Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Langille, Morgan G. I.; Zaneveld, Jesse; Caporaso, J. Gregory; McDonald, Daniel; Knights, Dan; Reyes, Joshua A; Clemente, José C.; Burkepile, Deron E.; Thurber, Rebecca L. Vega; Knight, Rob; Beiko, Robert G.; Huttenhower, Curtis

doi:10.1038/nbt.2676

Cited by 7,675 publications

(6,284 citation statements)

References 48 publications

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“…The resulting OTU table was uploaded to R v.3.0.2 (38) for further analyses. We also projected functional profiles from our 16S rRNA gene data using PICRUSt (39). These were compared with our metagenomic data sets and allowed us to predict changes in major functional gene groups over time, as well as in the bacteria cultured on each of the five media types.…”

Section: Methodsmentioning

confidence: 99%

Cutting Edge: IL-17–Secreting Innate Lymphoid Cells Are Essential for Host Defense against Fungal Infection

Gladiator

Wangler

Trautwein-Weidner

et al. 2013

The Journal of Immunology

336

321

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Soil microbiome modification may alter system function, which may enhance processes like bioremediation. In this study, we filled microcosms with gamma-irradiated soil that was reinoculated with the initial soil or cultivated bacterial subsets obtained on regular media (REG-M) or media containing crude oil (CO-M). We allowed 8 weeks for microbiome stabilization, added crude oil and monoammonium phosphate, incubated the microcosms for another 6 weeks, and then measured the biodegradation of crude oil components, bacterial taxonomy, and functional gene composition. We hypothesized that the biodegradation of targeted crude oil components would be enhanced by limiting the microbial taxa competing for resources and by specifically selecting bacteria involved in crude oil biodegradation (i.e., CO-M). Postincubation, large differences in taxonomy and functional gene composition between the three microbiome types remained, indicating that purposeful soil microbiome structuring is feasible. Although phylum-level bacterial taxonomy was constrained, operational taxonomic unit composition varied between microbiome types. Contrary to our hypothesis, the biodegradation of C 10 to C 50 hydrocarbons was highest when the original microbiome was reinoculated, despite a higher relative abundance of alkane hydroxylase genes in the CO-M microbiomes and of carbon-processing genes in the REG-M microbiomes. Despite increases in the relative abundances of genes potentially linked to hydrocarbon processing in cultivated subsets of the microbiome, reinoculation of the initial microbiome led to maximum biodegradation. IMPORTANCEIn this study, we show that it is possible to sustainably modify microbial assemblages in soil. This has implications for biotechnology, as modification of gut microbial assemblages has led to improved treatments for diseases like Clostridium difficile infection. Although the soil environment determined which major phylogenetic groups of bacteria would dominate the assemblage, we saw differences at lower levels of taxonomy and in functional gene composition (e.g., genes related to hydrocarbon degradation). Further studies are needed to determine the success of such an approach in nonsterile environments. Although the biodegradation of certain crude oil fractions was still the highest when we inoculated with the diverse initial microbiome, the possibility of discovering and establishing microbiomes that are more efficient in crude oil degradation is not precluded.O il production, oil spills, and the storage of oily wastes by the petroleum industry have led to massive releases of petroleum hydrocarbons into the environment, making them some of the most ubiquitous environmental pollutants (1). Conventional decontamination technologies such as excavation (i.e., dig and dump), incineration, and chemical treatment of contaminants are costly and may further disrupt disturbed ecosystems (2, 3). When effective, bioremediation is a cheaper and more sustainable approach to decontamination. Bioaugmentation, the addition...

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Section: Methodsmentioning

confidence: 99%

Cutting Edge: IL-17–Secreting Innate Lymphoid Cells Are Essential for Host Defense against Fungal Infection

Gladiator

Wangler

Trautwein-Weidner

et al. 2013

The Journal of Immunology

336

321

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“…Additional statistical, alpha diversity, and beta diversity analyses were performed by using linear discriminant analysis coupled with effect size measurements (LEfSe) (40), R, and Qiime (41). Enterotype analysis was implemented in R. Prediction of metagenome functional content was performed based on 16S rRNA sequences by using the PICRUSt software package (36).…”

Section: Subjectsmentioning

confidence: 99%

Dysbiosis and Alterations in Predicted Functions of the Subgingival Microbiome in Chronic Periodontitis

Kirst

Alfant

et al. 2015

Appl Environ Microbiol

188

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Chronic periodontitis is an inflammatory disease of the periodontium affecting nearly 65 million adults in the United States. Changes in subgingival microbiota have long been associated with chronic periodontitis. Recent culture-independent molecular studies have revealed the immense richness and complexity of oral microbial communities. However, data sets across studies have not been directly compared, and whether the observed microbial variations are consistent across different studies is not known. Here, we used 16S rRNA sequencing to survey the subgingival microbiota in 25 subjects with chronic periodontal disease and 25 healthy controls and compared our data sets with those of three previously reported microbiome studies. Consistent with data from previous studies, our results demonstrate a significantly altered microbial community structure with decreased heterogeneity in periodontal disease. Comparison with data from three previously reported studies revealed that subgingival microbiota clustered by study. However, differences between periodontal health and disease were larger than the technical variations across studies. Using a prediction score and applying five different distance metrics, we observed two predominant clusters. One cluster was driven by Fusobacterium and Porphyromonas and was associated with clinically apparent periodontitis, and the second cluster was dominated by Rothia and Streptococcus in the majority of healthy sites. The predicted functional capabilities of the periodontitis microbiome were significantly altered. Genes involved in bacterial motility, energy metabolism, and lipopolysaccharide biosynthesis were overrepresented in periodontal disease, whereas genes associated with transporters, the phosphotransferase system, transcription factors, amino acid biosynthesis, and glycolysis/gluconeogenesis were enriched in healthy controls. These results demonstrate significant alterations in microbial composition and function in periodontitis and suggest genes and metabolic pathways associated with periodontal disease. P eriodontal disease is a common disease affecting many adults in the United States. If left untreated, chronic periodontitis (CP) can lead to serious problems such as tooth loss. Indeed, periodontal disease is the number one cause of tooth loss in the United States, accounting for half of all tooth loss in U.S. adults (1). There is considerable evidence that the clinical impact of periodontal disease extends beyond the oral cavity (2). Strong associations have been found between periodontitis and a number of systemic conditions, including cardiovascular disease (3, 4), preterm delivery and low-birth-weight babies (5), diabetes mellitus (6-8), and rheumatoid arthritis (9-11).The activity of periodontal disease is determined by a complex interplay between the immune system and periodontal pathogens (12, 13). Alterations in subgingival microbiota have long been associated with the development and progression of periodontitis (14). In susceptible individuals, perturbations in...

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“…According to the reference database, the representative sequences for each OTU were aligned using PyNAST (Caporaso et al, 2010a). Finally, the phylogenetic tree was generated from the Graphlan (Langille et al, 2013) using information on both the relative abundance and phylogenetic relationship of observed species. QIIME 1.8.0 was used for sequence analysis including OTUs extraction for bacterioplankton community structure analysis, OTUs overlapping analysis, species diversity, species richness analysis and principal components analysis (PCA; Caporaso et al, 2010b).…”

Section: Sequence Assignment and Sequence Statistics Analysismentioning

confidence: 99%

Interactive network configuration maintains bacterioplankton community structure under elevated CO<sub>2</sub> in a eutrophic coastal mesocosm experiment

Lin¹,

Huang²,

Li³

et al. 2018

Biogeosciences

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Abstract. There is increasing concern about the effects of ocean acidification on marine biogeochemical and ecological processes and the organisms that drive them, including marine bacteria. Here, we examine the effects of elevated CO 2 on the bacterioplankton community during a mesocosm experiment using an artificial phytoplankton community in subtropical, eutrophic coastal waters of Xiamen, southern China. Through sequencing the bacterial 16S rRNA gene V3-V4 region, we found that the bacterioplankton community in this high-nutrient coastal environment was relatively resilient to changes in seawater carbonate chemistry. Based on comparative ecological network analysis, we found that elevated CO 2 hardly altered the network structure of high-abundance bacterioplankton taxa but appeared to reassemble the community network of low abundance taxa. This led to relatively high resilience of the whole bacterioplankton community to the elevated CO 2 level and associated chemical changes. We also observed that the Flavobacteria group, which plays an important role in the microbial carbon pump, showed higher relative abundance under the elevated CO 2 condition during the early stage of the phytoplankton bloom in the mesocosms. Our results provide new insights into how elevated CO 2 may influence bacterioplankton community structure.

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Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Cited by 7,675 publications

References 48 publications

Cutting Edge: IL-17–Secreting Innate Lymphoid Cells Are Essential for Host Defense against Fungal Infection

Cutting Edge: IL-17–Secreting Innate Lymphoid Cells Are Essential for Host Defense against Fungal Infection

Dysbiosis and Alterations in Predicted Functions of the Subgingival Microbiome in Chronic Periodontitis

Interactive network configuration maintains bacterioplankton community structure under elevated CO<sub>2</sub> in a eutrophic coastal mesocosm experiment

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Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Cited by 7,675 publications

References 48 publications

Cutting Edge: IL-17–Secreting Innate Lymphoid Cells Are Essential for Host Defense against Fungal Infection

Cutting Edge: IL-17–Secreting Innate Lymphoid Cells Are Essential for Host Defense against Fungal Infection

Dysbiosis and Alterations in Predicted Functions of the Subgingival Microbiome in Chronic Periodontitis

Interactive network configuration maintains bacterioplankton community structure under elevated CO&lt;sub&gt;2&lt;/sub&gt; in a eutrophic coastal mesocosm experiment

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Interactive network configuration maintains bacterioplankton community structure under elevated CO<sub>2</sub> in a eutrophic coastal mesocosm experiment