Paolo Bellassi

Sourdough fermentation is increasingly explored as a sustainable strategy for the valorisation of cereal-based by-products, although okara from oat- and rice-based beverage production remains largely underexplored. This study investigates the microbial evolution and nutritional characteristics of oat and rice okara sourdoughs obtained by spontaneous fermentation using the back-slopping technique. High-throughput sequencing revealed dynamic but matrix-dependent microbial composition. At the beginning of fermentation, oat okara was dominated by the Bacillus genus, while the Streptococcus genus was the most abundant in rice okara. After 30 days of back-slopping, the bacterial communities of both matrices were dominated by Lactobacillus, accounting for 80.1% and 73.3% of the relative abundance in oat and rice okara sourdoughs, respectively. Secondary bacterial taxa differed between matrices, with Weissella prevailing in oat okara (7.0%) and Acetobacter in rice okara (11.2%). Yeast communities showed a substrate-dependent temporal succession, being initially dominated by Pichia in both oat and rice okara sourdoughs (96.6% and 97.1%, respectively), whereas Saccharomyces became predominant at later fermentation stages, reaching 54.8% in oat okara and 83.5% in rice okara. From a nutritional perspective, okara sourdoughs exhibited promising characteristics, being rich in proteins and free amino acids, particularly glutamic acid, aspartic acid and leucine. The fatty acid profile was marked by oleic, linoleic and stearic acids, while nutritionally important minerals associated with musculoskeletal and immune function, such as calcium, zinc and selenium, were present in relevant quantities in the sourdoughs. These findings provide new insights into oat and rice okara sourdoughs and support the use of fermented okara as a sustainable ingredient with potential functional relevance.

Four strains, representing two novel Bifidobacterium species, were isolated from water kefir, a fermented beverage. 16S rRNA gene analysis suggested that the novel species share high identities (98.82–98.89%) with Bifidobacterium aquikefiri LMG 28769^T. Complete genomes were assembled with a short- and long-read hybrid sequencing approach. In agreement with the 16S rRNA gene analysis, phylogenetics with 117 marker genes places the novel species closest to B. aquikefiri LMG 28769^T as well. The isolates have average nucleotide identity (ANI) scores ranging from 81.46 to 84.84% and digital DNA–DNA hybridization (dDDH) scores from 23.9 to 38.5% with the closest related species, as well as ANI scores between the proposed new species of 80.50%, indicating that the isolates represent two novel species. Matrix-assisted laser desorption/ionization-time of flight chemotaxonomic analysis supported the gene-based taxonomic placement. We propose the names Bifidobacterium fermentum sp. nov. and Bifidobacterium aquikefiricola sp. nov. for these novel species within the Bifidobacterium genus. The proposed type strain B. fermentum WK012_4_13^T (= LMG 33104^T = DSM 116073^T; GenBank accession number GCF_041080835.1) has a genome size of 2.43 Mbp, with a G+C content of 56.00 mol%. The proposed type strain for B. aquikefiricola WK041_4_12^T (= LMG 33105^T = DSM 116074^T; GenBank accession number GCF_041080795.1) has a genome size of 2.36 Mbp and a G+C content of 53.94 mol%. B. fermentum cells are Gram-positive staining, non-motile, non-spore-forming, fructose-6-phosphate phosphoketolase (F6PPK)-positive, catalase- and oxidase-negative and bacillary club shaped. B. aquikefiricola cells are Gram-positive staining, non-motile, non-spore-forming, F6PPK-positive, catalase- and oxidase-negative and square rod shaped.

This paper introduces a novel method for raw cow milk classification combining speckle pattern (SP) imaging and AI-based processing of statistical parameters. Raw cow milk has been classified considering (i) 6 statistical features extracted from raw SP images, and (ii) 4 features extracted from the Gray-Level Co-occurrence Matrix (GLCM) computed on each SP image. We conducted 4 experimental campaigns, resulting in 24, 000 SP images retrieved from 20 milks produced by 20 cows. We then considered two different datasets: (i) a Complete dataset (made of all 24,000 frames), and (ii) a Reduced dataset, built by excluding data from one acquisition campaign. The two datasets were then split into training and testing sub-datasets. We trained three Wide Neural Networks (WNN) using different strategies. WNN1 and WNN2 have been trained and tested using the Complete and the Reduced datasets respectively, while WNN3 has been trained on the Reduced tested on the Complete dataset. WNN3 only attained 72% accuracy (revealing sensitivity to environmental conditions), while WNN1 and WNN2 achieved a test accuracy higher than 90%, demonstrating effectiveness without relying on computationally expensive models such as CNNs. This approach could be considered as a promising initial step for cow milk classification using SP imaging.

Archaeal cell factories are becoming of great interest given their ability to produce a broad range of value-added compounds. Moreover, the Archaea domain often includes extremophilic microorganisms, facilitating their cultivation at the industrial level under nonsterile conditions. Halophilic archaea are studied for their ability to grow in environments with high NaCl concentrations. In this study, nine strains of Halobacterium salinarum were isolated from three different types of salted food, sausage casings, salted codfish, and bacon, and their genomes were sequenced along with the genome of the collection strain CECT 395. A comparative genomic analysis was performed on these newly sequenced genomes and the publicly available ones for a total of 19 H. salinarum strains. We elucidated the presence of unique gene clusters of the species in relation to the different ecological niches of isolation (salted foods, animal hides, and solar saltern sediments). Moreover, genome mining at the single-strain level highlighted the metabolic potential of H. salinarum UC4242, which revealed the presence of different protechnological genes (vitamins and myo-inositol biosynthetic pathways, aroma- and texture-related features, and antimicrobial compounds). Despite the presence of genes of potential concern (e.g., those involved in biogenic amine production), all the food isolates presented archaeocin-related genes (halocin-C8 and sactipeptides).

A novel Gram-stain-positive, strictly aerobic, short rod-shaped bacterium, designated 2CT, was isolated from freshly packaged microfiltered milk. This strain was able to grow within the NaCl concentration range of 0–5 % (w/v), temperature range of 8–37 °C (optimally at 30 °C) and at pH 6.0–10.0. Phylogenetic analysis based on 16S rRNA gene sequences revealed that strain 2CT was closely related to species of the genus Microbacterium , with the highest sequence similarity (99.2 %) to Microbacterium lacticum DSM 20427T as well as Microbacterium flavum DSM 18909T (=YM18-098T). The phylogenetic tree based on 16S rRNA genes showed that strain 2CT clustered with M. flavum DSM 18909T. However, the phylogenetic tree based on concatenated 16S rRNA and four housekeeping genes showed that strain 2CT clustered with M. lacticum DSM 20427T. Furthermore, the phylogenomic tree showed that strain 2CT clustered with M. lacticum DSM 20427T and M. flavum DSM 18909T. The major respiratory quinones were MK-10, MK-11 and MK-12. The predominant cellular fatty acids were anteiso-C15 : 0, iso-C16 : 0 and anteiso-C17 : 0. The polar lipid composition of strain 2CT consisted of diphosphatidylglycerol, phosphatidylglycerol, three unidentified glycolipids and two unidentified lipids. The cell-wall peptidoglycan type was a variant of B1α {Gly} [l-Lys] d-Glu-l-Lys, with the amino acids lysine, glycine, alanine and glutamic acid. The whole-cell sugars consisted of galactose, glucose, ribose and minor amounts of rhamnose. In addition, strain 2CT showed a glycolyl-type cell wall. The genomic DNA G+C content was 69.8mol%, while the average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values with the closely related Microbacterium species were below the recognized thresholds of 95–96 % ANI and 70 % DDH for species definition. Based on the phenotypic and genotypic data, strain 2CT (=LMG 32277T=CECT 30329T) is considered to represent a new species, for which the name Microbacterium paulum sp. nov. is proposed.

This work investigated the microbiological quality and chemical profiles of two different dairy creams obtained by centrifugation vs. natural creaming separation systems. To this aim, an untargeted metabolomics approach based on UHPLC-QTOF mass spectrometry was used in combination with multivariate statistical tools to find potential marker compounds of the two different types of two dairy creams. Thereafter, we evaluated the chemical, microbiological and sensorial changes of a ricotta cheese made with a 30% milk cream (i.e., made by combining dairy creams from centrifugation and natural creaming separation) during its shelf-life period (12 days). Overall, microbiological analysis revealed no significant differences between the two types of dairy creams. On the contrary, the trend observed in the growth of degradative bacteria in ricotta during shelf-life was significant. Metabolomics revealed that triacylglycerols and phospholipids showed significant strong down-accumulation trends when comparing samples from the centrifugation and natural creaming separation methods. Additionally, 2,3-Pentanedione was among the best discriminant compounds characterising the shelf-life period of ricotta cheese (VIP score = 1.02), mainly related to sensorial descriptors, such as buttery and cheesy. Multivariate statistics showed a clear impact of the shelf-life period on the ricotta cheese, revealing 139 potential marker compounds (mainly included in amino acids and lipids). Therefore, the approach used showed the potential of a combined metabolomic, microbiological and sensory approach to discriminate ricotta cheese during the shelf-life period.

Pseudomonas fluorescens is a psychrotrophic species associated with milk spoilage because of its lipolytic and proteolytic activities. Consequently, monitoring P. fluorescens or its antecedent activity in milk is critical to preventing quality defects of the product and minimizing food waste. Therefore, in this study, untargeted metabolomics and peptidomics were used to identify the changes in milk related to P. fluorescens activity by simulating the low-temperature conditions usually found in milk during the cold chain. Both unsupervised and supervised multivariate statistical approaches showed a clear effect caused by the P. fluorescens inoculation on milk samples. Our results showed that the levels of phosphatidylglycerophosphates and glycerophospholipids were directly related to the level of contamination. In addition, our metabolomic approach allowed us to detect lipid and protein degradation products that were directly correlated with the degradative metabolism of P. fluorescens. Peptidomics corroborated the proteolytic propensity of P. fluorescens-contaminated milk, but with lower sensitivity. The results obtained from this study provide insights into the alterations related to P. fluorescens 39 contamination, both pre and post heat treatment. This approach could represent a potential tool to retrospectively understand the actual quality of milk under cold chain storage conditions, either before or after heat treatments.