Systems Biology Approaches For Host Pathogen Interaction Analysis

System Biology Approaches for Microbial Pathogenesis Interaction Analysis aids biological researchers to expand their research scope using piled up data generated through recent technological advancement. In addition, it also opens avenues for bioinformatics and computer science researchers to utilize their expertise in biological meaningful ways. It also covers network biology approaches to decipher complex multiple host-pathogen interactions in addition to giving valuable coverage of artificial intelligence. The host-pathogen interactions are generally considered as highly specific interactions leading to a variety of consequences. The utilization of data science approaches has revolutionized scientific research including host-pathogen interaction analyses. Data science approaches coupled with network biology has taken host-pathogen interaction analysis from specific interaction to a new paradigm of understanding consequences of these interaction in the biological network. Unfortunately, basic biological researchers are mostly unaware of these advancements. In contrast, data scientists are not familiar with biological aspects of such data. System Biology Approaches for Microbial Pathogenesis Interaction Analysis will bridge these gaps through a new paradigm of understanding consequences of interaction in biological networks. Covers network biology approaches to decipher complex multiple host-pathogen interactions Gives the biological researcher insights into artificial intelligence, providing an additional competitive edge Provides a new paradigm for understanding the consequences of interactions in biological networks

A thorough understanding of pathogenic microorganisms and their interactions with host organisms is crucial to prevent infectious threats due to the fact that Pathogen-Host Interactions (PHIs) have critical roles in initiating and sustaining infections. Therefore, the analysis of infection mechanisms through PHIs is indispensable to identify diagnostic biomarkers and next-generation drug targets and then to develop strategic novel solutions against drug-resistance and for personalized therapy. Traditional approaches are limited in capturing mechanisms of infection since they investigate hosts or pathogens individually. On the other hand, the systems biology approach focuses on the whole PHI system, and is more promising in capturing infection mechanisms. Here, we bring together studies on the below listed sections to present the current picture of the research on Computational Systems Biology of Pathogen-Host Interactions: - Computational Inference of PHI Networks using Omics Data - Computational Prediction of PHIs - Text Mining of PHI Data from the Literature - Mathematical Modeling and Bioinformatic Analysis of PHIs Computational Inference of PHI Networks using Omics Data Gene regulatory, metabolic and protein-protein networks of PHI systems are crucial for a thorough understanding of infection mechanisms. Great advances in molecular biology and biotechnology have allowed the production of related omics data experimentally. Many computational methods are emerging to infer molecular interaction networks of PHI systems from the corresponding omics data. Computational Prediction of PHIs Due to the lack of experimentally-found PHI data, many computational methods have been developed for the prediction of pathogen-host protein-protein interactions. Despite being emerging, currently available experimental PHI data are far from complete for a systems view of infection mechanisms through PHIs. Therefore, computational methods are the main tools to predict new PHIs. To this end, the development of new computational methods is of great interest. Text Mining of PHI Data from Literature Despite the recent development of many PHI-specific databases, most data relevant to PHIs are still buried in the biomedical literature, which demands for the use of text mining techniques to unravel PHIs hidden in the literature. Only some rare efforts have been performed to achieve this aim. Therefore, the development of novel text mining methods specific for PHI data retrieval is of key importance for efficient use of the available literature. Mathematical Modeling and Bioinformatic Analysis of PHIs After the reconstruction of PHI networks experimentally and/or computationally, their mathematical modeling and detailed computational analysis is required using bioinformatics tools to get insights on infection mechanisms. Bioinformatics methods are increasingly applied to analyze the increasing amount of experimentally-found and computationally-predicted PHI data.

A thorough understanding of pathogenic microorganisms and their interactions with host organisms is crucial to prevent infectious threats due to the fact that Pathogen-Host Interactions (PHIs) have critical roles in initiating and sustaining infections. Therefore, the analysis of infection mechanisms through PHIs is indispensable to identify diagnostic biomarkers and next-generation drug targets and then to develop strategic novel solutions against drug-resistance and for personalized therapy. Traditional approaches are limited in capturing mechanisms of infection since they investigate hosts or pathogens individually. On the other hand, the systems biology approach focuses on the whole PHI system, and is more promising in capturing infection mechanisms. Here, we bring together studies on the below listed sections to present the current picture of the research on Computational Systems Biology of Pathogen-Host Interactions: - Computational Inference of PHI Networks using Omics Data - Computational Prediction of PHIs - Text Mining of PHI Data from the Literature - Mathematical Modeling and Bioinformatic Analysis of PHIs Computational Inference of PHI Networks using Omics Data Gene regulatory, metabolic and protein-protein networks of PHI systems are crucial for a thorough understanding of infection mechanisms. Great advances in molecular biology and biotechnology have allowed the production of related omics data experimentally. Many computational methods are emerging to infer molecular interaction networks of PHI systems from the corresponding omics data. Computational Prediction of PHIs Due to the lack of experimentally-found PHI data, many computational methods have been developed for the prediction of pathogen-host protein-protein interactions. Despite being emerging, currently available experimental PHI data are far from complete for a systems view of infection mechanisms through PHIs. Therefore, computational methods are the main tools to predict new PHIs. To this end, the development of new computational methods is of great interest. Text Mining of PHI Data from Literature Despite the recent development of many PHI-specific databases, most data relevant to PHIs are still buried in the biomedical literature, which demands for the use of text mining techniques to unravel PHIs hidden in the literature. Only some rare efforts have been performed to achieve this aim. Therefore, the development of novel text mining methods specific for PHI data retrieval is of key importance for efficient use of the available literature. Mathematical Modeling and Bioinformatic Analysis of PHIs After the reconstruction of PHI networks experimentally and/or computationally, their mathematical modeling and detailed computational analysis is required using bioinformatics tools to get insights on infection mechanisms. Bioinformatics methods are increasingly applied to analyze the increasing amount of experimentally-found and computationally-predicted PHI data. Acknowledgements: We, editors of this e-book, acknowledge Emrah Nikerel (Yeditepe University, Turkey) and Arzucan Özgür (Bogaaziçi University, Turkey) for their contributions during the initiation of the Research Topic.

The book starts with a general introduction into the relevance of systems biology for understanding tuberculosis. This will be followed by several chapters which describe the application of systems biology to various aspects of the study of the pathogen, Mycobacterium tuberculosis, and its interaction with the host. The book provides the reader with an account of how the new science of systems biology is providing novel insights into the ancient scourge of tuberculosis. It will also describe how systems biology can be applied to the control of tuberculosis, including the development of new treatments, vaccines and diagnostics.

This detailed volume explores numerous multidisciplinary approaches employed to analyze the role of different molecules or strategies used by different guests to survive inside hosts. Divided into several sections, the book delves into animal-pathogen interaction, microbe-microbe interaction, as well as plant-pathogen interaction. Written for the highly successful Methods in Molecular Biology series, chapters include brief introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.uthoritative and practical, Host-Pathogen Interactions: Methods and Protocols provides many molecular and bioinformatics techniques currently in use at reputed laboratories in countries all around the world, vital for many kinds of host-pathogen interactions studies.

The systems biology of microbial infections aims at describing and analysing the confrontation of the host with bacterial and fungal pathogens. It intends to understand and to model the interaction of the host, in particular the immune system of humans or animals, with components of pathogens. This comprises experimental studies that provide spatio-temporal data from monitoring the response of host and pathogenic cells to perturbations or when interacting with each other, as well as the integrative analysis of genome-wide data from both the host and the pathogen. In perspective, the host-pathogen interaction should be described by a combination of spatio-temporal models with interacting molecular networks of the host and the pathogen. The aim is to unravel the main mechanisms of pathogenicity, to identify diagnostic biomarkers and potential drug targets, and to explore novel strategies for personalized therapy by computer simulations. Some microorganisms are part of the normal microbial flora, existing either in a mutualistic or commensal relationship with the host. Microorganisms become pathogenic if they posses certain physiological characteristics and virulence determinants as well as capabilities for immune evasion. Despite the different pathogenesis of infections, there are several common traits: (1) Before infection, pathogens must be able to overcome (epithelial) barriers. The infection starts by adhesion and colonization and is followed by entering of the pathogen into the host through the mucosa or (injured) skin. (2) Next, infection arises if the pathogen multiplies and overgrows the normal microbial flora, either at the place of entrance or in deeper tissue layers or organs. (3) After the growth phase, the pathogen damages the host’s cells, tissues and organs by producing toxins or destructive enzymes. Thus, systems biology of microbial infection comprises all levels of the pathogen and the host’s immune system. The investigation may start with the pathogen, its adhesion and colonization at the host, its interaction with host cell types e.g. epithelia cells, dendritic cells, macrophages, neutrophils, natural killer cells, etc. Because infection diseases are mainly found in patients with a weakened immune system, e.g. reduced activities of immune effector cells or defects in the epithelial barriers, systems biology of infection can also start with modelling of the immune defence including innate and adaptive immunity. Systems biological studies comprise both experimental and theoretical approaches. The experimental studies may be dedicated to reveal the relevance of certain genes or proteins in the above mentioned processes on the side of the pathogen and/or the host by applying functional and biochemical analyses based on knock-out mutants and knock- down experiments. At the theoretical, i.e. mathematical and computational, side systems biology of microbial infection comprises: (1) modelling of molecular mechanisms of bacterial or fungal infections, (2) modelling of non-protective and protective immune defences against microbial pathogens to generate information for possible immune therapy approaches, (3) modelling of infection dynamics and identification of biomarkers for diagnosis and for individualized therapy, (4) identifying essential virulence determinants and thereby predicting potential drug targets.

Most studies of bacterial or fungal infectious diseases focus separately on the pathogenic microbe, the host response, or the characterization of therapeutic compounds. Compartmentalization of pathogenesis-related research into an analysis of the “pathogen”, the “host,” or the “antimicrobial compound” has largely been dictated by the lack of model systems in which all of these approaches can be used simultaneously, as well as by the traditional view that microbiology, immunology, and chemical biology and pharmacology are separate disciplines. An increasing number of workers from different fields have turned to insects, fish, worms and other model hosts as facile, ethically expedient, relatively simple, and inexpensive hosts to model a variety of human infectious diseases and to study host responses and innate immunity. Because many of these hosts are genetically tractable, they can be used in conjunction with an appropriate pathogen to facilitate the discovery of novel features of the host innate immune response. This book provides a series of reports from the 1st International Conference on Model Hosts. This first of its kind meeting focused on invertebrate, vertebrate and amoeboid systems used for the study of host-pathogen interactions, virulence and immunity, as well as on the relevance of these pathogenesis systems and mammalian models. Importantly, a common, fundamental set of molecular mechanisms is employed by a significant number of microbial pathogens against a widely divergent array of metazoan hosts. Moreover, the evolutionarily conserved immune responses of these model hosts have contributed important insights to our understanding of the innate immune response of mammals. This book provides a series of reports from the 1st International Conference on Model Hosts. This first of its kind meeting focused on invertebrate, vertebrate and amoeboid systems used for the study of host-pathogen interactions, virulence and immunity, as well as on the relevance of these pathogenesis systems and mammalian models. Importantly, a common, fundamental set of molecular mechanisms is employed by a significant number of microbial pathogens against a widely divergent array of metazoan hosts. Moreover, the evolutionarily conserved immune responses of these model hosts have contributed important insights to our understanding of the innate immune response of mammals.