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Antimicrobial activity of natural extracts: the problematic of mathematical modeling
* 1, 2 , 3 , 3 , 4, 5 , 3 , 3 , * 1 , * 4, 5
1  REQUIMTE/LAQV, Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto, Rua Dr António Bernardino de Almeida 431, 4200-072 Porto, Portugal.
2  Universidade de Vigo, Nutrition and Bromatology Group, Department of Analytical Chemistry and Food Science, Faculty of Science, E32004 Ourense, Spain.
3  Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense Campus, E32004 Ourense, Spain.
4  Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense Campus, E32004 Ourense, Spain
5  Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolonia, 5300-253 Bragança, Portugal.
Academic Editor: Chi-Fai Chau

Abstract:

The antimicrobial activity of plants, algae and derived extracts has been a subject of interest for the scientific community. In particular, algae extracts have demonstrated their potential as a source of natural antimicrobial agents (Silva et al., 2020). Because of their antibacterial capacity and low toxicity, algal extracts have been studied as natural preservatives in food and cosmetic formulations. The use of these extracts has the potential to minimize the use of synthetic preservatives, which may be harmful to both human health and the environment. Nonetheless, the use of end-point techniques to calculate the minimal inhibitory concentration instead of creating growth inhibition curves, usually leads to an almost absence of mathematical modelling procedures on the bacterial inhibition behavior of natural extracts.

The goal of mathematical modelling is to describe the relationship between the concentration of an inhibitory agent (such as a drug or a toxin) and the growth rate of a population. For this purpose, the data obtained during the growth of six different bacteria in the presence of different concentrations of Ascophyllum nodosum (L.) extracts were recorded over 24 h. Later, the collected data was modeled based on different classical sigmoidal models e.g., Weibull, logistic, Gompertz, and modified Hill were applied to define the critical growth phases and infer the kinetic parameters.

The obtained parameters allow to conclude that the inhibition mechanisms behind the antibacterial effects of the algae extracts are diverse towards different microorganisms. The presence of the extract led to a diminution of the specific growth velocity in some cases such as Staphylococcus aureus, whereas in the replication of other bacteria such as Bacillus cereus, the extension of the lag phase was the predominant inhibition mechanism.

Silva, A.,et al . (2020). Antibacterial Use of Macroalgae Compounds against Foodborne Pathogens. Antibiotics, 9(10), 712. https://doi.org/10.3390/antibiotics9100712

The research leading to these results was supported by MICINN supporting the Ramón y Cajal grant for M.A. Prieto (RYC-2017-22891) and L. Cassani (ED481B-2021/152), and the pre-doctoral grants of P. Garcia-Oliveira (ED481A-2019/295) and M. Carpena (ED481A 2021/313). The authors thank the program BENEFICIOS DO CONSUMO DAS ESPECIES TINTORERA-(CO-0019-2021) that supports the work of F. Chamorro. The Authors are grateful to Ibero-American Program on Science and Technology (CYTED—AQUA-CIBUS, P317RT0003), to the Bio Based Industries Joint Undertaking (JU) under grant agreement No 888003 UP4HEALTH Project (H2020-BBI-JTI-2019) of C. Lourenço-Lopes and to AlgaMar company (www.algamar.com) for the collaboration and algae material provision.The authors would like to thank the EU and FCT for funding through the programs UIDB/50006/2020; UIDP/50006/2020 and Authors are grateful to Ibero-American Program on Science and Technology (CYTED— GENOPSYSEN, P222RT0117). MFB thanks FCT for the FCT Investigator (2020.03107.CEECIND).

Keywords: Ascophyllum nodosum exctrats, antimicrobial activity , Matematical models
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