Random Addition Concatenation Analysis: A Novel Approach to the Exploration of Phylogenomic Signal Reveals Strong Agreement between Core and Shell Genomic Partitions in the Cyanobacteria

Recent whole-genome approaches to microbial phylogeny have emphasized partitioning genes into functional classes, often focusing on differences between a stable core of genes and a variable shell. To rigorously address the effects of partitioning and combining genes in genome-level analyses, we developed a novel technique called Random Addition Concatenation Analysis (RADICAL). RADICAL operates by sequentially concatenating randomly chosen gene partitions starting with a single-gene partition and ending with the entire genomic data set. A phylogenetic tree is built for every successive addition, and the entire process is repeated creating multiple random concatenation paths. The result is a library of trees representing a large variety of differently sized random gene partitions. This library can then be mined to identify unique topologies, assess overall agreement, and measure support for different trees. To evaluate RADICAL, we used 682 orthologous genes across 13 cyanobacterial genomes. Despite previous assertions of substantial differences between a core and a shell set of genes for this data set, RADICAL reveals the two partitions contain congruent phylogenetic signal. Substantial disagreement within the data set is limited to a few nodes and genes involved in metabolism, a functional group that is distributed evenly between the core and the shell partitions. We highlight numerous examples where RADICAL reveals aspects of phylogenetic behavior not evident by examining individual gene trees or a “‘total evidence” tree. Our method also demonstrates that most emergent phylogenetic signal appears early in the concatenation process. The software is freely available at http://desalle.amnh.org

An Electronic Analog of Synthetic Genetic Networks

An electronic analog of a synthetic genetic network known as the repressilator is proposed. The repressilator is a synthetic biological clock consisting of a cyclic inhibitory network of three negative regulatory genes which produces oscillations in the expressed protein concentrations. Compared to previous circuit analogs of the repressilator, the circuit here takes into account more accurately the kinetics of gene expression, inhibition, and protein degradation. A good agreement between circuit measurements and numerical prediction is observed. The circuit allows for easy control of the kinetic parameters thereby aiding investigations of large varieties of potential dynamics

Predicting Prokaryotic Ecological Niches Using Genome Sequence Analysis

Automated DNA sequencing technology is so rapid that analysis has become the rate-limiting step. Hundreds of prokaryotic genome sequences are publicly available, with new genomes uploaded at the rate of approximately 20 per month. As a result, this growing body of genome sequences will include microorganisms not previously identified, isolated, or observed. We hypothesize that evolutionary pressure exerted by an ecological niche selects for a similar genetic repertoire in those prokaryotes that occupy the same niche, and that this is due to both vertical and horizontal transmission. To test this, we have developed a novel method to classify prokaryotes, by calculating their Pfam protein domain distributions and clustering them with all other sequenced prokaryotic species. Clusters of organisms are visualized in two dimensions as ‘mountains’ on a topological map. When compared to a phylogenetic map constructed using 16S rRNA, this map more accurately clusters prokaryotes according to functional and environmental attributes. We demonstrate the ability of this map, which we term a “niche map”, to cluster according to ecological niche both quantitatively and qualitatively, and propose that this method be used to associate uncharacterized prokaryotes with their ecological niche as a means of predicting their functional role directly from their genome sequence

What traits are carried on mobile genetic elements, and why?

Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes

The endogenous retrovirus ENS-1 provides active binding sites for transcription factors in embryonic stem cells that specify extra embryonic tissue

<p>Abstract</p> <p>Background</p> <p>Long terminal repeats (LTR) from endogenous retroviruses (ERV) are source of binding sites for transcription factors which affect the host regulatory networks in different cell types, including pluripotent cells. The embryonic epiblast is made of pluripotent cells that are subjected to opposite transcriptional regulatory networks to give rise to distinct embryonic and extraembryonic lineages. To assess the transcriptional contribution of ERV to early developmental processes, we have characterized <it>in vitro </it>and <it>in vivo </it>the regulation of ENS-1, a host adopted and developmentally regulated ERV that is expressed in chick embryonic stem cells.</p> <p>Results</p> <p>We show that <it>Ens-1 </it>LTR activity is controlled by two transcriptional pathways that drive pluripotent cells to alternative developmental fates. Indeed, both Nanog that maintains pluripotency and Gata4 that induces differentiation toward extraembryonic endoderm independently activate the LTR. Ets coactivators are required to support Gata factors' activity thus preventing inappropriate activation before epigenetic silencing occurs during differentiation. Consistent with their expression patterns during chick embryonic development, Gata4, Nanog and Ets1 are recruited on the LTR in embryonic stem cells; in the epiblast the complementary expression of Nanog and Gata/Ets correlates with the <it>Ens-1 </it>gene expression pattern; and Ens-1 transcripts are also detected in the hypoblast, an extraembryonic tissue expressing Gata4 and Ets2, but not Nanog. Accordingly, over expression of Gata4 in embryos induces an ectopic expression of <it>Ens-1</it>.</p> <p>Conclusion</p> <p>Our results show that <it>Ens-1 </it>LTR have co-opted conditions required for the emergence of extraembryonic tissues from pluripotent epiblasts cells. By providing pluripotent cells with intact binding sites for Gata, Nanog, or both, <it>Ens-1 </it>LTR may promote distinct transcriptional networks in embryonic stem cells subpopulations and prime the separation between embryonic and extraembryonic fates.</p

Origin and Examination of a Leafhopper Facultative Endosymbiont

Eukaryotes engage in intimate interactions with microbes that range in age and type of association. Although many conspicuous examples of ancient insect associates are studied (e.g., Buchneraaphidicola), fewer examples of younger associations are known. Here, we further characterize a recently evolved bacterial endosymbiont of the leafhopper Euscelidius variegatus (Hemiptera, Cicadellidae), called BEV. We found that BEV, continuously maintained in E. variegatus hosts at UC Berkeley since 1984, is vertically transmitted with high fidelity. Unlike many vertically transmitted, ancient endosymbioses, the BEV–E. variegatus association is not obligate for either partner, and BEV can be cultivated axenically. Sufficient BEV colonies were grown and harvested to estimate its genome size and provide a partial survey of the genome sequence. The BEV chromosome is about 3.8 Mbp, and there is evidence for an extrachromosomal element roughly 53 kb in size (e.g., prophage or plasmid). We sequenced 438 kb of unique short-insert clones, representing about 12% of the BEV genome. Nearly half of the gene fragments were similar to mobile DNA, including 15 distinct types of insertion sequences (IS). Analyses revealed that BEV not only shares virulence genes with plant pathogens, but also is closely related to the plant pathogenic genera Dickeya, Pectobacterium, and Brenneria. However, the slightly reduced genome size, abundance of mobile DNA, fastidious growth in culture, and efficient vertical transmission suggest that symbiosis with E. variegatus has had a significant impact on genome evolution in BEV

Single-nucleotide resolution analysis of the transcriptome structure of Clostridium beijerinckii NCIMB 8052 using RNA-Seq

<p>Abstract</p> <p>Background</p> <p><it>Clostridium beijerinckii </it>is an important solvent producing microorganism. The genome of <it>C. beijerinckii </it>NCIMB 8052 has recently been sequenced. Although transcriptome structure is important in order to reveal the functional and regulatory architecture of the genome, the physical structure of transcriptome for this strain, such as the operon linkages and transcript boundaries are not well understood.</p> <p>Results</p> <p>In this study, we conducted a single-nucleotide resolution analysis of the <it>C. beijerinckii </it>NCIMB 8052 transcriptome using high-throughput RNA-Seq technology. We identified the transcription start sites and operon structure throughout the genome. We confirmed the structure of important gene operons involved in metabolic pathways for acid and solvent production in <it>C. beijerinckii </it>8052, including <it>pta</it>-<it>ack</it>, <it>ptb</it>-<it>buk</it>, <it>hbd</it>-<it>etfA</it>-<it>etfB</it>-<it>crt </it>(<it>bcs</it>) and <it>ald</it>-<it>ctfA</it>-<it>ctfB</it>-<it>adc </it>(<it>sol</it>) operons; we also defined important operons related to chemotaxis/motility, transcriptional regulation, stress response and fatty acids biosynthesis along with others. We discovered 20 previously non-annotated regions with significant transcriptional activities and 15 genes whose translation start codons were likely mis-annotated. As a consequence, the accuracy of existing genome annotation was significantly enhanced. Furthermore, we identified 78 putative silent genes and 177 putative housekeeping genes based on normalized transcription measurement with the sequence data. We also observed that more than 30% of pseudogenes had significant transcriptional activities during the fermentation process. Strong correlations exist between the expression values derived from RNA-Seq analysis and microarray data or qRT-PCR results.</p> <p>Conclusions</p> <p>Transcriptome structural profiling in this research provided important supplemental information on the accuracy of genome annotation, and revealed additional gene functions and regulation in <it>C. beijerinckii</it>.</p

A statistical toolbox for metagenomics: assessing functional diversity in microbial communities

<p>Abstract</p> <p>Background</p> <p>The 99% of bacteria in the environment that are recalcitrant to culturing have spurred the development of metagenomics, a culture-independent approach to sample and characterize microbial genomes. Massive datasets of metagenomic sequences have been accumulated, but analysis of these sequences has focused primarily on the descriptive comparison of the relative abundance of proteins that belong to specific functional categories. More robust statistical methods are needed to make inferences from metagenomic data. In this study, we developed and applied a suite of tools to describe and compare the richness, membership, and structure of microbial communities using peptide fragment sequences extracted from metagenomic sequence data.</p> <p>Results</p> <p>Application of these tools to acid mine drainage, soil, and whale fall metagenomic sequence collections revealed groups of peptide fragments with a relatively high abundance and no known function. When combined with analysis of 16S rRNA gene fragments from the same communities these tools enabled us to demonstrate that although there was no overlap in the types of 16S rRNA gene sequence observed, there was a core collection of operational protein families that was shared among the three environments.</p> <p>Conclusion</p> <p>The results of comparisons between the three habitats were surprising considering the relatively low overlap of membership and the distinctively different characteristics of the three habitats. These tools will facilitate the use of metagenomics to pursue statistically sound genome-based ecological analyses.</p