In vitro antimicrobial activity of extracts and essential oils of Cinnamomum, Salvia, and Mentha spp. against foodborne pathogens: A meta-analysis study.

Essential oils (EOs) are a class of natural products that exhibit potent antimicrobial properties against a broad spectrum of bacteria. Inhibition diameters (IDs) and minimum inhibitory concentrations (MICs) are the typical measures of antimicrobial activity for extracts and EOs obtained from Cinnamomum, Salvia, and Mentha species. This study used a meta-analytical regression analysis to investigate the correlation between ID and MIC measurements and the variability in antimicrobial susceptibility tests. By utilizing pooled ID models, this study revealed significant differences in foodborne pathogens' susceptibility to extracts, which were dependent on both the plant species and the methodology employed (p < .05). Cassia showed the highest efficacy against Salmonella spp., exhibiting a pooled ID of 26.24 mm, while cinnamon demonstrated the highest efficacy against Bacillus cereus, with a pooled ID of 23.35 mm. Mint extract showed the greatest efficacy against Escherichia coli and Staphylococcus aureus. Interestingly, cinnamon extract demonstrated the lowest effect against Shiga toxin-producing E. coli, with a pooled ID of only 8.07 mm, whereas its EOs were the most effective against this bacterial strain. The study found that plant species influenced the MIC, while the methodology did not affect MIC measurements (p > .05). An inverse correlation between ID and MIC measurements was identified (p < .0001). These findings suggest that extracts and EOs obtained from Cinnamomum, Salvia, and Mentha spp. have the potential to inhibit bacterial growth. The study highlights the importance of considering various factors that may influence ID and MIC measurements when assessing the effectiveness of antimicrobial agents.

Tracking microbial quality, safety and environmental contamination sources in artisanal goat cheesemaking factories.

A harmonised microbiological survey was performed in two artisanal factories of raw goat milk cheeses (A and B) located in the Andalusian region (Spain). A total of 165 different control points or samples (raw materials, final products, food-contact surfaces [FCS], and air) were examined as microbial and pathogen sources of contamination of artisanal goat raw milk cheeses. For raw milk samples analysed from both producers, the concentrations of aerobic-mesophilic bacteria (AMB), total coliforms, coagulase-positive Staphylococcus spp. (CPS), lactic-acid bacteria (LAB) and moulds and yeasts ranged between 3.48 and 8.59, 2.45-5.48, 3.42-4.81, 4.99-8.59 and 3.35-6.85 log cfu/mL respectively. For the same microbial groups, the analysis of raw milk cheeses revealed concentrations ranging from 7.82 to 8.88, 2.00-6.82, 2.00-5.28, 8.11-9.57 and 2.00-5.76 log cfu/g, respectively. Although the raw material analysed from producer A presented higher microbial loads and between-batch variability, it was B the producer with the most loaded final products. Regarding the microbial air quality, the fermentation area, storage room, milk reception and packaging room were the most AMB loaded places, while the ripening chamber was the area with higher fungal loads in bioareosol from both producers. Conveyor belts, cutting machine, storage boxes and brine tank were highlighted as the most contaminated FCS evaluated. Staphylococcus aureus was the only pathogen detected within the set of 51 isolates from samples as revealed by MALDI-TOF and molecular PCR, with a prevalence of 12.5% for samples from the producer B. The public health risk attributed to the consumption of artisanal goat cheese should not be neglected, and may consider the whole cheesemaking processing chain, from microbiological quality of raw milk to the ready-to-eat final product, especially concerning the presence of S. aureus.

Meta-Analysis of In Vitro Antimicrobial Capacity of Extracts and Essential Oils of Syzygium aromaticum, Citrus L. and Origanum L.: Contrasting the Results of Different Antimicrobial Susceptibility Methods.

Diffusion methods, including agar disk-diffusion and agar well-diffusion, as well as dilution methods such as broth and agar dilution, are frequently employed to evaluate the antimicrobial capacity of extracts and essential oils (EOs) derived from Origanum L., Syzygium aromaticum, and Citrus L. The results are reported as inhibition diameters (IDs) and minimum inhibitory concentrations (MICs), respectively. In order to investigate potential sources of variability in antimicrobial susceptibility testing results and to assess whether a correlation exists between ID and MIC measurements, meta-analytical regression models were built using in vitro data obtained through a systematic literature search. The pooled ID models revealed varied bacterial susceptibilities to the extracts and in some cases, the plant species and methodology utilised impacted the measurements obtained (p < 0.05). Lemon and orange extracts were found to be most effective against E. coli (24.4 ± 1.21 and 16.5 ± 0.84 mm, respectively), while oregano extracts exhibited the highest level of effectiveness against B. cereus (22.3 ± 1.73 mm). Clove extracts were observed to be most effective against B. cereus and demonstrated the general trend that the well-diffusion method tends to produce higher ID (20.5 ± 1.36 mm) than the disk-diffusion method (16.3 ± 1.40 mm). Although the plant species had an impact on MIC, there is no evidence to suggest that the methodology employed had an effect on MIC (p > 0.05). The ID-MIC model revealed an inverse correlation (R2 = 47.7%) and highlighted the fact that the extract dose highly modulated the relationship (p < 0.0001). The findings of this study encourage the use of extracts and EOs derived from Origanum, Syzygium aromaticum, and Citrus to prevent bacterial growth. Additionally, this study underscores several variables that can impact ID and MIC measurements and expose the correlation between the two types of results.

From Cheese-Making to Consumption: Exploring the Microbial Safety of Cheeses through Predictive Microbiology Models.

Cheeses are traditional products widely consumed throughout the world that have been frequently implicated in foodborne outbreaks. Predictive microbiology models are relevant tools to estimate microbial behavior in these products. The objective of this study was to conduct a review on the available modeling approaches developed in cheeses, and to identify the main microbial targets of concern and the factors affecting microbial behavior in these products. Listeria monocytogenes has been identified as the main hazard evaluated in modelling studies. The pH, aw, lactic acid concentration and temperature have been the main factors contemplated as independent variables in models. Other aspects such as the use of raw or pasteurized milk, starter cultures, and factors inherent to the contaminating pathogen have also been evaluated. In general, depending on the production process, storage conditions, and physicochemical characteristics, microorganisms can grow or die-off in cheeses. The classical two-step modeling has been the most common approach performed to develop predictive models. Other modeling approaches, including microbial interaction, growth boundary, response surface methodology, and neural networks, have also been performed. Validated models have been integrated into user-friendly software tools to be used to obtain estimates of microbial behavior in a quick and easy manner. Future studies should investigate the fate of other target bacterial pathogens, such as spore-forming bacteria, and the dynamic character of the production process of cheeses, among other aspects. The information compiled in this study helps to deepen the knowledge on the predictive microbiology field in the context of cheese production and storage.