Biology subjects

Kogay, R.

Publications and source records attributed to Kogay, R..

3 recordsLinked to original sources

bioRxiv2020

Phylogenetic evidence of headful packaging strategy in gene transfer agents

Gene transfer agents (GTAs) are virus-like particles encoded and produced by many bacteria and archaea. Unlike viruses, GTAs package fragments of the host genome instead of the genes that encode the components of the GTA itself. As a result of this non-specific DNA packaging, GTAs can transfer genes within bacterial and archaeal communities. GTAs clearly evolved from viruses and are thought to have been maintained in prokaryotic genomes due to the advantages associated with their DNA transfer capacity. The most-studied GTA is produced by the alphaproteobacterium Rhodobacter capsulatus (RcGTA), which packages random portions of the host genome at a lower DNA density than usually observed in tailed bacterial viruses. How the DNA packaging properties of RcGTA evolved from those of the ancestral virus remains unknown. To address this question, we reconstructed the evolutionary history of the large subunit of the terminase (TerL), a highly conserved enzyme used by viruses and GTAs to package DNA. We found that RcGTA-like TerLs grouped within viruses that employ the headful packaging strategy. Because distinct mechanisms of viral DNA packaging correspond to differences in the TerL amino acid sequence, our finding suggests that RcGTA evolved from a headful packaging virus. Headful packaging is the least sequence-specific mode of DNA packaging, which would facilitate the switch from packaging of the viral genome to packaging random pieces of the host genome during GTA evolution.

evolutionary biology↗

bioRxiv2020

Selection for reducing energy cost of protein production drives the GC content and amino acid composition bias in gene transfer agents

Gene transfer agents (GTAs) are virus-like elements integrated into bacterial genomes, particularly, those of Alphaproteobacteria. The GTAs can be induced under nutritional stress, incorporate random fragments of bacterial DNA into mini-phage particles, lyse the host cells and infect neighboring bacteria, thus enhancing horizontal gene transfer. We show that the GTA genes evolve under pronounced positive selection for the reduction of the energy cost of protein production as shown by comparison of the amino acid compositions with both homologous viral genes and host genes. The energy saving in GTA genes is comparable to or even more pronounced than that in the genes encoding the most abundant, essential bacterial proteins. In cases when viruses acquire genes from GTAs, the bias in amino acid composition disappears in the course of evolution, showing that reduction of the energy cost of protein is an important factor of evolution of GTAs but not bacterial viruses. These findings strongly suggest that GTAs are bacterial adaptations rather than selfish, virus-like elements. Because GTA production kills the host cell and does not propagate the GTA genome, it appears likely that the GTAs are retained in the course of evolution via kin or group selection. Therefore, we hypothesize that GTA facilitate the survival of bacterial populations under energy-limiting conditions through the spread of metabolic and transport capabilities via horizontal gene transfer and increase of nutrient availability resulting from the altruistic suicide of GTA-producing cells. ImportanceKin and group selection remain controversial topics in evolutionary biology. We argue that these types of selection are likely to operate in bacterial populations by showing that bacterial Gene Transfer Agents (GTAs), but not related viruses, evolve under positive selection for the reduction of the energy cost of a GTA particle production. We hypothesize that GTAs are dedicated devices for the survival of bacteria under the conditions of nutrient limitation. The benefits conferred by GTAs under nutritional stress appear to include horizontal dissemination of genes that could provide bacteria with enhanced capabilities for nutrient utilization and the increase of nutrient availability through the lysis of GTA-producing bacteria.

evolutionary biology↗

bioRxiv2019

Machine-learning classification suggests that many alphaproteobacterial prophages may instead be gene transfer agents

Many of the sequenced bacterial and archaeal genomes encode regions of viral provenance. Yet, not all of these regions encode bona fide viruses. Gene transfer agents (GTAs) are thought to be former viruses that are now maintained in genomes of some bacteria and archaea and are hypothesized to enable exchange of DNA within bacterial populations. In Alphaproteobacteria, genes homologous to the head-tail gene cluster that encodes structural components of the Rhodobacter capsulatus GTA (RcGTA) are found in many taxa, even if they are only distantly related to Rhodobacter capsulatus. Yet, in most genomes available in GenBank RcGTA-like genes have annotations of typical viral proteins, and therefore are not easily distinguished from their viral homologs without additional analyses. Here, we report a support vector machine classifier that quickly and accurately distinguishes RcGTA-like genes from their viral homologs by capturing the differences in the amino acid composition of the encoded proteins. Our open-source classifier is implemented in Python and can be used to scan homologs of the RcGTA genes in newly sequenced genomes. The classifier can also be trained to identify other types of GTAs, or even to detect other elements of viral ancestry. Using the classifier trained on a manually curated set of homologous viruses and GTAs, we detected RcGTA-like head-tail gene clusters in 57.5% of the 1,423 examined alphaproteobacterial genomes. We also demonstrated that more than half of the in silico prophage predictions are instead likely to be GTAs, suggesting that in many alphaproteobacterial genomes the RcGTA-like elements remain unrecognized.\n\nData depositionSequence alignments and phylogenetic trees are available in a FigShare repository at DOI 10.6084/m9.figshare.8796419. The Python source code of the described classifier and additional scripts used in the analyses are available via a GitHub repository at https://github.com/ecg-lab/GTA-Hunter-v1

genomics↗