Comparative Proteomics of Octocoral and Scleractinian Skeletomes and the Evolution of Coral Calcification

Corals are the ecosystem engineers of coral reefs, one of the most biodiverse marine ecosystems. The ability of corals to form reefs depends on the precipitation of calcium carbonate (CaCO3) under biological control. However, several mechanisms underlying coral biomineralization remain elusive, for example, whether corals employ different molecular machineries to deposit different CaCO3 polymorphs (i.e., aragonite or calcite). Here, we used tandem mass spectrometry (MS/MS) to compare the proteins occluded in the skeleton of three octocoral and one scleractinian species: Tubipora musica and Sinularia cf. cruciata (calcite sclerites), the blue coral Heliopora coerulea (aragonitic skeleton), and the scleractinian aragonitic Montipora digitata. Reciprocal Blast analysis revealed extremely low overlap between aragonitic and calcitic species, while a core set of proteins is shared between octocorals producing calcite sclerites. However, the carbonic anhydrase CruCA4 is present in the skeletons of both polymorphs. Phylogenetic analysis highlighted several possible instances of protein co-option in octocorals. These include acidic proteins and scleritin, which appear to have been secondarily recruited for calcification and likely derive from proteins playing different functions. Similarities between octocorals and scleractinians included presence of a galaxin-related protein, carbonic anhydrases, and one hephaestin-like protein. Although the first two appear to have been independently recruited, the third appear to share a common origin. This work represents the first attempt to identify and compare proteins associated with coral skeleton polymorph diversity, providing several new research targets and enabling both future functional and evolutionary studies aimed at elucidating the origin and evolution of coral biomineralization.

Effect of the environment on horizontal gene transfer between bacteria and archaea

BackgroundHorizontal gene transfer, the transfer and incorporation of genetic material between different species of organisms, has an important but poorly quantified role in the adaptation of microbes to their environment. Previous work has shown that genome size and the number of horizontally transferred genes are strongly correlated. Here we consider how genome size confuses the quantification of horizontal gene transfer because the number of genes an organism accumulates over time depends on its evolutionary history and ecological context (e.g., the nutrient regime for which it is adapted).ResultsWe investigated horizontal gene transfer between archaea and bacteria by first counting reciprocal BLAST hits among 448 bacterial and 57 archaeal genomes to find shared genes. Then we used the DarkHorse algorithm, a probability-based, lineage-weighted method (Podell & Gaasterland, 2007), to identify potential horizontally transferred genes among these shared genes. By removing the effect of genome size in the bacteria, we have identified bacteria with unusually large numbers of shared genes with archaea for their genome size. Interestingly, archaea and bacteria that live in anaerobic and/or high temperature conditions are more likely to share unusually large numbers of genes. However, high salt was not found to significantly affect the numbers of shared genes. Numbers of shared (genome size-corrected, reciprocal BLAST hits) and transferred genes (identified by DarkHorse) were strongly correlated. Thus archaea and bacteria that live in anaerobic and/or high temperature conditions are more likely to share horizontally transferred genes. These horizontally transferred genes are over-represented by genes involved in energy conversion as well as the transport and metabolism of inorganic ions and amino acids.ConclusionsAnaerobic and thermophilic bacteria share unusually large numbers of genes with archaea. This is mainly due to horizontal gene transfer of genes from the archaea to the bacteria.In general, these transfers are from archaea that live in similar oxygen and temperature conditions as the bacteria that receive the genes. Potential hotspots of horizontal gene transfer between archaea and bacteria include hot springs, marine sediments, and oil wells. Cold spots for horizontal transfer included dilute, aerobic, mesophilic environments such as marine and freshwater surface waters.

The Co-regulation Data Harvester for Tetrahymena thermophila: automated high-throughput gene annotation and functional inference in a microbial eukaryote

Identifying co-regulated genes can provide a useful approach for defining pathway-specific machinery in an organism. To be efficient, this approach relies on thorough genome annotation, which is not available for most organisms with sequenced genomes. Studies in Tetrahymena thermophila, the most experimentally accessible ciliate, have generated a rich transcriptomic database covering many well-defined physiological states. Genes that are involved in the same pathway show significant co-regulation, and screens based on gene co-regulation have identified novel factors in specific pathways, for example in membrane trafficking. However, a limitation has been the relatively sparse annotation of the Tetrahymena genome, making it impractical to approach genome-wide analyses. We have therefore developed an efficient approach to analyze both co-regulation and gene annotation, called the Co-regulation Data Harvester (CDH). The CDH automates identification of co-regulated genes by accessing the Tetrahymena transcriptome database, determines their orthologs in other organisms via reciprocal BLAST searches, and collates the annotations of those orthologs' functions. Inferences drawn from the CDH reproduce and expand upon experimental findings in Tetrahymena. The CDH, which is freely available, represents a powerful new tool for analyzing cell biological pathways in Tetrahymena. Moreover, to the extent that genes and pathways are conserved between organisms, the inferences obtained via the CDH should be relevant, and can be explored, in many other systems.

RecBlast: Cloud-Based Large Scale Orthology Detection

BackgroundThe effective detection and comparison of orthologues is crucial for answering many questions in comparative genomics, phylogenetics and evolutionary biology. One of the most common methods for discovering orthologues is widely known as ‘Reciprocal Blast’. While this method is simple when comparing only two genomes, performing a large-scale comparison of Multiple Genes across Multiple Taxa becomes a labor-intensive and inefficient task. The low efficiency of this complicated process limits the scope and breadth of questions that would otherwise benefit from this powerful method.FindingsHere we present RecBlast, an intuitive and easy-to-use pipeline that enables fast and easy discovery of orthologues along and across the evolutionary tree. RecBlast is capable of running heavy, large-scale and complex Reciprocal Blast comparisons across multiple genes and multiple taxa, in a completely automatic way. RecBlast is available as a cloud-based web server, which includes an easy-to-use user interface, implemented using cloud computing and an elastic and scalable server architecture. RecBlast is also available as a powerful standalone software supporting multi-processing for large datasets, and a cloud image which can be easily deployed on Amazon Web Services cloud. We also include sample results spanning 448 human genes, which illustrate the potential of RecBlast in detecting orthologues and in highlighting patterns and trends across multiple taxa.ConclusionsRecBlast provides a fast, inexpensive and valuable insight into trends and phenomena across distance phyla, and provides data, visualizations and directions for downstream analysis. RecBlast's fully automatic pipeline provides a new and intuitive discovery platform for researchers from any domain in biology who are interested in evolution, comparative genomics and phylogenetics, regardless of their computational skills.

Whole-Genome Reciprocal BLAST Analysis Reveals that Planctomycetes Do Not Share an Unusually Large Number of Genes with Eukarya and Archaea

ABSTRACT The genome sequences of Rhodopirellula baltica, formerly Pirellula sp. strain 1, Blastopirellula marina, Gemmata obscuriglobus, and Kuenenia stuttgartiensis were used in a series of pairwise reciprocal best-hit analyses to evaluate the contested evolutionary position of Planctomycetes. Contrary to previous reports which suggested that R. baltica had a high percentage of genes with closest matches to Archaea and Eukarya, we show here that these Planctomycetes do not share an unusually large number of genes with the Archaea or Eukarya, compared with other Bacteria. Thus, best-hit analyses may assign phylogenetic affinities incorrectly if close relatives are absent from the sequence database.