Project description:<p>Microbial communities often undergo intricate compositional changes yet also maintain stable coexistence of diverse species. The mechanisms underlying long-term coexistence remain unclear, as system-wide studies have been largely limited to engineered communities, ex situ adapted cultures, or synthetic assemblies. Here we show how kefir, a natural milk-fermenting community of prokaryotes and yeasts, realises stable coexistence through spatiotemporal orchestration of species and metabolite dynamics. During milk fermentation, kefir grains (a polysaccharide matrix synthesized by kefir microbes) grow in mass but remain unchanged in composition. In contrast, the milk is colonized in a sequential manner in which early members open metabolic niches for followers. Through metabolomics and large-scale mapping of inter-species interactions, we show how microbes poorly suited for milk survive in, and even dominate the community, through metabolic cooperation and uneven partitioning between grain and milk. Overall, our findings reveal how inter-species interactions partitioned in space and time lead to stable coexistence.</p><p><br></p><p><strong>Linked metabolomics studies:</strong></p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1829' rel='noopener noreferrer' target='_blank'>MTBLS1829</a> Kefir fermentation curve (FIA-MS)</p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1830' rel='noopener noreferrer' target='_blank'>MTBLS1830</a> Interaction between the kefir isolates Lactococcus lactis and Acetobacter fabarum (GC-MS)</p><p><br></p><p><strong>Linked cross omic data:</strong></p><p>Genomes of isolated kefir species are available in the <a href='https://www.ncbi.nlm.nih.gov/' rel='noopener noreferrer' target='_blank'>NCBI database</a> under the accession: PRJNA375758 (bioproject ID: 375758).</p><p>Metatranscriptomic sequencing reads can be accessed from <a href='www.ebi.ac.uk/ena' rel='noopener noreferrer' target='_blank'>ENA</a> under the project id PRJEB37001.</p><p>Genome-scale metabolic models for kefir bacteria can be found at github.com/cdanielmachado/kefir_models.</p>
Project description:Kefir is a milk fermented by microorganisms with probiotic potential. Its consumption is associated with several beneficial effects, from antibacterial, healing, antioxidant, anti-inflammatory, anti-allergic, plasma glucose and cholesterol control to antitumor and antihypertensive activities. Despite its great potential, little is known about the bioactive molecules responsible for these actions. Therefore, the present project aims to perform the proteomic study of Kefir and its grain used for the milk fermentation aiming to identify the bioactive peptides, in particular those peptides with action in the cardiovascular system.
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.
Project description:The Kashmiri population is an ethno-linguistic group that resides in the Kashmir Valley in northern India. A longstanding hypothesis is that this population derives ancestry from Jewish and/or Greek sources. There is historical and archaeological evidence of ancient Greek presence in India and Kashmir. Further, some historical accounts suggest ancient Hebrew ancestry as well. To date, it has not been determined whether signatures of Greek or Jewish admixture can be detected in the Kashmiri population. Using genome-wide genotyping and admixture detection methods, we determined there are no significant or substantial signs of Greek or Jewish admixture in modern-day Kashmiris. The ancestry of Kashmiri Tibetans was also determined, which showed signs of admixture with populations from northern India and west Eurasia. These results contribute to our understanding of the existing population structure in northern India and its surrounding geographical areas.
Project description:<p>Microbial communities often undergo intricate compositional changes yet also maintain stable coexistence of diverse species. The mechanisms underlying long-term coexistence remain unclear, as system-wide studies have been largely limited to engineered communities, ex situ adapted cultures, or synthetic assemblies. Here we show how kefir, a natural milk-fermenting community of prokaryotes and yeasts, realises stable coexistence through spatiotemporal orchestration of species and metabolite dynamics. During milk fermentation, kefir grains (a polysaccharide matrix synthesized by kefir microbes) grow in mass but remain unchanged in composition. In contrast, the milk is colonized in a sequential manner in which early members open metabolic niches for followers. Through metabolomics and large-scale mapping of inter-species interactions, we show how microbes poorly suited for milk survive in, and even dominate the community, through metabolic cooperation and uneven partitioning between grain and milk. Overall, our findings reveal how inter-species interactions partitioned in space and time lead to stable coexistence.</p><p><br></p><p><strong>Linked metabolomics studies:</strong></p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1823' rel='noopener noreferrer' target='_blank'>MTBLS1823</a> Spent-medium assay, measured untargeted (FIA-qTOF) and targeted (HILIC, LC-MS)</p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1830' rel='noopener noreferrer' target='_blank'>MTBLS1830</a> Interaction between the kefir isolates Lactococcus lactis and Acetobacter fabarum (GC-MS)</p><p><br></p><p><strong>Linked cross omic data sets:</strong></p><p>Genomes of isolated kefir species are available in the NCBI database under the accession: PRJNA375758 (bioproject ID: 375758).</p><p>Metatranscriptomic sequencing data associated with this study are available in the European Nucleotide Archive (ENA): accession number <a href='https://www.ebi.ac.uk/ena/browser/view/PRJEB37001' rel='noopener noreferrer' target='_blank'>PRJEB37001</a>.</p><p>Genome-scale metabolic models for kefir bacteria can be found at github.com/cdanielmachado/kefir_models.</p>
Project description:<p>Microbial communities often undergo intricate compositional changes yet also maintain stable coexistence of diverse species. The mechanisms underlying long-term coexistence remain unclear, as system-wide studies have been largely limited to engineered communities, ex situ adapted cultures, or synthetic assemblies. Here we show how kefir, a natural milk-fermenting community of prokaryotes and yeasts, realizes stable coexistence through spatiotemporal orchestration of species and metabolite dynamics. During milk fermentation, kefir grains (a polysaccharide matrix synthesized by kefir microbes) grow in mass but remain unchanged in composition. In contrast, the milk is colonized in a sequential manner in which early members open metabolic niches for followers. Through metabolomics and large-scale mapping of inter-species interactions, we show how microbes poorly suited for milk survive in — and even dominate — the community, through metabolic cooperation and uneven partitioning between grain and milk. Overall, our findings reveal how inter-species interactions partitioned in space and time lead to stable coexistence.</p><p><br></p><p><strong>Linked metabolomics studies:</strong></p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1823' rel='noopener noreferrer' target='_blank'>MTBLS1823</a> Spent-medium assay, measured untargeted (FIA-qTOF) and targeted (HILIC, LC-MS)</p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1829' rel='noopener noreferrer' target='_blank'>MTBLS1829</a> Kefir fermentation curve (FIA-MS)</p><p><br></p><p><strong>Linked cross omic data:</strong></p><p>Genomes of isolated kefir species are available in the <a href='https://www.ncbi.nlm.nih.gov/' rel='noopener noreferrer' target='_blank'>NCBI database</a> under the accession: PRJNA375758 (bioproject ID: 375758).</p><p>Metatranscriptomic sequencing reads can be accessed from <a href='https://www.ebi.ac.uk/metabolights/editor/www.ebi.ac.uk/ena' rel='noopener noreferrer' target='_blank'>ENA</a> under the project id PRJEB37001.</p><p>Genome-scale metabolic models for kefir bacteria can be found at github.com/cdanielmachado/kefir_models.</p>
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.