Ribosomal RNA diversity predicts genome diversity in gut bacteria and their relatives

The mammalian gut is an attractive model for exploring the general question of how habitat impacts the evolution of gene content. Therefore, we have characterized the relationship between 16 S rRNA gene sequence similarity and overall levels of gene conservation in four groups of species: gut specialists and cosmopolitans, each of which can be divided into pathogens and non-pathogens. At short phylogenetic distances, specialist or cosmopolitan bacteria found in the gut share fewer genes than is typical for genomes that come from non-gut environments, but at longer phylogenetic distances gut bacteria are more similar to each other than are genomes at equivalent evolutionary distances from non-gut environments, suggesting a pattern of short-term specialization but long-term convergence. Moreover, this pattern is observed in both pathogens and non-pathogens, and can even be seen in the plasmids carried by gut bacteria. This observation is consistent with the finding that, despite considerable interpersonal variation in species content, there is surprising functional convergence in the microbiome of different humans. Finally, we observe that even within bacterial species or genera 16S rRNA divergence provides useful information about average conservation of gene content. The results described here should be useful for guiding strain selection to maximize novel gene discovery in large-scale genome sequencing projects, while the approach could be applied in studies seeking to understand the effects of habitat adaptation on genome evolution across other body habitats or environment types

Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses

Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by the Frontiers Research Foundation. The published article can be found at: http://www.frontiersin.org/Microbiology.Keywords: phylogenetic prediction, “virtual” metagenomes, systems biology, predictive metagenomics, ecotoxicology, 16S rRNA gene copy numbe

Coral-associated bacteria demonstrate phylosymbiosis and cophylogeny

Scleractinian corals' microbial symbionts influence host health, yet how coral microbiomes assembled over evolution is not well understood. We survey bacterial and archaeal communities in phylogenetically diverse Australian corals representing more than 425 million years of diversification. We show that coral microbiomes are anatomically compartmentalized in both modern microbial ecology and evolutionary assembly. Coral mucus, tissue, and skeleton microbiomes differ in microbial community composition, richness, and response to host vs. environmental drivers. We also find evidence of coral-microbe phylosymbiosis, in which coral microbiome composition and richness reflect coral phylogeny. Surprisingly, the coral skeleton represents the most biodiverse coral microbiome, and also shows the strongest evidence of phylosymbiosis. Interactions between bacterial and coral phylogeny significantly influence the abundance of four groups of bacteria-including Endozoicomonas-like bacteria, which divide into host-generalist and host-specific subclades. Together these results trace microbial symbiosis across anatomy during the evolution of a basal animal lineage

Effect of particle size distribution and chlorophyll content on beam attenuation spectra

The relationships between beam attenuation spectra, chlorophyll and pheophytin pigment concentrations, and particle size distributions are examined for a coastal region (Monterey Bay area) believed to have negligible concentrations of terrestrially derived dissolved organic compounds (during May 1977) but large quantities of phytoplankton and resuspended sediments. It was found that the slope of the beam attenuation spectra increases when the hyperbolic slope of the size distribution increases. The magnitude of this increase in slope was consistent with calculations based on a range of particle diameters from 0.5 to 30 µm, so that it would be possible to predict the slope of the particle size distribution if the slope of the beam attenuation spectra is known. The ratio of chlorophyll and pheophytin pigments to suspended volume concentrations affected the beam attenuation spectra to a lesser degree and in a more complex manner. Because of the strong effect of slope, it was concluded that the chlorophyll and pheophytin pigment content of suspended particles could not be efficiently predicted by means of beam attenuation measurements

Error in predicting hydrosol backscattering from remotely sensed reflectance

Monte Carlo simulations are carried out to determine the error in the inversion of backscattering from remotely sensed reflectance when geometrical shape factors of the light field are assumed to be unity. The results show that error in backscattering inversion can vary from a 40% overestimation to a 20% underestimation and is dependent on the solar angle and the hydrosol constituents contributing to backscattering. The simulations also demonstrate that for chlorophyll concentrations ranging from 0.05 to 20 mg m⁻³ the most dramatic change in the geometrical shape factor occurs near 1.0 to 1.5 mg m⁻³ chlorophyll. The potential importance of bacteria in influencing the shape factor and the subsequent effect of bacteria on the retrieval of the backscattering from remote sensing reflectance are shown. Quartzlike material's strong impact on geometrical shape factors and errors of retrieval of backscattering at low chlorophyll concentrations are also demonstrated. Remote sensing reflectance inversion schemes must include information about the backscattering function to be successful

Normalization and microbial differential abundance strategies depend upon data characteristics

BackgroundData from 16S ribosomal RNA (rRNA) amplicon sequencing present challenges to ecological and statistical interpretation. In particular, library sizes often vary over several ranges of magnitude, and the data contains many zeros. Although we are typically interested in comparing relative abundance of taxa in the ecosystem of two or more groups, we can only measure the taxon relative abundance in specimens obtained from the ecosystems. Because the comparison of taxon relative abundance in the specimen is not equivalent to the comparison of taxon relative abundance in the ecosystems, this presents a special challenge. Second, because the relative abundance of taxa in the specimen (as well as in the ecosystem) sum to 1, these are compositional data. Because the compositional data are constrained by the simplex (sum to 1) and are not unconstrained in the Euclidean space, many standard methods of analysis are not applicable. Here, we evaluate how these challenges impact the performance of existing normalization methods and differential abundance analyses.ResultsEffects on normalization: Most normalization methods enable successful clustering of samples according to biological origin when the groups differ substantially in their overall microbial composition. Rarefying more clearly clusters samples according to biological origin than other normalization techniques do for ordination metrics based on presence or absence. Alternate normalization measures are potentially vulnerable to artifacts due to library size. Effects on differential abundance testing: We build on a previous work to evaluate seven proposed statistical methods using rarefied as well as raw data. Our simulation studies suggest that the false discovery rates of many differential abundance-testing methods are not increased by rarefying itself, although of course rarefying results in a loss of sensitivity due to elimination of a portion of available data. For groups with large (~10×) differences in the average library size, rarefying lowers the false discovery rate. DESeq2, without addition of a constant, increased sensitivity on smaller datasets (<20 samples per group) but tends towards a higher false discovery rate with more samples, very uneven (~10×) library sizes, and/or compositional effects. For drawing inferences regarding taxon abundance in the ecosystem, analysis of composition of microbiomes (ANCOM) is not only very sensitive (for >20 samples per group) but also critically the only method tested that has a good control of false discovery rate.ConclusionsThese findings guide which normalization and differential abundance techniques to use based on the data characteristics of a given study

Johnston Island light scattering and transmission data : a data report

The data contained in this report represents over 3000 individual scattering measurements taken in the equatorial Pacific in the vicinity of Johnston Island. The purpose of the measurements was to obtain data that would aid in the determination of a correct model for the mixing processes in the vicinity of the island. Consequently a majority of the measurements are vertical profiles of the volume scattering function accompanying standard hydrographic data of salinity, temperature, and depth

Reducing the effects of fouling on chlorophyll estimates derived from long-term deployments of optical instruments

Two methods to alleviate the problem of fouling of moored flow tube optical instruments are presented. A chemical method diffuses a concentrated solution of bromine into the flow tube between sampling periods, creating a toxic environment for microorganisms. An optical method removes a baseline value from the red peak of chlorophyll a. Three spectral absorption meters equipped with the chemical system were deployed in the south eastern Bering Sea from March to September 1993. For a 40-, instrument the system prevented biofouling for the entire deployment, while an 11-m instrument was free of contamination for approximately 3.5 months. Reasonable estimates of in situ chlorophyll a were obtained from all three instruments by the subtraction of the baseline