Understanding HMF inhibition on yeast growth coupled with ethanol production for the improvement of bio-based industrial processes
Process Biochemistry, cilt.121, ss.425-438, 2022 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 121
- Basım Tarihi: 2022
- Doi Numarası: 10.1016/j.procbio.2022.07.015
- Dergi Adı: Process Biochemistry
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Communication Abstracts, Compendex, Food Science & Technology Abstracts, INSPEC, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
- Sayfa Sayıları: ss.425-438
- Anahtar Kelimeler: Bioethanol, COBRA, HMF, Microfluidics, Modelling, Yeast
- Boğaziçi Üniversitesi Adresli: Evet
Özet
Inhibitory compounds generated from biomass hydrolysis affect the production of biofuels. HMF is a furan derivative inhibitor and influences the ethanol yield by inhibiting enzymes such as alcohol dehydrogenase, aldehyde dehydrogenase and glycolysis. The most striking effect of HMF on the organisms is that it interferes with the microbial growth and is considered as the most potent inhibitor in bioethanol production. In this study, HMF inhibition within yeast cells is investigated by both computational (COBRA) and experimental approaches. The active subsystems in the medium with and without HMF and the coupling types of the reactions are determined to get an insight on how to improve bioethanol production by strain engineering techniques. While extracellular transport subsystem is prominent in term of flexibility, post transcriptional regulation is outstanding among transcriptional to metabolic regulation types. The strategies to increase biomass and ethanol simultaneously with gene/reaction deletion methods are discussed, and ethanol production can be increased by 17% up to 33.35 mmol gDW−1hr−1 with several reaction deletions. The genome scale metabolic model and the complementary experiment given here shed light on the biofuel management in the bio-based industry for future.