This collection of experimental and computational strategies and techniques for microbial genome-scale essentiality studies was developed and written by the leading research groups in the field. In addition to wet-lab protocols, the book describes statistical methods essential for planning and evaluating successful large-scale essentiality screens; in-silico prediction of gene essentiality using genome-scale reconstructed metabolic models; and data integration and comparative analysis of genomic databases. Each protocol follows the successful Methods in Molecular Biology™ series format, offering an introduction outlining the underlying principles, step-by-step instructions, a list of necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls.
Microbial Gene Essentiality: Protocols and Bioinformatics contains a comprehensive collection of experimental and computational strategies and techniques for microbial genome-scale essentiality studies, developed and presented by the leading groups in the field. In addition to wet-lab protocols, the book describes (i) statistical methods essential for planning successful large-scale essentiality screens, as well for data evaluation and analysis; (ii) in-silico prediction of gene essentiality using genome-scale reconstructed metabolic models; and (iii) data integration and comparative analysis in the context of genomic databases. This volume provides researchers with a first-stop guide for choosing the most appropriate strategy for planned essentiality studies. Experimental and computational aspects are equally important in genome-scale gene essentiality analysis, as in all other genomic technologies, and Microbial Gene Essentiality: Protocols and Bioinformatics reflects both of these aspects. All protocols follow the successful Methods in Molecular Biology series format, each offering an introduction outlining the principles behind the techniques, step-by-step instructions, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls, and are intended for both novice and expert scientists.