Similar Datasets
Project description:This study examines the proteolytic activity of the kefir grains (a combination of bacteria and yeast) on bovine milk proteins. SDS-PAGE analysis reveals substantial digestion of milk proteins by the kefir grains in comparison with control samples. Mass spectrometric analysis reveals that the kefir microorganisms released 609 new peptide fragments and significantly altered the abundance of around 1,500 peptides compared to the controls. These kefir-digested peptides derived from 55 milk proteins. We show that kefir contains 25 previously identified functional peptides with actions including antihypertensive, antimicrobial, opioid and anti-oxidative .
2016-05-09 | PXD001826 | Pride
Project description:We got insights into the B. bifidum PRL2010 genes whose expression resulted to be affected when bacterial cells were cultivated on kefir and kefiran as the unique carbon source. In order to exploit the transcriptome of PRL2010 grown on kefir and hefiran we performed global transcription profiling using PRL2010 microarrays hybridized with cDNA from the RNA samples of B. bifidum PRL2010 cultivated on these substrates. We isolated mRNA from B. bifidum PRL2010 cells collected from a culture of kefir grains and from PRL2010 cultivated on MRS plus kefiran at upon 12 hours following inoculation. Microarray analysis was performed with an oligonucleotide array based on the B. bifidum PRL2010 genome: a total of 8,130 oligonucleotide probes of 60bp in length were designed on 1707 ORFs using eArray5.0 (Agilent Technologies). 5 Oligos were designed for each gene on a 4x44k Agilent Microarrays(Agilent Technologies, Santa Clara, CA, USA). Replicates were distributed on the chip at random, non-adjacent positions.
2016-07-03 | E-GEOD-50506 | biostudies-arrayexpress
Project description:We got insights into the B. bifidum PRL2010 genes whose expression resulted to be affected when bacterial cells were cultivated on kefir and kefiran as the unique carbon source.
2016-01-01 | GSE50506 | GEO
Project description:Multi-omics has the promise to provide a detailed molecular picture for biological systems. Although obtaining multi-omics data is relatively easy, methods that analyze such data have been lagging. In this paper, we present an algorithm that uses probabilistic graph representations and external knowledge to perform optimum structure learning and deduce a multifarious interaction network for multi-omics data from a bacterial community. Kefir grain, a microbial community that ferments milk and creates kefir, represents a self-renewing, stable, natural microbial community. Kefir has been shown to associate with a wide range of health benefits. We obtained a controlled bacterial community using the two most abundant and well-studied species in kefir grains: Lentilactobacillus kefiri and Lactobacillus kefiranofaciens. We applied growth temperatures of 30°C and 37°C, and ob-tained transcriptomic, metabolomic, and proteomic data for the same 20 samples (10 samples per temperature). We obtained a multi-omics interaction network, which generated insights that would not have been possible with single-omics analysis. We identified interactions among transcripts, proteins, and metabolites suggesting active toxin/antitoxin systems. We also observed multifarious interactions that involved the shikimate pathway. These observations helped explain bacterial adaptation to different stress conditions, co-aggregation, and increased activation of L. kefiranofa-ciens at 37°C.
2023-08-18 | PXD042954 | Pride