Selenium bio-enrichment of Mediterranean fruit juices through lactic acid fermentation.

This work was carried out to elaborate selenium (Se) bio-enriched fermented Mediterranean fruit juices. To this purpose, pomegranate and table red grape juices were added with sodium selenite (Na2SeO3) and fermented by Levilactobacillus brevis CRL 2051 and Fructobacillus tropaeoli CRL 2034 individually or combined. To better evaluate the effect of selenite addition and starter strain inoculums on the total bacterial community of the fruit juices, fermentation trials were performed with raw and pasteurized fruit juices. No statistical significant differences were observed for total mesophilic microorganisms (TMM) and rod-shaped lactic acid bacteria (LAB) levels among raw and pasteurized juices inoculated with the starter strains, while significant differences between those juices with and without selenite were registered. LAB cocci, Pseudomonadaceae and yeasts were detected only for the raw juice preparations. The dominance of L. brevis CRL 2051 and F. tropaeoli CRL 2034 was confirmed by randomly amplified polymorphic DNA (RAPD)-PCR analysis. After fermentation, pH dropped for all inoculated trials and control raw juices. The soluble solid content (SSC) levels of the raw juices were higher than the corresponding pasteurized trials. The thermal treatment affected consistently yellowness of grape juice trials and redness of pomegranate juices. No microbial Se accumulation was registered for pomegranate juices, while F. tropaeoli CRL 2034 accumulated the highest amount of Se (65.5 µg/L) in the grape juice. For this reason, only trials carried out with raw grape juices were investigated by metagenomics analysis by Illumina MiSeq technology. Non-inoculated grape juices were massively fermented by acetic acid bacteria while Fructobacillus and Lactobacillus (previous genus name of Levilactobacillus) represented the highest operational taxonomy units (OTUs) relative abundance % of the trials inoculated with the starter strains as confirmed by this technique.

Microbial community dynamics in phyto-thermotherapy baths viewed through next generation sequencing and metabolomics approach.

Phyto-thermotherapy is a treatment consisting in immersing oneself in baths of self-heating alpine grass, to benefit of the heat and rich aromatic components released by the process. The aim of this study was to characterize the bacterial and fungal diversity of three phyto-thermal baths (PTB) performed in three different months, and to compare the data with the profile of the volatile organic compounds (VOCs) of the process. All the data collected showed that PTBs were structured in two stages: the first three days were characterised by an exponential rise of the temperature, a fast bacterial development, higher microbial diversity and higher concentrations of plant aliphatic hydrocarbons. The second stage was characterised by a stable high temperature, shrinkage of the microbial diversity with a predominance of few bacterial and fungi species and higher concentrations of volatiles of microbial origin. Erwinia was the dominant microbial species during the first stage and probably responsible of the self-heating process. In conclusion, PTBs has shown both similarities with common self-heating processes and important peculiarities such as the absence of pathogenic bacteria and the dominance of plant terpenoids with health characteristics among the VOCs confirming the evidence of beneficial effects in particular in the first three days.

Persistence of a mixed lactic acid bacterial starter culture during lysine fortification of sourdough breads by addition of pistachio powder.

Pistachio powder was added to flour or semolina to evaluate its contribution to increase the amount of lysine in bread. Bread production was carried out by sourdough technology using a selected 3-species (Lactobacillus sanfranciscensis/Leuconostoc citreum/Weissella cibaria) lactic acid bacterial (LAB) starter culture. All sourdoughs were subjected to a long-time fermentation (21 h) and showed levels of LAB around 109 CFU/g, indicating the suitability of pistachio powder for lactic fermentation. Yeasts were also detected, in particular in semolina trials. MiSeq Illumina technology was applied to investigate the bacterial composition of sourdoughs evidencing a different distribution of LAB species among the trials with Lactobacillus as major LAB group in almost all sourdoughs. Physicochemical parameters were comparable among the trials. After baking, pistachio powder was found not to influence the height of the breads, but pistachio breads were more firm than control breads. Color of the breads, void fraction and cell density, were influenced by pistachio powder. The amount of lysine increased consistently thanks to pistachio supplementation which also determined a higher presence of o-xylene, p-cymene and limonene and the appearance of α-pinene and 1-octen-3-ol in breads. Sensory tests showed the best appreciation scores for the breads produced with flour and pistachio powder.

Applying novel approaches for GC × GC-TOF-MS data cleaning and trends clustering in VOCs time-series analysis: Following the volatiles fate in grass baths through passive diffusion sampling.

Phytothermotherapy ("grass baths") is a traditional phytotherapy for rheumatism consisting of taking baths in hot fermenting grass. Scientific studies have demonstrated its efficiency in treating several rheumatic diseases. However the efficiency and repeatability of the therapy is dependent on the wild fermentations, determining sometimes the appearance of unpleasant conditions leading to the early abandonment of the therapy. The metabolism undergoing in the grass baths is unknown and there is not an established method to evaluate and predict grass baths quality. The aim of this study is to establish a simple VOCs profiling method able to evaluate the grass baths, predicting their evolution, through the identification of marker volatiles related to the best conditions and/or the spoilage. After replicating in real scale the traditional grass baths, the volatile profiles were measured using passive diffusion samplers injected in a thermal desorption-comprehensive GC × GC-TOF-MS. The high dimensionality of the data coupled with the limited number of time points, required a rigorous method development for the analysis of the data, achieved through the development of a novel R package for variable selection in GC × GC data matrices. The further application of a fuzzy clustering approach demonstrated to be a useful tool dealing with short time series, allowing to discard un-trending volatiles and giving a clear snapshot of the main trends in the data. A broad coverage of the volatolome was provided, thus suitable to describe the main metabolic changes ongoing in the grass baths. Coupling this data with the temperature and pH, and comparing it to the data from similar processes, like silage and compost, we demonstrated that the established method can be helpful to evaluate short time series, allowing us to obtain a list of volatiles as candidate markers for the quality of the grass baths. The established method gave a list of markers applicable to real scale grass baths to predict spoilage; furthermore it provides a list of volatiles where to search for candidate markers with reported health-related effects and can be used to generate hypothesis on the mechanisms of action of the treatment.