A comparative categorization of protein function encoded in bacterial or archeal genomic islands

Prevalence and diversity of type VI secretion systems in a model beneficial symbiosis

The type VI secretion system (T6SS) is widely distributed in diverse bacterial species and habitats where it is required for interbacterial competition and interactions with eukaryotic cells. Previous work described the role of a T6SS in the beneficial symbiont, Vibrio fischeri, during colonization of the light organ of Euprymna scolopes squid. However, the prevalence and diversity of T6SSs found within the distinct symbiotic structures of this model host have not yet been determined. Here, we analyzed 73 genomes of isolates from squid light organs and accessory nidamental glands (ANGs) and 178 reference genomes. We found that the majority of these bacterial symbionts encode diverse T6SSs from four distinct classes, and most share homology with T6SSs from more distantly related species, including pathogens of animals and humans. These findings indicate that T6SSs with shared evolutionary histories can be integrated into the cellular systems of host-associated bacteria with different effects on host health. Furthermore, we found that one T6SS in V. fischeri is located within a genomic island with high genomic plasticity. Five distinct genomic island genotypes were identified, suggesting this region encodes diverse functional potential that natural selection can act on. Finally, analysis of newly described T6SSs in roseobacter clade ANG isolates revealed a novel predicted protein that appears to be a fusion of the TssB-TssC sheath components. This work underscores the importance of studying T6SSs in diverse organisms and natural habitats to better understand how T6SSs promote the propagation of bacterial populations and impact host health.

Genus-wide comparison of Pseudovibrio bacterial genomes reveal diverse adaptations to different marine invertebrate hosts

Bacteria belonging to the genus Pseudovibrio have been frequently found in association with a wide variety of marine eukaryotic invertebrate hosts, indicative of their versatile and symbiotic lifestyle. A recent comparison of the sponge-associated Pseudovibrio genomes has shed light on the mechanisms influencing a successful symbiotic association with sponges. In contrast, the genomic architecture of Pseudovibrio bacteria associated with other marine hosts has received less attention. Here, we performed genus-wide comparative analyses of 18 Pseudovibrio isolated from sponges, coral, tunicates, flatworm, and seawater. The analyses revealed a certain degree of commonality among the majority of sponge- and coral-associated bacteria. Isolates from other marine invertebrate host, tunicates, exhibited a genetic repertoire for cold adaptation and specific metabolic abilities including mucin degradation in the Antarctic tunicate-associated bacterium Pseudovibrio sp. Tun.PHSC04_5.I4. Reductive genome evolution was simultaneously detected in the flatworm-associated bacteria and the sponge-associated bacterium P. axinellae AD2, through the loss of major secretion systems (type III/VI) and virulence/symbioses factors such as proteins involved in adhesion and attachment to the host. Our study also unraveled the presence of a CRISPR-Cas system in P. stylochi UST20140214-052 a flatworm-associated bacterium possibly suggesting the role of CRISPR-based adaptive immune system against the invading virus particles. Detection of mobile elements and genomic islands (GIs) in all bacterial members highlighted the role of horizontal gene transfer for the acquisition of novel genetic features, likely enhancing the bacterial ecological fitness. These findings are insightful to understand the role of genome diversity in Pseudovibrio as an evolutionary strategy to increase their colonizing success across a wide range of marine eukaryotic hosts.

Genomes of two new ammonia-oxidizing archaea enriched from deep marine sediments

Ammonia-oxidizing archaea (AOA) are ubiquitous and abundant and contribute significantly to the carbon and nitrogen cycles in the ocean. In this study, we assembled AOA draft genomes from two deep marine sediments from Donghae, South Korea, and Svalbard, Arctic region, by sequencing the enriched metagenomes. Three major microorganism clusters belonging to Thaumarchaeota, Epsilonproteobacteria, and Gammaproteobacteria were deduced from their 16S rRNA genes, GC contents, and oligonucleotide frequencies. Three archaeal genomes were identified, two of which were distinct and were designated Ca. “Nitrosopumilus koreensis” AR1 and “Nitrosopumilus sediminis” AR2. AR1 and AR2 exhibited average nucleotide identities of 85.2% and 79.5% to N. maritimus, respectively. The AR1 and AR2 genomes contained genes pertaining to energy metabolism and carbon fixation as conserved in other AOA, but, conversely, had fewer heme-containing proteins and more copper-containing proteins than other AOA. Most of the distinctive AR1 and AR2 genes were located in genomic islands (GIs) that were not present in other AOA genomes or in a reference water-column metagenome from the Sargasso Sea. A putative gene cluster involved in urea utilization was found in the AR2 genome, but not the AR1 genome, suggesting niche specialization in marine AOA. Co-cultured bacterial genome analysis suggested that bacterial sulfur and nitrogen metabolism could be involved in interactions with AOA. Our results provide fundamental information concerning the metabolic potential of deep marine sedimentary AOA.

Bacterial genome instability

Bacterial genomes are remarkably stable from one generation to the next but are plastic on an evolutionary time scale, substantially shaped by horizontal gene transfer, genome rearrangement, and the activities of mobile DNA elements. This implies the existence of a delicate balance between the maintenance of genome stability and the tolerance of genome instability. In this review, we describe the specialized genetic elements and the endogenous processes that contribute to genome instability. We then discuss the consequences of genome instability at the physiological level, where cells have harnessed instability to mediate phase and antigenic variation, and at the evolutionary level, where horizontal gene transfer has played an important role. Indeed, this ability to share DNA sequences has played a major part in the evolution of life on Earth. The evolutionary plasticity of bacterial genomes, coupled with the vast numbers of bacteria on the planet, substantially limits our ability to control disease.

Genomic determinants of organohalide-respiration in Geobacter lovleyi, an unusual member of the Geobacteraceae

BACKGROUND

Geobacter lovleyi is a unique member of the Geobacteraceae because strains of this species share the ability to couple tetrachloroethene (PCE) reductive dechlorination to cis-1,2-dichloroethene (cis-DCE) with energy conservation and growth (i.e., organohalide respiration). Strain SZ also reduces U(VI) to U(IV) and contributes to uranium immobilization, making G. lovleyi relevant for bioremediation at sites impacted with chlorinated ethenes and radionuclides. G. lovleyi is the only fully sequenced representative of this distinct Geobacter clade, and comparative genome analyses identified genetic elements associated with organohalide respiration and elucidated genome features that distinguish strain SZ from other members of the Geobacteraceae.

RESULTS

Sequencing the G. lovleyi strain SZ genome revealed a 3.9 Mbp chromosome with 54.7% GC content (i.e., the percent of the total guanines (Gs) and cytosines (Cs) among the four bases within the genome), and average amino acid identities of 53-56% compared to other sequenced Geobacter spp. Sequencing also revealed the presence of a 77 kbp plasmid, pSZ77 (53.0% GC), with nearly half of its encoded genes corresponding to chromosomal homologs in other Geobacteraceae genomes. Among these chromosome-derived features, pSZ77 encodes 15 out of the 24 genes required for de novo cobalamin biosynthesis, a required cofactor for organohalide respiration. A plasmid with 99% sequence identity to pSZ77 was subsequently detected in the PCE-dechlorinating G. lovleyi strain KB-1 present in the PCE-to-ethene-dechlorinating consortium KB-1. Additional PCE-to-cis-DCE-dechlorinating G. lovleyi strains obtained from the PCE-contaminated Fort Lewis, WA, site did not carry a plasmid indicating that pSZ77 is not a requirement (marker) for PCE respiration within this species. Chromosomal genomic islands found within the G. lovleyi strain SZ genome encode two reductive dehalogenase (RDase) homologs and a putative conjugative pilus system. Despite the loss of many c-type cytochrome and oxidative-stress-responsive genes, strain SZ retained the majority of Geobacter core metabolic capabilities, including U(VI) respiration.

CONCLUSIONS

Gene acquisitions have expanded strain SZ's respiratory capabilities to include PCE and TCE as electron acceptors. Respiratory processes core to the Geobacter genus, such as metal reduction, were retained despite a substantially reduced number of c-type cytochrome genes. pSZ77 is stably maintained within its host strains SZ and KB-1, likely because the replicon carries essential genes including genes involved in cobalamin biosynthesis and possibly corrinoid transport. Lateral acquisition of the plasmid replicon and the RDase genomic island represent unique genome features of the PCE-respiring G. lovleyi strains SZ and KB-1, and at least the latter signifies adaptation to PCE contamination.

High-density transcriptional initiation signals underline genomic islands in bacteria

Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of "alien" elements which probably undergo special temporal-spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these "exotic" regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased "non-optimal" codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for "alien" regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions.

Harvesting evolutionary signals in a forest of prokaryotic gene trees

Phylogenomic studies produce increasingly large phylogenetic forests of trees with patchy taxonomical sampling. Typically, prokaryotic data generate thousands of gene trees of all sizes that are difficult, if not impossible, to root. Their topologies do not match the genealogy of lineages, as they are influenced not only by duplication, losses, and vertical descent but also by lateral gene transfer (LGT) and recombination. Because this complexity in part reflects the diversity of evolutionary processes, the study of phylogenetic forests is thus a great opportunity to improve our understanding of prokaryotic evolution. Here, we show how the rich evolutionary content of such novel phylogenetic objects can be exploited through the development of new approaches designed specifically for extracting the multiple evolutionary signals present in the forest of life, that is, by slicing up trees into remarkable bits and pieces: clans, slices, and clips. We harvested a forest of 6,901 unrooted gene trees comprising up to 100 prokaryotic genomes (41 archaea and 59 bacteria) to search for evolutionary events that a species tree would not account for. We identified 1) trees and partitions of trees that reflected the lifestyle of organisms rather than their taxonomy, 2) candidate lifestyle-specific genetic modules, used by distinct unrelated organisms to adapt to the same environment, 3) gene families, nonrandomly distributed in the functional space, that were frequently exchanged between archaea and bacteria, sometimes without major changes in their sequences. Finally, 4) we reconstructed polarized networks of genetic partnerships between archaea and bacteria to describe some of the rules affecting LGT between these two Domains.

Inference and characterization of horizontally transferred gene families using stochastic mapping

Macrogenomic events, in which genes are gained and lost, play a pivotal evolutionary role in microbial evolution. Nevertheless, probabilistic-evolutionary models describing such events and methods for their robust inference are considerably less developed than existing methodologies for analyzing site-specific sequence evolution. Here, we present a novel method for the inference of gains and losses of gene families. First, we develop probabilistic-evolutionary models describing the dynamics of gene-family content, which are more biologically realistic than previously suggested models. In our likelihood-based models, gains and losses are represented by transitions between presence and absence, given an underlying phylogeny. We employ a mixture-model approach in which we allow both the gain rate and the loss rate to vary among gene families. Second, we use these models together with the analytic implementation of stochastic mapping to infer branch-specific events. Our novel methodology allows us to infer and quantify horizontal gene transfer (HGT) events. This enables us to rank various gene families and lineages according to their propensity to undergo gains and losses. Applying our methodology to 4,873 gene families shows that: 1) the novel mixture models describe the observed variability in gene-family content among microbes significantly better than previous models; 2) The stochastic mapping approach enables accurate inference of gain and loss events based on simulations; 3) At least 34% of the gene families analyzed are inferred to have experienced HGT at least once during their evolution; and 4) Gene families that were inferred to experience HGT are both enriched and depleted with respect to specific functional categories.

Functional replacement of a primary metabolic pathway via multiple independent eukaryote-to-eukaryote gene transfers and selective retention

Although lateral gene transfer (LGT) is now recognized as a major force in the evolution of prokaryotes, the contribution of LGT to the evolution and diversification of eukaryotes is less understood. Notably, transfers of complete pathways are believed to be less likely between eukaryotes, because the successful transfer of a pathway requires the physical clustering of functionally related genes. Here, we report that in one of the closest unicellular relatives of animals, the choanoflagellate, Monosiga, three genes whose products work together in the glutamate synthase cycle are of algal origin. The concerted retention of these three independently acquired genes is best explained as the consequence of a series of adaptive replacement events. More generally, this study argues that (i) eukaryote-to-eukaryote transfers of entire metabolic pathways are possible, (ii) adaptive functional replacements of primary pathways can occur, and (iii) functional replacements involving eukaryotic genes are likely to have also contributed to the evolution of eukaryotes. Lastly, these data underscore the potential contribution of algal genes to the evolution of nonphotosynthetic lineages.

NAD biosynthesis evolution in bacteria: lateral gene transfer of kynurenine pathway in Xanthomonadales and Flavobacteriales

The biosynthesis of quinolinate, the de novo precursor of nicotinamide adenine dinucleotide (NAD), may be performed by two distinct pathways, namely, the bacterial aspartate (aspartate-to-quinolinate) and the eukaryotic kynurenine (tryptophan-to-quinolinate). Even though the separation into eukaryotic and bacterial routes is long established, recent genomic surveys have challenged this view, because certain bacterial species also carry the genes for the kynurenine pathway. In this work, both quinolinate biosynthetic pathways were investigated in the Bacteria clade and with special attention to Xanthomonadales and Bacteroidetes, from an evolutionary viewpoint. Genomic screening has revealed that a small number of bacterial species possess some of the genes for the kynurenine pathway, which is complete in the genus Xanthomonas and in the order Flavobacteriales, where the aspartate pathway is absent. The opposite pattern (presence of the aspartate pathway and absence of the kynurenine pathway) in close relatives (Xylella ssp. and the order Bacteroidales, respectively) points to the idea of a recent acquisition of the kynurenine pathway through lateral gene transfer in these bacterial groups. In fact, sequence similarity comparison and phylogenetic reconstruction both suggest that at least part of the genes of the kynurenine pathway in Xanthomonas and Flavobacteriales is shared by eukaryotes. These results reinforce the idea of the role that lateral gene transfer plays in the configuration of bacterial genomes, thereby providing alternative metabolic pathways, even with the replacement of primary and essential cell functions, as exemplified by NAD biosynthesis.

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.