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1.
PLoS Comput Biol ; 18(10): e1010636, 2022 10.
Article in English | MEDLINE | ID: covidwho-2112639

ABSTRACT

Early and accurate detection of viruses in clinical and environmental samples is essential for effective public healthcare, treatment, and therapeutics. While PCR detects potential pathogens with high sensitivity, it is difficult to scale and requires knowledge of the exact sequence of the pathogen. With the advent of next-gen single-cell sequencing, it is now possible to scrutinize viral transcriptomics at the finest possible resolution-cells. This newfound ability to investigate individual cells opens new avenues to understand viral pathophysiology with unprecedented resolution. To leverage this ability, we propose an efficient and accurate computational pipeline, named Venus, for virus detection and integration site discovery in both single-cell and bulk-tissue RNA-seq data. Specifically, Venus addresses two main questions: whether a tissue/cell type is infected by viruses or a virus of interest? And if infected, whether and where has the virus inserted itself into the human genome? Our analysis can be broken into two parts-validation and discovery. Firstly, for validation, we applied Venus on well-studied viral datasets, such as HBV- hepatocellular carcinoma and HIV-infection treated with antiretroviral therapy. Secondly, for discovery, we analyzed datasets such as HIV-infected neurological patients and deeply sequenced T-cells. We detected viral transcripts in the novel target of the brain and high-confidence integration sites in immune cells. In conclusion, here we describe Venus, a publicly available software which we believe will be a valuable virus investigation tool for the scientific community at large.


Subject(s)
HIV Infections , Liver Neoplasms , Viruses , Humans , RNA-Seq , Sequence Analysis, RNA , Software
2.
PLoS One ; 17(10): e0276460, 2022.
Article in English | MEDLINE | ID: covidwho-2089429

ABSTRACT

Excessive neutrophil infiltration and dysfunction contribute to the progression and severity of hyper-inflammatory syndrome, such as in severe COVID19. In the current study, we re-analysed published scRNA-seq datasets of mouse and human neutrophils to classify and compare the transcriptional regulatory networks underlying neutrophil differentiation and inflammatory responses. Distinct sets of TF modules regulate neutrophil maturation, function, and inflammatory responses under the steady state and inflammatory conditions. In COVID19 patients, neutrophil activation was associated with the selective activation of inflammation-specific TF modules. SARS-CoV-2 RNA-positive neutrophils showed a higher expression of type I interferon response TF IRF7. Furthermore, IRF7 expression was abundant in neutrophils from severe patients in progression stage. Neutrophil-mediated inflammatory responses positively correlate with the expressional level of IRF7. Based on these results, we suggest that differential activation of activation-related TFs, such as IRF7 mediate neutrophil inflammatory responses during inflammation.


Subject(s)
COVID-19 , Neutrophils , Humans , COVID-19/genetics , COVID-19/metabolism , Inflammation/genetics , Interferon Type I/metabolism , Neutrophil Activation/genetics , Neutrophil Activation/physiology , Neutrophils/metabolism , RNA, Viral , RNA-Seq , SARS-CoV-2 , Single-Cell Analysis
3.
Brief Bioinform ; 23(5)2022 09 20.
Article in English | MEDLINE | ID: covidwho-2017730

ABSTRACT

We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data representation and the downstream analysis. Compared with current methods, CLEAR overcomes the heterogeneity of the experimental data with a specifically designed representation learning task and thus can handle batch effects and dropout events simultaneously. It achieves superior performance on a broad range of fundamental tasks, including clustering, visualization, dropout correction, batch effect removal, and pseudo-time inference. The proposed method successfully identifies and illustrates inflammatory-related mechanisms in a COVID-19 disease study with 43 695 single cells from peripheral blood mononuclear cells.


Subject(s)
COVID-19 , RNA , COVID-19/genetics , Cluster Analysis , Data Analysis , Humans , Leukocytes, Mononuclear , RNA-Seq , Sequence Analysis, RNA/methods
4.
Proc Natl Acad Sci U S A ; 119(36): e2120680119, 2022 09 06.
Article in English | MEDLINE | ID: covidwho-2001001

ABSTRACT

The systemic immune response to viral infection is shaped by master transcription factors, such as NF-κB, STAT1, or PU.1. Although long noncoding RNAs (lncRNAs) have been suggested as important regulators of transcription factor activity, their contributions to the systemic immunopathologies observed during SARS-CoV-2 infection have remained unknown. Here, we employed a targeted single-cell RNA sequencing approach to reveal lncRNAs differentially expressed in blood leukocytes during severe COVID-19. Our results uncover the lncRNA PIRAT (PU.1-induced regulator of alarmin transcription) as a major PU.1 feedback-regulator in monocytes, governing the production of the alarmins S100A8/A9, key drivers of COVID-19 pathogenesis. Knockout and transgene expression, combined with chromatin-occupancy profiling, characterized PIRAT as a nuclear decoy RNA, keeping PU.1 from binding to alarmin promoters and promoting its binding to pseudogenes in naïve monocytes. NF-κB-dependent PIRAT down-regulation during COVID-19 consequently releases a transcriptional brake, fueling alarmin production. Alarmin expression is additionally enhanced by the up-regulation of the lncRNA LUCAT1, which promotes NF-κB-dependent gene expression at the expense of targets of the JAK-STAT pathway. Our results suggest a major role of nuclear noncoding RNA networks in systemic antiviral responses to SARS-CoV-2 in humans.


Subject(s)
COVID-19 , Gene Expression Regulation , Monocytes , RNA, Long Noncoding , SARS-CoV-2 , Alarmins/genetics , COVID-19/genetics , COVID-19/immunology , Humans , Janus Kinases/genetics , Monocytes/immunology , NF-kappa B/genetics , RNA, Long Noncoding/genetics , RNA, Long Noncoding/metabolism , RNA-Seq , SARS-CoV-2/immunology , STAT Transcription Factors/genetics , Signal Transduction/genetics , Single-Cell Analysis
5.
Nature ; 609(7928): 754-760, 2022 09.
Article in English | MEDLINE | ID: covidwho-1984401

ABSTRACT

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1-5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.


Subject(s)
COVID-19 , GTPase-Activating Proteins , Genome-Wide Association Study , Guanine Nucleotide Exchange Factors , Host Microbial Interactions , SARS-CoV-2 , Alleles , Animals , COVID-19/complications , COVID-19/genetics , COVID-19/immunology , COVID-19/physiopathology , Disease Models, Animal , GTPase-Activating Proteins/antagonists & inhibitors , GTPase-Activating Proteins/genetics , GTPase-Activating Proteins/metabolism , Genetic Predisposition to Disease , Guanine Nucleotide Exchange Factors/antagonists & inhibitors , Guanine Nucleotide Exchange Factors/genetics , Guanine Nucleotide Exchange Factors/metabolism , Host Microbial Interactions/genetics , Host Microbial Interactions/immunology , Humans , Interferon Type I/genetics , Interferon Type I/immunology , Japan , Lung/pathology , Macrophages , Mesocricetus , Middle Aged , Pneumonia/complications , Pyrazoles/pharmacology , RNA-Seq , SARS-CoV-2/pathogenicity , Viral Load , Weight Loss
6.
Proc Natl Acad Sci U S A ; 119(33): e2203437119, 2022 08 16.
Article in English | MEDLINE | ID: covidwho-1960624

ABSTRACT

The mortality of coronavirus disease 2019 (COVID-19) is strongly correlated with pulmonary vascular pathology accompanied by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-triggered immune dysregulation and aberrant activation of platelets. We combined histological analyses using field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy analyses of the lungs from autopsy samples and single-cell RNA sequencing of peripheral blood mononuclear cells to investigate the pathogenesis of vasculitis and immunothrombosis in COVID-19. We found that SARS-CoV-2 accumulated in the pulmonary vessels, causing exudative vasculitis accompanied by the emergence of thrombospondin-1-expressing noncanonical monocytes and the formation of myosin light chain 9 (Myl9)-containing microthrombi in the lung of COVID-19 patients with fatal disease. The amount of plasma Myl9 in COVID-19 was correlated with the clinical severity, and measuring plasma Myl9 together with other markers allowed us to predict the severity of the disease more accurately. This study provides detailed insight into the pathogenesis of vasculitis and immunothrombosis, which may lead to optimal medical treatment for COVID-19.


Subject(s)
COVID-19 , Lung , Myosin Light Chains , SARS-CoV-2 , Severity of Illness Index , Thromboinflammation , Vasculitis , COVID-19/blood , COVID-19/complications , COVID-19/pathology , Humans , Leukocytes, Mononuclear , Lung/blood supply , Lung/metabolism , Lung/pathology , Lung/virology , Myosin Light Chains/blood , RNA-Seq , SARS-CoV-2/isolation & purification , Single-Cell Analysis , Spectrometry, X-Ray Emission , Thromboinflammation/pathology , Thromboinflammation/virology , Vasculitis/pathology , Vasculitis/virology
7.
Arch Virol ; 167(11): 2133-2142, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-1935817

ABSTRACT

Mammalian orthoreoviruses (MEVs) that can cause enteric, respiratory, and encephalitic infections have been identified in a wide variety of mammalian species. Here, we report a novel MRV type 1 strain detected in Miniopterus schreibersii that may have resulted from reassortment events. Using next-generation RNA sequencing (RNA-seq), we found that the ratios of the RNA levels of the 10 reovirus segments in infected cells were constant during the late stages of infection. We also discovered that the relative abundance of each segment differed. Notably, the relative abundance of M2 (encoding the µ1 protein) and S4 (encoding the σ3 protein) RNAs was higher than that of the others throughout the infection. Additionally, massive junctions were identified. These results support the hypothesis that defective genome segments are generated and that cross-family recombination occurs. These data may further the study of gene function, viral replication, and virus evolution.


Subject(s)
Chiroptera , Orthoreovirus , Reoviridae , Animals , Genome, Viral , Orthoreovirus/genetics , RNA , RNA-Seq , Reoviridae/genetics
8.
Comput Biol Med ; 147: 105684, 2022 08.
Article in English | MEDLINE | ID: covidwho-1930823

ABSTRACT

BACKGROUND: The world has been battling the continuous COVID-19 pandemic spread by the SARS-CoV-2 virus for last two years. The issue of viral disease prediction is constantly a matter of interest in virology and the study of disease transmission over the long years. OBJECTIVE: In this study, we aimed to implement genome association studies using RNA-Seq of COVID-19 and reveal highly expressed gene biomarkers and prediction based on the machine learning model of COVID-19 analysis to combat this pandemic. METHOD: We collected RNA-Seq gene count data for both healthy (Control) and non-healthy (Treated) COVID-19 cases. In this experiment, a sequence of bioinformatics strategies and statistical techniques, such as fold-change and adjusted p-value, were processed to identify differentially expressed genes (DEGs). We filtered biomarker sets of high DEGs, moderate DEGs, and low DEGs using DESeq2, Limma Trend, and Limma Voom methods based on intersection and union operations and applied machine learning techniques to predict COVID-19. RESULT: Through experimental analysis, 67 potential biomarkers were extracted, comprising 49 up-regulated and 18 down-regulated genes, using statistical techniques and a set-theory consensus strategy. We trained the machine learning models on 12 different biomarker sets and found that the SVM model performed better than the other classifiers with 99.07% classification accuracy for moderate DEGs. CONCLUSION: Our study revealed that identified differentially expressed genes of the moderate DEGs biomarker set, |log2FC| ≥ 2 with adjusted p-value < 0.05, work significantly as input features to implement a machine learning model using a kernel-based SVM technique to predict COVID-19.


Subject(s)
COVID-19 , Biomarkers , COVID-19/diagnosis , COVID-19/genetics , Humans , Pandemics , RNA-Seq , SARS-CoV-2/genetics
9.
Viruses ; 14(5)2022 05 23.
Article in English | MEDLINE | ID: covidwho-1875813

ABSTRACT

The generation of different types of defective viral genomes (DVG) is an unavoidable consequence of the error-prone replication of RNA viruses. In recent years, a particular class of DVGs, those containing long deletions or genome rearrangements, has gain interest due to their potential therapeutic and biotechnological applications. Identifying such DVGs in high-throughput sequencing (HTS) data has become an interesting computational problem. Several algorithms have been proposed to accomplish this goal, though all incur false positives, a problem of practical interest if such DVGs have to be synthetized and tested in the laboratory. We present a metasearch tool, DVGfinder, that wraps the two most commonly used DVG search algorithms in a single workflow for the identification of the DVGs in HTS data. DVGfinder processes the results of ViReMa-a and DI-tector and uses a gradient boosting classifier machine learning algorithm to reduce the number of false-positive events. The program also generates output files in user-friendly HTML format, which can help users to explore the DVGs identified in the sample. We evaluated the performance of DVGfinder compared to the two search algorithms used separately and found that it slightly improves sensitivities for low-coverage synthetic HTS data and DI-tector precision for high-coverage samples. The metasearch program also showed higher sensitivity on a real sample for which a set of copy-backs were previously validated.


Subject(s)
Defective Viruses , RNA Viruses , Defective Viruses/genetics , Genome, Viral , High-Throughput Nucleotide Sequencing , RNA Viruses/genetics , RNA-Seq
10.
Front Immunol ; 13: 798712, 2022.
Article in English | MEDLINE | ID: covidwho-1779939

ABSTRACT

The immune system is a complex and sophisticated biological system, spanning multiple levels of complexity, from the molecular level to that of tissue. Our current understanding of its function and complexity, of the heterogeneity of leukocytes, is a result of decades of concentrated efforts to delineate cellular markers using conventional methods of antibody screening and antigen identification. In mammalian models, this led to in-depth understanding of individual leukocyte subsets, their phenotypes, and their roles in health and disease. The field was further propelled forward by the development of single-cell (sc) RNA-seq technologies, offering an even broader and more integrated view of how cells work together to generate a particular response. Consequently, the adoption of scRNA-seq revealed the unexpected plasticity and heterogeneity of leukocyte populations and shifted several long-standing paradigms of immunology. This review article highlights the unprecedented opportunities offered by scRNA-seq technology to unveil the individual contributions of leukocyte subsets and their crosstalk in generating the overall immune responses in bony fishes. Single-cell transcriptomics allow identifying unseen relationships, and formulating novel hypotheses tailored for teleost species, without the need to rely on the limited number of fish-specific antibodies and pre-selected markers. Several recent studies on single-cell transcriptomes of fish have already identified previously unnoticed expression signatures and provided astonishing insights into the diversity of teleost leukocytes and the evolution of vertebrate immunity. Without a doubt, scRNA-seq in tandem with bioinformatics tools and state-of-the-art methods, will facilitate studying the teleost immune system by not only defining key markers, but also teaching us about lymphoid tissue organization, development/differentiation, cell-cell interactions, antigen receptor repertoires, states of health and disease, all across time and space in fishes. These advances will invite more researchers to develop the tools necessary to explore the immunology of fishes, which remain non-conventional animal models from which we have much to learn.


Subject(s)
Fishes/genetics , Fishes/immunology , Leukocytes/immunology , Leukocytes/metabolism , RNA-Seq , Single-Cell Analysis , Animals , Immunity , Single-Cell Analysis/methods
11.
Genes (Basel) ; 13(3)2022 03 15.
Article in English | MEDLINE | ID: covidwho-1760489

ABSTRACT

Despite the importance of and current demand for abaca (Musa textilis Nee) fiber, there has been limited study that capitalizes on RNA-seq to identify candidate genes associated with high fiber quality and bunchy top virus (AbBTV) resistance. Three varieties (Abuab, Inosa, and Tangongon), one wild banana variety (Musa balbisiana Colla) Pacol, and two developed backcrosses (Abuab × Pacol BC2 and BC3) were grown at the Institute of Plant Breeding (IPB), Laguna, Philippines. The pseudostems of 3-month-old suckers of each genotype were sampled for RNA-seq. Datasets were analyzed for differential expression (DE) implementing various model frameworks, including pairwise, genotypic and non-DE models. Results indicate that Abuab and BC3 induce the highest proportion (70%) of abaca-specific genes. Gene ontology (GO) enrichment analysis showed several genes associated with cellulose synthase activity, callose synthase, ß-glucosidase activity, glucan biosynthetic process, etc. KEGG pathway analysis showed several genes encoding for enzymes involved in the lignin biosynthetic pathway. Analysis using genotypic DE (GDE) between abaca bunchy top virus (AbBTV)-resistant and -susceptible groups revealed genes such as pathogenesis-related protein and NBS-LRR. As the genotypes were not infected with the pathogen, these genes are yet to be confirmed for their roles in disease resistance and are an interesting subject for further investigation.


Subject(s)
Musa , Carbohydrates , Dietary Fiber , Disease Resistance/genetics , Musa/genetics , Plant Breeding , RNA-Seq
12.
Int J Mol Sci ; 23(5)2022 Feb 24.
Article in English | MEDLINE | ID: covidwho-1715406

ABSTRACT

To better understand the molecular basis of respiratory diseases of viral origin, high-throughput gene-expression data are frequently taken by means of DNA microarray or RNA-seq technology. Such data can also be useful to classify infected individuals by molecular signatures in the form of machine-learning models with genes as predictor variables. Early diagnosis of patients by molecular signatures could also contribute to better treatments. An approach that has rarely been considered for machine-learning models in the context of transcriptomics is data augmentation. For other data types it has been shown that augmentation can improve classification accuracy and prevent overfitting. Here, we compare three strategies for data augmentation of DNA microarray and RNA-seq data from two selected studies on respiratory diseases of viral origin. The first study involves samples of patients with either viral or bacterial origin of the respiratory disease, the second study involves patients with either SARS-CoV-2 or another respiratory virus as disease origin. Specifically, we reanalyze these public datasets to study whether patient classification by transcriptomic signatures can be improved when adding artificial data for training of the machine-learning models. Our comparison reveals that augmentation of transcriptomic data can improve the classification accuracy and that fewer genes are necessary as explanatory variables in the final models. We also report genes from our signatures that overlap with signatures presented in the original publications of our example data. Due to strict selection criteria, the molecular role of these genes in the context of respiratory infectious diseases is underlined.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Machine Learning , Neural Networks, Computer , RNA-Seq/methods , Transcriptome/genetics , Algorithms , COVID-19/classification , COVID-19/virology , Gene Ontology , Humans , Reproducibility of Results , SARS-CoV-2/physiology
13.
Sci Immunol ; 7(68): eabf2846, 2022 02 11.
Article in English | MEDLINE | ID: covidwho-1685480

ABSTRACT

Macrophages regulate protective immune responses to infectious microbes, but aberrant macrophage activation frequently drives pathological inflammation. To identify regulators of vigorous macrophage activation, we analyzed RNA-seq data from synovial macrophages and identified SLAMF7 as a receptor associated with a superactivated macrophage state in rheumatoid arthritis. We implicated IFN-γ as a key regulator of SLAMF7 expression and engaging SLAMF7 drove a strong wave of inflammatory cytokine expression. Induction of TNF-α after SLAMF7 engagement amplified inflammation through an autocrine signaling loop. We observed SLAMF7-induced gene programs not only in macrophages from rheumatoid arthritis patients but also in gut macrophages from patients with active Crohn's disease and in lung macrophages from patients with severe COVID-19. This suggests a central role for SLAMF7 in macrophage superactivation with broad implications in human disease pathology.


Subject(s)
Inflammation/immunology , Macrophage Activation/immunology , Signaling Lymphocytic Activation Molecule Family/immunology , Transcriptome/immunology , Acute Disease , Adult , Arthritis, Rheumatoid/genetics , Arthritis, Rheumatoid/immunology , Arthritis, Rheumatoid/metabolism , COVID-19/genetics , COVID-19/immunology , COVID-19/metabolism , COVID-19/virology , Cells, Cultured , Chronic Disease , Crohn Disease/genetics , Crohn Disease/immunology , Crohn Disease/metabolism , Female , Humans , Inflammation/genetics , Inflammation/metabolism , Macrophage Activation/genetics , RNA-Seq/methods , Reverse Transcriptase Polymerase Chain Reaction/methods , SARS-CoV-2/immunology , SARS-CoV-2/physiology , Signaling Lymphocytic Activation Molecule Family/genetics , Signaling Lymphocytic Activation Molecule Family/metabolism , Single-Cell Analysis/methods , Synovial Membrane/immunology , Synovial Membrane/metabolism , Synovial Membrane/pathology , Transcriptome/genetics
14.
Database (Oxford) ; 20222022 01 17.
Article in English | MEDLINE | ID: covidwho-1672169

ABSTRACT

In recent years, efficient scRNA-seq methods have been developed, enabling the transcriptome profiling of single cells massively in parallel. Meanwhile, its high dimensionality and complexity bring challenges to the data analysis and require extensive collaborations between biologists and bioinformaticians and/or biostatisticians. The communication between these two units demands a platform for easy data sharing and exploration. Here we developed Single-Cell Transcriptomics Annotated Viewer (SCANNER), as a public web resource for the scientific community, for sharing and analyzing scRNA-seq data in a collaborative manner. It is easy-to-use without requiring special software or extensive coding skills. Moreover, it equipped a real-time database for secure data management and enables an efficient investigation of the activation of gene sets on a single-cell basis. Currently, SCANNER hosts a database of 19 types of cancers and COVID-19, as well as healthy samples from lungs of smokers and non-smokers, human brain cells and peripheral blood mononuclear cells (PBMC). The database will be frequently updated with datasets from new studies. Using SCANNER, we identified a larger proportion of cancer-associated fibroblasts cells and more active fibroblast growth-related genes in melanoma tissues in female patients compared to male patients. Moreover, we found ACE2 is mainly expressed in lung pneumocytes, secretory cells and ciliated cells and differentially expressed in lungs of smokers and never smokers.


Subject(s)
COVID-19 , Leukocytes, Mononuclear , Female , Gene Expression Profiling , Humans , Male , RNA-Seq , SARS-CoV-2 , Sequence Analysis, RNA , Single-Cell Analysis , Software
15.
Nature ; 602(7896): 268-273, 2022 02.
Article in English | MEDLINE | ID: covidwho-1671587

ABSTRACT

Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1-6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes-SUV420H1 (also known as KMT5B), ARID1B and CHD8-in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages-γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons-but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.


Subject(s)
Autism Spectrum Disorder , Genetic Predisposition to Disease , Neurons , Autism Spectrum Disorder/genetics , Autism Spectrum Disorder/metabolism , Autism Spectrum Disorder/pathology , Cerebral Cortex/cytology , DNA-Binding Proteins/genetics , GABAergic Neurons/metabolism , GABAergic Neurons/pathology , Histone-Lysine N-Methyltransferase/genetics , Humans , Neurons/classification , Neurons/metabolism , Neurons/pathology , Organoids/cytology , Proteomics , RNA-Seq , Single-Cell Analysis , Transcription Factors/genetics
16.
Cells ; 11(3)2022 01 30.
Article in English | MEDLINE | ID: covidwho-1667057

ABSTRACT

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still ongoing, as is research on the molecular mechanisms underlying cellular infection by coronaviruses, with the hope of developing therapeutic agents against this pandemic. Other important respiratory viruses such as 2009 pandemic H1N1 and H7N9 avian influenza virus (AIV), influenza A viruses, are also responsible for a possible outbreak due to their respiratory susceptibility. However, the interaction of these viruses with host cells and the regulation of post-transcriptional genes remains unclear. In this study, we detected and analyzed the comparative transcriptome profiling of SARS-CoV-2, panH1N1 (A/California/07/2009), and H7N9 (A/Shanghai/1/2013) infected cells. The results showed that the commonly upregulated genes among the three groups were mainly involved in autophagy, pertussis, and tuberculosis, which indicated that autophagy plays an important role in viral pathogenicity. There are three groups of commonly downregulated genes involved in metabolic pathways. Notably, unlike panH1N1 and H7N9, SARS-CoV-2 infection can inhibit the m-TOR pathway and activate the p53 signaling pathway, which may be responsible for unique autophagy induction and cell apoptosis. Particularly, upregulated expression of IRF1 was found in SARS-CoV-2, panH1N1, and H7N9 infection. Further analysis showed SARS-CoV-2, panH1N1, and H7N9 infection-induced upregulation of lncRNA-34087.27 could serve as a competitive endogenous RNA to stabilize IRF1 mRNA by competitively binding with miR-302b-3p. This study provides new insights into the molecular mechanisms of influenza A virus and SARS-CoV-2 infection.


Subject(s)
COVID-19/immunology , Immunity/immunology , Influenza A Virus, H1N1 Subtype/immunology , Influenza A Virus, H7N9 Subtype/immunology , Influenza, Human/immunology , RNA/immunology , Transcriptome/immunology , A549 Cells , Animals , COVID-19/genetics , COVID-19/virology , HEK293 Cells , Host-Pathogen Interactions/immunology , Humans , Immunity/genetics , Influenza A Virus, H1N1 Subtype/physiology , Influenza A Virus, H7N9 Subtype/physiology , Influenza, Human/genetics , Influenza, Human/virology , Interferon Regulatory Factor-1/genetics , Interferon Regulatory Factor-1/immunology , Interferon Regulatory Factor-1/metabolism , MicroRNAs/genetics , MicroRNAs/immunology , MicroRNAs/metabolism , Pandemics/prevention & control , RNA/genetics , RNA/metabolism , RNA, Long Noncoding/genetics , RNA, Long Noncoding/immunology , RNA, Long Noncoding/metabolism , RNA, Messenger/genetics , RNA, Messenger/immunology , RNA, Messenger/metabolism , RNA-Seq/methods , SARS-CoV-2/physiology , Signal Transduction/genetics , Signal Transduction/immunology , Transcriptome/genetics
17.
Mech Ageing Dev ; 202: 111636, 2022 03.
Article in English | MEDLINE | ID: covidwho-1665255

ABSTRACT

The stratification of mortality risk in COVID-19 patients remains extremely challenging for physicians, especially in older patients. Innovative minimally invasive molecular biomarkers are needed to improve the prediction of mortality risk and better customize patient management. In this study, aimed at identifying circulating miRNAs associated with the risk of COVID-19 in-hospital mortality, we analyzed serum samples of 12 COVID-19 patients by small RNA-seq and validated the findings in an independent cohort of 116 COVID-19 patients by qRT-PCR. Thirty-four significantly deregulated miRNAs, 25 downregulated and 9 upregulated in deceased COVID-19 patients compared to survivors, were identified in the discovery cohort. Based on the highest fold-changes and on the highest expression levels, 5 of these 34 miRNAs were selected for the analysis in the validation cohort. MiR-320b and miR-483-5p were confirmed to be significantly hyper-expressed in deceased patients compared to survived ones. Kaplan-Meier and Cox regression models, adjusted for relevant confounders, confirmed that patients with the 20% highest miR-320b and miR-483-5p serum levels had three-fold increased risk to die during in-hospital stay for COVID-19. In conclusion, high levels of circulating miR-320b and miR-483-5p can be useful as minimally invasive biomarkers to stratify older COVID-19 patients with an increased risk of in-hospital mortality.


Subject(s)
COVID-19/blood , COVID-19/mortality , Circulating MicroRNA/blood , Hospital Mortality , Hospitalization , MicroRNAs/blood , Aged , Aged, 80 and over , Biomarkers/blood , COVID-19/diagnosis , COVID-19/genetics , Circulating MicroRNA/genetics , Female , Humans , Male , MicroRNAs/genetics , Predictive Value of Tests , Prognosis , RNA-Seq , Risk Assessment , Risk Factors , Time Factors , Up-Regulation
18.
Sci Rep ; 12(1): 1329, 2022 01 25.
Article in English | MEDLINE | ID: covidwho-1655620

ABSTRACT

The SARS-CoV-2 pandemic has challenged humankind's ability to quickly determine the cascade of health effects caused by a novel infection. Even with the unprecedented speed at which vaccines were developed and introduced into society, identifying therapeutic interventions and drug targets for patients infected with the virus remains important as new strains of the virus evolve, or future coronaviruses may emerge that are resistant to current vaccines. The application of transcriptomic RNA sequencing of infected samples may shed new light on the pathways involved in viral mechanisms and host responses. We describe the application of the previously developed "dual RNA-seq" approach to investigate, for the first time, the co-regulation between the human and SARS-CoV-2 transcriptomes. Together with differential expression analysis, we describe the tissue specificity of SARS-CoV-2 expression, an inferred lipopolysaccharide response, and co-regulation of CXCL's, SPRR's, S100's with SARS-CoV-2 expression. Lipopolysaccharide response pathways in particular offer promise for future therapeutic research and the prospect of subgrouping patients based on chemokine expression that may help explain the vastly different reactions patients have to infection. Taken together these findings highlight unappreciated SARS-CoV-2 expression signatures and emphasize new considerations and mechanisms for SARS-CoV-2 therapeutic intervention.


Subject(s)
COVID-19 , Gene Expression Regulation, Viral , RNA-Seq , SARS-CoV-2 , Transcriptome , A549 Cells , COVID-19/genetics , COVID-19/metabolism , Humans , SARS-CoV-2/genetics , SARS-CoV-2/metabolism
19.
Cell Rep Med ; 3(2): 100522, 2022 02 15.
Article in English | MEDLINE | ID: covidwho-1650891

ABSTRACT

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.


Subject(s)
COVID-19/genetics , COVID-19/pathology , Lung/pathology , SARS-CoV-2 , Transcriptome/genetics , Adult , Aged , Aged, 80 and over , COVID-19/metabolism , COVID-19/virology , Case-Control Studies , Cohort Studies , Female , Gene Expression Regulation , Humans , Influenza, Human/genetics , Influenza, Human/pathology , Influenza, Human/virology , Lung/metabolism , Male , Middle Aged , Orthomyxoviridae , RNA-Seq/methods , Respiratory Distress Syndrome/genetics , Respiratory Distress Syndrome/microbiology , Respiratory Distress Syndrome/pathology , Viral Load
20.
Nat Commun ; 13(1): 460, 2022 01 24.
Article in English | MEDLINE | ID: covidwho-1651070

ABSTRACT

The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.


Subject(s)
COVID-19/transmission , Contact Tracing/methods , Disease Outbreaks/prevention & control , SARS-CoV-2/isolation & purification , Animals , COVID-19/epidemiology , COVID-19/virology , Chlorocebus aethiops , Humans , RNA-Seq/methods , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2/genetics , SARS-CoV-2/physiology , Time Factors , Vero Cells , Viral Load/genetics , Viral Load/physiology , Virus Replication/genetics , Virus Replication/physiology , Virus Shedding/genetics , Virus Shedding/physiology
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