Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling.

Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity.

Characterization of the archaeal community in foods: The neglected part of the food microbiota.

Despite the large number of studies conducted on archaea associated with extreme environments, the archaeal community composition in food products is still poorly known. Here, we investigated a new insight into exploring the archaeal community in several food matrices, with a particular focus on determining whether living archaea were present. A total of 71 samples of milk, cheese and its derived brine, honey, hamburger, clam, and trout were analyzed by high-throughput 16S rRNA sequencing. Archaea were detected in all the samples, ranging from 0.62 % of microbial communities in trout to 37.71 % in brine. Methanogens dominated 47.28 % of the archaeal communities, except for brine, which was dominated by halophilic taxa affiliated with the genus Haloquadratum (52.45 %). Clams were found to be a food with high richness and diversity of archaea and were targeted for culturing living archaea under different incubation time and temperature conditions. A subset of 16 communities derived from culture-dependent and culture-independent communities were assessed. Among the homogenates and living archaeal communities, the predominant taxa were distributed in the genera Nitrosopumilus (47.61 %) and Halorussus (78.78 %), respectively. A comparison of the 28 total taxa obtained by culture-dependent and culture-independent methods enabled their categorization into different groups, including detectable (8 out of 28), cultivable (8 out of 28), and detectable-cultivable (12 out of 28) taxa. Furthermore, using the culture method, the majority (14 out of 20) of living taxa grew at lower temperatures of 22 and 4 °C during long-term incubation, and few taxa (2 out of 20) were found at 37 °C during the initial days of incubation. Our results demonstrated the distribution of archaea in all analyzed food matrices, which opens new perspectives to expand our knowledge on archaea in foods and their beneficial and detrimental effects.

Identification of Pseudomonas jessenii and Pseudomonas gessardii as the most proteolytic Pseudomonas isolates in Iranian raw milk and their impact on stability of sterilized milk during storage.

Identification of the most proteolytic Pseudomonas strains that can produce heat-resistant proteases and contribute to the Ultra High Temperature (UHT) milk destabilization is of great interest. In the present study, among the 146 Pseudomonas isolates that encoded the aprX gene, five isolates with the highest proteolytic activity were selected and identified based on 16S rRNA, rpoD and gyrB gene sequences data. The identification results were confirmed by phylogenetic analysis based on multilocus sequence analysis and identified the representative isolates as P. jessenii (two isolates) and P. gessardii (three isolates). Casein zymography demonstrated the ability of these species to produce heat-resistant enzymes, AprX, with molecular mass of about 48 kDa during storage at 7° C for 72 h. In sterilized milk samples, the residual activity of AprX caused a considerable enhancement in the degree of protein hydrolysis, non-protein nitrogen and non-casein nitrogen contents of the samples during a two-month storage. This enhancement was slightly higher in samples containing enzyme produced by P. jessenii compared to P. gessardii ones, resulting in earlier onset of sterilized milk destabilization. Hence, this study revealed that P. jessenii and P. gessardii can play a considerable role in deterioration of Iranian commercial long-life milk.

The prevalence of Campylobacter spp. in vegetables, fruits, and fresh produce: a systematic review and meta-analysis.

There are a number of reports indicating correlation between outbreaks of campylobacteriosis and the consumption of raw vegetables. This study is a meta-analysis on the prevalence of Campylobacter in fresh vegetables and fruits without any location limitation, which was performed through a documented review of the available resources. Relevant literature was reviewed by trained reviewers, who examined the results for the inclusion of articles in the meta-analysis. The prevalence of Campylobacter in raw vegetables, the sample source, the Campylobacter species, and the method of detection were extracted. The prevalence of Campylobacter in vegetables, fruits, and fresh produce were estimated to be 0.53%. Analysis of the various sample groups initially showed that the bean and sprouts group was the vegetable with the highest prevalence of Campylobacter (11.08%). The rate of contamination was higher when both the molecular and conventional methods were employed. The highest prevalence of Campylobacter was found in Asia (33.4%). Despite the low prevalence, consumption of raw vegetables is inherently risky because no treatment is used to inactivate the pathogens. Therefore, proper sanitation methods are recommended to treat the raw products.