Meta-regression modelling of the inhibition diameter produced by extracts of Origanum, Syzygium and Citrus as a function of the minimum inhibitory concentration

Beatriz Nunes Silva; Olga Bonilla; Arícia Possas; Antonio Valero; José António Teixeira; Vasco Cadavez; Ursula Gonzales-Barron

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Meta-regression modelling of the inhibition diameter produced by extracts of Origanum, Syzygium and Citrus as a function of the minimum inhibitory concentration

^{1, 2, 3},

⁴,

⁴,

⁴,

José António Teixeira

^{3, 5},

Vasco Cadavez

²,

Ursula Gonzales-Barron

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2}

¹ CEB – Centre of Biological Engineering, University of Minho
² Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
³ LABBELS – Associate Laboratory, Braga 4710-057 Guimarães, Portugal
⁴ Department of Food Science and Technology, University of Córdoba, Campus Rabanales, 14014, Córdoba, Spain
⁵ CEB – Centre of Biological Engineering, University of Minho, Campus Gualtar, 4710-057 Braga, Portugal

Academic Editor: Arun Bhunia

Published: 30 September 2022 by MDPI in The 3rd International Electronic Conference on Foods: Food, Microbiome, and Health - A Celebration of the 10th Anniversary of Foods' Impact on Our Wellbeing session Food Microbiology, Microbiome and Food Biotechnology

https://doi.org/10.3390/Foods2022-12968 (registering DOI)

Abstract:

Inhibition diameter (ID) and minimum inhibitory concentration (MIC) are important methodologies for antimicrobial susceptibility testing. In this work, the objective was to evaluate if a correlation between ID and MIC results exists.

Such relationship was assessed utilising in-vitro data collected through systematic literature search on the susceptibility of pathogens to extracts of Origanum, Syzygium and Citrus. Suitable studies were identified and the following information was retrieved: study identification, testing method (ID or MIC), dose applied (“LogDose”), pathogen, ID value (mm) and MIC value (“LogMIC”; ml/mg for extracts, μl/ml for essential oils). Then, a mixed-effect linear model with weights on ID produced by Origanum (n=145), Syzygium (n=10) and Citrus (n=7) extracts, as a function of the MIC, extract dose and bacterium, was built.

The estimate for “LogDose” (18.00 [SE=0.227]) indicates tendency for greater ID values as the dose applied increases (p<.0001), and the estimate for “LogMIC” (-5.554 [SE=0.181]) implies that this moderator and ID values are inversely correlated (p<.0001). The model also revealed different overall ID for distinct pathogens when the same extract is applied at the same dose (p<.0001): STEC appears as the most resistant pathogen, followed by C. jejuni, L. monocytogenes, S. aureus and Salmonella spp. (the latter two were not significantly different).

Whereas the goodness-of-fit (R=0.860) indicates a satisfactory correlation between predicted and observed values, the model hinted that other non-quantifiable sources may affect the ID measurements (heterogeneity analysis showed that moderators explain 47.7% of the between-studies variability). Hence, ID methodologies may not be appropriate to compare results from different studies, as the measurements could be affected by errors and variations in the protocols, impacting on the degree of extract diffusion within the agar matrix.

This meta-regression provides insight on the effectiveness of Origanum, Syzygium and Citrus against various organisms, which can be useful to select biopreservatives for pathogen control.

Keywords: biopreservation; antimicrobial; mixed-effects model; meta-analysis

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