RT Journal Article
T1 Model-aided targeted volatile fatty acid production from food waste using a defined co-culture microbial community
A1 Regueira López, Alberte
A1 Turunen, Rosaliina
A1 Vuoristo, Kiira S.
A1 Carballa Arcos, Marta
A1 Lema Rodicio, Juan Manuel
A1 Uusitalo, Jaana M.
A1 Mauricio Iglesias, Miguel
K1 Model-aided design
K1 Carboxylate platform
K1 Process selectivity
K1 Mathematical model
AB The production of volatile fatty acids (VFA) is gaining momentum due to their central role in the emerging carboxylate platform. Particularly, the production of the longest VFA (from butyrate to caproate) is desired due to their increased economic value and easier downstream processing. While the use of undefined microbial cultures is usually preferred with organic waste streams, the use of defined microbial co-culture processes could tackle some of their drawbacks such as poor control over the process outcome, which often leads to low selectivity for the desired products. However, the extensive experimentation needed to design a co-culture system hinders the use of this technology. In this work, a workflow based on the combined use of mathematical models and wet experimentation is proposed to accelerate the design of novel bioprocesses. In particular, a co-culture consisting of Pediococcus pentosaceus and Megaphaera cerevisiae is used to target the production of high-value odd- and even‑carbon VFA. An unstructured kinetic model was developed, calibrated and used to design experiments with the goal of increasing the selectivity for the desired VFA, which were experimentally validated. In the case of even‑carbon VFA, the experimental validation showed an increase of 38 % in caproate yield and, in the case of enhanced odd‑carbon VFA experiments, the yield of butyrate and caproate diminished by 62 % and 94 %, respectively, while propionate became one of the main end products and valerate yield value increased from 0.007 to 0.085 gvalearte per gconsumed sugar. The workflow followed in this work proved to be a sound tool for bioprocess design due to its capacity to explore and design new experiments in silico in a fast way and ability to quickly adapt to new scenarios
PB Elsevier
SN 0048-9697
YR 2023
FD 2023
LK http://hdl.handle.net/10347/29374
UL http://hdl.handle.net/10347/29374
LA eng
NO Science of The Total Environment 857 (2023) 159521
NO This work was financially supported by the project BIOCHEM (ERA-IB-2 7th call, ERA-IB-16-056) funded by MINECO (PCIN 2016-102) and Academy of Finland (311738). A. Regueira would like to acknowledge the support of the Xunta de Galicia through a postdoctoral fellowship (ED481B-2021-012). A. Regueira, M. Carballa and M. Mauricio-Iglesias belong to the Galician Competitive Research Group ED431C-2021/37, co-funded by Xunta de Galicia and ERDF (EU)
DS Minerva
RD 28 abr 2026