Meta-Regression models describing the effects of essential oils and added lactic acid bacteria on pathogen inactivation in cheese

https://doi.org/10.1016/j.mran.2020.100131Get rights and content

Highlights

  • EOs in films/cheese surfaces are more effective for pathogen control than EOs in milk.

  • EO films produce faster inactivation of pathogens than EOs in milk or cheese surface.

  • Adding LAB to milk is more effective against LM than smearing on cheese.

  • Lemon balm, sage and basil EOs produce the greatest inhibition of LM and SA.

  • Clove, oregano and bay EOs produce the greatest inhibition against Salmonella.

Abstract

Biopreservatives such as plant-based antimicrobials and bacteriocinogenic starter cultures have been proposed as hurdles to increase microbiological safety of a variety of products, including cheese, and numerous studies have reported their pathogen inhibitory properties. For that reason, the objective of this meta-analysis was to summarise the inactivation of Listeria monocytogenes (LM), Staphylococcus aureus (SA) and Salmonella spp. (SS) in cheese attained by added lactic acid bacteria (LAB) and essential oils (EOs); and to compare the inhibitory effectiveness by application mode and specific antimicrobial. After systematic review, 1810 observations on log reduction data and study characteristics were extracted from 53 studies. Comparing among the factual methods of application of antimicrobials (in milk, cheese surface and incorporated in films), meta-regression models pointed out that addition of EOs to milk renders, as a whole, the lowest inhibitory effect against LM, SA and SS in the finished product; whereas for added LAB, incorporation in milk prompts a faster inactivation of LM than onto cheese surface. Lemon balm, sage and basil EOs showed the best inhibitory outcomes against LM and SA; whereas clove, oregano and bay EOs presented the highest bactericidal effect against SS. For a given increase in EO concentration, the application on cheese surface provides the greatest inhibitory effect against LM and SS, while EO-embedded films lead to a more rapid inactivation during maturation/storage. The experimental practice of inoculating the antimicrobial in cheese mixture should no longer be employed in challenge studies, since the meta-regression models have demonstrated that this application method biases the results, overestimating or underestimating the inhibitory effects of EOs or added LAB, respectively. This meta-analysis has also emphasised the need to further investigate the relationship between pathogen's inoculum size and their concentrations in time.

Introduction

Listeria monocytogenes (LM), Staphylococcus aureus (SA) and Salmonella spp. (SS) are some of the most common bacterial agents causing foodborne illnesses and are found in numerous food matrices, including different types of cheeses (Iannetti et al., 2016; Jackson et al., 2018; Rosengren et al., 2010; Kousta et al., 2010; Cremonesi et al., 2007; Almeida et al., 2007; Tekinşen and Özdemir, 2006; Cunha‐Neto et al., 2019; Elafify et al., 2019). A recent meta-analysis showed pooled prevalence of 12.8% for LM and 16% for SA in goat raw milk cheeses, while the prevalence of SS was lower (5.91%), but still concerning (Gonzales-Barron et al., 2017). LM and SS can cause illnesses even when in low numbers in any food product, including cheese (United States Food and Drug Administration 2003). On the other hand, a larger number of SA (above 105 log CFU/g) is required for this pathogen to be able to produce enterotoxins and impose a serious health threat (Duquenne et al., 2010). Nevertheless, SA imposes an important contamination issue since, even at low initial contamination levels, many factors can contribute to SA growth to a sufficiently high concentration that enables enterotoxin production in the curd/cheese (Paulin et al., 2012). Overall, soft and semi-soft cheeses made from different milk kinds and types (pasteurised, raw or low-heat-treated; and from cows, goats, sheep, etc.) sampled at retail level have revealed non-satisfactory results in terms of pathogen contamination by pathogens (EFSA and ECDC, 2018) thus underscoring the importance of improving the safety of cheeses to reduce the occurrence of pathogens.

Biopreservatives such as bacteriocinogenic lactic acid bacteria (LAB) used in starter cultures, and plant-based antimicrobials such as essential oils (EOs) are hurdles used to increase the microbiological safety of cheeses. The microbial inhibition offered by bacteriocinogenic LAB is mostly due to competition for substrates, production of antimicrobial substances (bacteriocins), production of organic acids that drop the pH during fermentation, and production of other non-proteinaceous compounds such as H2O2 (Tulini, 2014). The mechanism of action of EOs include a series of events on the cell surface, and, consequently, within the cytoplasm (Nazzaro et al., 2013). Modifications of membrane permeability and compromised transport of molecules can lead to degradation of the cell wall (damaging the cytoplasmic membrane), increased permeability (causing the leakage of cell contents), denaturation of enzymes and cellular proteins, loss of metabolites and ions (Nazzaro et al., 2013), and cytoplasm coagulation (Nazzaro et al., 2013; Gustafson et al., 1998).

Over the past years, several authors have performed challenge studies of foodborne pathogens inoculated in milk or cheese to assess the antimicrobial capacity of functional starter cultures or selected LAB (Ibrahim and Awad, 2018; Campagnollo et al., 2018; Atanasova et al., 2014) and plant-based antimicrobials (Artiga-Artigas et al., 2017; Wahba et al., 2010; Menon and Garg, 2001; Tehrani and Sadeghi, 2015; Dannenberg et al., 2016). Thus, a meta-analysis of the published results on the effect of antimicrobial biopreservatives will help evaluate their usefulness to control foodborne pathogens in cheeses (Xavier et al., 2014); and more specifically, compare the effectiveness of the different biopreservatives and modes of application. In this meta-regression study, the population is defined as cheeses with added lactic acid bacteria or essential oils, and the measured outcome is the mean log reduction of pathogens. This study aims to deliver an insight on the effects of biopreservation methods in cheese for the optimisation of these hurdle technologies to improve the safety of cheeses.

Section snippets

Data collection and description of the data set

Electronic literature search was carried out in Scopus, PubMed and Web of Science databases to find original and review articles, published since 2000, summarising biopreservation methods currently tested and/or applied in cheese-making and their efficiencies against pathogens. The search was done systematically and aimed to find quality studies validated by the scientific community.

The bibliographic searches were conducted by properly applying the AND and OR logical connectors to combine terms

Results and discussion

The results of the analysis of variance of the five meta-regression models adjusted are presented in Table 3. The EOs-SA model allowed for the inclusion of the highest number of moderating variables. The EOs-LM model does not contain inoculum level as fixed effect since this term reveal to be non-significant (p = 0.627). The EOs-SS model did not include storage temperature, nor inoculum level, as the first variable had only two levels (data was collected at either 4 or 10 °C) and the second

Conclusion

Literature data was used to build meta-analytical regression models capable of summarising the reduction in LM, SA and SS populations in cheese attained by added LAB and EOs; and elucidating inhibitory effectiveness by application mode and specific antimicrobial. These meta-regressions showed that the effectiveness of added LAB and EOs were regulated by storage temperature, exposure time, pathogen's inoculum size, antimicrobial concentration and method of application of the biopreservative

CRediT authorship contribution statement

Beatriz Nunes Silva: Data curation, Formal analysis, Investigation, Writing - original draft, Validation. Vasco Cadavez: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing - review & editing, Software, Resources, Supervision. José António Teixeira: Project administration, Writing - review & editing, Supervision. Ursula Gonzales-Barron: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project

Declaration of Competing Interests

None

Acknowledgements

The authors are grateful to EU PRIMA programme and the Portuguese Foundation for Science and Technology (FCT) for funding the ArtiSane Food project (PRIMA/0001/2018). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01–0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. Ms.

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