Modeling of vitamin K (Menaquinoe-7) fermentation by Bacillus subtilis natto in biofilm reactors

Ehsan Mahdinia, Sina Jahangiri Mamouri, Virendra M. Puri, Ali Demirci, Aydin Berenjian

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Menaquinoe-7 (MK-7) is the most potent form of vitamin K with numerous benefits for human health such as reducing the risks of cardiovascular diseases and osteoporosis in addition to having antitumor characteristics. Therefore, MK-7 production via bacterial fermentation has been studied intensely in the last few decades. Recently, biofilm reactors were implemented to enhance production levels in our lab. The specific objective of this study was to mathematically model the findings in batch biofilm reactors and thus further deepen our understanding of the conditions governing fermentation to pave the path to scaling up the production to pilot scale fermenters. The modified logistic equation was used to correlate substrate consumption with fermentation time and to model the substrate consumption in the four batch fermentations. Results indicated that this modified logistic model fits well with the experimental data for substrate consumption. Therefore there was no need for the other more complex models. Furthermore, this successfully modified-logistic equation was inserted into the Luedeking-Piret model to estimate MK-7 production based on substrate consumption, because of the typical MK-7 profiles in batch fermentations. There is sufficient evidence in the literature that MK-7 biosynthesis follows a mixed-metabolite pattern in Bacillus subtilis natto. Similarly, the modified-Gompertz model was used also for the same purpose. Results indicated that the modified Luedeking-Piret model fits more accurately for MK-7 production (R2 = 0.971, 0.943, 0.970, and 0.959) compared to the modified-Gompertz (R2 = 0.914, 0.943, 0.949 and 0.860).

Original languageEnglish (US)
Pages (from-to)196-202
Number of pages7
JournalBiocatalysis and Agricultural Biotechnology
StatePublished - Jan 2019

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Food Science
  • Bioengineering
  • Applied Microbiology and Biotechnology
  • Agronomy and Crop Science


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