The prokaryotic tree of life: past, present... and future?

Bioinformatic perspectives on NRPS/PKS megasynthases: advances and challenges

The increased understanding of both fundamental principles and mechanistic variations of NRPS/PKS megasynthases along with the unprecedented availability of microbial sequences has inspired a number of in silico studies of both enzyme families. The insights that can be extracted from these analyses go far beyond a rough classification of data and have turned bioinformatics into a frontier field of natural products research. As databases are flooded with NRPS/PKS gene sequence of microbial genomes and metagenomes, increasingly reliable structural prediction methods can help to uncover hidden treasures. Already, phylogenetic analyses have revealed that NRPS/PKS pathways should not simply be regarded as enzyme complexes, specifically evolved to product a selected natural product. Rather, they represent a collection of genetic opinions, allowing biosynthetic pathways to be shuffled in a process of perpetual chemical innovations and pathways diversification in nature can give impulses for specificities, protein interactions and genetic engineering of libraries of novel peptides and polyketides. The successful translation of the knowledge obtained from bioinformatic dissection of NRPS/PKS megasynthases into new techniques for drug discovery and design remain challenges for the future.

Bacterial flagellar diversity and evolution: seek simplicity and distrust it?

Flagella are the chief organelles of motility in bacteria. In recent years, several new findings have illuminated the evolution of bacterial flagella, including cut-down versions of the organelle in Buchnera, a dispensable ATPase and structural evidence for homology between FliG (a component of the flagellar motor) and MgtE (a magnesium transporter). However, a fresh examination of the phylogenetic distribution of flagellar genes warns against a simplistic model of early flagellar evolution.

The tree of genomes: an empirical comparison of genome-phylogeny reconstruction methods

BACKGROUND

In the past decade or more, the emphasis for reconstructing species phylogenies has moved from the analysis of a single gene to the analysis of multiple genes and even completed genomes. The simplest method of scaling up is to use familiar analysis methods on a larger scale and this is the most popular approach. However, duplications and losses of genes along with horizontal gene transfer (HGT) can lead to a situation where there is only an indirect relationship between gene and genome phylogenies. In this study we examine five widely-used approaches and their variants to see if indeed they are more-or-less saying the same thing. In particular, we focus on Conditioned Reconstruction as it is a method that is designed to work well even if HGT is present.

RESULTS

We confirm a previous suggestion that this method has a systematic bias. We show that no two methods produce the same results and most current methods of inferring genome phylogenies produce results that are significantly different to other methods.

CONCLUSION

We conclude that genome phylogenies need to be interpreted differently, depending on the method used to construct them.

Genomics of bacteria and archaea: the emerging dynamic view of the prokaryotic world

The first bacterial genome was sequenced in 1995, and the first archaeal genome in 1996. Soon after these breakthroughs, an exponential rate of genome sequencing was established, with a doubling time of approximately 20 months for bacteria and approximately 34 months for archaea. Comparative analysis of the hundreds of sequenced bacterial and dozens of archaeal genomes leads to several generalizations on the principles of genome organization and evolution. A crucial finding that enables functional characterization of the sequenced genomes and evolutionary reconstruction is that the majority of archaeal and bacterial genes have conserved orthologs in other, often, distant organisms. However, comparative genomics also shows that horizontal gene transfer (HGT) is a dominant force of prokaryotic evolution, along with the loss of genetic material resulting in genome contraction. A crucial component of the prokaryotic world is the mobilome, the enormous collection of viruses, plasmids and other selfish elements, which are in constant exchange with more stable chromosomes and serve as HGT vehicles. Thus, the prokaryotic genome space is a tightly connected, although compartmentalized, network, a novel notion that undermines the ‘Tree of Life’ model of evolution and requires a new conceptual framework and tools for the study of prokaryotic evolution.

Modular networks and cumulative impact of lateral transfer in prokaryote genome evolution

Lateral gene transfer is an important mechanism of natural variation among prokaryotes, but the significance of its quantitative contribution to genome evolution is debated. Here, we report networks that capture both vertical and lateral components of evolutionary history among 539,723 genes distributed across 181 sequenced prokaryotic genomes. Partitioning of these networks by an eigenspectrum analysis identifies community structure in prokaryotic gene-sharing networks, the modules of which do not correspond to a strictly hierarchical prokaryotic classification. Our results indicate that, on average, at least 81 +/- 15% of the genes in each genome studied were involved in lateral gene transfer at some point in their history, even though they can be vertically inherited after acquisition, uncovering a substantial cumulative effect of lateral gene transfer on longer evolutionary time scales.

The deep archaeal roots of eukaryotes

The set of conserved eukaryotic protein-coding genes includes distinct subsets one of which appears to be most closely related to and, by inference, derived from archaea, whereas another one appears to be of bacterial, possibly, endosymbiotic origin. The “archaeal” genes of eukaryotes, primarily, encode components of information-processing systems, whereas the “bacterial” genes are predominantly operational. The precise nature of the archaeo–eukaryotic relationship remains uncertain, and it has been variously argued that eukaryotic informational genes evolved from the homologous genes of Euryarchaeota or Crenarchaeota (the major branches of extant archaea) or that the origin of eukaryotes lies outside the known diversity of archaea. We describe a comprehensive set of 355 eukaryotic genes of apparent archaeal origin identified through ortholog detection and phylogenetic analysis. Phylogenetic hypothesis testing using constrained trees, combined with a systematic search for shared derived characters in the form of homologous inserts in conserved proteins, indicate that, for the majority of these genes, the preferred tree topology is one with the eukaryotic branch placed outside the extant diversity of archaea although small subsets of genes show crenarchaeal and euryarchaeal affinities. Thus, the archaeal genes in eukaryotes appear to descend from a distinct, ancient, and otherwise uncharacterized archaeal lineage that acquired some euryarchaeal and crenarchaeal genes via early horizontal gene transfer.

The eukaryotic tree of life: endosymbiosis takes its TOL

Resolving the structure of the eukaryotic tree of life remains one of the most important and challenging tasks facing biologists. The notion of six eukaryotic 'supergroups' has recently gained some acceptance, and several papers in 2007 suggest that resolution of higher taxonomic levels is possible. However, in organisms that acquired photosynthesis via secondary (i.e. eukaryote-eukaryote) endosymbiosis, the host nuclear genome is a mosaic of genes derived from two (or more) nuclei, a fact that is often overlooked in studies attempting to reconstruct the deep evolutionary history of eukaryotes. Accurate identification of gene transfers and replacements involving eukaryotic donor and recipient genomes represents a potentially formidable challenge for the phylogenomics community as more protist genomes are sequenced and concatenated data sets grow.