The coral core microbiome identifies rare bacterial taxa as ubiquitous endosymbionts.
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ABSTRACT:
SUBMITTER: D Ainsworth T
PROVIDER: S-EPMC4579478 | biostudies-literature | 2015 Oct
REPOSITORIES: biostudies-literature
Publications
The coral core microbiome identifies rare bacterial taxa as ubiquitous endosymbionts.
D Ainsworth Tracy T Krause Lutz L Bridge Thomas T Torda Gergely G Raina Jean-Baptise JB Zakrzewski Martha M Gates Ruth D RD Padilla-Gamiño Jacqueline L JL Spalding Heather L HL Smith Celia C Woolsey Erika S ES Bourne David G DG Bongaerts Pim P Hoegh-Guldberg Ove O Leggat William W
The ISME journal 20150417 10
Despite being one of the simplest metazoans, corals harbor some of the most highly diverse and abundant microbial communities. Differentiating core, symbiotic bacteria from this diverse host-associated consortium is essential for characterizing the functional contributions of bacteria but has not been possible yet. Here we characterize the coral core microbiome and demonstrate clear phylogenetic and functional divisions between the micro-scale, niche habitats within the coral host. In doing so, ...[more]
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Project description:Sequences of Coral Endosymbionts ITS Region Metagenome
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Project description:The human gut harbors thousands of bacterial taxa. A profusion of metagenomic sequence data has been generated from human stool samples in the last few years, raising the question of whether more taxa remain to be identified. We assessed metagenomic data generated by the Human Microbiome Project Consortium to determine if novel taxa remain to be discovered in stool samples from healthy individuals. To do this, we established a rigorous bioinformatics pipeline that uses sequence data from multiple platforms (Illumina GAIIX and Roche 454 FLX Titanium) and approaches (whole-genome shotgun and 16S rDNA amplicons) to validate novel taxa. We applied this approach to stool samples from 11 healthy subjects collected as part of the Human Microbiome Project. We discovered several low-abundance, novel bacterial taxa, which span three major phyla in the bacterial tree of life. We determined that these taxa are present in a larger set of Human Microbiome Project subjects and are found in two sampling sites (Houston and St. Louis). We show that the number of false-positive novel sequences (primarily chimeric sequences) would have been two orders of magnitude higher than the true number of novel taxa without validation using multiple datasets, highlighting the importance of establishing rigorous standards for the identification of novel taxa in metagenomic data. The majority of novel sequences are related to the recently discovered genus Barnesiella, further encouraging efforts to characterize the members of this genus and to study their roles in the microbial communities of the gut. A better understanding of the effects of less-abundant bacteria is important as we seek to understand the complex gut microbiome in healthy individuals and link changes in the microbiome to disease.
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Project description:Background: The accuracy of microbial community detection in 16S rRNA marker-gene and metagenomic studies suffers from contamination and sequencing errors that lead to either falsely identifying microbial taxa that were not in the sample or misclassifying the taxa of DNA fragment reads. Removing contaminants and filtering rare features are two common approaches to deal with this problem. While contaminant detection methods use auxiliary sequencing process information to identify known contaminants, filtering methods remove taxa that are present in a small number of samples and have small counts in the samples where they are observed. The latter approach reduces the extreme sparsity of microbiome data and has been shown to correctly remove contaminant taxa in cultured "mock" datasets, where the true taxa compositions are known. Although filtering is frequently used, careful evaluation of its effect on the data analysis and scientific conclusions remains unreported. Here, we assess the effect of filtering on the alpha and beta diversity estimation as well as its impact on identifying taxa that discriminate between disease states. Results: The effect of filtering on microbiome data analysis is illustrated on four datasets: two mock quality control datasets where the same cultured samples with known microbial composition are processed at different labs and two disease study datasets. Results show that in microbiome quality control datasets, filtering reduces the magnitude of differences in alpha diversity and alleviates technical variability between labs while preserving the between samples similarity (beta diversity). In the disease study datasets, DESeq2 and linear discriminant analysis Effect Size (LEfSe) methods were used to identify taxa that are differentially abundant across groups of samples, and random forest models were used to rank features with the largest contribution toward disease classification. Results reveal that filtering retains significant taxa and preserves the model classification ability measured by the area under the receiver operating characteristic curve (AUC). The comparison between the filtering and the contaminant removal method shows that they have complementary effects and are advised to be used in conjunction. Conclusions: Filtering reduces the complexity of microbiome data while preserving their integrity in downstream analysis. This leads to mitigation of the classification methods' sensitivity and reduction of technical variability, allowing researchers to generate more reproducible and comparable results in microbiome data analysis.
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Project description:Microbial communities have a key role in the physiology of the sponge host, and it is therefore essential to understand the stability and specificity of sponge-symbiont associations. Host-specific bacterial associations spanning large geographic distance are widely acknowledged in sponges. However, the full spectrum of specificity remains unclear. In particular, it is not known whether closely related sponges host similar or very different microbiota over wide bathymetric and geographic gradients, and whether specific associations extend to the rare members of the sponge microbiome. Using the ultra-deep Illumina sequencing technology, we conducted a comparison of sponge bacterial communities in seven closely related Hexadella species with a well-resolved host phylogeny, as well as of a distantly related sponge Mycale. These samples spanned unprecedentedly large bathymetric (15-960 m) gradients and varying European locations. In addition, this study included a bacterial community analysis of the local background seawater for both Mycale and the widespread deep-sea taxa Hexadella cf. dedritifera. We observed a striking diversity of microbes associated with the sponges, spanning 47 bacterial phyla. The data did not reveal any Hexadella microbiota co-speciation pattern, but confirmed sponge-specific and species-specific host-bacteria associations, even within extremely low abundant taxa. Oligotyping analysis also revealed differential enrichment preferences of closely related Nitrospira members in closely related sponges species. Overall, these results demonstrate highly diverse, remarkably specific and stable sponge-bacteria associations that extend to members of the rare biosphere at a very fine phylogenetic scale, over significant geographic and bathymetric gradients.
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Project description:In many studies, rare bacterial taxa have been found to increase in response to environmental changes. These changes have been proposed to contribute to the insurance of ecosystem functions. However, it has not been systematically tested if rare taxa are more likely to increase in abundance than dominant taxa. Here, we study whether rare soil bacterial taxa are more likely to respond to environmental disturbances and if rare taxa are more opportunistic than dominant taxa. To test this, we applied nine different disturbance treatments to a grassland soil and observed changes in bacterial community composition over 7 days. While 12% of the dominant taxa changed in abundance, only 1% of the rare taxa showed any effect. Rare taxa increased in response to a single disturbance treatment only, while dominant taxa responded to up to five treatments. We conclude that rare taxa are not more likely to contribute to community dynamics after disturbances than dominant taxa. Nevertheless, as rare taxa outnumber abundant taxa with here 230 taxa that changed significantly, the chance is high that some of these rare taxa might act as ecologically important keystone taxa. Therefore, rare and abundant taxa might both contribute to ecosystem insurance.
| S-EPMC7379498 | biostudies-literature
Project description:Despite the importance of microbial communities in ecosystem functions, the mechanisms underlying the assembly of rare taxa over time are poorly understood. It remains largely unknown whether rare taxa exhibit similar assembly processes to common taxa in local communities. We herein retrieved the 16S rRNA sequences of bacteria collected bimonthly for 2 years from the Pohang wastewater treatment plant. The transient-rare taxa showed different abundance distributions from the common taxa. Transient-rare taxon assemblages also exhibited higher temporal variations than common taxon assemblages, suggesting the distinct ecological patterns of the two assemblages. A multivariate analysis revealed that environmental parameters accounted for 25.3 and 61.6% of temporal variations in the transient-rare and common taxon assemblages, respectively. The fitting of all observed taxa to a neutral community model revealed that 96.4% of the transient-rare taxa (relative abundance, 71.4%) and 73.3% of the common taxa (relative abundance, 45.6%) followed the model, suggesting that stochastic mechanisms were more important than deterministic ones in the assembly of the transient-rare taxa. Collectively, the present results indicate that the transient-rare bacterial taxa at the Pohang wastewater treatment plant differed from the common taxa in ecological patterns, suggesting that dispersal is a key process in their assembly.
| S-EPMC7966942 | biostudies-literature
Project description:Cystic fibrosis (CF) patients suffer from chronic bacterial lung infections that lead to death in the majority of cases. The need to maintain lung function in these patients means that characterising these infections is vital. Increasingly, culture-independent analyses are expanding the number of bacterial species associated with CF respiratory samples; however, the potential significance of these species is not known. Here, we applied ecological statistical tools to such culture-independent data, in a novel manner, to partition taxa within the metacommunity into core and satellite species. Sputa and clinical data were obtained from 14 clinically stable adult CF patients. Fourteen rRNA gene libraries were constructed with 35 genera and 82 taxa, identified in 2139 bacterial clones. Shannon-Wiener and taxa-richness analyses confirmed no undersampling of bacterial diversity. By decomposing the distribution using the ratio of variance to the mean taxon abundance, we partitioned objectively the species abundance distribution into core and satellite species. The satellite group comprised 67 bacterial taxa from 33 genera and the core group, 15 taxa from 7 genera (including Pseudomonas (1 taxon), Streptococcus (2), Neisseria (2), Catonella (1), Porphyromonas (1), Prevotella (5) and Veillonella (3)], the last four being anaerobes). The core group was dominated by Pseudomonas aeruginosa. Other recognised CF pathogens were rare. Mantel and partial Mantel tests assessed which clinical factors influenced the composition observed. CF transmembrane conductance regulator genotype and antibiotic treatment correlated with all core taxa. Lung function correlated with richness. The clinical significance of these core and satellite species findings in the CF lung is discussed. GenBank accession numbers: FM995625–FM997761
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Project description:Coastal zones are exposed to various anthropogenic impacts, such as different types of wastewater pollution, e.g., treated wastewater discharges, leakage from sewage systems, and agricultural and urban runoff. These various inputs can introduce allochthonous organic matter and microbes, including pathogens, into the coastal marine environment. The presence of fecal bacterial indicators in the coastal environment is usually monitored using traditional culture-based methods that, however, fail to detect their uncultured representatives. We have conducted a year-around in situ survey of the pelagic microbiome of the dynamic coastal ecosystem, subjected to different anthropogenic pressures to depict the seasonal and spatial dynamics of traditional and alternative fecal bacterial indicators. To provide an insight into the environmental conditions under which bacterial indicators thrive, a suite of environmental factors and bacterial community dynamics were analyzed concurrently. Analyses of 16S rRNA amplicon sequences revealed that the coastal microbiome was primarily structured by seasonal changes regardless of the distance from the wastewater pollution sources. On the other hand, fecal bacterial indicators were not affected by seasons and accounted for up to 34% of the sequence proportion for a given sample. Even more so, traditional fecal indicator bacteria (Enterobacteriaceae) and alternative wastewater-associated bacteria (Lachnospiraceae, Ruminococcaceae, Arcobacteraceae, Pseudomonadaceae and Vibrionaceae) were part of the core coastal microbiome, i.e., present at all sampling stations. Microbial source tracking and Lagrangian particle tracking, which we employed to assess the potential pollution source, revealed the importance of riverine water as a vector for transmission of allochthonous microbes into the marine system. Further phylogenetic analysis showed that the Arcobacteraceae in our data set was affiliated with the pathogenic Arcobacter cryaerophilus, suggesting that a potential exposure risk for bacterial pathogens in anthropogenically impacted coastal zones remains. We emphasize that molecular analyses combined with statistical and oceanographic models may provide new insights for environmental health assessment and reveal the potential source and presence of microbial indicators, which are otherwise overlooked by a cultivation approach.
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Project description:BACKGROUND:Coral diseases are emerging as a serious threat to coral reefs worldwide. Of nine coral infectious diseases, whose pathogens have been characterized, six are caused by agents from the family Vibrionacae, raising questions as to their origin and role in coral disease aetiology. METHODOLOGY/PRINCIPAL FINDINGS:Here we report on a Vibrio zinc-metalloprotease causing rapid photoinactivation of susceptible Symbiodinium endosymbionts followed by lesions in coral tissue. Symbiodinium photosystem II inactivation was diagnosed by an imaging pulse amplitude modulation fluorometer in two bioassays, performed by exposing Symbiodinium cells and coral juveniles to non-inhibited and EDTA-inhibited supernatants derived from coral white syndrome pathogens. CONCLUSION/SIGNIFICANCE:These findings demonstrate a common virulence factor from four phylogenetically related coral pathogens, suggesting that zinc-metalloproteases may play an important role in Vibrio pathogenicity in scleractinian corals.
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Project description:BackgroundBananas (Musa spp.) are a globally significant crop and are severely afflicted by diseases for which there are no effective chemical controls. Banana microbiomes may provide novel solutions to these constraints but are difficult to manage due to their high diversity and variability between locations. Hence 'common core' taxa, which are a subset of the microbiome that frequent all, or most, individuals of a host species, represent logical targets for the development of microbiome management approaches. Here, we first performed a pot experiment to characterise the effects of two factors that are likely to differ between farms (viz. edaphic conditions and host genotype) on bacterial diversity in bulk soil and seven plant compartments. From this experiment, we created shortlisted core 'candidates' that were then refined using a survey of 52 field-grown Musa spp. We confirmed the importance of the core through network analysis and by comparing the sequences of our core taxa with those reported in 22 previous studies.ResultsDiversity was found to differ between plant compartments and soils, but not genotypes. Therefore, we identified populations that were frequent across most plants irrespective of the soil in which they were grown. This led to the selection of 36 'common core' bacteria, that represented 65-95% of the dominant taxa in field-grown plants and were identified as highly interconnected 'hubs' using network analysis - a characteristic shown to be indicative of microbes that influence host fitness in studies of other plants. Lastly, we demonstrated that the core taxa are closely related to banana-associated bacteria observed on five other continents.ConclusionsOur study provides a robust list of common core bacterial taxa for Musa spp. Further research may now focus on how changes in the frequencies and activities of these most persistent taxa influence host fitness. Notably, for several of our core taxa, highly similar populations have already been isolated in previous studies and may be amenable to such experimentation. This contribution should help to accelerate the development of effective Musa spp. microbiome management practices.
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