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.
Project description:Background: The soil environment is responsible for sustaining most terrestrial plant life on earth, yet we know surprisingly little about the important functions carried out by diverse microbial communities in soil. Soil microbes that inhabit the channels of decaying root systems, the detritusphere, are likely to be essential for plant growth and health, as these channels are the preferred locations of new root growth. Understanding the microbial metagenome of the detritusphere and how it responds to agricultural management such as crop rotations and soil tillage will be vital for improving global food production. Methods: The rhizosphere soils of wheat and chickpea growing under + and - decaying root were collected for metagenomics sequencing. A gene catalogue was established by de novo assembling metagenomic sequencing. Genes abundance was compared between bulk soil and rhizosphere soils under different treatments. Conclusions: The study describes the diversity and functional capacity of a high-quality soil microbial metagenome. The results demonstrate the contribution of the microbiome from decaying root in determining the metagenome of developing root systems, which is fundamental to plant growth, since roots preferentially inhabit previous root channels. Modifications in root microbial function through soil management, can ultimately govern plant health, productivity and food security.
Project description:This is the first metaproteomics-based featuring of the microbial community harbured in the traditional raw milk Caprino Nicastrese cheese
Project description:In a prior report, we observed two distinct lung microbiomes in healthy subjects that we termed â??pneumotypesâ??: pneumotypeSPT, characterized by high bacterial load and supraglottic predominant taxa (SPT) such as the anaerobes Prevotella and Veillonella; and pneumotypeBPT, with low bacterial burden and background predominant taxa (BPT) found in the saline lavage and bronchoscope. Here, we determined the prevalence of these two contrasting lung microbiome types, in a multi-center study of healthy subjects. We confirmed that a lower airway microbiome enriched with upper airway microbes (pneumotypeSPT) was present in ~45% of healthy individuals. Cross-sectional Multicenter cohort. BAL of 49 healthy subjects from three cohort had their lower airway microbiome assessed by 16S rDNA sequencing and microbial gene content (metagenome) was computationally inferred from taxonomic assignments. The amplicons from total 100 samples are barcoded; the barcode and other clinical characteristics (e.g. inflammatory biomarkers and metabolome data) for each sample are provided in the 'Pneumotype.sep.Map.A1.txt' file.