About this Research Topic
The growing interest in sustaining a biobased economy has driven the development of biological approaches for the production of value-added chemicals and other commodity chemicals by microbial fermentation. The major bottleneck in bioprocessing that makes the process challenging is the low yield and titres obtained from converting sugars to bioproducts leading to high downstream processing costs. In order to improve bioprocessing, it is important to optimize microbial cell factories to efficiently convert feedstocks into bioproducts by fine tuning the metabolic pathways that drive product formation. Additionally, increasing tolerance of the microbial cells to the desired products and their intermediates will ensure that cell growth and viability is maintained during fermentation. Therefore, successful strain development involves identifying and improving key genes required to move carbon flux from substrate to a desired product. Another important consideration requires identifying genes needed to improve tolerance to the desired product and its intermediates. Towards this goal, several functional genomics approaches are being used to identify target genes and key driver mutations that enhance the function of the gene.
Recent work has gone into engineering microbial hosts to produce non-native microbial compounds such as plant metabolites and other chemicals usually made by chemical synthesis. Since these compounds are typically not made by microbes, identifying and optimizing metabolic pathways that produce them by microbial fermentation is imperative but challenging. Also, even though the compounds are generally toxic to microorganisms, very little is known about genes that can be targeted to improve tolerance of such compounds to the microbial cell factory. In this research topic, we are looking forward to highlighting what novel functional tools are being developed and what existing genomics tools are being applied to address the challenge of microbial productivity and tolerance.
In this Research Topic, we highlight the application of genomic tools such as genomic library screens, genome shuffling, adaptive laboratory evolution and whole genome sequence analysis in identifying and modifying genes that result in improved microbial performance. We therefore encourage contributors to submit their findings in the form of original article, review article, opinion or mini-review that apply any of these genomic strategies. Ultimately, these articles will inform readers on new developments and applications of these approaches as well as how genomic tools can be further improved for microbial strain development.
Recent work has gone into engineering microbial hosts to produce non-native microbial compounds such as plant metabolites and other chemicals usually made by chemical synthesis. Since these compounds are typically not made by microbes, identifying and optimizing metabolic pathways that produce them by microbial fermentation is imperative but challenging. Also, even though the compounds are generally toxic to microorganisms, very little is known about genes that can be targeted to improve tolerance of such compounds to the microbial cell factory. In this research topic, we are looking forward to highlighting what novel functional tools are being developed and what existing genomics tools are being applied to address the challenge of microbial productivity and tolerance.
In this Research Topic, we highlight the application of genomic tools such as genomic library screens, genome shuffling, adaptive laboratory evolution and whole genome sequence analysis in identifying and modifying genes that result in improved microbial performance. We therefore encourage contributors to submit their findings in the form of original article, review article, opinion or mini-review that apply any of these genomic strategies. Ultimately, these articles will inform readers on new developments and applications of these approaches as well as how genomic tools can be further improved for microbial strain development.
Keywords: yeast, stress response, omics, systems biology, adaptive laboratory evolution, metabolism, functional genomics, genome shuffling
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