NEAT1 and MALAT1 are highly expressed in saliva and nasopharyngeal swab samples of COVID‐19 patients

Rodrigues, Ana Carolina; Adamóski, Douglas; Genelhould, Gustavo; Zhen, Felipe; Yamaguto, Guilherme Eiji; Araújo-Souza, Patrícia Savio de; Nogueira, Meri Bordignon; Raboni, Sônia Mara; Bonatto, Ana Cláudia; Gradia, Daniela Fiori; Oliveira, Jaqueline Carvalho de

doi:10.1111/omi.12351

Cited by 29 publications

(24 citation statements)

References 17 publications

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“…Among 66 deregulated lncRNA observed in the present study, expression of 17 lncRNA in the same direction has been reported by others; expression of 39 lncRNA has not yet been published and expression 10 lncRNA has been shown to alter in opposite direction (Table S9). Very recently it has been shown that that NEAT1 and MALAT1 are highly expressed in saliva and nasopharyngeal swab samples of COVID-19 patients [118] confirming the result in the present study. Increased in our earlier study [34] HCG11, HIF1A-AS2, LINC00115, LINC00174, LINC00265, LINC00312, LINC00473, LINC00605, LINC00662, LINC00842, MALAT1, MEG3, MEG9, MIAT, NEAT1, RMRP, hTR/TERC, ZNF674-AS1 (20) Decreased in the present study ARIH2OS, C1orf220, DANCR, DGCR5, DHRS4-AS1, DLEU1, DLGAP1-AS1, FAM201A, FLJ20021, FOXN3-AS1, GAS6-AS1, H19, KANSL1-AS1, LINC00526, LINC00707, LINC00880, LINC00893, MIR1915HG, NBR2, NCBP2AS2, PXN-AS1, RASSF8-AS1, SLC22A18AS, SLC25A21-AS1, SNHG32, SNHG5, SNHG9, ST7-AS1, TMEM161B-AS1, TMEM99, TMPO-AS1, TP53TG1, and WAC-AS1 (33) Decreased in our earlier study [34] LINC00488, LINC00857, PART1, and TP53TG1 (4)…”

Section: For Comparison Of Different Set Of Genes/proteinssupporting

confidence: 93%

Co-Regulation of Protein Coding Genes by Transcription Factor and Long Non-Coding RNA in SARS-CoV-2 Infected Cells: An In Silico Analysis

Saha

Laha

Chatterjee

et al. 2021

ncRNA

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Altered expression of protein coding gene (PCG) and long non-coding RNA (lncRNA) have been identified in SARS-CoV-2 infected cells and tissues from COVID-19 patients. The functional role and mechanism (s) of transcriptional regulation of deregulated genes in COVID-19 remain largely unknown. In the present communication, reanalyzing publicly available gene expression data, we observed that 66 lncRNA and 5491 PCG were deregulated in more than one experimental condition. Combining our earlier published results and using different publicly available resources, it was observed that 72 deregulated lncRNA interacted with 3228 genes/proteins. Many targets of deregulated lncRNA could also interact with SARS-CoV-2 coded proteins, modulated by IFN treatment and identified in CRISPR screening to modulate SARS-CoV-2 infection. The majority of the deregulated lncRNA and PCG were targets of at least one of the transcription factors (TFs), interferon responsive factors (IRFs), signal transducer, and activator of transcription (STATs), NFκB, MYC, and RELA/p65. Deregulated 1069 PCG was joint targets of lncRNA and TF. These joint targets are significantly enriched with pathways relevant for SARS-CoV-2 infection indicating that joint regulation of PCG could be one of the mechanisms for deregulation. Over all this manuscript showed possible involvement of lncRNA and mechanisms of deregulation of PCG in the pathogenesis of COVID-19.

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Section: For Comparison Of Different Set Of Genes/proteinssupporting

confidence: 93%

Co-Regulation of Protein Coding Genes by Transcription Factor and Long Non-Coding RNA in SARS-CoV-2 Infected Cells: An In Silico Analysis

Saha

Laha

Chatterjee

et al. 2021

ncRNA

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“…The higher expression level of lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1/NEAT2) has been considered to have a critical role in inflammation and cytokine production. Similar results were also observed in saliva and nasopharyngeal swabs of COVID-19 patients [ 74 ], however, details of the mechanisms of MALAT1 upregulation and the cytokine production mediated by MALAT1 in COVID-19 have not been well illustrated. Herein, we identified TF XBP1 as one of the upstream nodes of lncRNA MALAT1.…”

Section: Resultssupporting

confidence: 75%

Repurposing Multiple-Molecule Drugs for COVID-19-Associated Acute Respiratory Distress Syndrome and Non-Viral Acute Respiratory Distress Syndrome via a Systems Biology Approach and a DNN-DTI Model Based on Five Drug Design Specifications

Ting

Chen

2022

IJMS

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The coronavirus disease 2019 (COVID-19) epidemic is currently raging around the world at a rapid speed. Among COVID-19 patients, SARS-CoV-2-associated acute respiratory distress syndrome (ARDS) is the main contribution to the high ratio of morbidity and mortality. However, clinical manifestations between SARS-CoV-2-associated ARDS and non-SARS-CoV-2-associated ARDS are quite common, and their therapeutic treatments are limited because the intricated pathophysiology having been not fully understood. In this study, to investigate the pathogenic mechanism of SARS-CoV-2-associated ARDS and non-SARS-CoV-2-associated ARDS, first, we constructed a candidate host-pathogen interspecies genome-wide genetic and epigenetic network (HPI-GWGEN) via database mining. With the help of host-pathogen RNA sequencing (RNA-Seq) data, real HPI-GWGEN of COVID-19-associated ARDS and non-viral ARDS were obtained by system modeling, system identification, and Akaike information criterion (AIC) model order selection method to delete the false positives in candidate HPI-GWGEN. For the convenience of mitigation, the principal network projection (PNP) approach is utilized to extract core HPI-GWGEN, and then the corresponding core signaling pathways of COVID-19-associated ARDS and non-viral ARDS are annotated via their core HPI-GWGEN by KEGG pathways. In order to design multiple-molecule drugs of COVID-19-associated ARDS and non-viral ARDS, we identified essential biomarkers as drug targets of pathogenesis by comparing the core signal pathways between COVID-19-associated ARDS and non-viral ARDS. The deep neural network of the drug–target interaction (DNN-DTI) model could be trained by drug–target interaction databases in advance to predict candidate drugs for the identified biomarkers. We further narrowed down these predicted drug candidates to repurpose potential multiple-molecule drugs by the filters of drug design specifications, including regulation ability, sensitivity, excretion, toxicity, and drug-likeness. Taken together, we not only enlighten the etiologic mechanisms under COVID-19-associated ARDS and non-viral ARDS but also provide novel therapeutic options for COVID-19-associated ARDS and non-viral ARDS.

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“…Furthermore, the datasets we analyzed were generated from patient samples collected between January and April 2020, before the first SARS-CoV-2 variants were designated by the World Health Organization. While the overall trends in our data are reflected in recent work on lncRNAs in COVID-19, there remains a lack of variant specific studies [ 85 ]. Additional work on the expression of lncRNAs in variant specific samples may uncover further insights.…”

Section: Discussionmentioning

confidence: 99%

Long non-coding RNAs (lncRNAs) NEAT1 and MALAT1 are differentially expressed in severe COVID-19 patients: An integrated single-cell analysis

et al. 2022

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Hyperactive and damaging inflammation is a hallmark of severe rather than mild Coronavirus disease 2019 (COVID-19). To uncover key inflammatory differentiators between severe and mild COVID-19, we applied an unbiased single-cell transcriptomic analysis. We integrated two single-cell RNA-seq datasets with COVID-19 patient samples, one that sequenced bronchoalveolar lavage (BAL) cells and one that sequenced peripheral blood mononuclear cells (PBMCs). The combined cell population was then analyzed with a focus on genes associated with disease severity. The immunomodulatory long non-coding RNAs (lncRNAs) NEAT1 and MALAT1 were highly differentially expressed between mild and severe patients in multiple cell types. Within those same cell types, the concurrent detection of other severity-associated genes involved in cellular stress response and apoptosis regulation suggests that the pro-inflammatory functions of these lncRNAs may foster cell stress and damage. Thus, NEAT1 and MALAT1 are potential components of immune dysregulation in COVID-19 that may provide targets for severity related diagnostic measures or therapy.

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NEAT1 and MALAT1 are highly expressed in saliva and nasopharyngeal swab samples of COVID‐19 patients

Cited by 29 publications

References 17 publications

Co-Regulation of Protein Coding Genes by Transcription Factor and Long Non-Coding RNA in SARS-CoV-2 Infected Cells: An In Silico Analysis

Co-Regulation of Protein Coding Genes by Transcription Factor and Long Non-Coding RNA in SARS-CoV-2 Infected Cells: An In Silico Analysis

Repurposing Multiple-Molecule Drugs for COVID-19-Associated Acute Respiratory Distress Syndrome and Non-Viral Acute Respiratory Distress Syndrome via a Systems Biology Approach and a DNN-DTI Model Based on Five Drug Design Specifications

Long non-coding RNAs (lncRNAs) NEAT1 and MALAT1 are differentially expressed in severe COVID-19 patients: An integrated single-cell analysis

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