Systems level understanding of microbial life requires truly integrated data, methods and tools that will enable researchers to approach heretofore unapproachable problems – transformational problems in the areas of health, environment, energy and food as outlined in the 2009 National Research Council report, “A New Biology for the 21st Century” – but also questions of fundamental biological significance that underpin each of these problem areas. One critical aspect to answering these types of questions is to acquire a solid, predictive understanding of the metabolic functions and regulatory strategies of microbes and microbial communities. Numerous recent efforts have proposed increasingly complex and accurate genome-scale metabolic models and transcriptional regulatory networks. However, only recently have some models begun to capture gene regulatory information to allow accurate description of the responses of an organism to its environment.
These preliminary efforts have raised numerous methodological and practical questions about best practices for the integration of metabolic models, transcriptional regulatory networks and gene expression data, the predictive ability of such models and the ability to propagate models to thousands of sequenced microbes. In this Research Topic we welcome all efforts related to (a) the development of new and improved metabolic-regulatory models, (b) use of metabolic, regulatory or integrated metabolic-regulatory models to make predictions (e.g., gene function, cellular response, etc.), (c) propagation of metabolic, regulatory and genomic information to other microbes and/or use of propagations to explore impacts of environment, evolution and community on metabolic and regulatory diversity. The editors recognize that the efforts described in (a), (b) and (c) are lofty, and countless methodological decisions, biological assumptions, and computational implementation decisions must occur to achieve the maximal end-product. As such, in addition to papers which directly try to address one of the three ‘end goals’ of integrated models, we welcome incremental efforts which evaluate one or more of the numerous methodological decisions, biological assumptions or computational decisions that must be made in order to arrive at optimal integrated models, predictions or propagations in an effort to drive towards best practices in the creation of integrated metabolic and regulatory models of all microbial life.
Systems level understanding of microbial life requires truly integrated data, methods and tools that will enable researchers to approach heretofore unapproachable problems – transformational problems in the areas of health, environment, energy and food as outlined in the 2009 National Research Council report, “A New Biology for the 21st Century” – but also questions of fundamental biological significance that underpin each of these problem areas. One critical aspect to answering these types of questions is to acquire a solid, predictive understanding of the metabolic functions and regulatory strategies of microbes and microbial communities. Numerous recent efforts have proposed increasingly complex and accurate genome-scale metabolic models and transcriptional regulatory networks. However, only recently have some models begun to capture gene regulatory information to allow accurate description of the responses of an organism to its environment.
These preliminary efforts have raised numerous methodological and practical questions about best practices for the integration of metabolic models, transcriptional regulatory networks and gene expression data, the predictive ability of such models and the ability to propagate models to thousands of sequenced microbes. In this Research Topic we welcome all efforts related to (a) the development of new and improved metabolic-regulatory models, (b) use of metabolic, regulatory or integrated metabolic-regulatory models to make predictions (e.g., gene function, cellular response, etc.), (c) propagation of metabolic, regulatory and genomic information to other microbes and/or use of propagations to explore impacts of environment, evolution and community on metabolic and regulatory diversity. The editors recognize that the efforts described in (a), (b) and (c) are lofty, and countless methodological decisions, biological assumptions, and computational implementation decisions must occur to achieve the maximal end-product. As such, in addition to papers which directly try to address one of the three ‘end goals’ of integrated models, we welcome incremental efforts which evaluate one or more of the numerous methodological decisions, biological assumptions or computational decisions that must be made in order to arrive at optimal integrated models, predictions or propagations in an effort to drive towards best practices in the creation of integrated metabolic and regulatory models of all microbial life.