A comparative categorization of gene flux in diverse microbial species

Prediction of Horizontally and Widely Transferred Genes in Prokaryotes

Horizontal gene transfer (HGT) is the process whereby an organism acquires exogenous genes (horizontally transferred genes or HT genes) that are not inherited from the parent, but are derived from another organism. In prokaryotes, HGT has been considered as one of the important driving forces of evolution. Previously, genome-wide analyses have been conducted for estimating the proportion of HT genes in prokaryotic genomes, but the number of species examined at the time was limited, and gene annotation was relatively poor. Currently, tens of thousands of prokaryotic genomes have been published and gene annotation resources have improved. In the present study, HT gene prediction method was modified so that the estimate was robust to gene length, conducting a comprehensive search using 3017 representative prokaryotic genomes belonging to 1348 species. The result showed that an average of 13% (ranging from 0% to 30% across species) of protein-coding genes was predicted as being of horizontal origin. The proportion of the predicted HT genes per species was associated with the species’ habitat, while a positive correlation between the proportion and genomic nucleotide frequency was also observed. Moreover, the functions of the predicted HT genes were inferred and compared according to two popular databases, the Clusters of Orthologous Groups and the Kyoto Encyclopedia of Genes and Genomes. As a result, both databases indicated that many of the widely transferred genes were involved in mobile genetic elements (transposons, phages, and plasmids) as expected. Notably, the present study predicted that six as-yet-uncharacterized genes were widely distributed HT genes, and therefore, will be interesting targets for evolutionary studies. Thus, this study demonstrates that a data-driven approach using massive sequence data may contribute to a broader understanding of HGT in prokaryotes.

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

Background

Horizontal 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).

Results

We 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.

Conclusions

Anaerobic 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.

Estimating the extent of horizontal gene transfer in metagenomic sequences

BACKGROUND

Although the extent of horizontal gene transfer (HGT) in complete genomes has been widely studied, its influence in the evolution of natural communities of prokaryotes remains unknown. The availability of metagenomic sequences allows us to address the study of global patterns of prokaryotic evolution in samples from natural communities. However, the methods that have been commonly used for the study of HGT are not suitable for metagenomic samples. Therefore it is important to develop new methods or to adapt existing ones to be used with metagenomic sequences.

RESULTS

We have created two different methods that are suitable for the study of HGT in metagenomic samples. The methods are based on phylogenetic and DNA compositional approaches, and have allowed us to assess the extent of possible HGT events in metagenomes for the first time. The methods are shown to be compatible and quite precise, although they probably underestimate the number of possible events. Our results show that the phylogenetic method detects HGT in between 0.8% and 1.5% of the sequences, while DNA compositional methods identify putative HGT in between 2% and 8% of the sequences. These ranges are very similar to these found in complete genomes by related approaches. Both methods act with a different sensitivity since they probably target HGT events of different ages: the compositional method mostly identifies recent transfers, while the phylogenetic is more suitable for the detections of older events. Nevertheless, the study of the number of HGT events in metagenomic sequences from different communities shows a consistent trend for both methods: the lower amount is found for the sequences of the Sargasso Sea metagenome, while the higher quantity is found in the whale fall metagenome from the bottom of the ocean. The significance of these observations is discussed.

CONCLUSION

The computational approaches that are used to find possible HGT events in complete genomes can be adapted to work with metagenomic samples, where a level of high performance is shown in different metagenomic samples. The percentage of possible HGT events that were observed is close to that found for complete genomes, and different microbiomes show diverse ratios of putative HGT events. This is probably related with both environmental factors and the composition in the species of each particular community.

Viruses of the Archaea: a unifying view

DNA viruses of the Archaea have highly diverse and often exceptionally complex morphotypes. Many have been isolated from geothermally heated hot environments, raising intriguing questions about their origins, and contradicting the widespread notion of limited biodiversity in extreme environments. Here, we provide a unifying view on archaeal viruses, and present them as a particular assemblage that is fundamentally different in morphotype and genome from the DNA viruses of the other two domains of life, the Bacteria and Eukarya.

The origin and evolution of Archaea: a state of the art

Environmental surveys indicate that the Archaea are diverse and abundant not only in extreme environments, but also in soil, oceans and freshwater, where they may fulfil a key role in the biogeochemical cycles of the planet. Archaea display unique capacities, such as methanogenesis and survival at temperatures higher than 90 degrees C, that make them crucial for understanding the nature of the biota of early Earth. Molecular, genomics and phylogenetics data strengthen Woese's definition of Archaea as a third domain of life in addition to Bacteria and Eukarya. Phylogenomics analyses of the components of different molecular systems are highlighting a core of mainly vertically inherited genes in Archaea. This allows recovering a globally well-resolved picture of archaeal evolution, as opposed to what is observed for Bacteria and Eukarya. This may be due to the fact that no rapid divergence occurred at the emergence of present-day archaeal lineages. This phylogeny supports a hyperthermophilic and non-methanogenic ancestor to present-day archaeal lineages, and a profound divergence between two major phyla, the Crenarchaeota and the Euryarchaeota, that may not have an equivalent in the other two domains of life. Nanoarchaea may not represent a third and ancestral archaeal phylum, but a fast-evolving euryarchaeal lineage. Methanogenesis seems to have appeared only once and early in the evolution of Euryarchaeota. Filling up this picture of archaeal evolution by adding presently uncultivated species, and placing it back in geological time remain two essential goals for the future.

Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models

Background

Horizontal gene transfer (HGT) is considered a strong evolutionary force shaping the content of microbial genomes in a substantial manner. It is the difference in speed enabling the rapid adaptation to changing environmental demands that distinguishes HGT from gene genesis, duplications or mutations. For a precise characterization, algorithms are needed that identify transfer events with high reliability. Frequently, the transferred pieces of DNA have a considerable length, comprise several genes and are called genomic islands (GIs) or more specifically pathogenicity or symbiotic islands.

Results

We have implemented the program SIGI-HMM that predicts GIs and the putative donor of each individual alien gene. It is based on the analysis of codon usage (CU) of each individual gene of a genome under study. CU of each gene is compared against a carefully selected set of CU tables representing microbial donors or highly expressed genes. Multiple tests are used to identify putatively alien genes, to predict putative donors and to mask putatively highly expressed genes. Thus, we determine the states and emission probabilities of an inhomogeneous hidden Markov model working on gene level. For the transition probabilities, we draw upon classical test theory with the intention of integrating a sensitivity controller in a consistent manner. SIGI-HMM was written in JAVA and is publicly available. It accepts as input any file created according to the EMBL-format.

It generates output in the common GFF format readable for genome browsers. Benchmark tests showed that the output of SIGI-HMM is in agreement with known findings. Its predictions were both consistent with annotated GIs and with predictions generated by different methods.

Conclusion

SIGI-HMM is a sensitive tool for the identification of GIs in microbial genomes. It allows to interactively analyze genomes in detail and to generate or to test hypotheses about the origin of acquired genes.