156 research outputs found

    A fresh look at the evolution and diversification of photochemical reaction centers

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    In this review, I reexamine the origin and diversification of photochemical reaction centers based on the known phylogenetic relations of the core subunits, and with the aid of sequence and structural alignments. I show, for example, that the protein folds at the C-terminus of the D1 and D2 subunits of Photosystem II, which are essential for the coordination of the water-oxidizing complex, were already in place in the most ancestral Type II reaction center subunit. I then evaluate the evolution of reaction centers in the context of the rise and expansion of the different groups of bacteria based on recent large-scale phylogenetic analyses. I find that the Heliobacteriaceae family of Firmicutes appears to be the earliest branching of the known groups of phototrophic bacteria; however, the origin of photochemical reaction centers and chlorophyll synthesis cannot be placed in this group. Moreover, it becomes evident that the Acidobacteria and the Proteobacteria shared a more recent common phototrophic ancestor, and this is also likely for the Chloroflexi and the Cyanobacteria. Finally, I argue that the discrepancies among the phylogenies of the reaction center proteins, chlorophyll synthesis enzymes, and the species tree of bacteria are best explained if both types of photochemical reaction centers evolved before the diversification of the known phyla of phototrophic bacteria. The primordial phototrophic ancestor must have had both Type I and Type II reaction centers

    Analyses of the Microbial Diversity across the Human Microbiome

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    Analysis of human body microbial diversity is fundamental to understanding community structure, biology and ecology. The National Institutes of Health Human Microbiome Project (HMP) has provided an unprecedented opportunity to examine microbial diversity within and across body habitats and individuals through pyrosequencing-based profiling of 16 S rRNA gene sequences (16 S) from habits of the oral, skin, distal gut, and vaginal body regions from over 200 healthy individuals enabling the application of statistical techniques. In this study, two approaches were applied to elucidate the nature and extent of human microbiome diversity. First, bootstrap and parametric curve fitting techniques were evaluated to estimate the maximum number of unique taxa, Smax, and taxa discovery rate for habitats across individuals. Next, our results demonstrated that the variation of diversity within low abundant taxa across habitats and individuals was not sufficiently quantified with standard ecological diversity indices. This impact from low abundant taxa motivated us to introduce a novel rank-based diversity measure, the Tail statistic, (“τ”), based on the standard deviation of the rank abundance curve if made symmetric by reflection around the most abundant taxon. Due to τ’s greater sensitivity to low abundant taxa, its application to diversity estimation of taxonomic units using taxonomic dependent and independent methods revealed a greater range of values recovered between individuals versus body habitats, and different patterns of diversity within habitats. The greatest range of τ values within and across individuals was found in stool, which also exhibited the most undiscovered taxa. Oral and skin habitats revealed variable diversity patterns, while vaginal habitats were consistently the least diverse. Collectively, these results demonstrate the importance, and motivate the introduction, of several visualization and analysis methods tuned specifically for next-generation sequence data, further revealing that low abundant taxa serve as an important reservoir of genetic diversity in the human microbiome

    Germ Warfare in a Microbial Mat Community: CRISPRs Provide Insights into the Co-Evolution of Host and Viral Genomes

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    CRISPR arrays and associated cas genes are widespread in bacteria and archaea and confer acquired resistance to viruses. To examine viral immunity in the context of naturally evolving microbial populations we analyzed genomic data from two thermophilic Synechococcus isolates (Syn OS-A and Syn OS-B′) as well as a prokaryotic metagenome and viral metagenome derived from microbial mats in hotsprings at Yellowstone National Park. Two distinct CRISPR types, distinguished by the repeat sequence, are found in both the Syn OS-A and Syn OS-B′ genomes. The genome of Syn OS-A contains a third CRISPR type with a distinct repeat sequence, which is not found in Syn OS-B′, but appears to be shared with other microorganisms that inhabit the mat. The CRISPR repeats identified in the microbial metagenome are highly conserved, while the spacer sequences (hereafter referred to as “viritopes” to emphasize their critical role in viral immunity) were mostly unique and had no high identity matches when searched against GenBank. Searching the viritopes against the viral metagenome, however, yielded several matches with high similarity some of which were within a gene identified as a likely viral lysozyme/lysin protein. Analysis of viral metagenome sequences corresponding to this lysozyme/lysin protein revealed several mutations all of which translate into silent or conservative mutations which are unlikely to affect protein function, but may help the virus evade the host CRISPR resistance mechanism. These results demonstrate the varied challenges presented by a natural virus population, and support the notion that the CRISPR/viritope system must be able to adapt quickly to provide host immunity. The ability of metagenomics to track population-level variation in viritope sequences allows for a culture-independent method for evaluating the fast co-evolution of host and viral genomes and its consequence on the structuring of complex microbial communities

    Global distribution and diversity of marine Verrucomicrobia

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    Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in The ISME Journal 6 (2012): 1499-1505, doi:10.1038/ismej.2012.3.Verrucomicrobia is a bacterial phylum that is commonly detected in soil but little is known about the distribution and diversity of this phylum in the marine environment. To address this, we analyzed the marine microbial community composition in 506 samples from the International Census of Marine Microbes as well as eleven coastal samples taken from the California Current. These samples from both the water column and sediments covered a wide range of environmental conditions. Verrucomicrobia were present in 98% of the analyzed samples and thus appeared nearly ubiquitous in the ocean. Based on the occurrence of amplified 16S rRNA sequences, Verrucomicrobia constituted on average 2% of the water column and 1.4% of the sediment bacterial communities. The diversity of Verrucomicrobia displayed a biogeography at multiple taxonomic levels and thus, specific lineages appeared to have clear habitat preference. We found that Subdivision 1 and 4 generally dominated marine bacterial communities, whereas Subdivision 2 was confined to low salinity waters. Within the subdivisions, Verrucomicrobia community composition were significantly different in the water column compared to sediment as well as within the water column along gradients of salinity, temperature, nitrate, depth, and overall water column depth. Although we still know little about the ecophysiology of Verrucomicrobia lineages, the ubiquity of this phylum suggests that it may be important for the biogeochemical cycle of carbon in the ocean.We would like to thank the UCI Undergraduate Research Opportunity Program (S.F.), the National Science Foundation (OCE-0928544 and OCE-1046297, A.C.M.) and the Alfred P. Sloan Foundation (S.H., D.M.W., M.S.) for supporting the work

    Phylogenomic evidence for a common ancestor of mitochondria and the SAR11 clade

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    Mitochondria share a common ancestor with the Alphaproteobacteria, but determining their precise origins is challenging due to inherent difficulties in phylogenetically reconstructing ancient evolutionary events. Nonetheless, phylogenetic accuracy improves with more refined tools and expanded taxon sampling. We investigated mitochondrial origins with the benefit of new, deeply branching genome sequences from the ancient and prolific SAR11 clade of Alphaproteobacteria and publicly available alphaproteobacterial and mitochondrial genome sequences. Using the automated phylogenomic pipeline Hal, we systematically studied the effect of taxon sampling and missing data to accommodate small mitochondrial genomes. The evidence supports a common origin of mitochondria and SAR11 as a sister group to the Rickettsiales. The simplest explanation of these data is that mitochondria evolved from a planktonic marine alphaproteobacterial lineage that participated in multiple inter-specific cell colonization events, in some cases yielding parasitic relationships, but in at least one case producing a symbiosis that characterizes modern eukaryotic life

    Linking species concepts to natural product discovery in the post-genomic era

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    A widely accepted species concept for bacteria has yet to be established. As a result, species designations are inconsistently applied and tied to what can be considered arbitrary metrics. Increasing access to DNA sequence data and clear evidence that bacterial genomes are dynamic entities that include large numbers of horizontally acquired genes have added a new level of insight to the ongoing species concept debate. Despite uncertainties over how to apply species concepts to bacteria, there is clear evidence that sequence-based approaches can be used to resolve cohesive groups that maintain the properties of species. This cohesion is clearly evidenced in the genus Salinispora, where three species have been discerned despite very close relationships based on 16S rRNA sequence analysis. The major phenotypic differences among the three species are associated with secondary metabolite production, which occurs in species-specific patterns. These patterns are maintained on a global basis and provide evidence that secondary metabolites have important ecological functions. These patterns also suggest that an effective strategy for natural product discovery is to target the cultivation of new Salinispora taxa. Alternatively, bioinformatic analyses of biosynthetic genes provide opportunities to predict secondary metabolite novelty and reduce the redundant isolation of well-known metabolites. Although much remains to be learned about the evolutionary relationships among bacteria and how fundamental units of diversity can be resolved, genus and species descriptions remain the most effective method of scientific communication

    Gene prediction in metagenomic fragments: A large scale machine learning approach

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    <p>Abstract</p> <p>Background</p> <p>Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions.</p> <p>Results</p> <p>We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability.</p> <p>Conclusion</p> <p>Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments. In particular, the combination of linear discriminants and neural networks is promising and should be considered for integration into metagenomic analysis pipelines. The data sets can be downloaded from the URL provided (see Availability and requirements section).</p

    Tunable thermal expansion in framework materials through redox intercalation

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    Thermal expansion properties of solids are of fundamental interest and control of thermal expansion is important for practical applications but can be difficult to achieve. Many framework-type materials show negative thermal expansion when internal cages are empty but positive thermal expansion when additional atoms or molecules fill internal voids present. Here we show that redox intercalation offers an effective method to control thermal expansion from positive to zero to negative by insertion of Li ions into the simple negative thermal expansion framework material ScF3, doped with 10% Fe to enable reduction. The small concentration of intercalated Li ions has a strong influence through steric hindrance of transverse fluoride ion vibrations, which directly controls the thermal expansion. Redox intercalation of guest ions is thus likely to be a general and effective method for controlling thermal expansion in the many known framework materials with phonon-driven negative thermal expansion

    In Search of an Uncultured Human-Associated TM7 Bacterium in the Environment

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    We have identified an environmental bacterium in the Candidate Division TM7 with ≥98.5% 16S rDNA gene homology to a group of TM7 bacteria associated with the human oral cavity and skin. The environmental TM7 bacterium (referred to as TM7a-like) was readily detectable in wastewater with molecular techniques over two years of sampling. We present the first images of TM7a-like cells through FISH technique and the first images of any TM7 as viable cells through the STARFISH technique. In situ quantification showed TM7 concentration in wastewater up to five times greater than in human oral sites. We speculate that upon further characterization of the physiology and genetics of the TM7a-like bacterium from environmental sources and confirmation of its genomic identity to human-associated counterparts it will serve as model organisms to better understand its role in human health. The approach proposed circumvents difficulties imposed by sampling humans, provides an alternative strategy to characterizing some diseases of unknown etiology, and renders a much needed understanding of the ecophysiological role hundreds of unique Bacteria and Archaea strains play in mixed microbial communities
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