Systems Biology Approaches for Host-Pathogen Interaction Analysis

List of contributors Foreword Preface Acknowledgments Chapter 1: Host-pathogen interactions: a general introduction Rabbani Syed, Fahad M. Aldakheel, Shatha A. Alduraywish, Ayesha Mateen, Hadeel Alnajran and Huda Hussain Al-Numan 1.1 Introduction 1.1.1 Role of pathogen 1.1.2 Host-pathogen relationship and mechanisms 1.1.3 Classification of host-pathogen interactions 1.2 Methods for prediction of host-pathogen interactions 1.2.1 Ortholog-based protein interaction detection 1.2.2 Domain-based detection of protein interaction 1.2.3 Biological reasoning-based prediction of host-pathogen interactions 1.2.4 Domain/motif interaction-based predictions 1.2.5 Machine learning-based predictions of host-pathogen interactions 1.3 Online repositories for host-pathogen interactions 1.3.1 Database of fungal virulence factors 1.3.2 E-fungi 1.3.3 Fungi DB 1.3.4 Ensembl genomes 1.3.5 EuPathDB 1.3.6 HPIDB 1.3.7 PLEXdb 1.3.8 VFDB 1.4 Conclusion Acknowledgment References Chapter 2: Host-pathogen interactions: databases and approaches for data generation Yasmin Bano and Abhinav Shrivastava 2.1 Introduction 2.2 Databases for host-pathogen interactions 2.3 Bioinformatic methods to discover HPI networking 2.3.1 Biological methods 2.3.2 Computational methods 2.4 Microscopic imaging techniques as stage of the art 2.5 RNA-Seq profiling: tool for determining the HPI network 2.5.1 Bacteria-host interactions 2.5.2 Virus-host interactions 2.5.3 Fungus-host interaction and other pathogenic interactions 2.5.4 Technical approach of RNA-seq and data analysis 2.6 Artificial intelligence-driven analysis for HPIs 2.7 Challenges and opportunities 2.7.1 Challenges 2.7.2 Opportunities 2.8 Conclusion References Chapter 3: Generation of host-pathogen interaction data: an overview of recent technological advancements Fatima Noor, Usman Ali Ashfaq, Hafiz Rameez Khalid and Mohsin Khurshid 3.1 Introduction 3.2 Introduction of bioinformatics in light of NGS 3.3 A short glimpse of the “integration of omics” 3.4 Why is multiomics study preferred over single omics? 3.5 Advancements in the generation of host-pathogen interaction data 3.5.1 Biological big data and omics 3.5.2 Multiomics approaches to unravel the host-pathogen interactions 3.6 Bioinformatics resources and web-based databases for host-pathogen interactions 3.7 Challenges in the generation of host-pathogen interaction data 3.8 Discussion and future prospects 3.9 Conclusion References Chapter 4: Molecular omics: a promising systems biology approach to unravel host-pathogen interactions Samman Munir, Usman Ali Ashfaq, Muhammad Qasim, Tazeem Fatima, Sehar Aslam, Muhammad Hassan Sarfraz, A.K.M. Humayun Kober and Mohsin Khurshid 4.1 Introduction 4.2 Genomics approaches 4.3 Transcriptomics 4.4 Proteomics of host-pathogen interactions 4.4.1 Secretomics of host-pathogen interactions 4.5 Metabolomics approaches 4.5.1 Lipidomics approaches 4.5.2 Multiomics integration for the analysis of host-microbe interactions 4.5.3 Integrated transcriptomicsgenomics approaches 4.5.4 Integrated epigenomics and transcriptomics approaches 4.5.5 Integrated proteomics—genomics, transcriptomics, and metabolomics 4.6 Future perspectives References Chapter 5: Computational methods for detection of host-pathogen interactions Samvedna Singh, Himanshi Gupta and Shakti Sahi 5.1 Introduction 5.2 Computational techniques for prediction of host-pathogen interactions 5.2.1 Protein-protein interaction methods 5.2.2 RNA-mediated interaction-based method 5.2.3 Computational approaches using integrated pipelines 5.3 Case studies 5.3.1 Case study based on host-parasite interaction 5.3.2 Case study based on host-virus interaction 5.3.3 Case study based on host-bacteria interactions 5.3.4 Case study based on host-fungus interactions 5.4 Discussion References Further reading Chapter 6: Biological interaction networks and their application for microbial pathogenesis Nirupma Singh and Sonika Bhatnagar 6.1 Introduction: biological networks 6.1.1 What is a network? 6.1.2 Types of networks 6.1.3 Biological networks 6.1.4 Properties of biological networks 6.1.5 Host-pathogen interaction networks 6.2 Tools for construction and analysis of biological networks 6.2.1 Cytoscape 6.2.2 R studio 6.2.3 Important plugins and functions 6.3 Functional annotation and biological characterization of host and microbial proteins 6.3.1 DAVID 6.3.2 KOBAS 3.0 server 6.3.3 Biocyc 6.4 Ontology and pathway analysis to understand microbial pathogenesis 6.4.1 KEGG pathways 6.4.2 Wiki pathways 6.4.3 NCBI biosystems 6.5 Case study: host-pathogen interaction networks for CVD pathways in microbial diseases 6.6 Conclusion References Chapter 7: Dual transcriptomics data and detection of host-pathogen interactions Vahap Eldem, Yusuf Ula¸s C¸inar, Selahattin Bari¸s C¸ ay, Selim Can Kuralay, O¨zgecan Kayalar, Go¨kmen Zararsiz, Yakup Bakir and Fatih Dikmen 7.1 Introduction 7.2 Unraveling host-pathogen interactions via genome-wide dual RNA-Seq 7.3 Best practices in dual RNA-Seq: from experimental design to a step-wise guide to performing bioinformatic analysis 7.4 Challenges of dual RNA-Seq experiments and data analysis 7.5 Dual RNA-Seq in the era of third-generation sequencing 7.6 Dissecting the role of noncoding RNA in host-pathogen interactions using dual transcriptomic data 7.7 Future perspectives Acknowledgments References Chapter 8: Functional overrepresentation analysis and their application in microbial pathogenesis Shilpa Kumari, Neha Verma, Anil Kumar, Sunita Dalal and Kanu Priya 8.1 Introduction 8.2 Analysis via different databases 8.2.1 GO enrichment analysis/GO functional overrepresentation analysis 8.2.2 Functional overrepresentation analysis using DOSE (Disease Ontology Semantic and Enrichment Analysis) 8.2.3 Functional overrepresentation analysis using MeSH 8.2.4 Functional overrepresentation analysis using Reactome pathway (ReactomePA) 8.3 Application of statistical databases in microbial pathogenesis References Chapter 9: Advancements in systems biology-based analysis of microbial pathogenesis Neha Verma, Shilpa Kumari, Anil Kumar and Kanu Priya 9.1 Introduction of microbial pathogenesis 9.1.1 Mechanism of microbial pathogenesis 9.2 Systems biology of microbial pathogenesis 9.2.1 Host-pathogen interaction 9.2.2 Pathogen’s molecular interaction network 9.2.3 Host’s reaction to a microbial infection 9.3 Systems biology techniques to study microbial pathogenesis 9.3.1 OMICS data contributing to microbial pathogenesis (including genomics, transcriptomics, metabolomics, and proteomics) 9.3.2 Computational biology of host-pathogen interaction in microbial pathogenesis 9.3.3 High-throughput techniques 9.4 Conclusion References Chapter 10: Host-pathogen interactions with special reference to microbiota analysis and integration of systems biology approaches Fahad M. Aldakheel, Dalia Mohsen and Barkha Singhal 10.1 Introduction 10.2 Methods for identifying the microbiota: a brief account 10.3 Factors to be considered before identifying microbiota 10.3.1 Geographical factors and diet 10.4 Role of next-generation sequencing technologies for microbial community analysis in understanding host-pathogen interactions 10.5 Microbial community analysis for understanding the antibiotic resistance phenomenon through 16S sequencing 10.6 Gut microbiota analysis in COVID-19 through 16S metagenomic sequencing 10.7 Challenges and advantages of using systems biology in microbiota analysis 10.8 Pathogen-host interactions in bioinformatics 10.9 Systems biology and omics data 10.10 PHI and systems biology 10.11 Conclusion Acknowledgment References Chapter 11: Role of noncoding RNAs in host-pathogen interactions: a systems biology approach Kartavya Mathur, Ananya Gupta, Varun Rawat, Vineet Sharma and Shailendra Shakya 11.1 Introduction 11.2 Exploring different forms of noncoding RNAs 11.2.1 microRNAs 11.2.2 Long noncoding RNAs 11.2.3 Piwi-like RNAs 11.2.4 Small interfering RNA 11.2.5 Small nuclear RNA 11.2.6 Small nucleolar RNA 11.2.7 Ribonucleic acid enzymes (or ribozymes) 11.2.8 Circular RNAs 11.2.9 Competing endogenous RNA 11.3 Comprehending the role of ncRNAs in pathogen-host interplay 11.3.1 Role of ncRNAs in bacterial pathogenesis 11.3.2 Function of noncoding RNAs in viral infection 11.3.3 Role of ncRNAs in fungal pathogenesis 11.3.4 Role of ncRNAs in protozoan pathogenesis 11.3.5 Role of ncRNAs in helminth pathogenesis 11.4 Why is it important to study the function of ncRNAs? 11.5 RNA systems biology 11.6 Computational resources for identifying ncRNAs in host pathogenesis 11.6.1 ncRNA expression profiling 11.6.2 Functional annotation and interpretation of ncRNA transcriptome 11.6.3 ncRNA web resources 11.6.4 Predicting ncRNA function 11.6.5 Methods for predicting and investigating microRNA targets 11.6.6 Estimating interaction events of ncRNAs 11.6.7 Predicting ncRNA structure 11.6.8 Graph-based approaches for ncRNA structure and function prediction 11.7 How to explore the significance of miRNAs in infection development? 11.7.1 Mathematical modeling for comprehending host-pathogen interaction 11.8 Why network analysis is important for studying ncRNAs? 11.8.1 Network analysis to study the regulation of host-pathogen interaction 11.8.2 Predicting ncRNA-disease association and tripartite network 11.8.3 Corelational network analysis for ncRNAs 11.8.4 Competing endogenous RNA network analysis References Chapter 12: Systems biology in food industry: applications in food production, engineering, and pathogen detection Ananya Srivastava and Anuradha Mishra 12.1 Introduction 12.2 Networks used in systems biology 12.2.1 Gene regulatory networks 12.2.2 Signal transduction networks 12.2.3 Protein-protein interaction networks 12.2.4 Metabolic networks 12.3 Systems biology benefits for food production 12.3.1 Applied systems biology in nutrition and health 12.3.2 Systems biology in food production and processing 12.3.3 Biofortification and development of nutraceuticals 12.3.4 Systems biology in food safety and quality 12.4 Systems biology in foodborne pathogen detection 12.4.1 Pathogen detection techniques used in food sectors 12.4.2 Limitations 12.5 Future scope 12.6 Conclusion References Author index Subject index