Intro
Contents
About the Editor
1: Gut Microbiome in Microbial Pathogenicity
1.1 Introduction
1.2 Gut Microbiota and Gut Immunology
1.3 How Gut Microbiota Helps in Pathogen Resistance
1.4 Direct Mechanism by Gut Microflora for Colonization Resistance
1.5 The Intestine Serves as Barrier
1.6 Role of Gut Microbiota in Virulence of Pathogen
1.7 Evolving Microbiota and Drug Interaction for Personalized Medicine
1.8 Effect of Gut Microbiota on Drug Efficacy, Metabolism and Toxicity

1.9 Few Studies of Drug Metabolism Influencing Their Activity and Toxicity by Microbes
1.10 How Microbes Manipulate the Response of Immunomodulatory Drugs?
1.11 Modifying Gut Microbiota for Précised Medicine
1.12 New Insights
References
2: Role of Genome-Wide Association Studies in Host Genetics: Toward Understanding of Microbiome Association
2.1 Introduction
2.2 Diversity of Microbiomes
2.3 The Human Microbiome: Functional Link with Health and Diseases
2.4 Mechanistic Connection of Human Health and Dysbiosis: mGWAS Studies
2.5 Genesis of Diseases with Dysbiosis

2.6 mGWAS: Approaches and Tools
2.7 Current Challenges Underpinning mGWAS
2.8 Concluding Remark and Prospects
References
3: Understanding Microbiome Science Through Big Data Analysis
3.1 Introduction
3.1.1 The Origin of the Term ``Microbiome ́́
3.1.2 The Study of the Microbiome
3.2 Microbiome Big Data
3.2.1 Shotgun Sequencing
3.2.2 Metatranscriptomics
3.3 Roche 454 Genome Sequencing
3.4 Illumina
3.5 Qiagen Gene Reader
3.6 Ion Torrent Sequencing Technology
3.7 SMRT Sequencing
3.8 Oxford Nanopore Sequencing

3.8.1 Getting Insights from the Microbiome Data
3.9 Status of Microbiome Data Science
3.10 Tools to Study Microbiome Big Data
3.10.1 QIIME 2
3.10.1.1 Input
3.10.1.2 Output
3.10.1.3 Workflow
3.10.1.4 Pros and Cons
3.10.2 Mothur
3.10.2.1 Input
3.10.2.2 Output
3.10.2.3 Workflow
3.10.2.4 Pros and Cons
3.10.3 Qiita
3.10.3.1 Input
3.10.3.2 Output
3.10.3.3 Pros and Cons
3.10.4 Megan
3.10.4.1 Input
3.10.4.2 Output
3.10.4.3 Pros and Cons
3.10.5 MicrobiomeAnalyst
3.10.5.1 Input
3.10.5.2 Output
3.10.5.3 Pros and Cons
3.10.6 iMAP

3.10.6.1 Input
3.10.6.2 Output
3.10.6.3 Pros and Cons
3.10.7 MIMIX
3.10.7.1 Input
3.10.7.2 Output
3.10.7.3 Pros and Cons
3.11 Conclusions
References
4: Comparative Genomics Facilitates Drug Target Selection and Develops Intervention Strategies Against Leishmania Infections
4.1 Introduction
4.2 Treatment Regimen of Leishmaniasis with Historical Perspective
4.3 Leishmania Genome Project and Sequencing of the Various Leishmania Species
4.3.1 Why Leishmania major Friedlin Was Selected as the Reference Strain?