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66 results for “Functional microbiome”
Glacier shrinkage will accelerate downstream decomposition of organic matter and alters microbiome structure and function
<p>Two datasets supporting the publication, "Glacier shrinkage will accelerate downstream decomposition of organic matter and alters microbiome structure and function" in Global Change Biology.</p> <p><strong>DATA S1 </strong>Detailed metadata for sampled glacier-fed streams, including sample date and time, GPS coordinates, elevation, physical streamwater measurements, glacier characteristics, nutrient chemistry, and a column indicating samples used in metagenomics analyses.</p> <p><strong>DATA S2 </strong>Full patch-level dataset of extracellular enzyme activities (nmol h<sup>-1</sup> g<sup>-1</sup> DM sediment) and chlorophyll <em>a </em>(µg chlorophyll <em>a</em> g<sup>-1</sup> DM).</p>
Dataset for "Intra-intestinal analysis of the functional activity of microbiomes and its application to the common marmoset intestine"
<p>Dataset:</p> <p>data1_ExpressionProfile.xlsx: gene expression profile</p> <p>data2_AnnotationProfile.xlsx: gene annotation profile</p>
Intra-intestinal analysis of the functional activity of microbiomes and its application to the common marmoset intestine
<p>Supplementary Table Captions:</p> <p>Table S7. Assignment of genes to unknown gene clusters</p> <p>Table S8. AUC used to determine parameters for covariation analysis by benchmarking</p> <p>Table S9. Linked unknown gene clusters</p> <p>Table S10. Information on common marmosets</p> <p>Table S11. Dual index sequences</p> <p>Table S12. Sequencing statistics</p> <p>Table S13. RIN score of total RNA samples</p> <p>Table S14. Top 20 bacterial species in taxonomic profiling</p> <p>Table S15. Number of genes covered by the nonchimaeric genome in each parameter at the assembly step</p> <p>Table S16. Number of genes covered by the nonchimaeric genome in each parameter at the merge step</p> <p>Table S17. Distance between intestinal sites</p>
Degenerative Cervical Myelopathy (DCM) induces sex-specific dysbiosis in the mouse gut bacterial microbiome, altering abundance and function
<p><strong>Background:</strong> Degenerative cervical myelopathy (DCM) represents the commonest cause of spinal cord impairment induced by non-traumatic events in the elderly population. It describes a spectrum of disorders that cause progressive spinal cord compression, neurological impairment, loss of bladder and bowel functions, as well as gastrointestinal dysfunction. The gut microbiota has been increasingly recognized as an environmental factor that can modulate both the central nervous system and immune response through the microbiota-gut-brain axis. Changes in gut microbiota composition or in the microbiota producing factors have been linked in the progression and development of several different pathologies such as traumatic spinal cord injury (SCI). Little is known about the molecular mechanisms that trigger DCM manifestation, and the potential role of the gut microbiota.</p> <p><strong>Results: </strong>Herein DCM was induced in female and male C57BL/6 mice by implanting an aromatic polyether material underneath the C5-6 laminae. The extent of DCM-induced changes in microbiota composition, also known as dysbiosis, was assessed by 16S rRNA sequencing from fecal samples at 3 different time points (6, 9 and 12 weeks after DCM induction). Several bacterial members were identified based on BLAST against the largest collection of metagenome-derived genomes from the mouse gut up to date. In both, female and males DCM caused gut dysbiosis compared with the sham group. However, dysbiosis was more pronounced in males than females, where several bacterial members of the families <em>Lachnospiraceae</em> and <em>Muribaculaceae</em> were significantly altered in the DCM group. These changes were also associated with altered immune cell composition in gut-associated lymphoid tissue, blood, and microbe-derived metabolic changes in propionate, butyrate, and lactate-producing bacterial members.</p> <p><strong>Conclusions: </strong>Our results demonstrate for the first time that DCM causes dynamic changes over time in the gut microbiota. Furthermore, we identify specie-specific abundance changes during DCM progression. DCM strongly reduces the abundance of butyrate-producing bacteria, and lactate-producing bacteria in much less extent. Sequence-based pangenomics cores were not resolved between the latter bacteria, but the gap-filling reactions and metabolic modelling successfully identified pyruvate-to-butanoate and pyruvate-to-propionate genes such as Buk and ACH1, respectively. These results aid to better understand markers and the molecular mechanisms that over time trigger DCM manifestation in females and males.</p>
Data from: Parallel changes in gut microbiome composition and function during colonization, local adaptation and ecological speciation
<p>The processes of local adaptation and ecological speciation are often strongly shaped by biotic interactions such as competition and predation. One of the strongest lines of evidence that biotic interactions drive evolution comes from repeated divergence of lineages in association with repeated changes in the community of interacting species. Yet, relatively little is known about the repeatability of changes in gut microbial communities and their role in adaptation and divergence of host populations in nature. Here we utilize three cases of rapid, parallel adaptation and speciation in freshwater threespine stickleback to test for parallel changes in associated gut microbiomes. We find that features of the gut microbial communities have shifted repeatedly in the same direction in association with parallel divergence and speciation of stickleback hosts. These results suggest that changes to gut microbiomes can occur rapidly and predictably in conjunction with host evolution, and that host-microbe interactions might play an important role in host adaptation and diversification.</p>
Genome Database: Turnover of strain-level diversity modulates functional traits in the honeybee gut microbiome between nurses and foragers
<p>This repository contains the dataset used in the publication "Turnover of strain-level diversity modulates functional traits in the honeybee gut microbiome between nurses and foragers," which is currently under revision. A pre-print can be found <a href="https://doi.org/10.1101/2022.12.29.522137">here</a>. The database is based on previously published work to create a genomic database of honeybee gut microbes by Kirsten Ellegaard (2021), found <a href="https://zenodo.org/records/4661061">here.</a></p><p>The zipped folder deposited here after unzipping, should contain the following files and directories:</p><ul><li>honeybee_genome.fasta : fasta file containing the host (<i>Apis mellifera</i>) genome sequence</li><li>beebiome_db : fasta file of 198 concatenated genomes with one genome per entry (multi-line fasta) where the headers represent the genome identifier</li><li>beebiome_red_db : fasta file of 39 species representative genomes with one genome per entry (multi-line fasta) where the headers represent the genome identifier to be used for the analysis of intra-specific variation</li><li>fna_files : directory containing genome sequence files and concatenated files where the concatenated files contain one fasta entry renamed to the genome identifier and all contigs concatenated into one entry</li><li>ffn_files : directory containing one file per genome listing the nucleotide sequence of all the predicted genes</li><li>faa_files : directory containing one file per genome listing the amino acid sequence of all the predicted genes</li><li>bed_files : directory containing bed files where the location of each of the predicted genes are indicated based on their position in the concatenated genome file</li><li>single_ortho : directory containing one file per phylotype listing all the single-copy orthogroups (OGs) identified by orthofinder where each line represents an OG id followed by a list of genes from each of the genomes of that phylotype that belong to that OG and the corresponding sequences of these genes can be found in the ffn file belonging to the respective genome</li><li>red_bed_files : directory containing bed files for species representative genomes that only list the positions genes that belong to the core orthogroups of their phylotype</li></ul><p>Further information about how this genome database was used to analyze strain-level diversity can be found in the publication and accompanying code repository.</p>
Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights
<p>Prevailing 16S rRNA gene-amplicon methods for characterizing the bacterial microbiome of wildlife are economical, but result in coarse taxonomic classifications, are subject to primer and 16S copy number biases, and do not allow for direct estimation of microbiome functional potential. While deep shotgun metagenomic sequencing can overcome many of these limitations, it is prohibitively expensive for large sample sets. We evaluated the ability of shallow shotgun metagenomic sequencing to characterize taxonomic and functional patterns in the fecal microbiome of a model population of feral horses (Sable Island, Canada). Since 2007, this unmanaged population has been the subject of an individual-based, long-term ecological study. Using deep shotgun metagenomic sequencing, we determined the sequencing depth required to accurately characterize the horse microbiome. In comparing conventional versus high-throughput shotgun metagenomic library preparation techniques, we validate the use of more cost-effective lab methods. Finally, we characterize similarities between 16S amplicon and shallow shotgun characterization of the microbiome and demonstrate that the latter recapitulates biological patterns first described in a published amplicon dataset. Unlike amplicon data, we further demonstrate how shallow shotgun metagenomic data provide useful insights about microbiome functional potential which support previously hypothesized diet effects in this study system.</p>
Data from: Host phylogeny and functional traits differentiate gut microbiomes in a diverse natural community of small mammals
<p>Differences in the bacteria inhabiting mammalian gut microbiomes tend to reflect the phylogenetic relatedness of their hosts, a pattern dubbed phylosymbiosis. Although most research on this pattern has compared the gut microbiomes of host species across biomes, understanding the evolutionary and ecological processes that generate phylosymbiosis requires comparisons across phylogenetic scales and under similar ecological conditions. We analyzed the gut microbiomes of 14 sympatric small-mammal species in a semi-arid African savanna, hypothesizing that there would be a strong phylosymbiosis pattern associated with the different body sizes and diets of the mammalian lineages present. Consistent with phylosymbiosis, microbiome dissimilarity increased with phylogenetic distance among hosts, ranging from congeneric sets of mice and hares that did not differ significantly in microbiome composition to species from different taxonomic orders that had almost no gut bacteria in common. While phylosymbiosis was detected among just the 11 species of rodents, it was substantially weaker than comparisons involving all 14 species together. In contrast, microbiome diversity and composition were generally more strongly correlated with body size, dietary breadth, and dietary overlap in comparisons restricted to rodents than in those including all lineages. The starkest divides in microbiome composition thus reflected the broad evolutionary divergence of hosts, regardless of body size or dietary composition, while subtler microbiome differences reflected variation in ecologically important traits between closely related hosts. Strong phylosymbiotic patterns arose deep in the phylogeny, and ecological filters that promote functional differentiation of cooccurring host species may disrupt or obscure this pattern near the tips.</p>
Effect of Prebiotics on the Gut Microbiome Profile and Beta Cell Function
ClinicalTrials.gov study NCT04114357. IPD Sharing: NO. Countries: 1. Publications: 1.
Unravelling changes in the Pinus radiata root and soil microbiomes as a function of aridity
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Data from: Azteca ants maintain unique microbiomes across functionally distinct nest chambers
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Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights
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Data from: Parallel changes in gut microbiome composition and function during colonization, local adaptation and ecological speciation
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Data from: Host phylogeny and functional traits differentiate gut microbiomes in a diverse natural community of small mammals
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Absence of a functional gut microbiome impairs host amino acid metabolism in the Pacific spiny dogfish (Squalus suckleyi)
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Database for mi-faser: Functional sequencing read annotation for high precision microbiome analysis
<p><strong>[Database for mi-faser]</strong></p> <p><strong>mi-faser: </strong><em>microbiome - functional annotation of sequencing reads</em></p> <p>A super-fast ( < 20min/10GB of reads ) and accurate ( > 90% precision ) method for annotation of molecular functionality encoded in sequencing read data without the need for assembly or gene finding.</p> <p>Web Service: http://services.bromberglab.org/mifaser/|<br> Repository: https://bitbucket.org/bromberglab/mifaser_base/</p>
PIBAC: Extensive cultivation of the pig gut microbiome identifies novel bacterial diversity and functions and enables tailored functional studies
<p>In-depth cultivation of the pig gut microbiome towards novel bacterial diversity and tailored functional studies:</p> <ul> <li>780 MAGs from all-in-one assembly of 295 pig gut metagenomic samples (Xiao, 2016)</li> <li>38 isolates representing novel species (single draft genomes)</li> <li>representing in total 617 species (hqMAGs-dereplicated_genomes, comp>90%, con<5%</li> </ul> <p>More information you can find here:</p> <p>https://github.com/tillrobin/PIBAC</p> <p>https://www.dsmz.de/pibac</p> <p> </p> <p>External study providing data:</p> <p>Xiao, Liang, et al. "A reference gene catalogue of the pig gut microbiome." Nature microbiology 1.12 (2016): 16161. <a href="https://doi.org/10.1038/nmicrobiol.2016.161">https://doi.org/10.1038/nmicrobiol.2016.161</a> </p>
Data from: The Sphagnum microbiome supports greatly bog ecosystem functioning under extreme conditions
Sphagnum-dominated bogs represent a unique yet widely distributed type of terrestrial ecosystem, and strongly contribute to global biosphere functioning. Sphagnum is colonised by highly diverse microbial communities, but less is known about their function. We identified a high functional diversity within the Sphagnum microbiome applying an Illumina-based metagenomic approach followed by de novo assembly and MG-RAST annotation. An inter-environmental comparison revealed that the Sphagnum microbiome harbours specific genetic features that distinguish it significantly from microbiomes of higher plants and peat soils. The differential traits especially support ecosystem functioning by a symbiotic life style under poikilohydric and ombrotrophic conditions. To realise a plasticity-stability balance, we found abundant subsystems responsible to cope with oxidative and drought stresses, to exchange (mobile) genetic elements, and genes that encode for resistance to detrimental environmental factors, repair, and self-controlling mechanisms. Multiple microbe-microbe and plant-microbe interactions were also found to play a crucial role as indicated by diverse genes necessary for biofilm formation, interaction via quorum sensing and nutrient exchange. A high proportion of genes involved in nitrogen cycle and recycling of organic material supported the role of bacteria for nutrient supply. 16S rDNA analysis indicated a higher structural diversity than that which had been previously detected using PCR-dependent techniques. Altogether, the diverse Sphagnum microbiome has the ability to support the life of the host plant and the entire ecosystem under changing environmental conditions. Beyond this, the moss microbiome presents a promising bio-resource for environmental biotechnology – with respect to novel enzymes or stress-protecting bacteria.
Scale dependence in functional equivalence and difference in the soil microbiome
<p>Climatic history can shape the functioning of soil microbial communities and thus rates of ecosystem processes such as organic matter decomposition. For example, broad spatial scale differences in climatic history, such as contrasting precipitation regimes, have been shown to generate unique microbial functional responses to contemporary moisture conditions. Yet it is an open question as to whether local differences in soil microclimate similarly influence the functional potential of decomposer communities. Here, we use a multi-scale approach within and among two temperate forest field sites to investigate this question. Soils from fifty-four microsites, that vary in their soil moisture climate-regimes, were used as inocula for a common leaf litter (<em>Quercus rubra</em>) in a controlled, laboratory microcosm study. Microcosms were placed under dry, mesic and wet lab-moisture conditions and the rate of carbon (C) mineralization of the litter was measured over 202 days. Our results reveal differences in decomposition rates under controlled conditions that highlight broad-scale functional differences between the soil communities at each site. Specifically, we found that C mineralization differed by as much as two-fold for soil communities when compared between the sites. Our results also show that functional differences of soil communities are observable within one site but not the other. In the site where local-scale functional legacies were apparent, the historical soil moisture microclimate-regimes generated as much as an 89% change in C mineralization rates of the leaf litter under the same contemporary, lab-imposed moisture conditions. A similar pattern was not observable in the other site; instead, laboratory moisture conditions explained almost all variation in C mineralization. Our findings confirm those from prior studies where regional-scale moisture-regime differences shape microbial function, and extends this prior work by providing evidence that pronounced local-scale differences in soil moisture microclimate-regimes can generate microbial functional legacies.</p>
DRAM raw annotations for "Cover Crop Root Exudates Impact Soil Microbiome Functional Trajectories in Agricultural Soils" Seitz et al 2024
<p>Additional File 5: <span>Raw DRAM MAG annotations. </span></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.