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245 1 0 _aGenetics, genetic manipulation, and approaches to strain improvement of filamentous fungi.
490 0 _vIn Manual of Industrial MicroBiology and Biotechnology, Third Edition, p.318-329, 2010
520 3 _aThis chapter focuses on some recently developed genetic tools and strain improvement approaches for further optimizing protein production in filamentous fungi in the "omics" era. The technologies and approaches described are mainly focused on Aspergillus niger, but in principle could be applied to any of the other industrially relevant filamentous fungi. Within the past 5 years, genome sequences for the most important industrial filamentous fungi have become available, facilitating four main areas of current research: (i)genome mining and identification of new compounds and enzymes; (ii)in silico reconstitution of metabolic pathways; (iii)systems biology approaches to comprehensively understand the complex regulation of growth, physiology, and metabolism in fungi; and (iv)further development of industrial strains as cell factories for the production of enzymes or compounds. Two recent publications provide good examples of how the application of systems biology tools helps to understand biological processes in filamentous fungi and generates leads for process and strain improvement programs. One key step in the improvement of fungal production strains is their optimization at the molecular level. Two complementary approaches can be followed: nonrecombinant and recombinant methods. The chapter discusses some of the concepts and tools that have proven particularly powerful for optimizing industrial fungal strains. It also focuses on alternative strain improvement approaches, and summarizes some rules of thumb that are found to be critical for successful cultivation of filamentous fungi in a bioreactor.
650 1 4 _aFUNGI
650 1 4 _aBIOREACTOR
700 1 2 _aMeyer, V.
700 1 2 _aRam, A. F.
700 1 2 _aPunt, P. J.
856 4 0 _uhttps://drive.google.com/file/d/1OvmUZI-cfQpRzYtM1sw8_xd42ilzDzFO/view?usp=drivesdk
_zPara ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
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