Systems Biology Modeling to Study Pathogen–Host Interactions

Cesur, Müberra Fatma; Durmuş, Saliha

doi:10.1007/978-1-4939-7604-1_10

Cited by 11 publications

(7 citation statements)

References 62 publications

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“…Interestingly, the major enriched GO terms for the differentially expressed genes in non-infected baseline samples were denoted by the cytokine-mediated signaling pathway and type 1 interferon signaling pathway. Among these, AIM2 inflammasome (associated with induction of pyroptosis, activation of pro-inflammatory cytokines, and viral suppression) ( 51 , 52 ) IFI27 (also known as ISG12a ) contributes to IFN-dependent perturbation of normal mitochondrial function and enhanced cellular apoptosis ( 53 ), and the IFN-dependent antiviral factor BST2 were all significantly downregulated in CF AECs. In response to RV infection, several common responses were found, including interferon signaling.…”

Section: Discussionmentioning

confidence: 99%

Rhinovirus Infection Drives Complex Host Airway Molecular Responses in Children With Cystic Fibrosis

et al. 2020

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Early-life viral infections are responsible for pulmonary exacerbations that can contribute to disease progression in young children with cystic fibrosis (CF). The most common respiratory viruses detected in the CF airway are human rhinoviruses (RV), and augmented airway inflammation in CF has been attributed to dysregulated airway epithelial responses although evidence has been conflicting. Here, we exposed airway epithelial cells from children with and without CF to RV in vitro. Using RNA-Seq, we profiled the transcriptomic differences of CF and non-CF airway epithelial cells at baseline and in response to RV. There were only modest differences between CF and non-CF cells at baseline. In response to RV, there were 1,442 and 896 differentially expressed genes in CF and non-CF airway epithelial cells, respectively. The core antiviral responses in CF and non-CF airway epithelial cells were mediated through interferon signaling although type 1 and 3 interferon signaling, when measured, were reduced in CF airway epithelial cells following viral challenge consistent with previous reports. The transcriptional responses in CF airway epithelial cells were more complex than in non-CF airway epithelial cells with diverse over-represented biological pathways, such as cytokine signaling and metabolic and biosynthetic pathways. Network analysis highlighted that the differentially expressed genes of CF airway epithelial cells' transcriptional responses were highly interconnected and formed a more complex network than observed in non-CF airway epithelial cells. We corroborate observations in fully differentiated air-liquid interface (ALI) cultures, identifying genes involved in IL-1 signaling and mucin glycosylation that are only dysregulated in the Ling et al. Rhinovirus Infection Drives Network Responses CF airway epithelial response to RV infection. These data provide novel insights into the CF airway epithelial cells' responses to RV infection and highlight potential pathways that could be targeted to improve antiviral and anti-inflammatory responses in CF.

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Section: Discussionmentioning

confidence: 99%

Rhinovirus Infection Drives Complex Host Airway Molecular Responses in Children With Cystic Fibrosis

et al. 2020

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“…From them, HERV-W was excluded due to lack of PPI data. Virus–host PPI data for the 10 selected viruses were collected from PHISTO database, which is one of the most comprehensive databases for pathogen–human host PPI data and contains only experimentally detected interactions that are imported from several PPI databases [ 75 , 135 ]. For the selected viruses, a unified virus–host PPI network was constructed and visualized in Cytoscape [ 85 ].…”

Section: Methodsmentioning

confidence: 99%

Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches

Onisiforou

Spyrou

2021

Briefings in Bioinformatics

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During the course of a viral infection, virus–host protein–protein interactions (PPIs) play a critical role in allowing viruses to replicate and survive within the host. These interspecies molecular interactions can lead to viral-mediated perturbations of the human interactome causing the generation of various complex diseases. Evidences suggest that viral-mediated perturbations are a possible pathogenic etiology in several neurodegenerative diseases (NDs). These diseases are characterized by chronic progressive degeneration of neurons, and current therapeutic approaches provide only mild symptomatic relief; therefore, there is unmet need for the discovery of novel therapeutic interventions. In this paper, we initially review databases and tools that can be utilized to investigate viral-mediated perturbations in complex NDs using network-based analysis by examining the interaction between the ND-related PPI disease networks and the virus–host PPI network. Afterwards, we present our theoretical-driven integrative network-based bioinformatics approach that accounts for pathogen–genes–disease-related PPIs with the aim to identify viral-mediated pathogenic mechanisms focusing in multiple sclerosis (MS) disease. We identified seven high centrality nodes that can act as disease communicator nodes and exert systemic effects in the MS-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways network. In addition, we identified 12 KEGG pathways, 5 Reactome pathways and 52 Gene Ontology Immune System Processes by which 80 viral proteins from eight viral species might exert viral-mediated pathogenic mechanisms in MS. Finally, our analysis highlighted the Th17 differentiation pathway, a disease communicator node and part of the 12 underlined KEGG pathways, as a key viral-mediated pathogenic mechanism and a possible therapeutic target for MS disease.

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“…Some of the approaches used in systems biology include identification of key molecules or biomarkers, inference between networks and disease module discovery [84]. The advancement of -omics technologies supported by high throughput sequencing has increased the whole-system analyses focusing on host-pathogen interaction between genes, proteins and small ligands [85]. This is accomplished by carrying out dual RNA sequencing whereby both host and pathogen transcriptomes are profiled during the course of an infection.…”

Section: Application Of Systems Biology In Understanding Host-pathogen Interactionsmentioning

confidence: 99%

Assessing Host-Pathogen Interaction Networks via RNA-Seq Profiling: A Systems Biology Approach

Sareshma¹,

Bhassu²

2021

Applications of RNA-Seq in Biology and Medicine

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RNA sequencing is a valuable tool brought about by advances in next generation sequencing (NGS) technology. Initially used for transcriptome mapping, it has grown to become one of the ‘gold standards’ for studying molecular changes that occur in niche environments or within and across infections. It employs high-throughput sequencing with many advantages over previous methods. In this chapter, we review the experimental approaches of RNA sequencing from isolating samples all the way to data analysis methods. We focus on a number of NGS platforms that offer RNA sequencing with each having their own strengths and drawbacks. The focus will also be on how RNA sequencing has led to developments in the field of host-pathogen interactions using the dual RNA sequencing technique. Besides dual RNA sequencing, this review also explores the application of other RNA sequencing techniques such as single cell RNA sequencing as well as the potential use of newer techniques like ‘spatialomics’ and ribosome-profiling in host-pathogen interaction studies. Finally, we examine the common challenges faced when using RNA sequencing and possible ways to overcome these challenges.

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Systems Biology Modeling to Study Pathogen–Host Interactions

Cited by 11 publications

References 62 publications

Rhinovirus Infection Drives Complex Host Airway Molecular Responses in Children With Cystic Fibrosis

Rhinovirus Infection Drives Complex Host Airway Molecular Responses in Children With Cystic Fibrosis

Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches

Assessing Host-Pathogen Interaction Networks via RNA-Seq Profiling: A Systems Biology Approach

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