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The Individual Microbe: Single-Cell Analysis and Agent-Based Modelling

The Individual Microbe: Single-Cell Analysis and Agent-Based Modelling PDF Author: Johan H. J. Leveau
Publisher: Frontiers Media SA
ISBN: 2889457494
Category :
Languages : en
Pages : 187

Book Description
Recent technological advances in single-cell microbiology, using flow cytometry, microfluidics, x-ray fluorescence microprobes, and single-cell -omics, allow for the observation of individuals within populations. Simultaneously, individual-based models (or more generally agent-based models) allow for individual microbes to be simulated. Bridging these techniques forms the foundation of individual-based ecology of microbes (µIBE). µIBE has elucidated genetic and phenotypic heterogeneity that has important consequences for a number of human interests, including antibiotic or biocide resistance, the productivity and stability of industrial fermentations, the efficacy of food preservatives, and the potential of pathogens to cause disease. Individual-based models can help us to understand how these sets of traits of individual microbes influence the above. This eBook compiles all publications from a recent Research Topic in Frontiers in Microbiology. It features recent research where individual observational and/or modelling techniques are applied to gain unique insights into the ecology of microorganisms. The Research Topic “The Individual Microbe: Single-Cell Analysis and Agent-Based Modelling” arose from the 2016 @ASM conference of the same name hosted by the American Society for Microbiology at its headquarters in Washington, D.C. We are grateful to ASM for funding and hosting this conference.

The Individual Microbe: Single-Cell Analysis and Agent-Based Modelling

The Individual Microbe: Single-Cell Analysis and Agent-Based Modelling PDF Author: Johan H. J. Leveau
Publisher: Frontiers Media SA
ISBN: 2889457494
Category :
Languages : en
Pages : 187

Book Description
Recent technological advances in single-cell microbiology, using flow cytometry, microfluidics, x-ray fluorescence microprobes, and single-cell -omics, allow for the observation of individuals within populations. Simultaneously, individual-based models (or more generally agent-based models) allow for individual microbes to be simulated. Bridging these techniques forms the foundation of individual-based ecology of microbes (µIBE). µIBE has elucidated genetic and phenotypic heterogeneity that has important consequences for a number of human interests, including antibiotic or biocide resistance, the productivity and stability of industrial fermentations, the efficacy of food preservatives, and the potential of pathogens to cause disease. Individual-based models can help us to understand how these sets of traits of individual microbes influence the above. This eBook compiles all publications from a recent Research Topic in Frontiers in Microbiology. It features recent research where individual observational and/or modelling techniques are applied to gain unique insights into the ecology of microorganisms. The Research Topic “The Individual Microbe: Single-Cell Analysis and Agent-Based Modelling” arose from the 2016 @ASM conference of the same name hosted by the American Society for Microbiology at its headquarters in Washington, D.C. We are grateful to ASM for funding and hosting this conference.

Microbiomics

Microbiomics PDF Author:
Publisher: Academic Press
ISBN: 0128172827
Category : Medical
Languages : en
Pages : 394

Book Description
Microbiomics: Dimensions, Applications, and Translational Implications of Human and Environmental Microbiome Research describes a new, holistic approach to microbiomics. International experts provide in-depth discussion of current research methods for studying human, environmental, viral and fungal microbiomes, as well as the implications of new discoveries for human health, nutrition, disease, cancer research, probiotics and in the food and agricultural industries. Distinct chapters covering culturomics and sub-microbiomes, such as the viriome and mycetobiome, provide an integrative framework for the expansion of microbiomics into new areas of application, as well as crosspollination between research areas. Detailed case studies include the use of microbiomics to develop natural products with antimicrobial properties, microbiomic enhancements in food and beverage technology, microbes for bioprotection and biopreservation, microbial tools to reduce antibiotic resistance, and maintenance and cultivation of human microbial communities. - Provides an integrated approach for realizing the potential of microbiomics across the life, environmental, food and agricultural sciences - Includes thorough analysis of human, environmental, viral and mycetol microbiomes, as well as methods and technology for identifying microbiotes - Features chapter contributions from international leaders in microbiomic methods, technology and applications

Mathematical Modeling of Biofilms

Mathematical Modeling of Biofilms PDF Author: IWA Task Group on Biofilm Modeling
Publisher: IWA Publishing
ISBN: 1843390876
Category : Science
Languages : en
Pages : 194

Book Description
Over 90% of bacterial biomass exists in the form of biofilms. The ability of bacteria to attach to surfaces and to form biofilms often is an important competitive advantage for them over bacteria growing in suspension. Some biofilms are "good" in natural and engineered systems; they are responsible for nutrient cycling in nature and are used to purify waters in engineering processes. Other biofilms are "bad" when they cause fouling and infections of humans and plants. Whether we want to promote good biofilms or eliminate bad biofilms, we need to understand how they work and what works to control them. Mathematical Modeling of Biofilms provides guidelines for the selection and use of mathematical models of biofilms. The whole range of existing models - from simple analytical expressions to complex numerical models - is covered. The application of the models for the solution of typical problems is demonstrated, and the performance of the models is tested in comparative studies. With the dramatic evolution of the computational capacity still going on, modeling tools for research and practice will become more and more significant in the next few years. This report provides the foundation to understand the models and to select the most appropriate one for a given use. Mathematical Modeling of Biofilms gives a state-of-the-art overview that is especially valuable for educating students, new biofilm researchers, and design engineers. Through a series of three benchmark problems, the report demonstrates how to use the different models and indicates when simple or highly complex models are most appropriate. This is the first report to give a quantitative comparison of existing biofilm models. The report supports model-based design of biofilm reactors. The report can be used as basis for teaching biofilm-system modeling. The report provides the foundation for researchers seeking to use biofilm modeling or to develop new biofilm models. Scientific and Technical Report No.18

The Role of Dispersal and Transmission in Structuring Microbial Communities

The Role of Dispersal and Transmission in Structuring Microbial Communities PDF Author: Peter Deines
Publisher: Frontiers Media SA
ISBN: 2832506798
Category : Science
Languages : en
Pages : 152

Book Description


Microbial Biofilms

Microbial Biofilms PDF Author: Hilary M. Lappin-Scott
Publisher: Cambridge University Press
ISBN: 9780521542128
Category : Medical
Languages : en
Pages : 332

Book Description
Biochemistry and ecology of biofilms from industrial, medical and other viewpoints.

Modelling Microorganisms in Food

Modelling Microorganisms in Food PDF Author: Stanley Brul
Publisher: Elsevier
ISBN: 1845692942
Category : Technology & Engineering
Languages : en
Pages : 309

Book Description
Predicting the growth and behaviour of microorganisms in food has long been an aim in food microbiology research. In recent years, microbial models have evolved to become more exact and the discipline of quantitative microbial ecology has gained increasing importance for food safety management, particularly as minimal processing techniques have become more widely used. These processing methods operate closer to microbial death, survival and growth boundaries and therefore require even more precise models. Written by a team of leading experts in the field, Modelling microorganims in food assesses the latest developments and provides an outlook for the future of microbial modelling.Part one discusses general issues involved in building models of microbial growth and inactivation in foods, with chapters on the historical background of the field, experimental design, data processing and model fitting, the problem of uncertainty and variability in models and modelling lag-time. Further chapters review the use of quantitative microbiology tools in predictive microbiology and the use of predictive microbiology in risk assessment.The second part of the book focuses on new approaches in specific areas of microbial modelling, with chapters discussing the implications of microbial variability in predictive modelling and the importance of taking into account microbial interactions in foods. Predicting microbial inactivation under high pressure and the use of mechanistic models are also covered. The final chapters outline the possibility of incorporating systems biology approaches into food microbiology.Modelling microorganisms in food is a standard reference for all those in the field of food microbiology. - Assesses the latest developments in microbial modelling - Discusses the issues involved in building models of microbial growth - Chapters review the use of quantitative microbiology tools in predictive microbiology

Principles in Microbiome Engineering

Principles in Microbiome Engineering PDF Author: Matthew W. Chang
Publisher: John Wiley & Sons
ISBN: 3527825487
Category : Science
Languages : en
Pages : 340

Book Description
Principles in Microbiome Engineering Provides an overview of the techniques and applications insight into the complex composition and interactions of microbiomes Microbiomes, the communities of microorganisms that inhabit specific ecosystems or organisms, can be engineered to modify the structure of microbiota and reestablish ecological balance. In recent years, a better understanding of microbial composition and host-microbe interactions has led to the development of new applications for improving human health and increasing agricultural productivity and quality. Principles in Microbiome Engineering introduces readers to the tools and applications involved in manipulating the composition of a microbial community to improve the function of an eco-system. Covering a range of key topics, this up-to-date volume discusses current research in areas such as microbiome-based therapeutics for human diseases, crop plant breeding, animal husbandry, soil engineering, food and beverage applications, and more. Divided into three sections, the text first describes the critical roles of systems biology, synthetic biology, computer modelling, and machine learning in microbiome engineering. Next, the volume explores various state-of-the-art applications, including cancer immunotherapy and prevention of diseases associated with the human microbiome, followed by a concluding section offering perspectives on the future of microbiome engineering and potential applications. Introduces a variety of applications of microbiome engineering in the fields of medicine, agriculture, and food and beverage products Presents current research into the complex interactions and relationships between microbiomes and biotic and abiotic elements of their environments Examines the use of technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Big Data analytics to advance understanding of microbiomes Discusses the engineering of microbiomes to address human health conditions such as neuro psychiatric disorders and autoimmune and inflammatory diseases Edited and authored by leading researchers in the rapidly evolving field, Principles in Microbiome Engineering is an essential resource for biotechnologists, biochemists, microbiologists, pharmacologists, and practitioners working in the biotechnology and pharmaceutical industries.

Pattern formation in biology

Pattern formation in biology PDF Author: Luis Diambra
Publisher: Frontiers Media SA
ISBN: 2832525687
Category : Science
Languages : en
Pages : 157

Book Description


Computational Systems Biology of Pathogen-Host Interactions

Computational Systems Biology of Pathogen-Host Interactions PDF Author: Saliha Durmuş
Publisher: Frontiers Media SA
ISBN: 2889198219
Category : Microbiology
Languages : en
Pages : 200

Book Description
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.

In Silico Immunology

In Silico Immunology PDF Author: Darren D.R. Flower
Publisher: Springer Science & Business Media
ISBN: 0387392416
Category : Medical
Languages : en
Pages : 453

Book Description
This book outlines three emergent disciplines, which are now poised to engineer a paradigm shift from hypothesis- to data-driven research: theoretical immunology, immunoinformatics, and Artificial Immune Systems. It details how these disciplines will enable new understanding to emerge from the analysis of complex datasets. Coverage shows how these three are set to transform immunological science and the future of health care.