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287 results for “Bacterial communities”
Integrated genome-wide investigations of the housefly, a global vector of diseases reveal unique dispersal patterns and bacterial communities across farms
<p><span><span><span><span><span><span><span><span><span><span><span><b>Background:</b>Houseflies (<i>Musca domestica</i>L.) live in intimate association with numerous microorganisms and is a vector of human pathogens. In temperate areas, houseflies will<span>overwinter in environments constructed by humans and recolonize surrounding areas in early summer. However, the </span>dispersal patterns and associated bacteria across season and location are unclear.We used genotyping-by-sequencing (GBS) for the simultaneous identification and genotyping of thousands of Single Nucleotide Polymorphisms (SNPs) to establish dispersal patterns of houseflies across farms. Secondly, we used16S rRNA gene amplicon sequencing to establish the variation and association between bacterial communities and the housefly across farms. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Results: </b>Using GBS we identified 18,000 SNPs across 400 individualssampled within and between 11 dairy farms in Denmark. There was evidence for sub-structuring of Danish housefly populations and with genetic structure that differed across season and sex. Further, there was a strong isolation by distance (IBD) effect, but with large variation suggesting that other hidden geographic barriers are important. Large individual variations were observed in the community structure of the microbiome and it was found to be dependent on location, sex, and collection time. Furthermore, the relative prevalence of putative pathogens was highly dependent on location and collection time.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Conclusion:</b>We were able to identify SNPs for the determination of the spatiotemporal housefly genetic structure, and to establish the variation and association between bacterial communities and the housefly across farms using novel <span>next</span><span>‐</span><span>generation sequencing (NGS)</span>techniques. These results are important for disease prevention given the fine-scale population structure and IBD for the housefly, and that individual houseflies carry location specific bacteria including putative pathogens. </span></span></span></span></span></span></span></span></span></span></span></p>
Diversity of bacterial communities on four frequently used surfaces in a large Brazilian teaching hospital
<p>Frequently used hand-touch surfaces in hospital settings have been implicated as a vehicle of microbial transmission. In this study, we aimed to investigate the overall bacterial population on four frequently used surfaces using a culture-independent Illumina massively parallel sequencing approach of the 16S rRNA genes. Surface samples were collected from four sites, namely elevator buttons (EB), bank machine keyboard buttons (BMKB), restroom surfaces, and the employee biometric time clock system (EBTCS), in a large public and teaching hospital in Sao Paulo. Taxonomical composition revealed the abundance of Firmicutes phyla, followed by Actinobacteria and Proteobacteria, with a total of 926 bacterial families and 2832 bacterial genera. Moreover, our analysis revealed the presence of some potential pathogenic bacterial genera, including <em>Salmonella enterica</em>, <em>Klebsiella pneumoniae</em>, and <em>Staphylococcus aureus</em>. The presence of these pathogens in frequently used surfaces enhances the risk of exposure to any susceptible individuals. Some of the factors that may contribute to the richness of bacterial diversity on these surfaces are poor personal hygiene and ineffective routine schedules of cleaning, sanitizing, and disinfecting. Strict standards of infection control in hospitals and increased public education about hand hygiene are recommended to decrease the risk of transmission in hospitals among patients.</p>
Molecular investigation of bacterial communities on two frequently used surfaces in the São Paulo institute of tropical medicine
<p>In this study, we aimed to investigate the overall bacterial population on two frequently used surfaces in the São Paulo institute of tropical medicine (ITM) using a culture-independent Illumina massively parallel sequencing approach of the 16S rRNA genes. The massive parallel sequencing data presented here were derived from the surface samples collected from restroom surfaces and the fingerprint door clock system (FDLS) in our ITM in São Paulo.</p>
Sequences, taxonomic assignments, and R script from Comparison of Lava Cave Bacterial Mat Communities to Overlying Surface Soil Bacterial Communities from Lava Beds National Monument, USA
<p>This set of files contain the 16S rDNA, taxonomic assignments from the greengenes database, and the R script for processing the data. </p> <p><strong>Abstract</strong></p> <p>Lava caves around the world often support extensive microbial mats on ceilings and walls in a range of colors. Little is known about lava cave microbial diversity and how these subsurface mats differ from microbial communities in overlying surface soils. We generated and analyzed bacterial 16S rDNA from 454 pyrosequencing from three colors of microbial mats (tan, white, and yellow) from seven lava caves in Lava Beds National Monument, CA, USA, and compared them with surface soils overlying each cave. <em>Actinobacteria</em> dominated in all samples, with 39% (caves) and 21% (surface soils). <em>Proteobacteria</em> made up 30% of phyla from caves and 36% from surface soil with <em>Gamma</em>- 20% and <em>Alpha</em>- 10% in the caves and <em>Gamma</em>- 18% with <em>Alpha</em>-17% in soil. Other major phyla in caves were <em>Nitrospirae</em> (7%) followed by Minor Phyla (7%), compared to surface soils with <em>Bacteriodetes</em> (8%) and Minor phyla (8%). A very high proportion (53.33%) of the most abundant sequences could not be identified to genus, indicating a high degree of novelty. Surface soil samples had more OTUs and greater diversity indices than cave samples. The same phyla were represented in both soils and cave microbial mats, but the overlap was only 11.2% at the operational taxonomic unit (OTU). Although surface soil microbes immigrate into underlying caves, the environment selects for microbes able to live in the cave habitats, resulting in very different cave microbial communities. In terms of species richness, diversity by mat color differed, but not significantly. Number of entrances per cave, distance from an entrance, cave length, and temperature also contributed to observed differences in diversity. With high levels of novel microbes, caves may represent excellent habitats for the isolation of new bioactive compounds. This study is the first comprehensive comparisons of bacterial communities in lava caves with the overlying soil community.</p>
Resource competition predicts assembly of in vitro gut bacterial communities
<p>Microbiota dynamics arise from a plethora of interspecies interactions, including resource competition, cross-feeding, and pH modulation. The individual contributions of these mechanisms are challenging to untangle, especially in natural or complex laboratory environments where the landscape of resource competition is unclear. Here, we developed a framework to estimate the extent of multi-species niche overlaps by combining metabolomics data of individual species, growth measurements in pairwise spent media, and mathematical models. When applied to an in vitro model system of human gut commensals in complex media, our framework revealed that a simple model of resource competition described most pairwise interactions. By grouping metabolomic features depleted by the same set of species, we constructed a coarse-grained consumer-resource model that predicted assembly compositions to reasonable accuracy. Moreover, deviations from model predictions enabled us to identify and incorporate into the model additional interactions, including pH-mediated effects and cross-feeding, which improved model performance. In sum, our work provides an experimental and theoretical framework to dissect microbial interactions in complex in vitro environments.</p>
Vegetation variables and rhizosphere bacterial communities from ten paired sites in southwestern Finland, 2021
<p>Plant invasions can have major impacts on ecosystems not only in aboveground but also in belowground through changes in microbiota. Particularly legumes, which often host nitrogen-fixing symbionts (rhizobia), can be expected to modify soil bacterial communities. We examined the effect of the invasive herbaceous legume, <em>Lupinus polyphyllus</em>, on the alpha diversity and community composition of soil bacteria. We also explored whether vegetation cover, the cover of other (non-invasive) legumes or number of vascular plants was associated with soil bacterial communities. We sampled rhizosphere soil and surveyed vegetation from ten paired sites (invaded more than ten years ago and uninvaded locations) in southwestern Finland, and identified bacterial DNA by using 16S rRNA gene amplicon sequencing. The plant invader and the three vegetation variables considered had no effect on soil bacterial alpha diversity in terms of bacterial richness, Shannon and Inverse Simpson diversity indices. The composition of soil bacterial communities differed between invaded and uninvaded soils at four out of the ten sites. However, the differences in the relative abundances of top bacterial families between the two soil origins were inconsistent across sites, including rhizobia in the family of <em>Bradyrhizobiaceae</em> that the study species is hosting. Moreover, vegetation cover, legume cover after excluding the study species, and number of plant species explained a small proportion of the variation in the bacterial community composition. Our findings indicate that <em>L</em><em>. polyphyllus</em> has the potential to modify the soil bacterial community composition locally, at least at sites where it has been present for more than a decade.</p>
Data from: Effects of pesticides on soil bacterial, fungal and protist communities, soil functions and crop quality in vineyards
<p>Pesticides can have unintentional effects on non-target organisms and change biotic communities. Such changes might be particularly important in soil microbial communities which drive many ecosystem functions and may affect crop quality. Here, we investigated, in a 3-year study, how vegetation control (by herbicide application) and soil copper content (from long-term copper-based fungicide application), affect biodiversity and the community structure of soil bacteria, fungi and protists and associated soil functions (respiration, decomposition) in Swiss vineyards. Furthermore, we determined the effects of these two management practices on grape quality as the most direct ecosystem service to farmers. Across all study years, the community composition of microorganisms was affected by herbicide application, however, a significant loss of operational taxonomic units (OTUs) was only observed in fungi and protists. Soil copper content reduced OTU richness of bacteria and protists in some years but had no significant effect on fungal richness. Copper changed the community composition in all three groups of soil microorganisms. While we found no effect of copper on soil functions, herbicide application reduced microbial respiration and biomass by about 39% and 45% respectively. However, decomposition rates remained virtually unchanged by any pesticide. Yeast assimilable nitrogen (YAN) levels in grape must were below the critical threshold of 140 mg/L in 40% of the vineyards without herbicide application and the variety Chasselas , whereas in vineyards with herbicide application it was only 20%. Synthesis and applications: Application of pesticides led to changes in richness and composition of soil microbial communities and directly reduced some soil functions (microbial biomass and respiration), but not all (decomposition). Some grape quality parameters can be indirectly enhanced by pesticide application, highlighting the trade-off between the interests of nature conservation and the interests of the farmer. Balancing these two diverging interests requires the establishment of alternative vineyard management allowing reduced pesticide application.</p>
Salinity of irrigation water selects distinct bacterial communities associated with Date palm (Phoenix dactylifera L.) root
<p>Saline water irrigation has been used extensively in date palm (<em>Phoenix dactylifera </em>L.) agriculture as an alternative to non-saline freshwater due to water scarcity in hyper-arid environments. However, how saline water irrigation affects date palm root-associated bacterial communities is unknown. Here, we investigated the effect of irrigation sources (non-saline vs saline water) on date palm root-associated bacterial communities and their diversity using 16S rRNA gene metabarcoding. The bacterial richness, Shannon diversity and evenness didn’t differ significantly between the irrigation sources. Soil electrical conductivity (EC) and irrigation water pH were negatively related to Shannon diversity and evenness respectively, while soil organic matter displayed a positive correlation with Shannon diversity. Of total, 40.5% OTUs were unique to non-saline water irrigation and 26% to saline water irrigation. The multivariate analyses displayed strong structuring of bacterial communities according to irrigation sources, and both soil EC and irrigation water pH were the major factors affecting communities. The genera <em>Bacillus</em>, <em>Micromonospora</em> and <em>Mycobacterium</em> were dominated while saline water irrigation whereas contrasting pattern was observed for <em>Rhizobium</em>, <em>Streptomyces</em> and <em>Acidibacter</em>. This study suggests that while saline water irrigation date palm root select specific bacterial taxa, potentially playing a crucial role in alleviating salinity stress of the host.</p>
Untargeted metabolomics data for the publication Weiss et al. 2022 "In vitro interaction network of a synthetic gut bacterial community"
<p>This dataset contains the untargeted metabolomics data for the publication Weiss et al. 2022 "In vitro interaction network of a synthetic gut bacterial community". The dataset has also been submitted to MetaboLights repository with ID "MTBLS3535". Please refer to the MetaboLights repository for the most up-to-date datasets. </p> <p>Publication abstract:</p> <p>A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM<sup>12</sup>) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM<sup>12</sup> interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, <em>Enterococcus faecalis</em> KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM<sup>12</sup> interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.</p>
Data for: Can heavy metal pollution induce soil bacterial community resistance to antibiotics in boreal forests?
<p>The emergence of microbial antibiotic resistance is a central threat to global health, food security, and development. It has been shown that heavy metal pollution can give rise to microbial resistance to antibiotics, but how wide-spread this phenomenon is remains an open question that urgently needs filling to enable appropriate environmental risk assessments. Here, we determined whether long-term differences in heavy metal pollution in boreal forests had affected soil microbial communities such that they had increased microbial resistance to antibiotics. First, we assessed variation in metal concentrations in samples collected across a distance trajectory from the pollution source, and also the microbial rates and levels of bacterial community resistance to the heavy metal Cu and the antibiotics tetracycline and vancomycin in those samples. Second, we tested if the exposure to Cu or tetracycline could increase bacterial community resistance to Cu and to antibiotics in soils with high versus low background levels of metal contamination. Metal pollution had affected microbial community structures and suppressed decomposer functioning. Importantly, bacterial community Cu resistance increased with higher metal concentrations, which coincided with an induced bacterial community resistance to tetracycline, but not to vancomycin. Laboratory experiments revealed that bacterial community Cu resistance could be further induced in both the low and high end of the pollution gradient, but also that these short-term inductions of community metal tolerance did not coincide with enhanced antibiotic resistance. This yielded a surprising negative correlation between long-term and short-term effects by metals on microbial metal and antibiotic resistances. One mechanism that could provide protection against both metal cations and tetracycline is the small multidrug resistance (SMR) family, which is an energy demanding physiological mechanism that may take time to confer protection. This may explain the different microbial responses to long-term gradients and metal addition experiments. Policy implications. We show that metal pollution in boreal forests will promote antibiotic resistance in soil bacterial communities, revealing an overlooked reservoir of antibiotic resistance. We recommend that environmental risk assessments for any activity giving rise to increased soil metal concentrations need to also consider the induction of microbial antibiotic resistance.</p>
Bacterial Communities Composition across the French National Territory
<p>Bacterial Communities Composition across the French National Territory : the dataset is composed of 1798 samples and 35 bacterial and archaeal <em>phyla</em> or sub-<em>phyla</em>.</p>
Deep microbiome-based characterization of the alterations in resident bacterial communities of pasteurized bovine milk contaminated with Salmonella Typhimurium over time
Open the record for dataset details and reuse information.
Bacterial communities and toxicity of rotting fish carcases on sandy beaches
<p>Bacterial communities and toxicity of rotting fish carcases on sandy beaches</p>
Fig. 1 in Bacterial communities associated with Megalopyge opercularis (Smith) (Lepidoptera: Megalopygidae): exploring poisonous lepidopterans
Fig. 1. Records of Megalopyge opecularis in North America.
KuafuPrimer: Machine learning facilitates the design of 16S rRNA gene primers with minimal bias in bacterial communities
<p>KuafuPrimer is a machine learning-aided method that learns community characteristics from several samples to design 16S rRNA gene primers with minimal bias for microbial communities. It is built on <strong>Python 3.9.0</strong>, <strong>Pytorch 1.12.0</strong>. Here are some large size files required to run KuafuPrimer, and users need to download and put them in correct directories before running the program.</p> <ol> <li>Silva_ref_data.zip: processed files of silva dataset that should be put in <code>Model_data/Silva_ref_data/</code>.</li> <li>DeepAnno16_publicated_model.zip: parameters of the trained DeepAnno16 model that should be put in <code>Model_data/DeepAnno16_publicated_model/</code> .</li> </ol> <p>For more information, please refer to https://github.com/zhanghaoyu9931/KuafuPrimer.</p>
Dataset - Dynamic persistence of intracellular bacterial communities of uropathogenic Escherichia coli in a human bladder-chip model of urinary tract infections
<p>Dataset for manuscript posted at biorxiv: https://doi.org/10.1101/2021.01.03.42483 and in revision for eLife. Data corresponding to each main figure and its associated figure supplements are in seperate .zip folders.</p>
Bacterial and archaeal communities in the Clarion-Clipperton Zone: comparison between adjacent seamount and abyssal plain communities
<p>This dataset contrasts microbial communities from abyssal plain and seamount samples, collected on the DeepCCZ cruise to the western Clarion-Clipperton Zone in May-June 2018. This cruise sampled paired plain and seamount sites in three Areas of Particular Environmental Interest (APEIs). Samples included CTD casts to collect overlying water and sediment cores and polymetallic nodules (only present on the plains in two APEIs) collected using an ROV.</p> <p>Genomic DNA was extracted from these samples; 16S rRNA genes were amplified using primers targeting the V4-V5 hypervariable regions (as recommended by Parada et al. 2016 doi: 10.1111/1462-2920.13023); and sequenced used PE250v2 chemistry on an Illumina MiSeq. Sequences were quality-controlled, clustered into amplicon sequence variants (ASVs) using DADA2 (Callahan et al. 2016 doi: 10.1038/nmeth.3869), and classified using Silva v138 (Quast et al. 2013 doi: 10.1093/nar/gks1219). Differential abundances between comparisons of interest were calculated using DESeq2 on unnormalized datasets following the authors' recommendations (Love et al. 2014 doi: 10.1186/s13059-014-0550-8). Raw sequences are archived with the Sequence Read Archive (https://www.ncbi.nlm.nih.gov/sra) under project code PRJNA660809.</p> <p>Datasets archived here include:</p> <p>1) DeepCCZ_topography_metadata.xlsx: sampling location and other collection metadata, as well as all available environmental data (e.g., inorganic nutrients, total organic carbon, cell abundance counts), for DNA samples archived in this dataset</p> <p>2) DeepCCZ_topography_unnormalized_counts.xlsx: quality-controlled but otherwise unprocessed ASV results, including sequences associated with each ASV</p> <p>3) DeepCCZ_topography_relabund_UniFrac_with3ums.xlsx: quality-controlled ASV results, subsampled to a lower read count that accommodates the lower-yield 3 µm filter size samples; this sheet includes both relative abundances and a weighted UniFrac distance matrix</p> <p>4) DeepCCZ_topography_relabund_UniFrac_no3ums.xlsx: quality-controlled ASV results, subsampled to a higher read count that excludes the lower-yield 3 µm filter size samples; this sheet includes both relative abundances and a weighted UniFrac distance matrix</p> <p>5) DeepCCZ_topography_DESeq_*.xlsx (7 files): a series of results from numerous DESeq2 tests (Love et al. 2014 doi: 10.1186/s13059-014-0550-8) to identify differentially abundant ASVs in different sample categories. Tests were run on non-subsampled counts, as recommended.</p> <p>6) DeepCCZ_topography_diversity_metrics.xlsx: ASV richness, Pielou's evenness, and Shannon diversity for both levels of subsampling</p> <p> </p> <p>Contact for questions about this dataset: Emma Wear, ekwear.oceans@gmail.com</p>
Supplementary materials for different sources of calcium in the diet on intestinal bacterial community and function of weaned piglets
<p>Supplementary materials for different sources of calcium in the diet on intestinal bacterial community and function of weaned piglets</p>
Bacterial Community Diversity and Bacterial Interaction Network in Eight Mosquito Species
<p>Sequences of the V4 region of 16S rRNA from 111 mosquito samples. </p> <p>This dataset was used for analysis of bacterial diversity and bacterial interaction network in eight mosquito species. Result of the analysis is in the article "Bacterial Community Diversity and Bacterial Interaction Network in Eight Mosquito Species" (Genes 2022, 13(11), 2052; https://doi.org/10.3390/genes13112052).</p>
Different assembly mechanisms of leaf epiphytic and endophytic bacterial communities underlie their higher diversity in more diverse forests
<p><span>Plant microbiomes are known to influence host fitness and ecosystem functioning, but mechanisms regulating their structure are poorly understood. </span><span>Here, we explored the assembly mechanisms of leaf epiphytic and endophytic bacterial communities using a subtropical forest biodiversity experiment. </span></p> <p><span>Both epiphytic and endophytic bacterial diversity increased as host tree diversity increased. However, the increased epiphytic diversity in more diverse forests was driven by greater epiphytic diversity (i.e., greater α diversity) on individual trees, whereas the increased endophytic diversity in more diverse forests was driven by greater dissimilarity in endophytic composition (i.e., greater β diversity) among trees. </span><span>Mechanistically, responses of epiphytes to changes in host diversity were consistent with mass effects, whereas responses of endophytes were consistent with species sorting. </span></p> <p><span><strong>Synthesis</strong>: These results provided novel experimental evidence that biodiversity declines of plant species will lead to biodiversity declines of plant-associated microbiomes, but the underlying mechanism may differ between habitats on the plant host.</span></p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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