains understudied. MethodsHere, 10X genome-based single-cell RNA sequencing was used to generate an unbiased classification of cellular diversity in the extraorbital lacrimal gland (ELG) of C57BL/6J mice. From 48,077 high-quality cells, an atlas of cell heterogeneity was produced, and cell types were defined by classic marker genes. The possible functions of these cells and the pseudotime trajectories for certain cell populations were analyzed through bioinformatics. In addition, a preliminary analysis of the cell-cell communication network in ELG was performed. ResultsOver 41 subclasses of cells were identified, including 9 kinds of glandular epithelial cells, 7 kinds of fibroblasts, 10 kinds of myeloid-derived immune cells, at least 10 kinds of lymphoid-derived immune cells, 3 kinds of vascular-associated cell subsets, and 2 kinds of Schwann cells. Analysis of cell-cell communication networks revealed that innate lymphoid cells were closely associated with other cells. ConclusionsThis study provides the first comprehensive transcriptome atlas and related database of mouse ELG. This resource can aid in a deeper understanding of lacrimal gland biology and pathophysiology of its related diseases.

bioinformatics↗

Signal recovery in single cell batch integration

Data integration to align cells across batches has become a cornerstone of single cell data analysis, critically affecting downstream results. Yet, how much biological signal is erased during integration? Currently, there are no guidelines for when the biological differences between samples are separable from batch effects, and thus, data integration usually involve a lot of guesswork: Cells across batches should be aligned to be "appropriately" mixed, while preserving "main cell type clusters". We show evidence that current paradigms for single cell data integration are unnecessarily aggressive, removing biologically meaningful variation. To remedy this, we present a novel statistical model and computationally scalable algorithm, CellANOVA, to recover biological signal that is lost during single cell data integration. CellANOVA utilizes a "pool-of-controls" design concept, applicable across diverse settings, to separate unwanted variation from biological variation of interest. When applied with existing integration methods, CellANOVA allows the recovery of subtle biological signals and corrects, to a large extent, the data distortion introduced by integration. Further, CellANOVA explicitly estimates cell- and gene-specific batch effect terms which can be used to identify the cell types and pathways exhibiting the largest batch variations, providing clarity as to which biological signals can be recovered. These concepts are illustrated on studies of diverse designs, where the biological signals that are recovered by CellANOVA are shown to be validated by orthogonal assays. In particular, we show that CellANOVA is effective in the challenging case of single-cell and single-nuclei data integration, where the recovered biological signals are replicated in an independent study.

bioinformatics↗

Integration of microbial and chemical synthesis for the efficient production of plitidepsin, a promising anticancer and antiviral agent

Plitidepsin, a marine-derived anticancer medicine, is being tested in phase III clinical trials for treating COVID-19. However, the current supply of plitidepsin relies on laborious chemical synthesis processes. Here, we present a new approach that combines microbial and chemical synthesis to produce plitidepsin. We screened a Tistrella strain library to identify a high-yield didemnin B producer, and then introduced a second copy of the didemnin biosynthetic gene cluster into its genome, resulting in the highest yield of didemnin B reported in the literature. Next, we developed two straightforward chemical strategies to convert didemnin B to plitidepsin, one of which involved a one-step synthetic route giving over 90% overall yield. We also synthesized two new didemnin analogues and assessed their anticancer and antiviral activities. Our findings offer a practical and sustainable solution for producing plitidepsin and its derivatives, potentially expediting didemnin drug development.

synthetic biology↗

Glial Draper signaling triggers cross-neuron plasticity in bystander neurons after neuronal cell death

Neuronal cell death and subsequent brain dysfunction are hallmarks of aging and neurodegeneration, but how the nearby healthy neurons (bystanders) respond to the cell death of their neighbors is not fully understood. In the Drosophila larval neuromuscular system, bystander motor neurons can structurally and functionally compensate for the loss of their neighbors by increasing their axon terminal size and activity. We termed this compensation as cross-neuron plasticity, and in this study, we demonstrated that the Drosophila engulfment receptor, Draper, and the associated kinase, Shark, are required in glial cells. Surprisingly, overexpression of the Draper-I isoform boosts cross-neuron plasticity, implying that the strength of plasticity correlates with Draper signaling. Synaptic plasticity normally declines as animals age, but in our system, functional cross-neuron plasticity can be induced at different time points, whereas structural cross-neuron plasticity can only be induced at early stages. Our work uncovers a novel role for glial Draper signaling in cross-neuron plasticity that may enhance nervous system function during neurodegeneration and provides insights into how healthy bystander neurons respond to the loss of their neighboring neurons.

neuroscience↗

Nucleolar structure connects with global nuclear organization

The nucleolus is a multi-functional nuclear body. To tease out the roles of nucleolar structure without resorting to multi-action drugs, we knocked down RNA polymerase I subunit RPA194 in HeLa cells by siRNA. Loss of RPA194 resulted in nucleolar structural segregation and effects on both nucleolus-proximal and distal nuclear components. The perinucleolar compartment was disrupted, centromere-nucleolus interactions were significantly reduced, and the intranuclear locations of specific genomic loci were altered. Moreover, Cajal bodies, distal from nucleoli, underwent morphological and compositional changes. To distinguish whether these global reorganizations are the results of nucleolar structural disruption or inhibition of ribosome synthesis, the pre-ribosomal RNA processing factor, UTP4, was also knocked down, which did not lead to nucleolar segregation, nor the intranuclear effects seen with RPA195A knockdown, demonstrating that they do not arise from a cessation of ribosome synthesis. These findings point to a commutative system that links nucleolar structure to the maintenance and spatial organization of certain nuclear bodies and genomic loci.

cell biology↗