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90 results for “microbial compositions”
Physical soil characteristics, microbial community composition, extracellular enzymatic activity, biologically based phosphorus (BBP) pools, and available phosphorus from two soil depths, four microhabitats, and four landforms at the Jornada Experimental Range, 2021.
This dataset contains physical soil characteristics, PLFA based microbial community composition, extracellular enzymatic activity, nitrate and ammonium activity, and phosphorus availability in various phosphorus pools (Biologically Based Phosphorus, potassium sulfate, Olsen-P). Soils were collected from two depths (0-2cm, 2-30 cm), four microhabitats (grass, shrub, biocrust, interspace), and four landforms (alluvial flat, alluvial fan remnant, erosional scarplet, fan piedmont – see coordinates) within the Jornada Experimental Range in July 2021 to answer questions about how these variables change across these spatial scales in drylands. This project was a collaboration between researchers at New Mexico State University and The University of Texas at El Paso as part of the Drylands Critical Zone Thematic Cluster within the Critical Zone Network. This dataset is complete.
Microbial Community Composition in Lakes - Taxonomic/Ecological characteristics of the sample at North Temperate Lakes LTER 2000 - 2007
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by a combination of taxonomic and ecological characteristics of the sample allows the user to retrieve sample information [sample IDs, sample dates, lake information (region, type, size, depth) and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites)] and clone information [clone IDs, sequence data, and characteristics of the sequence (length, chimera status, accession number, taxonomic affiliation)]. The data can be filtered by ecological characteristics of the sample [lake name, sample date, lake information (region, type, size, depth)] and taxonomic characteristics of the community members [clone ID, ARISA fragment length (raw or binned), and/or taxonomic characteristics (Phylum and Phylum-Class)]. The output can include links to individual sample records, which contain links to the taxonomic composition of the sample inferred by dynamically matching clones to ARISA fragments in the individual sample. The output can also include links to clone records directly (though this creates a very large number of lines in the output and is not recommended). Project ID's 30 Lakes - Survey of 30 lakes in northern and southern Wisconsin. June, August and October, 2002. See http://microbes.limnology.wisc.edu/lakes30.html. Lake Characteristics. CB0000 - Time series monitoring microbial community composition in Crystal Bog. 2000-2002. CBX_02 - Food web manipulation experiment i
Microbial Community Composition in lakes - Ecological characteristics of the sample at North Temperate Lakes LTER 2002 - 2007
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by ecological characteristics of the sample allows the user to retrieve sample IDs, sample dates, lake information (region, type, size, depth) and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites). The data can be filtered by lake name, sample date, lake information (region, type, size, depth), and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites). The output includes links to individual sample records, which contain links to the taxonomic composition of the sample inferred by dynamically matching clones to ARISA fragments in the individual sample
Microbial Community Composition in Lakes - Taxonomic characteristics of the clones at North Temperate Lakes LTER 2000 - 2007
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by taxonomic characteristics of the clone allows the user to retrieve clone IDs, sequence data, and characteristics of the sequence (length, chimera status, accession number, taxonomic affiliation). The data can be filtered by clone ID, ARISA fragment length (raw or binned), and/or taxonomic characteristics (Phylum and Phylum-Class). The output includes links to individual clone records, which contain more detailed information about how the clone was generated (researcher, library ID, project ID, primer sets used, etc.).
Data and code from "Water availability is a stronger driver of soil microbial processing of organic nitrogen than tree species composition"
<p>#### Data description<br> Data from large scale, long-term tree diversity experiment in southwestern France (<a href="https://sites.google.com/view/orpheeexperiment/home">ORPHEE</a>), additionally manipulating water contraint. Variables presented are soil nitrogen cycling rates measured using isotope pool dilutions.</p> <p>Companion paper is found here:</p> <p>Maxwell TL, Augusto L, Tian Y, Wanek W & Fanin N (2023). Water availability is a stronger driver of soil microbial processing of organic nitrogen than tree species composition. <em>European Journal of Soil Science</em>. <a href="https://doi.org/10.1111/ejss.13350">https://doi.org/10.1111/ejss.13350</a></p> <p>#### Metadata<br> Soil sampling: July 2020<br> Maxwell_ShortComm_Data.csv data description</p> <p>ID: unique identifier per sample<br> Block: numbered 1-6. Blocks 1,3,6 are control (unirrigated), Blocks, 2,4,5 are irrigated<br> Plot: numbered plot according to the ORPHEE design. Plot 1 = BP, Plot 5 = PP, Plot 9 = BP_PP<br> Espece: species ID. BP = pure birch (<em>Betula pendula</em>), PP = pure pine (<em>Pinus pinaster</em>), BP_PP (50% mixed birch-pine)<br> Rep: sample replicate, 3 replicates per plot<br> Sample name: long unique identifier per sample. Concatenation of Block, Plot, and Espece<br> PD: gross protein depolymerization rates (micrograms nitrogen per grams dry soil per day = µg N g-1 d-1)<br> AAU: gross free amino acid uptake rates (µg N g-1 d-1)<br> Cmicrobial_ug_g: microbial biomass carbon (µg C g-1)<br> Nmicrobial_ug_g: microbial biomass nitrogen (µg N g-1)<br> MRT_FAA_hrs: mean residence time of free amino acids (hours)<br> FAA_ugN_g: free amino acids (µg N g-1)<br> Moisture_percent: soil moisture percent (%)<br> N_nonfumige_ug_g: nitrogen from non fumigated soils, i.e. extractable N (µg N g-1)<br> C_nonfumige_ug_g: nitrogen from non fumigated soils, i.e. extractableC (µg C g-1)</p>
Alpine soil islands plant and soil microbial community composition, 2024.
High alpine ecosystems are particularly sensitive to climate-driven change, with vegetation expansion increasingly observed in historically barren soils. In late August and early September 2024, we revisited 50 previously established vegetation plots in Green Lakes Valley (Niwot Ridge LTER) to evaluate patterns of plant colonization and community change over time. Using legacy vegetation data from 2008 and 2015, we assessed changes in plant cover and composition in relation to microtopography and prior plant occurrence. Concurrently, we collected soil samples for 16S and 18S rRNA gene sequencing to characterize bacterial, archaeal, and eukaryotic microbial communities associated with these plots. Vegetation was resampled using spatially referenced 1-meter radius surveys, estimating species incidence and cover and documenting moss, lichen, sedge, and grass diversity. Together, these above- and belowground data provide insight into how priority effects, fine-scale environmental variation, and plant–microbe interactions influence alpine community dynamics, and may inform predictive models of ecosystem responses to ongoing climatic shifts.
Soil microbial community composition (16S) data from a laboratory redox fluctuation experiment conducted with an Oxisol and Mollisol
To test the response of microbial communities to periodic oxygen limitation, we conducted a laboratory experiment where two contrasting soils (a rainforest Oxisol from Puerto Rico, and an Iowa cropland Mollisol) were incubated under headspace treatments where oxygen availability varied cyclically over time. Treatments consisted of 0, 2, 4, 8, or 12 d of anoxic conditions (dinitrogen headspace) followed by 4 d of oxic conditions (i.e., ambient oxygen concentrations), and these treatments were repeated for a total of 384 d. At 0, 48, and 384 days, DNA was extracted from replicates from each treatment for sequencing of 16S rRNA amplicons. Companion biogeochemical measurements from this experiment were published previously by Huang et al. (2021a,b). These data support the Hall et al. (2022) manuscript published in Frontiers in Microbiology.
Plumes and Blooms: Microbial eukaryote diversity and composition
These are amplicon sequencing data collected during Plumes and Blooms (PnB) cruises conducted from March, 2011, through September, 2014. The V9 hypervariable region of the 18S rRNA gene derived from microbial eukaryotic communities was amplified and sequenced from 345 discrete seawater samples. Sample collection and laboratory methods are described in Catlett et al. 2020 and Catlett et al. in review. Bioinformatic and data manipulation methods follow those employed in Catlett et al. in review. The data are provided in two tables: one includes amplicon sequence variant (ASV) sequences and relative sequence abundances for each sampling event, and the other includes ASV taxonomy predictions for each ASV sequence. References: Catlett, D., P. G. Matson, C. A. Carlson, E. G. Wilbanks, D. A. Siegel, and M. D. Iglesias‐Rodriguez. 2020. Evaluation of accuracy and precision in an amplicon sequencing workflow for marine protist communities. Limnol. Oceanogr.: Methods. 18(1): 20-40. https://doi.org/10.1002/lom3.10343. Catlett, D., D. A. Siegel, P. G. Matson, E. K. Wear, C. A. Carlson, T. S. Lankiewicz, and M. D. Iglesias‐Rodriguez. In review. Integrating phytoplankton pigment and DNA meta-barcoding observations to determine phytoplankton community composition in the coastal ocean. Limnol. Oceanogr.
Data from: Hierarchical social networks shape gut microbial composition in wild Verreaux's sifaka
<p>In wild primates, social behaviour influences exposure to environmentally acquired and directly transmitted microorganisms. Prior studies indicate that gut microbiota reflect pairwise social interactions among chimpanzee and baboon hosts. Here, we demonstrate that higher-order social network structure—beyond just pairwise interactions—drives gut bacterial composition in wild lemurs, which live in smaller and more cohesive groups than previously studied anthropoid species. Using 16S rRNA gene sequencing and social network analysis of grooming contacts, we estimate the relative impacts of hierarchical (i.e. multilevel) social structure, individual demographic traits, diet, scent-marking, and habitat overlap on bacteria acquisition in a wild population of Verreaux's sifaka (<em>Propithecus</em> <em>verreauxi</em>) consisting of seven social groups. We show that social group membership is clearly reflected in the microbiomes of individual sifaka, and that social groups with denser grooming networks have more homogeneous gut microbial compositions. Within social groups, adults, more gregarious individuals, and individuals that scent-mark frequently harbour the greatest microbial diversity. Thus, the community structure of wild lemurs governs symbiotic relationships by constraining transmission between hosts and partitioning environmental exposure to microorganisms. This social cultivation of mutualistic gut flora may be an evolutionary benefit of tight-knit group living.</p>
Plant management but not fertilization mediates soil carbon emission and microbial community composition in subtropical Eucalyptus plantations
<p><span>The diversity of </span><span>plant functional group</span><span>s</span><span> in plantations affects soil carbon, but we have limited understanding of the underlying mechanisms for how plant management affects soil carbon dynamics. Here, we conducted a 3-year manipulation experiment of plant functional groups that included understory removal, tree root trenching, and fertilization treatments in 2-year-old and 6-year-old <em>Eucalyptus</em> plantations in the subtropical region. The results showed that soil respiration was significantly suppressed by understory removal (-38%), tree root trenching (-41%), and their interactions (-54%), but that fertilization alone and in interactions had no significant effect. The Chao1 indices for soil bacterial and fungal diversity significantly decreased with understory removal in the 2-year-old plantation and with tree root trenching in the 6-year-old plantation. Soil bacterial and fungal communities were also affected by understory removal and tree root trenching. Soil respiration, physicochemical characteristics, microbial diversity, and community composition were significantly affected by plantation age. Reductions in soil carbon emissions were associated with reductions in plant functional groups and soil microbial groups, while increases in soil respiration were associated with soil physicochemical factors, soil temperature, and plantation age. Our findings highlight that plant managements are of great significance to the soil carbon emission processes in afforested plantations.</span></p>
16S Phyloseq R object accompanying the paper: Effects of storage methods on total bacterial count and microbial composition of bovine colostrum
<p>This ready to load <strong>phyloseq</strong> R S4 object contains the ASV table, taxonomy table and sample metadata (16S V3-V4). This data was build using the DaDa2 (version 1.12.1) and phyloseq (version 1.32) R packages using our raw Illumina MiSeq PE300 sequencing data deposited at NCBI-SRA under BioProject: PRJNA872909.</p> <p>The accompanying (peer-reviewed) scientific article can be found here: </p> <ul> <li>https://www.todo</li> <li>DOI: todo</li> </ul> <p> </p> <p><strong>Study/draft abstract:</strong></p> <p>Lisa Robbers, Hannes Bijkerk, Lars Ravesloot, Alex Bossers, Mirjam Nielen, Ruurd Jorritsma, Ad Koets, Lindert Benedictus</p> <p>Neonatal calves need to acquire passive immunity through maternal colostrum, as they are immunologically naïve and the structure of the bovine placenta does not allow passage of maternal antibodies during pregnancy. Milked colostrum is not initially sterile and may even contain high bacterial counts. Minimizing total bacterial counts in colostrum is generally advised, however bacterial quality of colostrum comprises more than just bacterial quantities, but also depends on the specific bacteria present. While duration and temperature of colostrum storage are known to affect total plate counts (TPC), less is known about the effects of storage on the actual bacterial composition of the TPC. We speculated that, depending on the storage conditions, colostrum is a substrate in which certain bacterial species can thrive affecting the quality of colostrum.</p> <p>We therefore aimed to characterize the effects of different colostrum storage methods on the composition of the viable, aerobic, microbial community. Colostrum samples were stored at different temperatures and for different durations. Next, bacterial growth was assessed using the aerobe plate count culture method, followed by 16S rRNA gene amplicon sequencing. Differences in the TPC bacterial compositions of the stored colostrum samples, as determined by 16S rRNA gene amplicon sequencing, were mostly explained by the variation in bacterial composition of the colostrum sample directly after milking. In line with earlier studies, the results from our study show that the TPC increased when colostrum was stored for 24 hours at room temperature, but not when stored in a refrigerator for the same duration. Community structure of the TPC of colostrum stored at room temperature for 24 hours and stored in a refrigerator for a week was significantly different from the baseline samples. The 16S rRNA sequencing results indicate this is because of increased numbers of <em>Enterobacteriaceae.</em> <em>Enterobacteriaceae</em> abundance in refrigerated samples seemed to remain stable for the first 24 hours, but increased drastically after one week. The results indicate that microbial composition of stored colostrum is mostly influenced by the composition of the colostrum sample directly after milking, which is most probably the result of contamination or other environmental influences during the milking process. This study provides a deeper insight in the changes in the microbial composition of colostrum TPC during practical storage conditions and provides a primer for more detailed research into the determinants of bacterial composition of colostrum and the linked health effects.</p>
CS#1H Monitoring Data of Subsurface Passage in Managed Aquifer Recharge: Microbial and Organic Composition Analysis
<div>This dataset contains flow cytometry and cultivation-based microbial data, along with measurements of natural organic matter (NOM) characterized by fluorescence, absorbance, and liquid chromatography-organic carbon detection (LC-OCD) from CS#1H. Data were collected over a one-year monitoring period at two sampling locations: the infiltration ditch and the abstraction well. </div>
Microbial community composition of earthworm-invaded and earthworm-free soils of the Canadian boreal forest
<p>Earthworm invasion in North American forests has the potential to greatly impact soil microbiomes by altering soil physicochemical properties. We characterized and compared microbial communities of earthworm-invaded and non-invaded soils in previously described sites across three major soil types found in the Canadian boreal forest using phospholipid fatty acid (PLFA) analysis and metabarcoding of the 16S rRNA gene (bacteria and archaea) and ITS2 region (fungi).</p>
Data from: Hierarchical social networks shape gut microbial composition in wild Verreaux's sifaka
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Effects of parental care on skin microbial community composition in poison frogs
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Microbial community composition of earthworm-invaded and earthworm-free soils of the Canadian boreal forest
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Data from: Responses of subsoil organic carbon to climate warming and cooling is determined by microbial community rather than its molecular composition
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Plant management but not fertilization mediates soil carbon emission and microbial community composition in subtropical Eucalyptus plantations
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Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition
<ol> <li>Microbial communities are increasingly recognised as crucial for animal health. However, our understanding of how microbial communities are structured across wildlife populations is poor. Mechanisms such as interspecific associations are important in structuring free-living communities, but we still lack an understanding of how important interspecific associations are in structuring gut microbial communities in comparison to other factors such as host characteristics or spatial proximity of hosts.</li> </ol> <p> </p> <ol> <li>Here we ask how gut microbial communities are structured in a population of North American moose (<i>Alces alces</i>). We identify key microbial interspecific associations within the moose gut and quantify how important they are relative to key host characteristics, such as body condition, for predicting microbial community composition.</li> </ol> <p> </p> <ol> <li>We sampled gut microbial communities from 55 moose in a population experiencing decline due to a myriad of factors, including pathogens and malnutrition. We examined microbial community dynamics in this population utilizing novel graphical network models that can explicitly incorporate spatial information.</li> </ol> <p> </p> <ol> <li>We found that interspecific associations were the most important mechanism structuring gut microbial communities in moose and detected both positive and negative associations. Models only accounting for associations between microbes had higher predictive value compared to models including moose sex, evidence of previous pathogen exposure, or body condition. Adding spatial information on moose location further strengthened our model and allowed us to predict microbe occurrences with ~90% accuracy.</li> </ol> <p> </p> <ol> <li>Collectively, our results suggest that microbial interspecific associations coupled with host spatial proximity are vital in shaping gut microbial communities in a large herbivore. In this case, previous pathogen exposure and moose body condition were not as important in predicting gut microbial community composition. The approach applied here can be used to quantify interspecific associations and gain a more nuanced understanding of the spatial and host factors shaping microbial communities in non-model hosts.</li> </ol>
Data from: Do temperate tree species diversity and identity influence soil microbial community function and composition?
Studies of biodiversity-ecosystem function in treed ecosystems have generally focused on aboveground functions. The present study investigates inter-trophic links between tree diversity and soil microbial community function and composition.We examined how microbial communities in surface mineral soil responded to experimental gradients of tree species richness (SR), functional diversity (FD), community-weighted mean trait value (CWM) and tree identity. The site was a 4-yr-old common garden experiment near Montreal, Canada, consisting of deciduous and evergreen tree species mixtures. Microbial community composition, community-level physiological profiles (CLPP) and respiration were evaluated using phospholipid fatty acid (PLFA) analysis and the MicroRespTM system, respectively. The relationship between tree species richness and glucose induced respiration (GIR), basal respiration (BR), metabolic quotient (qCO2) followed a positive but saturating shape. Microbial communities associated with species mixtures were more active (basal respiration (BR)), with higher biomass (glucose induced respiration (GIR)), and used a greater number of carbon sources than monocultures. Communities associated with deciduous tree species used a greater number of carbon sources than those associated with evergreen species, suggesting a greater soil carbon storage capacity. There were no differences in microbial composition (PLFA) between monocultures and SR mixtures. The FD and the CWM of several functional traits affected both BR and GIR. In general, the CWM of traits had stronger effects than did FD, suggesting that certain traits of dominant species have more effect on ecosystem processes than does FD. Both the functions of GIR and BR were positively related to aboveground tree community productivity. Both tree diversity (SR) and identity (species and functional identity – leaf habit) affected soil microbial community respiration, biomass and composition. For the first time, we identified functional traits related to life history strategy, as well as root traits that influence another trophic level, soil microbial community function, via effects on BR and GIR.
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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.