Epirus Cheese Microbial Profiles
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PROVIDER: PRJEB85759 | ENA |
REPOSITORIES: ENA
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Project description:The intra sub-species diversity of six strains of Lactococcus lactis subsp. lactis was investigated at the genomic level and in terms of phenotypic and transcriptomic profiles in UF-cheese model. Six strains were isolated from various sources, but all are exhibiting a dairy phenotype. Our results showed that, the six strains exhibited small phenotypic differences since similar behaviour in terms of growth was obtained during cheese ripening while only different acidification capability was detected. Even if all strains displayed high genomic similarities, sharing a high core genome of almost two thousands genes, the expression of this core genome directly in the cheese matrix revealed major strain-specific differences. This strains with the same dairy origin. Strains were cultured on skimmed raw milk ultrafiltration (UF) retentate. The UF retentate was pre-incubated overnight at 4 °C, then 45 minutes at 50 °C and homogenized during 1.5 minutes at 24 000 rpm with an ultra-turax (Imlab, France). After addition of rennet (0.3 µl ml-1), 400 g UF retentate was inoculated at 2 106 CFU/g with L. lactis subsp. lactis strains. After incubation for 8 hours at 30 °C, the cheeses were transferred at 12° C until 7 days for ripening simulation. At least three independent cultures of the six strains were performed. Total RNA was extracted from cells grown 24 hours in UF-cheese and radiolabelled cDNA were prepared and hybridized on nylon arrays. 1948 amplicons specific of Lactococcus lactis IL1403 genes were spotted twice on the array. 3 independent repetitions were performed.
2012-09-07 | E-GEOD-23987 | biostudies-arrayexpress
Project description:Historic Rebel cheese: microbial communities, volatilome, terpenes and fatty acid profiles reveal a huge biodiversity in cheeses produced in a limited area
| PRJNA644819 | ENA
Project description:Cheese is generally considered a safe and nutritious food, but foodborne illnesses linked to cheese consumption have occurred in many countries. Several microbial risk assessments related to Listeria monocytogenes, Staphylococcus aureus, and Escherichia coli infections, causing cheese-related foodborne illnesses, have been conducted. Although the assessments of microbial risk in soft and low moisture cheeses such as semi-hard and hard cheeses have been accomplished, it has been more focused on the correlations between pathogenic bacteria and soft cheese, because cheese-associated foodborne illnesses have been attributed to the consumption of soft cheeses. As a part of this microbial risk assessment, predictive models have been developed to describe the relationship between several factors (pH, Aw, starter culture, and time) and the fates of foodborne pathogens in cheese. Predictions from these studies have been used for microbial risk assessment as a part of exposure assessment. These microbial risk assessments have identified that risk increased in cheese with high moisture content, especially for raw milk cheese, but the risk can be reduced by preharvest and postharvest preventions. For accurate quantitative microbial risk assessment, more data including interventions such as curd cooking conditions (temperature and time) and ripening period should be available for predictive models developed with cheese, cheese consumption amounts and cheese intake frequency data as well as more dose-response models.
| S-EPMC4811779 | biostudies-other
Project description:IntroductionLactic acid bacteria (LAB) communities shape the sensorial and functional properties of artisanal hard-cooked and long-ripened cheeses made with raw bovine milk like Parmigiano Reggiano (PR) cheese. While patterns of microbial evolution have been well studied in PR cheese, there is a lack of information about how this microbial diversity affects the metabolic and functional properties of PR cheese.MethodsTo fill this information gap, we characterized the cultivable fraction of natural whey starter (NWS) and PR cheeses at different ripening times, both at the species and strain level, and investigated the possible correlation between microbial composition and the evolution of peptide profiles over cheese ripening.Results and discussionThe results showed that NWS was a complex community of several biotypes belonging to a few species, namely, Streptococcus thermophilus, Lactobacillus helveticus, and Lactobacillus delbrueckii subsp. lactis. A new species-specific PCR assay was successful in discriminating the cheese-associated species Lacticaseibacillus casei, Lacticaseibacillus paracasei, Lacticaseibacillus rhamnosus, and Lacticaseibacillus zeae. Based on the resolved patterns of species and biotype distribution, Lcb. paracasei and Lcb. zeae were most frequently isolated after 24 and 30 months of ripening, while the number of biotypes was inversely related to the ripening time. Peptidomics analysis revealed more than 520 peptides in cheese samples. To the best of our knowledge, this is the most comprehensive survey of peptides in PR cheese. Most of them were from β-caseins, which represent the best substrate for LAB cell-envelope proteases. The abundance of peptides from β-casein 38-88 region continuously increased during ripening. Remarkably, this region contains precursors for the anti-hypertensive lactotripeptides VPP and IPP, as well as for β-casomorphins. We found that the ripening time strongly affects bioactive peptide profiles and that the occurrence of Lcb. zeae species is positively linked to the incidence of eight anti-hypertensive peptides. This result highlighted how the presence of specific LAB species is likely a pivotal factor in determining PR functional properties.
| S-EPMC10985727 | biostudies-literature
Project description:The anaerobic digestion microbiomes has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and phenotypics, in their ability to reflect the full-scale anaerobic digestion microbiome. The phenotypic fingerprinting reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and phenotypic traits, yielded certain similar features yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, phenotypic fingerprinting is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.
2021-05-26 | PXD024788 | Pride
Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
2017-05-12 | PXD006118 | Pride
Project description:The interactions that occur during the ripening of smear cheeses are not well understood. Yeast-yeast interactions and yeast-bacterium interactions were investigated within a microbial community composed of three yeasts and six bacteria found in cheese. The growth dynamics of this community was precisely described during the ripening of a model cheese, and the Lotka-Volterra model was used to evaluate species interactions. Subsequently, the effects on ecosystem functioning of yeast omissions in the microbial community were evaluated. It was found both in the Lotka-Volterra model and in the omission study that negative interactions occurred between yeasts. Yarrowia lipolytica inhibited mycelial expansion of Geotrichum candidum, whereas Y. lipolytica and G. candidum inhibited Debaryomyces hansenii cell viability during the stationary phase. However, the mechanisms involved in these interactions remain unclear. It was also shown that yeast-bacterium interactions played a significant role in the establishment of this multispecies ecosystem on the cheese surface. Yeasts were key species in bacterial development, but their influences on the bacteria differed. It appeared that the growth of Arthrobacter arilaitensis or Hafnia alvei relied less on a specific yeast function because these species dominated the bacterial flora, regardless of which yeasts were present in the ecosystem. For other bacteria, such as Leucobacter sp. or Brevibacterium aurantiacum, growth relied on a specific yeast, i.e., G. candidum. Furthermore, B. aurantiacum, Corynebacterium casei, and Staphylococcus xylosus showed reduced colonization capacities in comparison with the other bacteria in this model cheese. Bacterium-bacterium interactions could not be clearly identified.
| S-EPMC2223212 | biostudies-literature
Project description:Aside from their amino acid content, dairy proteins are valuable for their ability to carry encrypted bioactive peptides whose activities are latent until released by digestive enzymes or endogenous enzymes within the food. Peptides can possess a wide variety of functionalities, such as antibacterial, antihypertensive, and antioxidative properties, as demonstrated by in vitro and in vivo studies. This phenomenon raises the question as to what impact various traditional cheese-making processes have on the formation of bioactive peptides in the resulting products. In this study, we have profiled the naturally-occurring peptides in two hard and two soft traditional cheeses and have identified their known bioactive sequences. While past studies have typically identified fewer than 100 peptide sequences in a single cheese, we have used modern instrumentation to identify between 2900 and 4700 sequences per cheese, an increase by a factor of about 50. We demonstrated substantial variations in proteolysis and peptide formation between the interior and rind of each cheese, which we ascribed to the differences in microbial composition between these regions. We identified a total of 111 bioactive sequences among the four cheeses, with the greatest number of sequences, 89, originating from Mimolette. The most common bioactivities identified were antimicrobial and inhibition of the angiotensin-converting enzyme. This work revealed that cheese proteolysis and the resulting peptidomes are more complex than originally thought in terms of the number of peptides released, variation in peptidome across sites within a single cheese, and variation in bioactive peptides among cheese-making techniques.
2020-12-23 | PXD021426 | Pride
Project description:Cheese fermentation and flavour formation are the result of complex biochemical reactions driven by the activity of multiple microorganisms. Here, we studied the roles of microbial interactions in flavour formation in a year-long Cheddar cheese making process, using a commercial starter culture containing Streptococcus thermophilus and Lactococcus strains. By using an experimental strategy whereby certain strains were left out from the starter culture, we show that S. thermophilus has a crucial role in boosting Lactococcus growth and shaping flavour compound profile. Controlled milk fermentations with systematic exclusion of single Lactococcus strains, combined with genomics, genome-scale metabolic modelling, and metatranscriptomics, indicated that S. thermophilus proteolytic activity relieves nitrogen limitation for Lactococcus and boosts de novo nucleotide biosynthesis. While S. thermophilus had large contribution to the flavour profile, Lactococcus cremoris also played a role by limiting diacetyl and acetoin formation, which otherwise results in an off-flavour when in excess. This off-flavour control could be attributed to the metabolic re-routing of citrate by L. cremoris from diacetyl and acetoin towards α-ketoglutarate. Further, closely related Lactococcus lactis strains exhibited different interaction patterns with S. thermophilus, highlighting the significance of strain specificity in cheese making. Our results highlight the crucial roles of competitive and cooperative microbial interactions in shaping cheese flavour profile.
| S-EPMC10739706 | biostudies-literature