Adrian Sharma

Combined metagenomic and metatranscriptomic datasets make it possible to study the molecular evolution of diverse microbial species recovered from their native habitats. The link between gene expression level and sequence conservation was examined using shotgun pyrosequencing of microbial community DNA and RNA from diverse marine environments, and from forest soil. Across all samples, expressed genes with transcripts in the RNA sample were significantly more conserved than non-expressed gene sets relative to best matches in reference databases. This discrepancy, observed for many diverse individual genomes and across entire communities, coincided with a shift in amino acid usage between these gene fractions. Expressed genes trended toward GC-enriched amino acids, consistent with a hypothesis of higher levels of functional constraint in this gene pool. Highly expressed genes were significantly more likely to fall within an orthologous gene set shared between closely related taxa (core genes). However, non-core genes, when expressed above the level of detection, were, on average, significantly more highly expressed than core genes based on transcript abundance normalized to gene abundance. Finally, expressed genes showed broad similarities in function across samples, being relatively enriched in genes of energy metabolism and underrepresented by genes of cell growth. These patterns support the hypothesis, predicated on studies of model organisms, that gene expression level is a primary correlate of evolutionary rate across diverse microbial taxa from natural environments. Despite their complexity, meta-omic datasets can reveal broad evolutionary patterns across taxonomically, functionally, and environmentally diverse communities.

Actinobacteria often constitute a large fraction of the bacterioplankton in freshwater systems. Cultivation-independent methods have revealed that the so-called acI lineage frequently represents the most numerous taxon among assemblages of freshwater Actinobacteria and even among total freshwater bacterioplankton. Bacteria affiliated with this uncultivated lineage have been detected in freshwater habitats located in various continents and climatic zones but have never been found among terrestrial or offshore marine systems. So far, this ecologically important lineage of freshwater Actinobacteria is not represented by a recognized taxon. In this study, we established a stable mixed culture containing a strain affiliated with the acI lineage from a freshwater lake in Austria. The proportion of the strain in the culture could be increased by manipulation of the medium composition by more than one order of magnitude, however all subsequent attempts to isolate this strain into pure culture were unsuccessful. Some of the phenotypic traits of this acI strain were determined and its taxonomic position within the Actinobacteria was analysed. Phylogenetic analysis of this organism's 16S rRNA gene revealed a distant relationship with cultivated organisms and recognized species (89 % gene sequence similarity with the latter). Furthermore, this analysis did not support a clear assignment of the strain to any of the recognized families within the phylum Actinobacteria. It is suggested that a candidate taxon, 'Candidatus Planktophila limnetica' is established to represent this strain.

A common approach for investigating evolutionary relationships between genes and organisms is to compare extant DNA or protein sequences and infer an evolutionary tree. This methodology is known as molecular phylogenetics and may be the most informative means for exploring phage evolution, since there are few morphological features that can be used to differentiate between these tiny biological entities. In addition, phage genomes can be mosaic, meaning different genes or genomic regions can exhibit conflicting evolutionary histories due to lateral gene transfer or homologous recombination between different phage genomes. Molecular phylogenetics can be used to identify and study such genome mosaicism. This chapter provides a general introduction to the theory and methodology used to reconstruct phylogenetic relationships from molecular data. Also included is a discussion on how the evolutionary history of different genes within the same set of genomes can be compared, using a collection of T4-type phage genomes as an example. A compilation of programs and packages that are available for conducting phylogenetic analyses is supplied as an accompanying appendix.