1
|
Castillo S, Patil KR, Jouhten P. Yeast Genome-Scale Metabolic Models for Simulating Genotype-Phenotype Relations. PROGRESS IN MOLECULAR AND SUBCELLULAR BIOLOGY 2019; 58:111-133. [PMID: 30911891 DOI: 10.1007/978-3-030-13035-0_5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Understanding genotype-phenotype dependency is a universal aim for all life sciences. While the complete genotype-phenotype relations remain challenging to resolve, metabolic phenotypes are moving within the reach through genome-scale metabolic model simulations. Genome-scale metabolic models are available for commonly investigated yeasts, such as model eukaryote and domesticated fermentation species Saccharomyces cerevisiae, and automatic reconstruction methods facilitate obtaining models for any sequenced species. The models allow for investigating genotype-phenotype relations through simulations simultaneously considering the effects of nutrient availability, and redox and energy homeostasis in cells. Genome-scale models also offer frameworks for omics data integration to help to uncover how the translation of genotypes to the apparent phenotypes is regulated at different levels. In this chapter, we provide an overview of the yeast genome-scale metabolic models and the simulation approaches for using these models to interrogate genotype-phenotype relations. We review the methodological approaches according to the underlying biological reasoning in order to inspire formulating novel questions and applications that the genome-scale metabolic models could contribute to. Finally, we discuss current challenges and opportunities in the genome-scale metabolic model simulations.
Collapse
Affiliation(s)
- Sandra Castillo
- VTT Technical Research Centre of Finland Ltd., Tietotie 2, 02044, Espoo, Finland
| | - Kiran Raosaheb Patil
- European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117, Heidelberg, Germany
| | - Paula Jouhten
- VTT Technical Research Centre of Finland Ltd., Tietotie 2, 02044, Espoo, Finland.
| |
Collapse
|
2
|
Santos SC, de Sousa AS, Dionísio SR, Tramontina R, Ruller R, Squina FM, Vaz Rossell CE, da Costa AC, Ienczak JL. Bioethanol production by recycled Scheffersomyces stipitis in sequential batch fermentations with high cell density using xylose and glucose mixture. BIORESOURCE TECHNOLOGY 2016; 219:319-329. [PMID: 27498013 DOI: 10.1016/j.biortech.2016.07.102] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 07/20/2016] [Accepted: 07/24/2016] [Indexed: 05/23/2023]
Abstract
Here, it is shown three-step investigative procedures aiming to improve pentose-rich fermentations performance, involving a simple system for elevated mass production by Scheffersomyces stipitis (I), cellular recycle batch fermentations (CRBFs) at high cell density using two temperature strategies (fixed at 30°C; decreasing from 30 to 26°C) (II), and a short-term adaptation action seeking to acclimatize the microorganism in xylose rich-media (III). Cellular propagation provided 0.52gdrycellweightgRS(-1), resulting in an expressive value of 45.9gdrycellweightL(-1). The yeast robustness in CRBF was proven by effective ethanol production, reaching high xylose consumption (81%) and EtOH productivity (1.53gL(-1)h(-1)). Regarding the short-term adaptation, S. stipitis strengthened its robustness, as shown by a 6-fold increase in xylose reductase (XR) activity. The short fermentation time (20h for each batch) and the fermentation kinetics for ethanol production from xylose are quite promising.
Collapse
Affiliation(s)
- Samantha Christine Santos
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil; School of Chemical Engineering, State University of Campinas - UNICAMP, 500 Albert Einstein Av, Zip Code 13083-852 Campinas, SP, Brazil.
| | - Amanda Silva de Sousa
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil; Institute of Biology, State University of Campinas - UNICAMP, 500 Albert Einstein Av, Zip Code 13083-852 Campinas, SP, Brazil
| | - Suzane Rodrigues Dionísio
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil
| | - Robson Tramontina
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil; Institute of Biology, State University of Campinas - UNICAMP, 500 Albert Einstein Av, Zip Code 13083-852 Campinas, SP, Brazil
| | - Roberto Ruller
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil
| | - Fabio Márcio Squina
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil
| | - Carlos Eduardo Vaz Rossell
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil
| | - Aline Carvalho da Costa
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil; School of Chemical Engineering, State University of Campinas - UNICAMP, 500 Albert Einstein Av, Zip Code 13083-852 Campinas, SP, Brazil
| | - Jaciane Lutz Ienczak
- Brazilian Bioethanol Science and Technology Laboratory - CTBE/CNPEM, 10000 Giuseppe Maximo Scolfaro St, Zip Code 13083-852 Campinas, SP, Brazil
| |
Collapse
|