Probing infectious disease by single-cell RNA sequencing: Progresses and perspectives

Luo, Geyang; Gao, Qian; Zhang, Shuye; Yan, Bo

doi:10.1016/j.csbj.2020.10.016

Cited by 42 publications

(28 citation statements)

References 119 publications

(119 reference statements)

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“…Therefore, immune responses against HuNoV in the other tissues should be determined in future studies. In addition, single cell mRNA sequencing will provide more precise immune response information for each cell type in specific tissues infected with HuNoV [ 74 , 75 , 76 , 77 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of the Immune Responses in the Ileum of Gnotobiotic Pigs Infected with the Recombinant GII.p12_GII.3 Human Norovirus by mRNA Sequencing

Park

Ahn

Han

et al. 2021

Viruses

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Norovirus genogroup II (NoV GII) induces acute gastrointestinal food-borne illness in humans. Because gnotobiotic pigs can be infected with human norovirus (HuNoV) GII, they are frequently used to analyze the associated pathogenic mechanisms and immune responses, which remain poorly understood. Recently, mRNA sequencing analysis (RNA-Seq) has been used to identify cellular responses to viruses. In this study, we investigated the host immune response and possible mechanisms involved in virus evasion in the ileum of gnotobiotic pigs infected with HuNoV by RNA-Seq. HuNoV was detected in the feces, blood, and tissues of the jejunum, ileum, colon, mesenteric lymph node, and spleen of pigs infected with HuNoV. In analysis of mRNA sequencing, expression of anti-viral protein genes such as OAS1, MX1, and MX2 were largely decreased, whereas type I IFN was increased in pigs infected with HuNoV. In addition, expression of TNF and associated anti-inflammatory cytokine genes such as IL10 was increased in HuNoV-infected pigs. Expression of genes related to natural killer (NK) cell cytotoxicity and CD8+ T cell exhaustion was increased, whereas that of MHC class I genes was decreased. Expression profiles of selected genes were further confirmed by qRT-PCR and Western blot. These results suggest that infection with HuNoV induces NK cell-mediated cytotoxicity but suppresses type I IFN- and CD8+ T cell-mediated antiviral responses.

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Section: Discussionmentioning

confidence: 99%

Analysis of the Immune Responses in the Ileum of Gnotobiotic Pigs Infected with the Recombinant GII.p12_GII.3 Human Norovirus by mRNA Sequencing

Park

Ahn

Han

et al. 2021

Viruses

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“…Transcriptional heterogeneity, within and across the complex human specimens like blood, is a major obstacle in understanding inflammation and multicellular immune response [26]. Single-cell RNA sequencing (scRNA-Seq) is a new technology that provides significantly greater benefits to researchers than bulk RNA sequencing.…”

Section: Rna-seq Profiling Of Host-pathogen Interactionsmentioning

confidence: 99%

Introductory Chapter: Applications of RNA-Seq Diagnostics in Biology and Medicine

Louis¹

2021

Applications of RNA-Seq in Biology and Medicine

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“…The latter is crucial for two main reasons: (a) failure to deliver proper antibiotic therapy in bacterial meningitis can lead to severe, permanent sequelae and invasive disease (especially due to Neisseria meningitidis ) [ 4 ], and even death, and (b) unnecessary antibiotic or overtreatment of viral meningitis cases can lead to antimicrobial resistance, increased health care services cost, changes in human microbiome, and high levels of stress to the suffering patients [ 5 ]. Several differential diagnostic approaches have therefore been developed or proposed, ranging from simple procedures, such as measuring lactate and other parameters (for instance, albumino-cytological dissociation) [ 6 , 7 ], to sophisticated strategies, such as sequencing approaches, through metagenomics [ 8 ], host transcriptome analysis, or even single-cell RNA sequencing approaches [ 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in Differential Diagnostics of Meningitis: A Nationwide Study

et al. 2021

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Differential diagnosis between bacterial and viral meningitis is crucial. In our study, to differentiate bacterial vs. viral meningitis, three machine learning (ML) algorithms (multiple logistic regression (MLR), random forest (RF), and naïve-Bayes (NB)) were applied for the two age groups (0–14 and >14 years) of patients with meningitis by both conventional (culture) and molecular (PCR) methods. Cerebrospinal fluid (CSF) neutrophils, CSF lymphocytes, neutrophil-to-lymphocyte ratio (NLR), blood albumin, blood C-reactive protein (CRP), glucose, blood soluble urokinase-type plasminogen activator receptor (suPAR), and CSF lymphocytes-to-blood CRP ratio (LCR) were used as predictors for the ML algorithms. The performance of the ML algorithms was evaluated through a cross-validation procedure, and optimal predictions of the type of meningitis were above 95% for viral and 78% for bacterial meningitis. Overall, MLR and RF yielded the best performance when using CSF neutrophils, CSF lymphocytes, NLR, albumin, glucose, gender, and CRP. Also, our results reconfirm the high diagnostic accuracy of NLR in the differential diagnosis between bacterial and viral meningitis.

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Probing infectious disease by single-cell RNA sequencing: Progresses and perspectives

Cited by 42 publications

References 119 publications

Analysis of the Immune Responses in the Ileum of Gnotobiotic Pigs Infected with the Recombinant GII.p12_GII.3 Human Norovirus by mRNA Sequencing

Analysis of the Immune Responses in the Ileum of Gnotobiotic Pigs Infected with the Recombinant GII.p12_GII.3 Human Norovirus by mRNA Sequencing

Introductory Chapter: Applications of RNA-Seq Diagnostics in Biology and Medicine

Artificial Intelligence in Differential Diagnostics of Meningitis: A Nationwide Study

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