Gaba-producing lactobacilli boost cognitive reactivity to negative mood without improving cognitive performance: A human Double-Blind Placebo-Controlled Cross-Over study.

BACKGROUND: Psychobiotic bacteria are probiotics able to influence stress-related behavior, sleep, and cognitive outcomes. Several in vitro and human studies were performed to assess their physiological potential, to find strains having psychotropic activity in humans, and to elucidate the metabolic pathways involved. In our previous in vitro study, we identified two strains Levilactobacillus brevis P30021 and Lactiplantibacillus plantarum P30025, able to produce GABA and acetylcholine, being promising candidates to provide an effect on mood and cognitive performance. AIM: To investigate the effects of probiotics in the alleviation on the cognitive performance of moderately stressed healthy adults. Secondary outcomes were related to mood improvement, production of GABA, glutamate, acetylcholine, and choline and modification of the microbiota composition. METHODS: A 12-week randomized, double-blind, placebo-controlled, cross-over study investigated the effects of a probiotic formulation (Levilactobacillus brevis P30021 and Lactiplantibacillus plantarum P30025) on psychological, memory, and cognition parameters in 44 (Probiotic = 44, Placebo = 43) adults with a mean age of 29 ±â€¯5.7 years old by CogState Battery test. Subjects-inclusion criteria was a mild-moderate (18.7 ±â€¯4.06) stress upon diagnosis using the DASS-42 questionnaire. RESULTS: Probiotic treatment had no effect on subjective stress measures. The probiotic formulation showed a significant beneficial effect on depressive symptoms by reducing cognitive reactivity to sad mood (p = 0.034). Rumination significantly improved after intake of the probiotic (p = 0.006), suggesting a potential benefit in reducing the negative cognitive effects associated with depression and improving overall mental health. When stratifying the treated subjects according to the response, we found an increase in the abundance of the probiotic genera in the gut microbiota of positive responders (p = 0.009 for Lactiplantibacillus and p = 0.004 for L.brevis). No relevant correlations were observed between the neurotransmitter concentration in the faecal sample, scores of LEIDS, DASS-42, and cognitive tests. CONCLUSION: We highlight the potential of this probiotic preparation to act as psycobiotics for the relief of negative mood feelings. The assessment of the psychotropic effects of dietary interventions in human participants has many challenges. Further interventional studies investigating the effect of these psychobiotic bacteria in populations with stressed-related disorders are required including longer period of intervention and larger sample size in order to verify the effects of the treatment on further stress-related indicators.

Relationships between diet and gut microbiome in an Italian and Dutch cohort: does the dietary protein to fiber ratio play a role?

PURPOSE: To investigate the relationships between the habitual diet, the protein to fiber ratio (P/F), and the gut microbiome in one Italian and one Dutch cohort of healthy subjects consuming an omnivore diet. METHODS: The Italian cohort included 19 males (M_IT, BMI 25.2 ± 0.72 kg/m2, age 25.4 ± 0.96 years) and 20 females (F_IT, BMI 23.9 ± 0.81 kg/m2, age 23.8 ± 0.54 years); the Dutch cohort included 30 females (F_NL, BMI: 23.9 ± 0.81 kg/m2, age: 23.8 ± 0.54 years). Individual diets were recorded through Food Frequency Questionnaires and analyzed to assess the nutrient composition. Gut microbiome was assessed in fecal samples. RESULTS: M_IT consumed higher levels of proteins than F_NL and F_IT, whereas dietary fiber intake did not differ among groups. Data showed that consumption of plant protein to animal protein (PP/AP) and PP to total proteins ratio can determine a differentiation of F_NL more than the absolute amount of dietary fiber. Conversely, the protein to fiber (P/F) and AP to total proteins better characterized M_IT. M_IT harbored the highest abundance of proteolytic microorganisms and the lowest microbial gene richness. Conversely, F_NL had more fiber-degrading microorganisms like Bacteroides thetaiotaomicron, Bacteroides xylanisolvens, Roseburia sp., Coprococcus eutactus and Parabacteroides along with the highest number of genes encoding carbohydrate-active enzymes and gene richness. It was predicted that by each unit decrease in the P/F a 3% increase in gene richness occurred. CONCLUSION: Study findings suggested that dietary P/F, rather than the absolute amount of dietary fiber, could contribute to the shaping of the microbiome towards a more proteolytic or fiber-degrading gut ecosystem. CLINICALTRIALS: gov Identifier NCT04205045-01-10-2018, retrospectively registered. Dutch Trial Register NTR7531-05-10-2018.

Microbiome signatures associated with flavor development differentiate Protected Designation of origin water Buffalo Mozzarella cheese from different production areas.

Water Buffalo Mozzarella (BM) is a typical cheese from Southern Italy with unique flavor profile and texture. It is produced following a traditional back-slopping procedure and received the Protected Designation of Origin (PDO) label. To better understand the link between the production area, the microbiome composition and the flavor profile of the products, we performed a multiomic characterization of PDO BM collected from 57 different dairies located in the two main PDO production area, i.e. Caserta (n = 35) and Salerno (n = 22). Thus, we assessed the microbiome by high-throughput shotgun metagenomic sequencing and the Volatile Organic Compounds (VOCs) by gas chromatography/mass spectrometry (GC/MS). Streptococcus thermophilus, Lactobacillus helveticus, and Lactobacillus delbrueckii subsp. delbrueckii were identified as the core microbiome present in all samples. However, the microbiome taxonomic profiles resulted in a clustering of the samples based on their geographical origin, also showing that BM from Caserta had a greater microbial diversity. Consistently, Caserta and Salerno samples also showed different VOC profiles. These results suggest that the microbiome and its specific metabolic activity are part of the terroir that shape BM specific features, linking this traditional product with the area of production, thus opening new clues for improving traceability and fraud protection of traditional products.

Microbiome dynamics, antibiotic resistance gene patterns and spoilage-associated genomic potential in fresh anchovies stored in different conditions.

Fresh fish is a highly perishable product and is easily spoiled by microbiological activity and chemical oxidation of lipids. However, microbial spoilage is the main factor linked with the rapid fish sensorial degradation due to the action of specific spoilage organisms (SSOs) that have the ability to dominate over other microorganisms and produce metabolites responsible for off-flavours. We explored the microbial dynamics in fresh anchovies stored in different packaging (air, modified atmosphere, under vacuum) and temperatures (0, 4 and 10 °C) using shotgun metagenomics, highlighting the selection of different microbial species according to the packaging type. Indeed, Pseudoalteromonas nigrifaciens, Psychrobacter cryohalolentis and Ps. immobilis, Pseudomonas deceptionensis and Vibrio splendidus have been identified as the main SSOs in aerobically stored anchovies, while Shewanella baltica, Photobacterium iliopiscarium, Ps. cryohalolentis and Ps. immobilis prevailed in VP and MAP. In addition, we identified the presence of spoilage-associated genes, leading to the potential production of biogenic amines and different off-flavors (H2S, TMA). In particular, the abundance of microbial genes leading to BA biosynthesis increased at higher storage temperature, while those related to H2S and TMA production were enriched in aerobically and VP packed anchovies, suggesting that MAP could be an effective strategy in delaying the production of these compounds. Finally, we provided evidence of the presence of a wide range of antibiotic resistance genes conferring resistance to different classes of antibiotic (ß-lactams, tetracyclines, polymyxins, trimethoprims and phenicols) and highlighted that storage at higher temperature (4 and 10 °C) boosted the abundance of ARG-carrying taxa, especially in aerobically and MAP packed fish.

Fermented foods, their microbiome and its potential in boosting human health.

Fermented foods (FFs) are part of the cultural heritage of several populations, and their production dates back 8000 years. Over the last ~150 years, the microbial consortia of many of the most widespread FFs have been characterised, leading in some instances to the standardisation of their production. Nevertheless, limited knowledge exists about the microbial communities of local and traditional FFs and their possible effects on human health. Recent findings suggest they might be a valuable source of novel probiotic strains, enriched in nutrients and highly sustainable for the environment. Despite the increasing number of observational studies and randomised controlled trials, it still remains unclear whether and how regular FF consumption is linked with health outcomes and enrichment of the gut microbiome in health-associated species. This review aims to sum up the knowledge about traditional FFs and their associated microbiomes, outlining the role of fermentation with respect to boosting nutritional profiles and attempting to establish a link between FF consumption and health-beneficial outcomes.

Negative plant-soil feedback in Arabidopsis thaliana: Disentangling the effects of soil chemistry, microbiome, and extracellular self-DNA.

Nutrient deficiency, natural enemies and litter autotoxicity have been proposed as possible mechanisms to explain species-specific negative plant-soil feedback (PSF). Another potential contributor to negative PSF is the plant released extracellular self-DNA during litter decay. In this study, we sought to comprehensively investigate these hypotheses by using Arabidopsis thaliana (L.) Heynh as a model plant in a feedback experiment. The experiment comprised a conditioning phase and a response phase in which the conditioned soils underwent four treatments: (i) addition of activated carbon, (ii) washing with tap water, (iii) sterilization by autoclaving, and (iv) control without any treatment. We evaluated soil chemical properties, microbiota by shotgun sequencing and the amount of A. thaliana extracellular DNA in the differently treated soils. Our results showed that washing and sterilization treatments mitigated the negative PSF effect. While shifts in soil chemical properties were not pronounced, significant changes in soil microbiota were observed, especially after sterilization. Notably, plant biomass was inversely associated with the content of plant self-DNA in the soil. Our results suggest that the negative PSF observed in the conditioned soil was associated to increased amounts of soilborne pathogens and plant self-DNA. However, fungal pathogens were not limited to negative conditions, butalso found in soils enhancing A.thaliana growth. In-depth multivariate analysis highlights that the hypothesis of negative PSF driven solely by pathogens lacks consistency. Instead, we propose a multifactorial explanation for the negative PSF buildup, in which the accumulation of self-DNA weakens the plant's root system, making it more susceptible to pathogens.

Explainable artificial intelligence and microbiome data for food geographical origin: the Mozzarella di Bufala Campana PDO Case of Study.

Identifying the origin of a food product holds paramount importance in ensuring food safety, quality, and authenticity. Knowing where a food item comes from provides crucial information about its production methods, handling practices, and potential exposure to contaminants. Machine learning techniques play a pivotal role in this process by enabling the analysis of complex data sets to uncover patterns and associations that can reveal the geographical source of a food item. This study aims to investigate the potential use of explainable artificial intelligence for identifying the food origin. The case of study of Mozzarella di Bufala Campana PDO has been considered by examining the composition of the microbiota in each samples. Three different supervised machine learning algorithms have been compared and the best classifier model is represented by Random Forest with an Area Under the Curve (AUC) value of 0.93 and the top accuracy of 0.87. Machine learning models effectively classify origin, offering innovative ways to authenticate regional products and support local economies. Further research can explore microbiota analysis and extend applicability to diverse food products and contexts for enhanced accuracy and broader impact.

Microbiome mapping in beef processing reveals safety-relevant variations in microbial diversity and genomic features.

The microbiome of surfaces along the beef processing chain represents a critical nexus where microbial ecosystems play a pivotal role in meat quality and safety of end products. This study offers a comprehensive analysis of the microbiome along beef processing using whole metagenomics with a particular focus on antimicrobial resistance and virulence-associated genes distribution. Our findings highlighted that microbial communities change dynamically in the different steps along beef processing chain, influenced by the specific conditions of each micro-environment. Brochothrix thermosphacta, Carnobacterium maltaromaticum, Pseudomonas fragi, Psychrobacter cryohalolentis and Psychrobacter immobilis were identified as the key species that characterize beef processing environments. Carcass samples and slaughterhouse surfaces exhibited a high abundance of antibiotic resistance genes (ARGs), mainly belonging to aminoglycosides, ß-lactams, amphenicols, sulfonamides and tetracyclines antibiotic classes, also localized on mobile elements, suggesting the possibility to be transmitted to human pathogens. We also evaluated how the initial microbial contamination of raw beef changes in response to storage conditions, showing different species prevailing according to the type of packaging employed. We identified several genes leading to the production of spoilage-associated compounds, and highlighted the different genomic potential selected by the storage conditions. Our results suggested that surfaces in beef processing environments represent a hotspot for beef contamination and evidenced that mapping the resident microbiome in these environments may help in reducing meat microbial contamination, increasing shelf-life, and finally contributing to food waste restraint.

Exposure to environmental pollutants selects for xenobiotic-degrading functions in the human gut microbiome.

Environmental pollutants from different chemical families may reach the gut microbiome, where they can be metabolized and transformed. However, how our gut symbionts respond to the exposure to environmental pollution is still underexplored. In this observational, cohort study, we aim to investigate the influence of environmental pollution on the gut microbiome composition and potential activity by shotgun metagenomics. We select as a case study a population living in a highly polluted area in Campania region (Southern Italy), proposed as an ideal field for exposomic studies and we compare the fecal microbiome of 359 subjects living in areas with high, medium and low environmental pollution. We highlight changes in gut microbiome composition and functionality that were driven by pollution exposure. Subjects from highly polluted areas show higher blood concentrations of dioxin and heavy metals, as well as an increase in microbial genes related to degradation and/or resistance to these molecules. Here we demonstrate the dramatic effect that environmental xenobiotics have on gut microbial communities, shaping their composition and boosting the selection of strains with degrading capacity. The gut microbiome can be considered as a pivotal player in the environment-health interaction that may contribute to detoxifying toxic compounds and should be taken into account when developing risk assessment models. The study was registered at ClinicalTrials.gov with the identifier NCT05976126.

Microbiome mapping in dairy industry reveals new species and genes for probiotic and bioprotective activities.

The resident microbiome in food industries may impact on food quality and safety. In particular, microbes residing on surfaces in dairy industries may actively participate in cheese fermentation and ripening and contribute to the typical flavor and texture. In this work, we carried out an extensive microbiome mapping in 73 cheese-making industries producing different types of cheeses (fresh, medium and long ripened) and located in 4 European countries. We sequenced and analyzed metagenomes from cheese samples, raw materials and environmental swabs collected from both food contact and non-food contact surfaces, as well as operators' hands and aprons. Dairy plants were shown to harbor a very complex microbiome, characterized by high prevalence of genes potentially involved in flavor development, probiotic activities, and resistance to gastro-intestinal transit, suggesting that these microbes may potentially be transferred to the human gut microbiome. More than 6100 high-quality Metagenome Assembled Genomes (MAGs) were reconstructed, including MAGs from several Lactic Acid Bacteria species and putative new species. Although microbial pathogens were not prevalent, we found several MAGs harboring genes related to antibiotic resistance, highlighting that dairy industry surfaces represent a potential hotspot for antimicrobial resistance (AR) spreading along the food chain. Finally, we identified facility-specific strains that can represent clear microbial signatures of different cheesemaking facilities, suggesting an interesting potential of microbiome tracking for the traceability of cheese origin.

Improved sampling and DNA extraction procedures for microbiome analysis in food-processing environments.

Deep investigation of the microbiome of food-production and food-processing environments through whole-metagenome sequencing (WMS) can provide detailed information on the taxonomic composition and functional potential of the microbial communities that inhabit them, with huge potential benefits for environmental monitoring programs. However, certain technical challenges jeopardize the application of WMS technologies with this aim, with the most relevant one being the recovery of a sufficient amount of DNA from the frequently low-biomass samples collected from the equipment, tools and surfaces of food-processing plants. Here, we present the first complete workflow, with optimized DNA-purification methodology, to obtain high-quality WMS sequencing results from samples taken from food-production and food-processing environments and reconstruct metagenome assembled genomes (MAGs). The protocol can yield DNA loads >10 ng in >98% of samples and >500 ng in 57.1% of samples and allows the collection of, on average, 12.2 MAGs per sample (with up to 62 MAGs in a single sample) in ~1 week, including both laboratory and computational work. This markedly improves on results previously obtained in studies performing WMS of processing environments and using other protocols not specifically developed to sequence these types of sample, in which <2 MAGs per sample were obtained. The full protocol has been developed and applied in the framework of the European Union project MASTER (Microbiome applications for sustainable food systems through technologies and enterprise) in 114 food-processing facilities from different production sectors.