Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3.
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ABSTRACT:
SUBMITTER: Beghini F
PROVIDER: S-EPMC8096432 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cryoconite holes are small ponds present on the surface of most glaciers filled with meltwater and sediment at the bottom. Although they are characterized by extreme conditions, they host bacterial communities with high taxonomic and functional biodiversity. Despite that evidence for a potential niche for anaerobic microorganisms and anaerobic processes has recently emerged, the composition of the microbial communities of the cryoconite reported so far has not shown the relevant presence of anaerobic taxa. We hypothesize that this is due to the lower growth yield of anaerobes compared to aerobic microorganisms. In this work, we aim at evaluating whether the anaerobic bacterial community represents a relevant fraction of the biodiversity of the cryoconite and at describing its structure and functions. We collected sediment samples from cryoconite holes on the Forni Glacier (Italy) and sequenced both 16S rRNA amplicon genes and 16S rRNA amplicon transcripts at different times of the day along a clear summer day. Results showed that a relevant fraction of taxa has been detected only by 16S rRNA transcripts and was undetectable in 16S rRNA gene amplicons. Furthermore, in the transcript approach, anaerobic taxa were overrepresented compared with DNA sequencing. The metatranscriptomics approach was used also to investigate the expression of the main metabolic functions. Results showed the occurrence of syntrophic and commensalism relationships among fermentative bacteria, hydrogenothrophs, and consumers of fermentation end products, which have never been reported so far in cryoconite. IMPORTANCE Recent evidence disclosed the presence of a potential niche for anaerobic microorganisms and anaerobic processes in supraglacial sediments (cryoconite), but a detailed description of the structure and functions of the anaerobic population is still lacking. This work used rRNA and mRNA sequencing and demonstrated that anaerobes are very active in these environments and represent a relevant albeit neglected part of the ecosystem functions in these environments.
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Project description:BackgroundPolyethylene (PE) is one of the most abundant plastic wastes which accumulates in marine and terrestrial environments. As microbial degradation has been a promising approach for the bioremediation of polluted environments, identification of the microbial community profile where these pollutants accumulate, has recently been in focus.ObjectiveWe have investigated the taxonomic and functional characteristics of polyethylene- degrading microorganisms in a plastic waste recycling site in Tehran, Iran.Materials and methodsWe have analyzed and compared a 16S rRNA dataset from this study with 15 datasets from 4 diverse plastic and oil polluted habitats to identify and evaluate bacterial communities involved in bioremediation.ResultsOur findings reveal that Proteobacteria, Actinobacteria, Acidobacteria and Cloroflexi were the dominant phyla and Actinobacteria, Alphaproteobacteria, Gammaproteobacteria and Acidimicrobia were dominant classes in these samples. The most dominant Kegg Orthology associated with PE bioremediation in these samples are related to peroxidases, alcohol dehydrogenases, monooxygenases and dioxygenases.ConclusionsLong-term presence of contaminants in soil could lead to changes in bacterial phyla abundance, resulting in metabolic adaptations to optimize biological activity and waste management in a diverse group of bacteria.
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Project description:BackgroundSynthetic microbial communities offer an opportunity to conduct reductionist research in tractable model systems. However, deriving abundances of highly related strains within these communities is currently unreliable. 16S rRNA gene sequencing does not resolve abundance at the strain level, standard methods for analysis of shotgun metagenomic sequencing do not account for ambiguous mapping between closely related strains, and other methods such as quantitative PCR (qPCR) scale poorly and are resource prohibitive for complex communities. We present StrainR2, which utilizes shotgun metagenomic sequencing paired with a k-mer-based normalization strategy to provide high accuracy strain-level abundances for all members of a synthetic community, provided their genomes.ResultsBoth in silico, and using sequencing data derived from gnotobiotic mice colonized with a synthetic fecal microbiota, StrainR2 resolves strain abundances with greater accuracy than other tools utilizing shotgun metagenomic sequencing reads and can resolve complex mixtures of highly related strains. Through experimental validation and benchmarking, we demonstrate that StrainR2's accuracy is comparable to that of qPCR on a subset of strains resolved using absolute quantification. Further, it is capable of scaling to communities of hundreds of strains and efficiently utilizes memory being capable of running both on personal computers and high-performance computing nodes.ConclusionsUsing shotgun metagenomic sequencing reads is a viable method for determining accurate strain-level abundances in synthetic communities using StrainR2.
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Project description:Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples. From the Qinghai Oilfield located in the Tibetan Plateau, northwest China, oil production mixtures were taken from four oil production wells (No. 813, 516, 48 and 27) and one injection well (No. 517) in the Yue-II block. The floating oil and water phases of the production mixtures were separated overnight by gravitational separation. Subsequently, the microbial community and the characteristics of the water solution (W813, W516, W48, and W27) and floating crude oil (O813, O516, O48, and O27) samples were analyzed. A similar analysis was performed with the injection water solution (W517).
2016-04-01 | E-GEOD-55293 | biostudies-arrayexpress
Project description:Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic ?-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.
| S-EPMC5029178 | biostudies-literature
Project description:BackgroundDiet plays a crucial role in sculpting microbial communities. Similar diets appear to drive convergence of gut microbial communities between host species. Captivity usually provides an identical diet and environment to different animal species that normally have similar diets. Whether different species' microbial gut communities can be homogenized by a uniform diet in captivity remains unclear.MethodsIn this study, we compared gut microbial communities of three insectivorous bat species (Rhinolophus ferrumequinum, Vespertilio sinensis, and Hipposideros armiger) in captivity and in the wild using 16S rDNA sequencing. In captivity, R. ferrumequinum and V. sinensis were fed yellow mealworms, while H. armiger was fed giant mealworms to rule out the impact of an identical environment on the species' gut microbial communities.ResultsWe found that the microbial communities of the bat species we studied clustered by species in the wild, while the microbial communities of R. ferrumequinum and V. sinensis in captivity clustered together. All microbial functions found in captive V. sinensis were shared by R. ferrumequinum. Moreover, the relative abundances of all metabolism related KEGG pathways did not significantly differ between captive R. ferrumequinum and V. sinensis; however, the relative abundance of "Glycan Biosynthesis and Metabolism" differed significantly between wild R. ferrumequinum and V. sinensis.ConclusionOur results suggest that consuming identical diets while in captivity tends to homogenize the gut microbial communities among bat species. This study further highlights the importance of diet in shaping animal gut microbiotas.
| S-EPMC6499062 | biostudies-literature
Project description:Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples.
2016-04-01 | GSE55293 | GEO
Project description:BackgroundTaxonomic classification of genetic markers for microbiome analysis is affected by the numerous choices made from sample preparation to bioinformatics analysis. Paired-end read merging is routinely used to capture the entire amplicon sequence when the read ends overlap. However, the exclusion of unmerged reads from further analysis can result in underestimating the diversity in the sequenced microbial community and is influenced by bioinformatic processes such as read trimming and the choice of reference database. A potential solution to overcome this is to concatenate (join) reads that do not overlap and keep them for taxonomic classification. The use of concatenated reads can outperform taxonomic recovery from single-end reads, but it remains unclear how their performance compares to merged reads. Using various sequenced mock communities with different amplicons, read length, read depth, taxonomic composition, and sequence quality, we tested how merging and concatenating reads performed for genus recall and precision in bioinformatic pipelines combining different parameters for read trimming and taxonomic classification using different reference databases.ResultsThe addition of concatenated reads to merged reads always increased pipeline performance. The top two performing pipelines both included read concatenation, with variable strengths depending on the mock community. The pipeline that combined merged and concatenated reads that were quality-trimmed performed best for mock communities with larger amplicons and higher average quality sequences. The pipeline that used length-trimmed concatenated reads outperformed quality trimming in mock communities with lower quality sequences but lost a significant amount of input sequences for taxonomic classification during processing. Genus level classification was more accurate using the SILVA reference database compared to Greengenes.ConclusionsMerged sequences with the addition of concatenated sequences that were unable to be merged increased performance of taxonomic classifications. This was especially beneficial in mock communities with larger amplicons. We have shown for the first time, using an in-depth comparison of pipelines containing merged vs concatenated reads combined with different trimming parameters and reference databases, the potential advantages of concatenating sequences in improving resolution in microbiome investigations.
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Project description:Profiling microbial community function from metagenomic sequencing data remains a computationally challenging problem. Mapping millions of DNA reads from such samples to reference protein databases requires long run-times, and short read lengths can result in spurious hits to unrelated proteins (loss of specificity). We developed ShortBRED (Short, Better Representative Extract Dataset) to address these challenges, facilitating fast, accurate functional profiling of metagenomic samples. ShortBRED consists of two components: (i) a method that reduces reference proteins of interest to short, highly representative amino acid sequences ("markers") and (ii) a search step that maps reads to these markers to quantify the relative abundance of their associated proteins. After evaluating ShortBRED on synthetic data, we applied it to profile antibiotic resistance protein families in the gut microbiomes of individuals from the United States, China, Malawi, and Venezuela. Our results support antibiotic resistance as a core function in the human gut microbiome, with tetracycline-resistant ribosomal protection proteins and Class A beta-lactamases being the most widely distributed resistance mechanisms worldwide. ShortBRED markers are applicable to other homology-based search tasks, which we demonstrate here by identifying phylogenetic signatures of antibiotic resistance across more than 3,000 microbial isolate genomes. ShortBRED can be applied to profile a wide variety of protein families of interest; the software, source code, and documentation are available for download at http://huttenhower.sph.harvard.edu/shortbred.
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Project description:A remaining challenge within microbial ecology is to understand the determinants of richness and diversity observed in environmental microbial communities. In a range of systems, including activated sludge bioreactors, the microbial residence time (MRT) has been previously shown to shape the microbial community composition. However, the physiological and ecological mechanisms driving this influence have remained unclear. Here, this relationship is explored by analyzing an activated sludge system fed with municipal wastewater. Using a model designed in this study based on Monod-growth kinetics, longer MRTs were shown to increase the range of growth parameters that enable persistence, resulting in increased richness and diversity in the modeled community. In laboratory experiments, six sequencing batch reactors treating domestic wastewater were operated in parallel at MRTs between 1 and 15 days. The communities were characterized using both 16S ribosomal RNA and non-target messenger RNA sequencing (metatranscriptomic analysis), and model-predicted monotonic increases in richness were confirmed in both profiles. Accordingly, taxonomic Shannon diversity also increased with MRT. In contrast, the diversity in enzyme class annotations resulting from the metatranscriptomic analysis displayed a non-monotonic trend over the MRT gradient. Disproportionately high abundances of transcripts encoding for rarer enzymes occur at longer MRTs and lead to the disconnect between taxonomic and functional diversity profiles.
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